pax_global_header00006660000000000000000000000064130237260000014503gustar00rootroot0000000000000052 comment=deabb9cbabb7cf8f9d990fe36c198b5da0d7d038 pyresample-1.2.9/000077500000000000000000000000001302372600000136755ustar00rootroot00000000000000pyresample-1.2.9/.bumpversion.cfg000066400000000000000000000001521302372600000170030ustar00rootroot00000000000000[bumpversion] current_version = 1.2.9 commit = True tag = True [bumpversion:file:pyresample/version.py] pyresample-1.2.9/.gitchangelog.rc000066400000000000000000000144031302372600000167360ustar00rootroot00000000000000## ## Format ## ## ACTION: [AUDIENCE:] COMMIT_MSG [!TAG ...] ## ## Description ## ## ACTION is one of 'chg', 'fix', 'new' ## ## Is WHAT the change is about. ## ## 'chg' is for refactor, small improvement, cosmetic changes... ## 'fix' is for bug fixes ## 'new' is for new features, big improvement ## ## AUDIENCE is optional and one of 'dev', 'usr', 'pkg', 'test', 'doc' ## ## Is WHO is concerned by the change. ## ## 'dev' is for developpers (API changes, refactors...) ## 'usr' is for final users (UI changes) ## 'pkg' is for packagers (packaging changes) ## 'test' is for testers (test only related changes) ## 'doc' is for doc guys (doc only changes) ## ## COMMIT_MSG is ... well ... the commit message itself. ## ## TAGs are additionnal adjective as 'refactor' 'minor' 'cosmetic' ## ## They are preceded with a '!' or a '@' (prefer the former, as the ## latter is wrongly interpreted in github.) Commonly used tags are: ## ## 'refactor' is obviously for refactoring code only ## 'minor' is for a very meaningless change (a typo, adding a comment) ## 'cosmetic' is for cosmetic driven change (re-indentation, 80-col...) ## 'wip' is for partial functionality but complete subfunctionality. ## ## Example: ## ## new: usr: support of bazaar implemented ## chg: re-indentend some lines !cosmetic ## new: dev: updated code to be compatible with last version of killer lib. ## fix: pkg: updated year of licence coverage. ## new: test: added a bunch of test around user usability of feature X. ## fix: typo in spelling my name in comment. !minor ## ## Please note that multi-line commit message are supported, and only the ## first line will be considered as the "summary" of the commit message. So ## tags, and other rules only applies to the summary. The body of the commit ## message will be displayed in the changelog without reformatting. ## ## ``ignore_regexps`` is a line of regexps ## ## Any commit having its full commit message matching any regexp listed here ## will be ignored and won't be reported in the changelog. ## ignore_regexps = [ r'@minor', r'!minor', r'@cosmetic', r'!cosmetic', r'@refactor', r'!refactor', r'@wip', r'!wip', r'^Merge commit .* into HEAD', r'^([cC]hg|[fF]ix|[nN]ew)\s*:\s*[p|P]kg:', r'^([cC]hg|[fF]ix|[nN]ew)\s*:\s*[d|D]ev:', r'^(.{3,3}\s*:)?\s*[fF]irst commit.?\s*$', ] ## ``section_regexps`` is a list of 2-tuples associating a string label and a ## list of regexp ## ## Commit messages will be classified in sections thanks to this. Section ## titles are the label, and a commit is classified under this section if any ## of the regexps associated is matching. ## section_regexps = [ ('New', [ r'^[nN]ew\s*:\s*((dev|use?r|pkg|test|doc)\s*:\s*)?([^\n]*)$', ]), ('Changes', [ r'^[cC]hg\s*:\s*((dev|use?r|pkg|test|doc)\s*:\s*)?([^\n]*)$', ]), ('Fix', [ r'^([Bb]ug)?[fF]ix\s*:\s*((dev|use?r|pkg|test|doc)\s*:\s*)?([^\n]*)$', ]), ('Other', None ## Match all lines ), ] ## ``body_process`` is a callable ## ## This callable will be given the original body and result will ## be used in the changelog. ## ## Available constructs are: ## ## - any python callable that take one txt argument and return txt argument. ## ## - ReSub(pattern, replacement): will apply regexp substitution. ## ## - Indent(chars=" "): will indent the text with the prefix ## Please remember that template engines gets also to modify the text and ## will usually indent themselves the text if needed. ##git log --pretty=format:"- %s%n%b" --since="$(git show -s --format=%ad `git rev-list --tags --max-count=1`)" ## - Wrap(regexp=r"\n\n"): re-wrap text in separate paragraph to fill 80-Columns ## ## - noop: do nothing ## ## - ucfirst: ensure the first letter is uppercase. ## (usually used in the ``subject_process`` pipeline) ## ## - final_dot: ensure text finishes with a dot ## (usually used in the ``subject_process`` pipeline) ## ## - strip: remove any spaces before or after the content of the string ## ## Additionally, you can `pipe` the provided filters, for instance: #body_process = Wrap(regexp=r'\n(?=\w+\s*:)') | Indent(chars=" ") #body_process = Wrap(regexp=r'\n(?=\w+\s*:)') #body_process = noop body_process = ReSub(r'(?m)\s*^Signed-off-by: .*$\s*', '') ## ``subject_process`` is a callable ## ## This callable will be given the original subject and result will ## be used in the changelog. ## ## Available constructs are those listed in ``body_process`` doc. subject_process = (strip | ReSub(r'^([cC]hg|[fF]ix|[nN]ew)\s*:\s*((dev|use?r|pkg|test|doc)\s*:\s*)?([^\n@]*)(@[a-z]+\s+)*$', r'\4') | #ucfirst | final_dot) final_dot) #subject_process = noop ## ``tag_filter_regexp`` is a regexp ## ## Tags that will be used for the changelog must match this regexp. ## tag_filter_regexp = r'^v[0-9]+\.[0-9]+(\.[0-9]+)?$' ## ``unreleased_version_label`` is a string ## ## This label will be used as the changelog Title of the last set of changes ## between last valid tag and HEAD if any. unreleased_version_label = "%%version%% (unreleased)" ## ``output_engine`` is a callable ## ## This will change the output format of the generated changelog file ## ## Available choices are: ## ## - rest_py ## ## Legacy pure python engine, outputs ReSTructured text. ## This is the default. ## ## - mustache() ## ## Template name could be any of the available templates in ## ``templates/mustache/*.tpl``. ## Requires python package ``pystache``. ## Examples: ## - mustache("markdown") ## - mustache("restructuredtext") ## ## - makotemplate() ## ## Template name could be any of the available templates in ## ``templates/mako/*.tpl``. ## Requires python package ``mako``. ## Examples: ## - makotemplate("restructuredtext") ## output_engine = rest_py #output_engine = mustache("restructuredtext") #output_engine = mustache("markdown") #output_engine = makotemplate("restructuredtext") ## ``include_merges`` is a boolean ## ## This option tells git-log whether to include merge commits in the log. ## The default is to include them. include_merges = False pyresample-1.2.9/.gitignore000066400000000000000000000007731302372600000156740ustar00rootroot00000000000000### PYTHON IGNORES ### *.py[cod] # C extensions *.so # Packages *.egg *.egg-info dist build doc/build eggs parts bin var sdist develop-eggs .installed.cfg lib lib64 # Installer logs pip-log.txt # Unit test / coverage reports .coverage .tox nosetests.xml #Translations *.mo #Mr Developer .mr.developer.cfg ### C IGNORES ### # Object files *.o # Libraries *.lib *.a # Shared objects (inc. Windows DLLs) *.dll *.so *.so.* *.dylib # Executables *.exe *.out *.app # Others *~ # PyCharm Settings .idea pyresample-1.2.9/.travis.yml000066400000000000000000000031541302372600000160110ustar00rootroot00000000000000language: python python: - '2.6' - '2.7' - '3.3' - '3.4' - '3.5' before_install: - sudo add-apt-repository ppa:ubuntugis/ppa -y - sudo apt-get update -qq - sudo apt-get install libfreetype6-dev - sudo apt-get install libgeos-3.3.8 libgeos-c1 libgeos-dev install: - if [[ $TRAVIS_PYTHON_VERSION == "2.6" ]]; then pip install "matplotlib<1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "2.6" ]]; then pip install unittest2; fi - if [[ $TRAVIS_PYTHON_VERSION == "2.6" ]]; then pip install importlib; fi - if [[ $TRAVIS_PYTHON_VERSION == "2.6" ]]; then pip install "sphinx<1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "2.7" ]]; then pip install "matplotlib>=1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "2.7" ]]; then pip install "sphinx>=1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "3.3" ]]; then pip install "matplotlib<1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "3.3" ]]; then pip install "sphinx<1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "3.4" ]]; then pip install "matplotlib>=1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "3.4" ]]; then pip install "sphinx>=1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "3.5" ]]; then pip install "matplotlib>=1.5.0"; fi - if [[ $TRAVIS_PYTHON_VERSION == "3.5" ]]; then pip install "sphinx>=1.5.0"; fi - pip install -r requirements.txt - pip install -e ".[pykdtree,quicklook]" - pip install coveralls script: # Once doctests pass this should be uncommented to replace the other coverage run line - coverage run --source=pyresample setup.py test && cd docs && mkdir doctest && sphinx-build -E -n -b doctest ./source ./doctest after_success: coveralls notifications: slack: pytroll:96mNSYSI1dBjGyzVXkBT6qFt pyresample-1.2.9/LICENSE.txt000066400000000000000000000167511302372600000155320ustar00rootroot00000000000000 GNU LESSER GENERAL PUBLIC LICENSE Version 3, 29 June 2007 Copyright (C) 2007, 2015 Free Software Foundation, Inc. Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. This version of the GNU Lesser General Public License incorporates the terms and conditions of version 3 of the GNU General Public License, supplemented by the additional permissions listed below. 0. Additional Definitions. As used herein, "this License" refers to version 3 of the GNU Lesser General Public License, and the "GNU GPL" refers to version 3 of the GNU General Public License. "The Library" refers to a covered work governed by this License, other than an Application or a Combined Work as defined below. An "Application" is any work that makes use of an interface provided by the Library, but which is not otherwise based on the Library. Defining a subclass of a class defined by the Library is deemed a mode of using an interface provided by the Library. A "Combined Work" is a work produced by combining or linking an Application with the Library. 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You may place library facilities that are a work based on the Library side by side in a single library together with other library facilities that are not Applications and are not covered by this License, and convey such a combined library under terms of your choice, if you do both of the following: a) Accompany the combined library with a copy of the same work based on the Library, uncombined with any other library facilities, conveyed under the terms of this License. b) Give prominent notice with the combined library that part of it is a work based on the Library, and explaining where to find the accompanying uncombined form of the same work. 6. Revised Versions of the GNU Lesser General Public License. The Free Software Foundation may publish revised and/or new versions of the GNU Lesser General Public License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns. Each version is given a distinguishing version number. If the Library as you received it specifies that a certain numbered version of the GNU Lesser General Public License "or any later version" applies to it, you have the option of following the terms and conditions either of that published version or of any later version published by the Free Software Foundation. If the Library as you received it does not specify a version number of the GNU Lesser General Public License, you may choose any version of the GNU Lesser General Public License ever published by the Free Software Foundation. If the Library as you received it specifies that a proxy can decide whether future versions of the GNU Lesser General Public License shall apply, that proxy's public statement of acceptance of any version is permanent authorization for you to choose that version for the Library. pyresample-1.2.9/MANIFEST.in000066400000000000000000000002231302372600000154300ustar00rootroot00000000000000include docs/Makefile recursive-include docs/source * include test/test_files/* include LICENSE.txt include MANIFEST.in include pyresample/ewa/*.h pyresample-1.2.9/README000077700000000000000000000000001302372600000160272README.mdustar00rootroot00000000000000pyresample-1.2.9/README.md000066400000000000000000000055541302372600000151650ustar00rootroot00000000000000[![Build Status](https://travis-ci.org/pytroll/pyresample.svg?branch=master)](https://travis-ci.org/pytroll/pyresample) [![Build status](https://ci.appveyor.com/api/projects/status/10qdrecp45rgkf73/branch/master?svg=true)](https://ci.appveyor.com/project/davidh-ssec/pyresample-ly2q0/branch/master) Python package for geospatial resampling ---------------------------------------- Resampling (reprojection) of geospatial image data in Python. Pyresample uses a kd-tree approach for resampling. Pyresample is designed for resampling of remote sensing data and supports resampling from both fixed grids and geolocated swath data. Several types of resampling are supported including nearest neighbour, gaussian weighting and weighting with a user defined radial function. Pyresample works with Numpy arrays including support for masked arrays. Support for parallel resampling using multiple processor cores. Plotting capablity using Basemap. As of v0.8.0 [pykdtree](https://github.com/storpipfugl/pykdtree) can be used to speed up processing. Pyresample is tested with Python 2.6, 2.7, 3.2, 3.3, and 3.4. Note: For numpy >= 1.6.2 use pyresample >= 0.7.13 [Documentation](https://pyresample.readthedocs.org/en/latest/) Look at [pytroll.org](http://pytroll.org/) for more information. ===News=== * *2015-02-03*: Pyresample-1.1.3 released. Switch to LGPLv3. * *2014-12-17*: Pyresample-1.1.2 released. Fix to allow tests to run on travis. * *2014-12-10*: Pyresample-1.1.1 released. Wrapping of longitudes and latitudes is now implemented. * *2013-10-23*: Pyresample-1.1.0 released. Added option for calculating uncertainties for weighted kd-tree resampling. From now on pyresample will adhere to [http://semver.org/ semantic versioning]. * *2013-07-03*: Pyresample-1.0.0 released. Minor API change to the geometry.py module as the boundary variable is removed and replaced by proj_x_coords and proj_y_coords. Caching scheme removed from projection coordinate calculation in geometry.py as it introduced excessive complications. The numexpr package is now used for minor bottleneck optimization if available. Version number bumped to 1.0.0 as pyresample has been running stable in production environments for several years now. * *2013-03-20*: Pyresample-0.8.0 released. Enables use of pykdtree. Fixes projection handling for 'latlong' projection. * *2013-01-21*: Pyresample-0.7.13 released. Fixes numpy incompability introduced with numpy v1.6.2 * *2012-10-18*: Pyresample-0.7.12 released. Better integration with Basemap with support for plotting using globe projections (geos, ortho and nspere). Documentation updated with correct description of the epsilon parameter. * *2012-07-03*: Pyresample-0.7.11 released. Support for plotting in Plate Carree projection and bugfixes for meridians and parallels in plots. Added utils.fwhm2sigma convenience function for use in Gauss resampling. pyresample-1.2.9/appveyor.yml000066400000000000000000000057201302372600000162710ustar00rootroot00000000000000environment: global: # SDK v7.0 MSVC Express 2008's SetEnv.cmd script will fail if the # /E:ON and /V:ON options are not enabled in the batch script intepreter # See: http://stackoverflow.com/a/13751649/163740 CMD_IN_ENV: "cmd /E:ON /V:ON /C .\\appveyor\\run_with_compiler.cmd" # Don't build pykdtree with openmp because it isn't supported in appveyor's compilers USE_OMP: "0" matrix: - PYTHON: "C:\\Python27_32" PYTHON_VERSION: "2.7.8" PYTHON_ARCH: "32" MINICONDA_VERSION: "" - PYTHON: "C:\\Python27_64" PYTHON_VERSION: "2.7.8" PYTHON_ARCH: "64" MINICONDA_VERSION: "" - PYTHON: "C:\\Python34_32" PYTHON_VERSION: "3.4.1" PYTHON_ARCH: "32" MINICONDA_VERSION: "3" - PYTHON: "C:\\Python34_64" PYTHON_VERSION: "3.4.1" PYTHON_ARCH: "64" MINICONDA_VERSION: "3" - PYTHON: "C:\\Python35_32" PYTHON_VERSION: "3.5" PYTHON_ARCH: "32" MINICONDA_VERSION: "3" - PYTHON: "C:\\Python35_64" PYTHON_VERSION: "3.5" PYTHON_ARCH: "64" MINICONDA_VERSION: "3" install: - "git submodule update --init --recursive" - ECHO "Filesystem root:" - ps: "ls \"C:/\"" - ECHO "Installed SDKs:" - ps: "ls \"C:/Program Files/Microsoft SDKs/Windows\"" # install miniconda with the powershell script install.ps1 - "powershell ./appveyor/install.ps1" # Prepend newly installed Python to the PATH of this build (this cannot be # done from inside the powershell script as it would require to restart # the parent CMD process). - "SET PATH=%PYTHON%;%PYTHON%\\Scripts;%PATH%" # Check that we have the expected version and architecture for Python - "python --version" - "python -c \"import struct; print(struct.calcsize('P') * 8)\"" # Install the build dependencies of the project. If some dependencies contain # compiled extensions and are not provided as pre-built wheel packages, # pip will build them from source using the MSVC compiler matching the # target Python version and architecture - "conda update --yes conda" - "conda config --add channels conda-forge" - "conda create -q --yes -n test python=%PYTHON_VERSION% basemap-data-hires sphinx pyproj scipy pykdtree" - "activate test" - "pip install coveralls" - "where python" build: false # Not a C# project, build stuff at the test step instead. test_script: # Build the compiled extension and run the project tests - "%CMD_IN_ENV% python setup.py test" after_test: # If tests are successful, create a whl package for the project. - "%CMD_IN_ENV% python setup.py bdist_wheel bdist_wininst" - ps: "ls dist" artifacts: # Archive the generated wheel package in the ci.appveyor.com build report. - path: dist\* #on_success: # - TODO: upload the content of dist/*.whl to a public wheelhouse # notifications: - provider: Slack incoming_webhook: secure: 7bEOYCIxHE5PkCF156zjxbJIeKkv7UpZulyn+Di09jqDlpvZjR0Qj3a1LK9AOjgwWgaQYbeI4BEYEdeq7pPxDs9snK8qvvbFDbuLAzg+HEQ= pyresample-1.2.9/appveyor/000077500000000000000000000000001302372600000155425ustar00rootroot00000000000000pyresample-1.2.9/appveyor/install.ps1000066400000000000000000000044271302372600000176440ustar00rootroot00000000000000# Sample script to install anaconda under windows # Authors: Stuart Mumford # Borrwed from: Olivier Grisel and Kyle Kastner # License: BSD 3 clause $MINICONDA_URL = "http://repo.continuum.io/miniconda/" function DownloadMiniconda ($miniconda_version, $platform_suffix) { $webclient = New-Object System.Net.WebClient $filename = "Miniconda" + $miniconda_version + "-latest" + "-Windows-" + $platform_suffix + ".exe" $url = $MINICONDA_URL + $filename $basedir = $pwd.Path + "\" $filepath = $basedir + $filename if (Test-Path $filename) { Write-Host "Reusing" $filepath return $filepath } # Download and retry up to 3 times in case of network transient errors. Write-Host "Downloading" $filename "from" $url $retry_attempts = 2 for($i=0; $i -lt $retry_attempts; $i++){ try { $webclient.DownloadFile($url, $filepath) break } Catch [Exception]{ Start-Sleep 1 } } if (Test-Path $filepath) { Write-Host "File saved at" $filepath } else { # Retry once to get the error message if any at the last try $webclient.DownloadFile($url, $filepath) } return $filepath } function InstallMiniconda ($miniconda_version, $architecture, $python_home) { Write-Host "Installing miniconda" $miniconda_version "for" $architecture "bit architecture to" $python_home if (Test-Path $python_home) { Write-Host $python_home "already exists, skipping." return $false } if ($architecture -eq "32") { $platform_suffix = "x86" } else { $platform_suffix = "x86_64" } $filepath = DownloadMiniconda $miniconda_version $platform_suffix Write-Host "Installing" $filepath "to" $python_home $args = "/InstallationType=AllUsers /S /AddToPath=1 /RegisterPython=1 /D=" + $python_home Write-Host $filepath $args Start-Process -FilePath $filepath -ArgumentList $args -Wait -Passthru #Start-Sleep -s 15 if (Test-Path $python_home) { Write-Host "Miniconda $miniconda_version ($architecture) installation complete" } else { Write-Host "Failed to install Python in $python_home" Exit 1 } } function main () { InstallMiniconda $env:MINICONDA_VERSION $env:PYTHON_ARCH $env:PYTHON } main pyresample-1.2.9/appveyor/run_with_compiler.cmd000066400000000000000000000043171302372600000217650ustar00rootroot00000000000000:: To build extensions for 64 bit Python 3, we need to configure environment :: variables to use the MSVC 2010 C++ compilers from GRMSDKX_EN_DVD.iso of: :: MS Windows SDK for Windows 7 and .NET Framework 4 (SDK v7.1) :: :: To build extensions for 64 bit Python 2, we need to configure environment :: variables to use the MSVC 2008 C++ compilers from GRMSDKX_EN_DVD.iso of: :: MS Windows SDK for Windows 7 and .NET Framework 3.5 (SDK v7.0) :: :: 32 bit builds do not require specific environment configurations. :: :: Note: this script needs to be run with the /E:ON and /V:ON flags for the :: cmd interpreter, at least for (SDK v7.0) :: :: More details at: :: https://github.com/cython/cython/wiki/64BitCythonExtensionsOnWindows :: http://stackoverflow.com/a/13751649/163740 :: :: Author: Olivier Grisel :: License: CC0 1.0 Universal: http://creativecommons.org/publicdomain/zero/1.0/ @ECHO OFF SET COMMAND_TO_RUN=%* SET WIN_SDK_ROOT=C:\Program Files\Microsoft SDKs\Windows SET MAJOR_PYTHON_VERSION="%PYTHON_VERSION:~0,1%" SET MINOR_PYTHON_VERSION=%PYTHON_VERSION:~2,1% IF %MAJOR_PYTHON_VERSION% == "2" ( SET WINDOWS_SDK_VERSION="v7.0" SET SET_SDK_64=Y ) ELSE IF %MAJOR_PYTHON_VERSION% == "3" ( SET WINDOWS_SDK_VERSION="v7.1" IF %MINOR_PYTHON_VERSION% LEQ 4 ( SET SET_SDK_64=Y ) ELSE ( SET SET_SDK_64=N ) ) ELSE ( ECHO Unsupported Python version: "%MAJOR_PYTHON_VERSION%" EXIT 1 ) IF "%PYTHON_ARCH%"=="64" ( IF %SET_SDK_64% == Y ( ECHO Configuring Windows SDK %WINDOWS_SDK_VERSION% for Python %MAJOR_PYTHON_VERSION% on a 64 bit architecture SET DISTUTILS_USE_SDK=1 SET MSSdk=1 "%WIN_SDK_ROOT%\%WINDOWS_SDK_VERSION%\Setup\WindowsSdkVer.exe" -q -version:%WINDOWS_SDK_VERSION% "%WIN_SDK_ROOT%\%WINDOWS_SDK_VERSION%\Bin\SetEnv.cmd" /x64 /release ECHO Executing: %COMMAND_TO_RUN% call %COMMAND_TO_RUN% || EXIT 1 ) ELSE ( ECHO Using default MSVC build environment for 64 bit architecture ECHO Executing: %COMMAND_TO_RUN% call %COMMAND_TO_RUN% || EXIT 1 ) ) ELSE ( ECHO Using default MSVC build environment for 32 bit architecture ECHO Executing: %COMMAND_TO_RUN% call %COMMAND_TO_RUN% || EXIT 1 ) pyresample-1.2.9/changelog.rst000066400000000000000000000657631302372600000163770ustar00rootroot00000000000000Changelog ========= v1.2.9 (2016-12-13) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.8 → 1.2.9. [Martin Raspaud] - Merge pull request #52 from mitkin/mitkin-pr-setuptools32. [Martin Raspaud] Specify minimum version of setuptools - Specify minimum version of setuptools. [Mikhail Itkin] Prior to version 3.2 setuptools would not recognize correctly the language of `*.cpp` extensions and would assume it's `*.c` no matter what. Version 3.2 of setuptools fixes that. - Fix sphinx dependency to support python 2.6 and 3.3. [Martin Raspaud] v1.2.8 (2016-12-06) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.7 → 1.2.8. [Martin Raspaud] - Correct style in setup.py. [Martin Raspaud] - Make pykdtree a requirement. [Martin Raspaud] - Correct style in geometry.py. [Martin Raspaud] - Allow precision errors when comparing area_extents. [Martin Raspaud] - Allow numbers in proj dict when building proj4 string. [Martin Raspaud] v1.2.7 (2016-11-15) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.6 → 1.2.7. [Martin Raspaud] - Add bump and changelog config files. [Martin Raspaud] - Merge pull request #49 from Funkensieper/fix-polygon-area. [Martin Raspaud] Fix polygon area - Disable snapping of angles in get_polygon_area() [Stephan Finkensieper] - Add option to disable snapping in Arc.angle() - Don't snap angles when computing polygon areas in order to prevent negative area values - Adjust reference values in tests on overlap-rate - Fix polygon area computation for R != 1. [Stephan Finkensieper] Parentheses were missing, see http://mathworld.wolfram.com/SphericalTriangle.html for reference. Only affects earth radius R != 1 which is not implemented yet. - Install pykdtree from conda forge in pre-master. [davidh-ssec] - Merge pull request #47 from mitkin/feature_plot-cmap. [David Hoese] Add option to choose colormap - Add option to choose colormap. [Mikhail Itkin] Make possible to indicate which colormap to use when plotting image v1.2.6 (2016-10-19) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.5 → 1.2.6. [Martin Raspaud] - Pre master (#44) [Radar, Satellite and Nowcasting Division] * add a subset function to the geometry file Often subsets of the SEVIRI disk are save in SEVIRI products. This new function calculated the area extent needed for the specification of the area, starting from the SEVIRI full disk area object. * added the get_area_extent_for_subset function to the geometry.py file * new function for getting area subsets * new function get_xy_from_proj_coordinates retrieve the pixel indices x and y from the map projection coordinates in meter (very similar to get_xy_from_lonlat) * removed pyc file, that should not be in the git repository - Add appveyor status badge to README. [davidh-ssec] - Merge remote-tracking branch 'deni90/master' into pre-master-davidh. [davidh-ssec] - Fix test_custom_uncert and test_gauss_uncert for mips* [Daniel Knezevic] - Fix pykdtree install on appveyor by turning off OpenMP. [davidh-ssec] - Update appveyor config to install missing headers required by pykdtree. [davidh-ssec] - Change appveyor to use conda-forge instead of IOOS. [davidh-ssec] - Add slack notifications from appveyor. [davidh-ssec] v1.2.5 (2016-07-21) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.4 → 1.2.5. [Martin Raspaud] - Fix EWA fornav for integer data and add test. [davidh-ssec] There was a bug when doing the averaging in EWA where the current pixel was being rounded based on the previous pixel's value instead of the current pixel. This only affects integer data because values above 0 are rounded up by 0.5 and values below 0 are rounded by 0.5, for floats this round value is 0.0. - Fix certain compilers not liking integers being passed to isnan. [davidh-ssec] - Replace catch_warnings in all tests with astropy version. [davidh- ssec] - Use catch_warnings from astropy (or at least try to) [davidh-ssec] - Test removing version specific warning checks in `test_swath_wrap` [davidh-ssec] - Move USE_CYTHON handling to if main block in setup.py. [davidh-ssec] - Fix isnan definition only if a macro doesn't already exist. [davidh- ssec] Numpy does some special macro stuff to define a good npy_isnan function. Some systems define a macro for it, others don't. Hopefully this works for all systems. A better solution might be to define a templated isnan that calls npy_isnan if it isn't an integer. - fix EWA compile failure on windows python 3.5. [David Hoese] - Make pykdtree install on appveyor optional. [davidh-ssec] - Add pykdtree to appveyor dependencies. [davidh-ssec] - Fix setup.py test on windows for multiprocessing tests. [davidh-ssec] On Windows when new processes are started the initially command is imported or re-executed. For setup.py this is a big problem since the usual boilerplate does not include `if __name__ == "__main__"` so the setup.py test command gets rerun and rerun. This results in the child processes never actually being run for newer versions of python (2.7+). There still seems to be an issue with `test_nearest_resize` on Windows. - Merge pull request #41 from cpaulik/fix-windows-ewa. [David Hoese] Fix Windows CI import Error - Install scipy in Windows CI to fix import problems. [Christoph Paulik] - Fix copy/paste error in EWA fornav. [davidh-ssec] I had started rewriting EWA in cython then realized it was faster in straight C++ so copied/pasted the cython code and modified it. Seems like I missed this 'or' hanging around. - Fix NAN constant/macro for EWA on Windows. [davidh-ssec] - Merge branch 'add-windows-CI' into fix-windows-ewa. [davidh-ssec] - CI: Add IOOS conda channel to get basemap for Windows and python > 2. [Christoph Paulik] - Merge branch 'add-windows-CI' into fix-windows-ewa. [davidh-ssec] - Add pyproj to conda install in Appveyor CI. [Christoph Paulik] - Make extra_compile_args platform dependent. [Christoph Paulik] - Add Appveyor CI configuration. [Christoph Paulik] - Fix EWA resampling's isnan to work better with windows. [davidh-ssec] v1.2.4 (2016-06-27) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.3 → 1.2.4. [Martin Raspaud] - Fix setup.py extension import and use error. [davidh-ssec] - Fix case when __builtins__ is a dict. [Martin Raspaud] v1.2.3 (2016-06-21) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.2 → 1.2.3. [Martin Raspaud] - Fix list of package names in setup.py. [davidh-ssec] 'pyresample.ewa' wasn't listed before and was not importable from an installed package. v1.2.2 (2016-06-21) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.1 → 1.2.2. [Martin Raspaud] - Add the header files to the MANIFEST.in. [Martin Raspaud] Without this, the compilation of the ewa extension crashes. v1.2.1 (2016-06-21) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.2.0 → 1.2.1. [Martin Raspaud] - Include EWA header files as dependency for extensions. [davidh-ssec] The .c and .cpp files are automatically included because they are listed as sources, but the header files are not. When building a source tarball (uploading to PyPI) the _fornav_templates.h file was not included and building would fail. - Merge branch 'pre-master' of github.com:mraspaud/pyresample into pre- master. [Adam.Dybbroe] - Merge branch 'pre-master' of github.com:mraspaud/pyresample into pre- master. [Adam.Dybbroe] Conflicts: docs/source/conf.py - Run the base class init function first. [Adam.Dybbroe] v1.2.0 (2016-06-17) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.1.6 → 1.2.0. [Martin Raspaud] - Merge branch 'northaholic-feature-lonlat2colrow' into pre-master. [Adam.Dybbroe] - Add two convenience methods lonlat2colrow and colrow2lonlat to AreaDefinition-class. [Sauli Joro] - Fix bug in EWA grid origin calculation. [davidh-ssec] Forgot that cell height was negative so ended up subtracting a negative, going in the wrong direction for the Y origin of the grid. - Merge pull request #37 from davidh-ssec/feature-ewa-resampling. [David Hoese] Feature ewa resampling - Fix bug in EWA conversion from AreaDefinition to upper-left origin X/Y. [davidh-ssec] I was using the area extent for the origin x/y locations, but the extent is actually the outer edge of the pixels so half a pixel needs to be added to each coordinate. - Add EWA C extensions to mocked modules for read the docs. [davidh- ssec] Readthedocs.org fails to import the _ll2cr and _fornav extensions because it seems to not compile them properly. Their documentation isn't necessarily needed so I'm hoping that mocking them will let the import work. - Add pyresample.ewa to API documentation list. [davidh-ssec] - Update EWA wrapper functions to use explicit kwargs. [davidh-ssec] - Correct comments and documentation in EWA documentation. [davidh-ssec] - Add ll2cr and fornav wrappers to make calling easier. [davidh-ssec] Updated documentation with correct usage and added information why EWA is different than kdtree - Fix print statements in documentation so doctests are python 3 compatible. [davidh-ssec] - Add pillow dependency for plot tests and quicklook extra. [davidh- ssec] - Add 'areas.cfg' file to repository and modify doctests to use that instead. [davidh-ssec] - Run doctests after unittests on travis. [davidh-ssec] - Fix documentation for AreaDefinition object. [davidh-ssec] - Update documentation to be numpy style and get rid of all warnings when building docs. [davidh-ssec] - Create special requirements.txt for docs. [davidh-ssec] Readthedocs really doesn't like an empty string for the requirements file - Try empty string for requirements file in readthedocs yaml. [davidh- ssec] - Fix readthedocs yaml config file. [davidh-ssec] Readthedocs was using the requirements file during package installation, but was failing to install basemap (not needed for documentation build) so I attempted to make it an empty string in the yaml file. This makes Rtd hang on the build process. This should at least stop the hanging. - Add napoleon docs extension and intial testing with numpy style docstrings. [davidh-ssec] - Add working example for EWA resampling to docs. [davidh-ssec] I originally had this example but removed it when I had import problems. After I figured those out I forgot to put the original example back. - Add basemap back in to the requirements.txt so that it can be installed on travis. [davidh-ssec] Similarly removed the requirements file when readthedocs is running and mocked third-party packages to documentation can still be built - Fix setup.py requiring numpy for extension includes. [davidh-ssec] The EWA extensions require the numpy headers to be built. These are normally found by importing numpy and doing `numpy.get_includes()`. Obviously if this is run on a new environment numpy is probably not installed so a simple `python setup.py install` will fail. - Add "quicklook" extra in to travis test install. [davidh-ssec] These packages are needed to properly test the "plot" package. These were included in requirements.txt but have been moved for now. - Move plot test imports in to test functions for cleaner test failures. [davidh-ssec] - Add readthedocs yaml file for configuration. [davidh-ssec] - Remove mocked modules from sphinx docs conf.py. [davidh-ssec] This is the first step in making pyresamples docs buildable in the current readthedocs version - Replace relative imports with absolute imports. [davidh-ssec] I noticed a lot of warnings and import problems with building pyresample's documentation because of these relative imports - Add EWA documentation to swath.rst. [davidh-ssec] - Add tests for EWA fornav module. [davidh-ssec] - Update documentation for ll2cr and fornav cython. [davidh-ssec] - Merge remote-tracking branch 'davidh_fork/feature-ewa-resampling' into feature-ewa-resampling. [davidh-ssec] # Conflicts: # pyresample/ewa/_fornav.pyx # pyresample/ewa/_ll2cr.pyx - Remove old and unused polar2grid ll2cr and fornav python modules. [davidh-ssec] - Fix travis tests on python 2.6. [davidh-ssec] - Add ewa ll2cr tests to main test suite. [davidh-ssec] - Add simple tests for ewa ll2cr. [davidh-ssec] These tests were adapted from Polar2Grid so some of the terminology or organization might reflect P2G's design rather than satpy or pyresample. - Revert import multiprocessing setup.py for python 2.6 compatibility. [davidh-ssec] - Fix old polar2grid import in ll2cr module. [davidh-ssec] - Add method for converting area def to areas.def string format. [davidh-ssec] - Remove unused code from fornav wrapper. [davidh-ssec] - Add initial EWA files copied from Polar2Grid. [davidh-ssec] - Add basic documentation to fornav cython function. [davidh-ssec] - Remove old and unused polar2grid ll2cr and fornav python modules. [davidh-ssec] - Fix travis tests on python 2.6. [davidh-ssec] - Add ewa ll2cr tests to main test suite. [davidh-ssec] - Add simple tests for ewa ll2cr. [davidh-ssec] These tests were adapted from Polar2Grid so some of the terminology or organization might reflect P2G's design rather than satpy or pyresample. - Revert import multiprocessing setup.py for python 2.6 compatibility. [davidh-ssec] - Fix old polar2grid import in ll2cr module. [davidh-ssec] - Add method for converting area def to areas.def string format. [davidh-ssec] - Remove unused code from fornav wrapper. [davidh-ssec] - Add initial EWA files copied from Polar2Grid. [davidh-ssec] - Add .gitignore with python and C patterns. [davidh-ssec] - Update tests so they don't fail on OSX. [davidh-ssec] OSX seems to calculate slightly different results from `_spatial_mp.Cartesian` regardless of numexpr being installed. Although the changes are small they seem to affect the results enough to fail this test compared to normal linux execution. - Add 'load_tests' for easier test selection. [davidh-ssec] PyCharm and possibly other IDEs don't really play well with unittest TestSuites, but work as expected when `load_tests` is used. - Make kd_tree test work on older numpy version. [Martin Raspaud] VisibleDeprecationWarning is not available in numpy <1.9. - Adapt to newest pykdtree version. [Martin Raspaud] The kdtree object's attribute `data_pts` has been renamed to `data`. - Run tests on python 3.5 in travis also. [Martin Raspaud] v1.1.6 (2016-02-25) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.1.5 → 1.1.6. [Martin Raspaud] - Fix #35 supporting scipy kdtree again. [Martin Raspaud] A previous commit was looking for a 'data_pts' attribute in the kdtree object, which is available in pykdtree, but not scipy. - Merge pull request #32 from mitkin/master. [Martin Raspaud] [tests] Skip deprecation warnings in test_gauss_multi_uncert - Merge remote-tracking branch 'gh-pytroll/pre-master' [Mikhail Itkin] - Put quotes around pip version specifiers to make things work. [Martin Raspaud] - Install the right matplotlib in travis. [Martin Raspaud] The latest matplotlib (1.5) doesn't support python 2.6 and 3.3. This patch chooses the right matplotlib version to install depending on the python version at hand. - Skip deprecation warnings. [Mikhail Itkin] Catch the rest of the warnings. Check if there is only one, and whether it contains the relevant message ('possible more than 8 neighbours found'). This patch is necessary for python 2.7.9 and newer - Merge pull request #31 from bhawkins/fix-kdtree-dtype. [Martin Raspaud] Fix possible type mismatch with pykdtree. - Add test to expose pykdtree TypeError exception. [Brian Hawkins] - Fix possible type mismatch with pykdtree. [Brian Hawkins] v1.1.5 (2015-10-12) ------------------- - update changelog. [Martin Raspaud] - Bump version: 1.1.4 → 1.1.5. [Martin Raspaud] - Don't build on 3.2 anymore (because of coverage's lack of support for 3.2). [Martin Raspaud] - Fix build badge adress. [Martin Raspaud] - Fix the unicode problem in python3. [Martin Raspaud] v1.1.4 (2015-10-08) ------------------- Fix ~~~ - Bugfix: Accept unicode proj4 strings. Fixes #24. [Martin Raspaud] Other ~~~~~ - update changelog. [Martin Raspaud] - Bump version: 1.1.3 → 1.1.4. [Martin Raspaud] - Add python-configobj as a rpm requirement in setup.cfg. [Martin Raspaud] - Add setup.cfg to allow rpm generation with bdist_rpm. [Martin Raspaud] - Bugfix to address a numpy DeprecationWarning. [Martin Raspaud] Numpy won't take non-integer indices soon, so make index an int. - Merge branch 'release-1.1.3' [Martin Raspaud] - Merge branch 'licence-lgpl' into pre-master. [Martin Raspaud] - Switch to lgplv3, and bump up version number. [Martin Raspaud] - Swith badge to main repository. [Martin Raspaud] - Merge branch 'hotfix-v1.1.2' into pre-master. [Martin Raspaud] - Merge branch 'hotfix-v1.1.2' [Martin Raspaud] - Bump up version number. [Martin Raspaud] - Merge branch 'mitkin-master' into hotfix-v1.1.2. [Martin Raspaud] - Merge branch 'master' of https://github.com/mitkin/pyresample into mitkin-master. [Martin Raspaud] - [test_plot] allow travis to test plot.py. [Mikhail Itkin] - [pip+travis] use `requirements.txt` [Mikhail Itkin] Use `requirements.txt` instead of setuptools' `extras_require` for installing basemap. That is because PyPi basemap version won't find libgeos library so we resolve to use latest basemap from git. `Extras_require` don't allow providing custom links, only PyPi package names, so we have to specify links in requirements.txt. `dependency_links` argument to `setup` call is meant for cruicial dependencies, not custom ones, so we don't use them neither. - [README] markdown + build status. [Mikhail Itkin] * Using markdown extension, added `README` symlink * Added travis build status badge - remove pip `-e` switch. [Mikhail Itkin] - Merge branch 'master' of github.com:mitkin/pyresample. [Mikhail Itkin] - don't use setup.py for basemap installation. [Mikhail Itkin] Instead of putting basemap and matplotlib into `extras_require` install them directly - don't use setup.py for basemap installation. [Mikhail Itkin] Instead of putting basemap and matplotlib into `extras_require` install them directly - Using ubuntu GIS custom ppa. [Mikhail Itkin] Added custom ppa with more up-to-date libgeos dependencies - Install extra requirements using pip functionality. [Mikhail Itkin] - Added more meaningful "quicklooks" name. [Mikhail Itkin] Using quicklooks name as it's what matplotlib and basemap are needed for - [setup] added plotting dependencies. [Mikhail Itkin] pyresample/plot requires two extra dependencies: * matplotlib * basemap - [travis] added system dependencies. [Mikhail Itkin] * matplotlib requires libfreetype6-dev * basemap requires libgeos libgeos-c1 and libgeos-dev - Merge branch 'release-v1.1.1' [Martin Raspaud] - Merge branch 'release-v1.1.1' [Martin Raspaud] - Restore API functionality by importing necessary modules in __init__ [Martin Raspaud] - Merge branch 'release-v1.1.1' into pre-master. [Martin Raspaud] Conflicts: pyresample/geometry.py pyresample/kd_tree.py test/test_geometry.py - Removing old test directory. [Martin Raspaud] - Merge the hotfix and the unittest restructuring into the release branch. [Martin Raspaud] - Merge branch 'release-v1.1.1' into hotfix-1.1.1. [Thomas Lavergne] Conflicts: pyresample/geometry.py test/test_geometry.py test/test_grid.py - Be specific about the valid range of longitudes. [Thomas Lavergne] - Be more specific about the valid longitude range [-180:+180[. Add a test for utils.wrap_longitudes() [Thomas Lavergne] - Add check on valid latitude in [-90:+90] (and associated test) [Thomas Lavergne] - Automatic longitude wrapping (bugfix towards 1.1.1) [Thomas Lavergne] - Merge branch 'release-v1.1.1' into pre-master. [Martin Raspaud] - Add news about new release. [Martin Raspaud] - remove some relative imports. [Martin Raspaud] - Cleanup and bump up version number to v1.1.1. [Martin Raspaud] - Add pykdtree to the list of requirements for travis. [Martin Raspaud] - Add .travis.yml file for automatic testing. [Martin Raspaud] - Correct handling of long type in kd_tree.py for Python 2. [Martin Valgur] - Made testing of a Proj4 string independent of the order of elements inside the string since the order was different on Python 2 and 3. Replaced deprecated failIf with assertFalse. [Martin Valgur] - Multiple small fixes to make the code work on both Python 2 and 3. shmem_as_ndarray() now uses numpy.frombuffer() to provide equivalent functionality. [Martin Valgur] - Got rid of dependencies on the six package. [Martin Valgur] - Applied python-modernize to pyresample. [Martin Valgur] - Update README. [Martin Raspaud] - Merge branch 'pre-master' of https://code.google.com/p/pyresample into pre-master. [Martin Raspaud] - A stray line of code is removed and I take back the recent enhancement concerning swath to swath mapping. [Adam Dybbroe] - Removed debug printouts. [Adam Dybbroe] - More active support of swath to swath reprojection. [Adam Dybbroe] - Add a plot on multiprocessing performance increases. [Martin Raspaud] - Added outer_boundary_corners property to the area def class. [Adam Dybbroe] - corrected docs. [Esben S. Nielsen] - modified uncert count to show above 0. Updated docs to relect uncert option. [Esben S. Nielsen] - cleaned up code a bit in kd_tree.py. [Esben S. Nielsen] - made API doc work with readthedocs and bumped version number. [Esben S. Nielsen] - cleaned up code and tests. [Esben S. Nielsen] - added masking of uncert counts. [Esben S. Nielsen] - test passes again for uncertainty calculations. [Esben S. Nielsen] - changed uncertainty API. First working uncertainty version. [Esben S. Nielsen] - not quite there. [Esben S. Nielsen] - basic uncertainty implemented. [Esben S. Nielsen] - updated docs. [Esben S. Nielsen] - Fixing bug, and adding unittest-main run. [Adam Dybbroe] - Making get_xy_from_lonlat work on arrays of points as well as single points. [Adam Dybbroe] - renamed functions in geometry.py and added proj_x_coords and proj_y_coords properties. [Esben S. Nielsen] - corrected __eq__ in geometry. [Esben S. Nielsen] - Merge branch 'pre-master' of https://code.google.com/p/pyresample into pre-master. [Adam Dybbroe] - now kd_tree resampling selects dtype. [Esben S. Nielsen] - removed random print statement. [Esben S. Nielsen] - made get_capabilites function. [Esben S. Nielsen] - test passes again. [Esben S. Nielsen] - removed caching from geometry. [Esben S. Nielsen] - Merge branch 'pre-master' of https://code.google.com/p/pyresample into pre-master. [Martin Raspaud] - Optimize transform_lonlats with numexpr. [Martin Raspaud] - Unittests should work for both py2.6 and 2.7. [Adam Dybbroe] - updated docs. [Esben S. Nielsen] - fixed unit tests. [Esben S. Nielsen] - Using assertRaises in py2.6 and py2.7 compatible version. [Adam Dybbroe] - bugfix to unittest suite. [Adam Dybbroe] - Trying to make test-functions compatible with both python 2.6 and 2.7. [Adam Dybbroe] - Fixing bug in get_xy_from_lonlat and adding unittests on this function. [Adam Dybbroe] - Adding function get_xy_from_lonlat. [Adam Dybbroe] - integrated pykdtree and handled latlong projection bug. [Esben S. Nielsen] - updated unit tests according to deprecation warnings. [Esben S. Nielsen] - Better parsing of a area definition (allow ':' in value fields) [Lars Orum Rasmussen] - updated docs. [Esben S. Nielsen] - Merge branch 'pre-master' of https://code.google.com/p/pyresample into pre-master. [Martin Raspaud] - doc version. [esn] - improved Basemap integration with globe projections. Updated docs on epsilon. [esn] - Accomodate for allclose behaviour change in numpy 1.6.2. [Martin Raspaud] From 1.6.2 numpy.allclose does not accept arrays that cannot be broadcasted to the same shape. Hence a ValueError catch to return False. - updadet doc for plotting. [Esben S. Nielsen] - updated plot test to use AGG. [Esben S. Nielsen] - Now handles plotting in Plate Carre projection. Added utils.fwhm2sigma function. [Esben S. Nielsen] - Merge branch 'master' of https://code.google.com/p/pyresample. [Esben S. Nielsen] - added pypi info. [Esben S. Nielsen] - built docs. [Esben S. Nielsen] - corrected test_swath.py to account for implementation specific precision. [Esben S. Nielsen] - more datatype specifications. [Esben S. Nielsen] - removed warning check for python 2.5. [Esben S. Nielsen] - corrected multi channnel bug. Added warnings for potential problematic neighbour query condition. [Esben S. Nielsen] - Now str() generates a unique string for area and coordinate definition object. [Lars Orum Rasmussen] - corrected manifest so doc images are included. [Esben S. Nielsen] - Moved tests dir to test. Updated MANIFEST.in. [Esben S. Nielsen] - Added MANIFEST.in. [Esben S. Nielsen] - Applied setup.py patches. Made plotting more robust. [Esben S. Nielsen] - applied patch for getting version number. [Esben S. Nielsen] - Bugfixing quicklooks. [StorPipfugl] - Updated docs. [StorPipfugl] - Updated docs. [StorPipfugl] - Updated docs. [StorPipfugl] - Added Basemap integration. [StorPipfugl] - Added Basemap integration. [StorPipfugl] - Updated docs. [StorPipfugl] - Rebuild docs. [StorPipfugl] - Made setup.py more robust. [StorPipfugl] - New doc version. [StorPipfugl] - Updated tests. [StorPipfugl] - Reduced size of linesample arrays. Restructures kd_tree query to remove redundant lon lat calculations. [StorPipfugl] - Added geographic filtering. Swaths can now be concatenated and appended. User no langer have to ravel data before resampling. [StorPipfugl] - Updated docs. [StorPipfugl] - Updated install_requires. [StorPipfugl] - version 0.7.3. [StorPipfugl] - Bugfixes: Correct number of channels in empty result set. Resampling of masked data to 1d swath now works. [StorPipfugl] - Added Martin's spherical geometry operations. Updated documentation. [StorPipfugl] - Added equal and not equal operators for geometry defs. Restructured the geometry module to be pickable. Added correct handling of empty result data sets. [StorPipfugl] - Incomplete - taskpyresample. [StorPipfugl] - Set svn:mime-type. [StorPipfugl] - Corrected doc errors. [StorPipfugl] - Removed dist dir. [StorPipfugl] - No commit message. [StorPipfugl] - Updated documentation. New release. [StorPipfugl] - Started updating docstrings. [StorPipfugl] - Restructured API. [StorPipfugl] - Now uses geometry types. Introduced API symmetry between swath->grid and grid->swath resampling. [StorPipfugl] - Consolidated version tag. [StorPipfugl] - Mime types set. [StorPipfugl] - Mime types set. [StorPipfugl] - Removed test. [StorPipfugl] - Removed unneeded function. [StorPipfugl] - Mime types set. [StorPipfugl] - Mime types set. [StorPipfugl] - No commit message. [StorPipfugl] - Moved to Google Code under GPLv3 license. [StorPipfugl] - moved to Google Code. [StorPipfugl] pyresample-1.2.9/docs/000077500000000000000000000000001302372600000146255ustar00rootroot00000000000000pyresample-1.2.9/docs/Makefile000066400000000000000000000061051302372600000162670ustar00rootroot00000000000000# Makefile for Sphinx documentation # # You can set these variables from the command line. SPHINXOPTS = -a SPHINXBUILD = sphinx-build PAPER = BUILDDIR = build # Internal variables. PAPEROPT_a4 = -D latex_paper_size=a4 PAPEROPT_letter = -D latex_paper_size=letter ALLSPHINXOPTS = -d $(BUILDDIR)/doctrees $(PAPEROPT_$(PAPER)) $(SPHINXOPTS) source .PHONY: help clean html dirhtml pickle json htmlhelp qthelp latex changes linkcheck doctest help: @echo "Please use \`make ' where is one of" @echo " html to make standalone HTML files" @echo " dirhtml to make HTML files named index.html in directories" @echo " pickle to make pickle files" @echo " json to make JSON files" @echo " htmlhelp to make HTML files and a HTML help project" @echo " qthelp to make HTML files and a qthelp project" @echo " latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter" @echo " changes to make an overview of all changed/added/deprecated items" @echo " linkcheck to check all external links for integrity" @echo " doctest to run all doctests embedded in the documentation (if enabled)" clean: -rm -rf $(BUILDDIR)/* html: $(SPHINXBUILD) -b html $(ALLSPHINXOPTS) $(BUILDDIR)/html @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/html." dirhtml: $(SPHINXBUILD) -b dirhtml $(ALLSPHINXOPTS) $(BUILDDIR)/dirhtml @echo @echo "Build finished. The HTML pages are in $(BUILDDIR)/dirhtml." pickle: $(SPHINXBUILD) -b pickle $(ALLSPHINXOPTS) $(BUILDDIR)/pickle @echo @echo "Build finished; now you can process the pickle files." json: $(SPHINXBUILD) -b json $(ALLSPHINXOPTS) $(BUILDDIR)/json @echo @echo "Build finished; now you can process the JSON files." htmlhelp: $(SPHINXBUILD) -b htmlhelp $(ALLSPHINXOPTS) $(BUILDDIR)/htmlhelp @echo @echo "Build finished; now you can run HTML Help Workshop with the" \ ".hhp project file in $(BUILDDIR)/htmlhelp." qthelp: $(SPHINXBUILD) -b qthelp $(ALLSPHINXOPTS) $(BUILDDIR)/qthelp @echo @echo "Build finished; now you can run "qcollectiongenerator" with the" \ ".qhcp project file in $(BUILDDIR)/qthelp, like this:" @echo "# qcollectiongenerator $(BUILDDIR)/qthelp/pyresample.qhcp" @echo "To view the help file:" @echo "# assistant -collectionFile $(BUILDDIR)/qthelp/pyresample.qhc" latex: $(SPHINXBUILD) -b latex $(ALLSPHINXOPTS) $(BUILDDIR)/latex @echo @echo "Build finished; the LaTeX files are in $(BUILDDIR)/latex." @echo "Run \`make all-pdf' or \`make all-ps' in that directory to" \ "run these through (pdf)latex." changes: $(SPHINXBUILD) -b changes $(ALLSPHINXOPTS) $(BUILDDIR)/changes @echo @echo "The overview file is in $(BUILDDIR)/changes." linkcheck: $(SPHINXBUILD) -b linkcheck $(ALLSPHINXOPTS) $(BUILDDIR)/linkcheck @echo @echo "Link check complete; look for any errors in the above output " \ "or in $(BUILDDIR)/linkcheck/output.txt." doctest: $(SPHINXBUILD) -b doctest $(ALLSPHINXOPTS) $(BUILDDIR)/doctest @echo "Testing of doctests in the sources finished, look at the " \ "results in $(BUILDDIR)/doctest/output.txt." pyresample-1.2.9/docs/areas.cfg000066400000000000000000000220741302372600000164060ustar00rootroot00000000000000REGION: afghanistan { NAME: Afghanistan PCS_ID: merc PCS_DEF: proj=merc,lat_ts=35,a=6370997.0,lon_0=67.5,lat_0=35 XSIZE: 1600 YSIZE: 1600 AREA_EXTENT: (-1600000.0, 1600000.0, 1600000.0, 4800000.0) }; REGION: EuropeCanary { NAME: Northern globe MSG image 0 degrees PCS_ID: geos0 PCS_DEF: proj=geos, lon_0=0.0, a=6378169.00, b=6356583.80, h=35785831.0 XSIZE: 3000 YSIZE: 1200 #AREA_EXTENT: (-4820647.75308, 1967264.34239, 4180561.74437, 5567748.14137) #AREA_EXTENT: (-4820147.6858850112, 1966764.2751930435, 4181061.8115659896, 5567248.074173444) AREA_EXTENT: (-4823148.0890508275, 1969764.6783588605, 4178061.4084001728, 5570248.4773392612) }; REGION: AfHorn { NAME: Eastern globe MSG image 0 degrees PCS_ID: geos0 PCS_DEF: proj=geos, lon_0=0.0, a=6378169.00, b=6356583.80, h=35785831.0 XSIZE: 1100 YSIZE: 1600 #AREA_EXTENT: (2266804.5917747435, -1330678.8040398397, 5567248.074173444, 3469966.2612673608) AREA_EXTENT: (2263804.1886089267, -1327678.4008740226, 5564247.6710076267, 3472966.6644331776) }; REGION: afhorn { NAME: Africa horn 3km resolution PCS_ID: merc50 PCS_DEF: proj=merc,ellps=bessel,lon_0=50.0 XSIZE: 1622 YSIZE: 1622 AREA_EXTENT: (-2432000.0,-1130348.139543,2432000.0,3733651.860457) }; REGION: met09globe { NAME: Cropped globe MSG image 0 degrees PCS_ID: geos0 PCS_DEF: proj=geos, lon_0=0.0, a=6378169.00, b=6356583.80, h=35785831.0 #PCS_DEF: proj=geos, lon_0=0.0, a=6378144.0, b=6356759.0, h=35785831.0, rf=295.49 XSIZE: 3620 YSIZE: 3620 #AREA_EXTENT: (-5430729.7301287707, -5430729.7301287707, 5430729.7301287707, 5430729.7301287707) AREA_EXTENT: (-5432229.9317116784, -5429229.5285458621, 5429229.5285458621, 5432229.9317116784) }; REGION: met09globeFull { NAME: Full globe MSG image 0 degrees PCS_ID: geos0 PCS_DEF: proj=geos, lon_0=0.0, a=6378169.00, b=6356583.80, h=35785831.0 #PCS_DEF: proj=geos, lon_0=0.0, a=6378144.0, b=6356759.0, h=35785831.0, rf=295.49 XSIZE: 3712 YSIZE: 3712 AREA_EXTENT: (-5570248.4773392612, -5567248.074173444, 5567248.074173444, 5570248.4773392612) }; REGION: met07globe { NAME: Full globe IODC image 57 degrees PCS_ID: geos57 PCS_DEF: proj=geos, lon_0=57.0, a=6378140.00, b=6356755.0, h=35785831.0 # PCS_DEF: proj=geos, lon_0=57.0, a=6378169.0, b=6356584.0, h=35785831.0, rf=295.49 XSIZE: 2500 YSIZE: 2500 AREA_EXTENT: (-5621225.237846375, -5621225.237846375, 5621225.237846375, 5621225.237846375) }; REGION: germ { NAME: Germany PCS_ID: ps50n1 PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=5,lat_ts=50,a=6378144.0,b=6356759.0 XSIZE: 1024 YSIZE: 1024 AREA_EXTENT: (-155100.436345,-4441495.37946,868899.563655,-3417495.37946) }; REGION: euro4 { NAME: Euro 4km area - Europe PCS_ID: ps60n PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=14,lat_ts=60 XSIZE: 1024 YSIZE: 1024 AREA_EXTENT: (-2717181.7304994687,-5571048.1403121399,1378818.2695005313,-1475048.1403121399) }; REGION: MSGHRVN { NAME: High resolution northern quarter globe MSG image 0 degrees PCS_ID: geos0 PCS_DEF: proj=geos, lon_0=0.0, a=6378144.0, b=6356759.0, h=35785831.0, rf=295.49 XSIZE: 11136 YSIZE: 2784 AREA_EXTENT: (-5568742.4, 2655354.0, 5568742.4, 5439725.2) }; REGION: scan { NAME: Scandinavia PCS_ID: ps60n PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=14,lat_ts=60 XSIZE: 512 YSIZE: 512 AREA_EXTENT: (-1268854.1266382949, -4150234.8425892727, 779145.8733617051, -2102234.8425892727) }; REGION: scan2 { NAME: Scandinavia - 2km area PCS_ID: ps60n PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=14,lat_ts=60 XSIZE: 1024 YSIZE: 1024 AREA_EXTENT: (-1268854.1266382949, -4150234.8425892727, 779145.8733617051, -2102234.8425892727) }; REGION: scan1 { NAME: Scandinavia - 1km area PCS_ID: ps60n PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=14,lat_ts=60 XSIZE: 2048 YSIZE: 2088 AREA_EXTENT: (-1268854.1266382949, -4150234.8425892727, 779145.8733617051, -2062234.8425892727) }; REGION: mesanX { NAME: Mesan-X rotated lon/lat 1.8km PCS_ID: mesan PCS_DEF: proj=ob_tran,o_proj=eqc,o_lat_p=30,o_lon_p=10,lon_0=-10,a=6371000.0 XSIZE: 1476 YSIZE: 1608 AREA_EXTENT: (1067435.7598983962, -1278764.8903419089, 3791765.9965939857, 1690140.6680267097) }; REGION: mesanE { NAME: Europe Mesan rotated lon/lat 1.8km PCS_ID: mesan PCS_DEF: proj=ob_tran,o_proj=eqc,o_lat_p=30,o_lon_p=10,lon_0=-10,a=6371000.0 XSIZE: 5093 YSIZE: 6294 AREA_EXTENT: (289083.00056196708, -2957836.6467769896, 5381881.121371055, 3335826.6850212598) }; REGION: baws { NAME: BAWS PCS_ID: baws PCS_DEF: proj=aea,ellps=bessel,lon_0=14,lat_1=60,lat_2=60 XSIZE: 1400 YSIZE: 1400 AREA_EXTENT: (-475617, 5324430, 924383, 6724430) }; REGION: eurotv { NAME: Europe TV - 6.2x5.0km PCS_ID: eurotv PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=14,lat_ts=60,a=6378144.0,b=6356759.0 XSIZE: 1024 YSIZE: 1024 AREA_EXTENT: (-3503748.8201907813, -6589593.1340587894, 2842567.6359087573, -1499856.5846593212) }; REGION: eurotv4n { NAME: Europe TV4 - 4.1x4.1km PCS_ID: eurotv4n PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=14,lat_ts=60,a=6378144.0,b=6356759.0 XSIZE: 2048 YSIZE: 1152 AREA_EXTENT: (-5103428.6786669521, -6772478.6005340703, 3293371.3213330479, -2049278.6005340703) }; REGION: eurol { NAME: Euro 3.0km area - Europe PCS_ID: ps60wgs84 PCS_DEF: proj=stere,ellps=WGS84,lat_0=90,lon_0=0,lat_ts=60 XSIZE: 2560 YSIZE: 2048 AREA_EXTENT: (-3780000.0, -7644000.0, 3900000.0, -1500000.0) }; REGION: scanl { NAME: Scandinavia - Large PCS_ID: ps60wgs84 PCS_DEF: proj=stere,ellps=WGS84,lat_0=90,lon_0=0,lat_ts=60 XSIZE: 2900 YSIZE: 2900 AREA_EXTENT: (-900000.0, -4500000.0,2000000.0, -1600000.0) }; REGION: euron1 { NAME: Northern Europe - 1km PCS_ID: ps60wgs84 PCS_DEF: proj=stere,ellps=WGS84,lat_0=90,lon_0=0,lat_ts=60 XSIZE: 3072 YSIZE: 3072 AREA_EXTENT: (-1000000.0, -4500000.0, 2072000.0, -1428000.0) }; REGION: nsea { NAME: North Baltic Sea PCS_ID: merc PCS_DEF: proj=merc,ellps=WGS84,lat_ts=0,lon_0=15 XSIZE: 1024 YSIZE: 1024 AREA_EXTENT: (-322789.07638000086, 7784901.986829306, 1725210.9236199991, 9832901.9868293069) }; REGION: ssea { NAME: South Baltic Sea PCS_ID: merc PCS_DEF: proj=merc,ellps=WGS84,lat_ts=0,lon_0=15 XSIZE: 1024 YSIZE: 1024 AREA_EXTENT: (-801407.36204689811, 7003690.6636438016, 1246592.6379531019, 9051690.6636438016) }; REGION: euro { NAME: Euro area - Europe PCS_ID: ps60n PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=14,lat_ts=60 XSIZE: 512 YSIZE: 512 AREA_EXTENT: (-2717181.7304994687,-5571048.1403121399,1378818.2695005313,-1475048.1403121399) }; REGION: euro_north { NAME: Europe 3km/pixel PCS_ID: euro_north PCS_DEF: proj=stere,lon_0=8.00,lat_0=50.00,lat_ts=50.00,ellps=WGS84 XSIZE: 800 YSIZE: 870 AREA_EXTENT: (-1370912.16,-909970.17,1029087.84,1700029.83) }; REGION: ease_sh { NAME: Antarctic EASE grid PCS_ID: ease_sh PCS_DEF: proj=laea, lat_0=-90, lon_0=0, a=6371228.0, units=m XSIZE: 425 YSIZE: 425 AREA_EXTENT: (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) }; REGION: ease_nh { NAME: Arctic EASE grid PCS_ID: ease_nh PCS_DEF: proj=laea, lat_0=90, lon_0=0, a=6371228.0, units=m XSIZE: 425 YSIZE: 425 AREA_EXTENT: (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) }; # VIIRS test areas: REGION: npp_sample_m { NAME: North America - NPP sample data - M-bands PCS_ID: laeaw12060 PCS_DEF: proj=laea,a=6370997.0,lat_0=60.0,lon_0=-120.0 XSIZE: 1500 YSIZE: 1500 AREA_EXTENT: (-1700000, -1400000, 1100000, 1400000) }; REGION: npp_sample_i { NAME: North America - NPP sample data - I-bands PCS_ID: laeaw12060 PCS_DEF: proj=laea,a=6370997.0,lat_0=60.0,lon_0=-120.0 XSIZE: 1200 YSIZE: 800 AREA_EXTENT: (-200000, 100000, 400000, 500000) }; REGION: scan500m { NAME: Scandinavia - 500m area PCS_ID: ps60n PCS_DEF: proj=stere,ellps=bessel,lat_0=90,lon_0=14,lat_ts=60 XSIZE: 4096 YSIZE: 4176 AREA_EXTENT: (-1268854.1266382949, -4150234.8425892727, 779145.8733617051, -2062234.8425892727) }; pyresample-1.2.9/docs/requirements.txt000066400000000000000000000000001302372600000200770ustar00rootroot00000000000000pyresample-1.2.9/docs/source/000077500000000000000000000000001302372600000161255ustar00rootroot00000000000000pyresample-1.2.9/docs/source/API.rst000066400000000000000000000013171302372600000172720ustar00rootroot00000000000000pyresample API ====================== pyresample.geometry --------------------------------- .. automodule:: geometry :members: pyresample.image --------------------------------- .. automodule:: image :members: pyresample.grid --------------------------------- .. automodule:: grid :members: pyresample.kd_tree --------------------------------- .. automodule:: kd_tree :members: pyresample.utils --------------------------------- .. automodule:: utils :members: pyresample.data_reduce --------------------------------- .. automodule:: data_reduce :members: pyresample.plot --------------------------------- .. automodule:: plot :members: pyresample.ewa -------------- .. automodule:: ewa :members: pyresample-1.2.9/docs/source/_static/000077500000000000000000000000001302372600000175535ustar00rootroot00000000000000pyresample-1.2.9/docs/source/_static/images/000077500000000000000000000000001302372600000210205ustar00rootroot00000000000000pyresample-1.2.9/docs/source/_static/images/tb37_multi.png000066400000000000000000007356601302372600000235400ustar00rootroot00000000000000PNG  IHDRW[YsBIT|d pHYsaa?i IDATxw|eſ3B TRUAAE XPWvsY]VT\Y V @JB3cw JI!JLy;{<9b 6lذaÆJZ aÆ 6l8`+6lذaÆJMlذaÆ 6*6aÆ 6lبDʆ 6lذaa+6lذaÆJMlذaÆ 6*6aÆ 6lبD8I,\͛zM6lذaÆ  Kʪ8BZp!GذaÆ 6~gfԨQ5 G#"W-Z4h\s}~^^˖-cĈ߿ V^-?O޽u'2x 6nٳu~6Nq>cڷoOaa!w}7|/fΜ9|'dffҹsgB jl p~MC(8(:Dڭ4݊-o~C<Ι|9]*g4/ǿ|L!6$q8\QQ0Da+ntT 8Q0pE 1\h8AGE@N#D'qҁ8 _^o!--4p@vŷ~(G /0(**:iɊ7п~c < 2^{nu뢪ò8k,[CAq!#ӗa`"8)B9 G |o:̻p&f^ơY8f.w_$sDȎB:*44Ah!"e܀I"xr Z%#7T "F :*")' SF0^< PN9)1N":ne >B()8HrRh;c HaF~aÆ':LdXJt^RpM!>#BŸJ(_#.iC~&MS19uP z`-ftR? 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If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. #sys.path.insert(0, '/opt/lib/python2.5/site-packages') sys.path.insert(0, os.path.abspath('../../')) sys.path.insert(0, os.path.abspath('../../pyresample')) # sys.path.append('') # print sys.path # -- General configuration ----------------------------------------------- # Add any Sphinx extension module names here, as strings. They can be extensions # coming with Sphinx (named 'sphinx.ext.*') or your custom ones. extensions = [ 'sphinx.ext.doctest', 'sphinx.ext.autodoc', 'sphinx.ext.napoleon'] # DocTest Settings doctest_test_doctest_blocks = '' # Napoleon Settings (to support numpy style docs) napoleon_numpy_docstring = False napoleon_numpy_docstring = True napoleon_use_admonition_for_examples = True napoleon_use_admonition_for_notes = True napoleon_use_admonition_for_references = True # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix of source filenames. source_suffix = '.rst' # The encoding of source files. #source_encoding = 'utf-8' # The master toctree document. master_doc = 'index' # General information about the project. project = u'pyresample' copyright = u'2013, Esben S. Nielsen' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # import version as current_version # The short X.Y version. version = current_version.__version__ # The full version, including alpha/beta/rc tags. release = current_version.__version__ # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. #language = None # There are two options for replacing |today|: either, you set today to some # non-false value, then it is used: #today = '' # Else, today_fmt is used as the format for a strftime call. #today_fmt = '%B %d, %Y' # List of documents that shouldn't be included in the build. #unused_docs = [] # List of directories, relative to source directory, that shouldn't be searched # for source files. exclude_trees = [] # The reST default role (used for this markup: `text`) to use for all documents. #default_role = None # If true, '()' will be appended to :func: etc. cross-reference text. #add_function_parentheses = True # If true, the current module name will be prepended to all description # unit titles (such as .. function::). #add_module_names = True # If true, sectionauthor and moduleauthor directives will be shown in the # output. They are ignored by default. #show_authors = False # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # A list of ignored prefixes for module index sorting. #modindex_common_prefix = [] # -- Options for HTML output --------------------------------------------- # The theme to use for HTML and HTML Help pages. Major themes that come with # Sphinx are currently 'default' and 'sphinxdoc'. html_theme = 'default' # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. #html_theme_options = {} # Add any paths that contain custom themes here, relative to this directory. #html_theme_path = [] # The name for this set of Sphinx documents. If None, it defaults to # " v documentation". #html_title = None # A shorter title for the navigation bar. Default is the same as html_title. #html_short_title = None # The name of an image file (relative to this directory) to place at the top # of the sidebar. #html_logo = None # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 # pixels large. #html_favicon = None # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # If not '', a 'Last updated on:' timestamp is inserted at every page bottom, # using the given strftime format. #html_last_updated_fmt = '%b %d, %Y' # If true, SmartyPants will be used to convert quotes and dashes to # typographically correct entities. #html_use_smartypants = True # Custom sidebar templates, maps document names to template names. #html_sidebars = {} # Additional templates that should be rendered to pages, maps page names to # template names. #html_additional_pages = {} # If false, no module index is generated. #html_use_modindex = True # If false, no index is generated. #html_use_index = True # If true, the index is split into individual pages for each letter. #html_split_index = False # If true, links to the reST sources are added to the pages. #html_show_sourcelink = True # If true, an OpenSearch description file will be output, and all pages will # contain a tag referring to it. The value of this option must be the # base URL from which the finished HTML is served. #html_use_opensearch = '' # If nonempty, this is the file name suffix for HTML files (e.g. ".xhtml"). #html_file_suffix = '' # Output file base name for HTML help builder. htmlhelp_basename = 'pyresampledoc' # -- Options for LaTeX output -------------------------------------------- # The paper size ('letter' or 'a4'). #latex_paper_size = 'letter' # The font size ('10pt', '11pt' or '12pt'). #latex_font_size = '10pt' # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, author, documentclass [howto/manual]). latex_documents = [ ('index', 'pyresample.tex', u'pyresample Documentation', u'Esben S. Nielsen', 'manual'), ] # The name of an image file (relative to this directory) to place at the top of # the title page. #latex_logo = None # For "manual" documents, if this is true, then toplevel headings are parts, # not chapters. #latex_use_parts = False # Additional stuff for the LaTeX preamble. #latex_preamble = '' # Documents to append as an appendix to all manuals. #latex_appendices = [] # If false, no module index is generated. #latex_use_modindex = True pyresample-1.2.9/docs/source/data_reduce.rst000066400000000000000000000050331302372600000211200ustar00rootroot00000000000000Reduction of swath data ======================= Given a swath and a cartesian grid or grid lons and lats pyresample can reduce the swath data to only the relevant part covering the grid area. The reduction is coarse in order not to risk removing relevant data. From **data_reduce** the function **swath_from_lonlat_grid** can be used to reduce the swath data set to the area covering the lon lat grid .. doctest:: >>> import numpy as np >>> from pyresample import geometry, data_reduce >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> grid_lons, grid_lats = area_def.get_lonlats() >>> reduced_lons, reduced_lats, reduced_data = \ ... data_reduce.swath_from_lonlat_grid(grid_lons, grid_lats, ... lons, lats, data, ... radius_of_influence=3000) **radius_of_influence** is used to calculate a buffer zone around the grid where swath data points are not reduced. The function **get_valid_index_from_lonlat_grid** returns a boolean array of same size as the swath indicating the relevant swath data points compared to the grid .. doctest:: >>> import numpy as np >>> from pyresample import geometry, data_reduce >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> grid_lons, grid_lats = area_def.get_lonlats() >>> valid_index = data_reduce.get_valid_index_from_lonlat_grid(grid_lons, grid_lats, ... lons, lats, ... radius_of_influence=3000) pyresample-1.2.9/docs/source/geo_def.rst000066400000000000000000000272361302372600000202610ustar00rootroot00000000000000Geometry definitions ==================== The module **pyresample.geometry** contains classes for describing different kinds of types of remote sensing data geometries. The use of the different classes is described below. Remarks ------- All longitudes and latitudes provided to **pyresample.geometry** must be in degrees. Longitudes must additionally be in the [-180;+180[ validity range. As of version 1.1.1, the **pyresample.geometry** contructors will check the range of longitude values, send a warning if some of them fall outside validity range, and automatically correct the invalid values into [-180;+180[. Use function **utils.wrap_longitudes** for wrapping longitudes yourself. AreaDefinition -------------- The cartographic definition of grid areas used by Pyresample is contained in an object of type AreaDefintion. The following arguments are needed to initialize an area: * **area_id** ID of area * **name**: Description * **proj_id**: ID of projection * **proj_dict**: Proj4 parameters as dict * **x_size**: Number of grid columns * **y_size**: Number of grid rows * **area_extent**: (x_ll, y_ll, x_ur, y_ur) where * **x_ll**: projection x coordinate of lower left corner of lower left pixel * **y_ll**: projection y coordinate of lower left corner of lower left pixel * **x_ur**: projection x coordinate of upper right corner of upper right pixel * **y_ur**: projection y coordinate of upper right corner of upper right pixel Creating an area definition: .. doctest:: >>> from pyresample import geometry >>> area_id = 'ease_sh' >>> name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = 'proj=laea, lat_0=-90, lon_0=0, a=6371228.0, units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> proj_dict = {'a': '6371228.0', 'units': 'm', 'lon_0': '0', ... 'proj': 'laea', 'lat_0': '-90'} >>> area_def = geometry.AreaDefinition(area_id, name, proj_id, proj_dict, x_size, ... y_size, area_extent) >>> print(area_def) Area ID: ease_sh Name: Antarctic EASE grid Projection ID: ease_sh Projection: {'a': '6371228.0', 'lat_0': '-90', 'lon_0': '0', 'proj': 'laea', 'units': 'm'} Number of columns: 425 Number of rows: 425 Area extent: (-5326849.0625, -5326849.0625, 5326849.0625, 5326849.0625) pyresample.utils **************** The utils module of pyresample has convenience functions for constructing area defintions. The function **get_area_def** can construct an area definition based on area extent and a proj4-string or a list of proj4 arguments. .. doctest:: >>> from pyresample import utils >>> area_id = 'ease_sh' >>> area_name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> area_def = utils.get_area_def(area_id, area_name, proj_id, proj4_args, ... x_size, y_size, area_extent) >>> print(area_def) Area ID: ease_sh Name: Antarctic EASE grid Projection ID: ease_sh Projection: {'a': '6371228.0', 'lat_0': '-90', 'lon_0': '0', 'proj': 'laea', 'units': 'm'} Number of columns: 425 Number of rows: 425 Area extent: (-5326849.0625, -5326849.0625, 5326849.0625, 5326849.0625) The **load_area** function can be used to parse area definitions from a configuration file. Assuming the file **areas.cfg** exists with the following content .. code-block:: bash REGION: ease_sh { NAME: Antarctic EASE grid PCS_ID: ease_sh PCS_DEF: proj=laea, lat_0=-90, lon_0=0, a=6371228.0, units=m XSIZE: 425 YSIZE: 425 AREA_EXTENT: (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) }; REGION: ease_nh { NAME: Arctic EASE grid PCS_ID: ease_nh PCS_DEF: proj=laea, lat_0=90, lon_0=0, a=6371228.0, units=m XSIZE: 425 YSIZE: 425 AREA_EXTENT: (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) }; An area definition dict can be read using .. doctest:: >>> from pyresample import utils >>> area = utils.load_area('areas.cfg', 'ease_nh') >>> print(area) Area ID: ease_nh Name: Arctic EASE grid Projection ID: ease_nh Projection: {'a': '6371228.0', 'lat_0': '90', 'lon_0': '0', 'proj': 'laea', 'units': 'm'} Number of columns: 425 Number of rows: 425 Area extent: (-5326849.0625, -5326849.0625, 5326849.0625, 5326849.0625) Note: In the configuration file **REGION** maps to **area_id** and **PCS_ID** maps to **proj_id**. Several area definitions can be read at once using the region names in an argument list .. doctest:: >>> from pyresample import utils >>> nh_def, sh_def = utils.load_area('areas.cfg', 'ease_nh', 'ease_sh') >>> print(sh_def) Area ID: ease_sh Name: Antarctic EASE grid Projection ID: ease_sh Projection: {'a': '6371228.0', 'lat_0': '-90', 'lon_0': '0', 'proj': 'laea', 'units': 'm'} Number of columns: 425 Number of rows: 425 Area extent: (-5326849.0625, -5326849.0625, 5326849.0625, 5326849.0625) GridDefinition -------------- If the lons and lats grid values are known the area definition information can be skipped for some types of resampling by using a GridDefinition object instead an AreaDefinition object. .. doctest:: >>> import numpy as np >>> from pyresample import geometry >>> lons = np.ones((100, 100)) >>> lats = np.ones((100, 100)) >>> grid_def = geometry.GridDefinition(lons=lons, lats=lats) SwathDefinition --------------- A swath is defined by the lon and lat values of the data points .. doctest:: >>> import numpy as np >>> from pyresample import geometry >>> lons = np.ones((500, 20)) >>> lats = np.ones((500, 20)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) Two swaths can be concatenated if their coloumn count matches .. doctest:: >>> import numpy as np >>> from pyresample import geometry >>> lons1 = np.ones((500, 20)) >>> lats1 = np.ones((500, 20)) >>> swath_def1 = geometry.SwathDefinition(lons=lons1, lats=lats1) >>> lons2 = np.ones((300, 20)) >>> lats2 = np.ones((300, 20)) >>> swath_def2 = geometry.SwathDefinition(lons=lons2, lats=lats2) >>> swath_def3 = swath_def1.concatenate(swath_def2) Geographic coordinates and boundaries ------------------------------------- A ***definition** object allows for retrieval of geographic coordinates using array slicing (slice stepping is currently not supported). All ***definition** objects exposes the coordinates **lons**, **lats** and **cartesian_coords**. AreaDefinition exposes the full set of projection coordinates as **projection_x_coords** and **projection_y_coords** Get full coordinate set: .. doctest:: >>> from pyresample import utils >>> area_id = 'ease_sh' >>> area_name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> area_def = utils.get_area_def(area_id, area_name, proj_id, proj4_args, ... x_size, y_size, area_extent) >>> lons, lats = area_def.get_lonlats() Get slice of coordinate set: .. doctest:: >>> from pyresample import utils >>> area_id = 'ease_sh' >>> area_name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> area_def = utils.get_area_def(area_id, area_name, proj_id, proj4_args, ... x_size, y_size, area_extent) >>> cart_subset = area_def.get_cartesian_coords()[100:200, 350:] If only the 1D range of a projection coordinate is required it can be extraxted using the **proj_x_coord** or **proj_y_coords** property of a geographic coordinate .. doctest:: >>> from pyresample import utils >>> area_id = 'ease_sh' >>> area_name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> area_def = utils.get_area_def(area_id, area_name, proj_id, proj4_args, ... x_size, y_size, area_extent) >>> proj_x_range = area_def.proj_x_coords Spherical geometry operations ----------------------------- Some basic spherical operations are available for ***definition** objects. The spherical geometry operations are calculated based on the corners of a GeometryDefinition (2D SwathDefinition or Grid/AreaDefinition) and assuming the edges are great circle arcs. It can be tested if geometries overlaps .. doctest:: >>> import numpy as np >>> from pyresample import utils >>> area_id = 'ease_sh' >>> area_name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> area_def = utils.get_area_def(area_id, area_name, proj_id, proj4_args, ... x_size, y_size, area_extent) >>> lons = np.array([[-40, -11.1], [9.5, 19.4], [65.5, 47.5], [90.3, 72.3]]) >>> lats = np.array([[-70.1, -58.3], [-78.8, -63.4], [-73, -57.6], [-59.5, -50]]) >>> swath_def = geometry.SwathDefinition(lons, lats) >>> print(swath_def.overlaps(area_def)) True The fraction of overlap can be calculated .. doctest:: >>> import numpy as np >>> from pyresample import utils >>> area_id = 'ease_sh' >>> area_name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> area_def = utils.get_area_def(area_id, area_name, proj_id, proj4_args, ... x_size, y_size, area_extent) >>> lons = np.array([[-40, -11.1], [9.5, 19.4], [65.5, 47.5], [90.3, 72.3]]) >>> lats = np.array([[-70.1, -58.3], [-78.8, -63.4], [-73, -57.6], [-59.5, -50]]) >>> swath_def = geometry.SwathDefinition(lons, lats) >>> overlap_fraction = swath_def.overlap_rate(area_def) And the polygon defining the (great circle) boundaries over the overlapping area can be calculated .. doctest:: >>> import numpy as np >>> from pyresample import utils >>> area_id = 'ease_sh' >>> area_name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> area_def = utils.get_area_def(area_id, area_name, proj_id, proj4_args, ... x_size, y_size, area_extent) >>> lons = np.array([[-40, -11.1], [9.5, 19.4], [65.5, 47.5], [90.3, 72.3]]) >>> lats = np.array([[-70.1, -58.3], [-78.8, -63.4], [-73, -57.6], [-59.5, -50]]) >>> swath_def = geometry.SwathDefinition(lons, lats) >>> overlap_polygon = swath_def.intersection(area_def) It can be tested if a (lon, lat) point is inside a GeometryDefinition .. doctest:: >>> import numpy as np >>> from pyresample import utils >>> area_id = 'ease_sh' >>> area_name = 'Antarctic EASE grid' >>> proj_id = 'ease_sh' >>> proj4_args = '+proj=laea +lat_0=-90 +lon_0=0 +a=6371228.0 +units=m' >>> x_size = 425 >>> y_size = 425 >>> area_extent = (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) >>> area_def = utils.get_area_def(area_id, area_name, proj_id, proj4_args, ... x_size, y_size, area_extent) >>> print((0, -90) in area_def) True pyresample-1.2.9/docs/source/geo_filter.rst000066400000000000000000000031601302372600000207760ustar00rootroot00000000000000Geographic filtering ==================== The module **pyresample.geo_filter** contains classes to filter geo data GridFilter ---------- Allows for filtering of data based on a geographic mask. The filtering uses a bucket sampling approach. The following example shows how to select data falling in the upper left and lower right quadrant of a full globe Plate Carrée projection using an 8x8 filter mask .. doctest:: >>> import numpy as np >>> from pyresample import geometry, geo_filter >>> lons = np.array([-170, -30, 30, 170]) >>> lats = np.array([20, -40, 50, -80]) >>> swath_def = geometry.SwathDefinition(lons, lats) >>> data = np.array([1, 2, 3, 4]) >>> filter_area = geometry.AreaDefinition('test', 'test', 'test', ... {'proj' : 'eqc', 'lon_0' : 0.0, 'lat_0' : 0.0}, ... 8, 8, ... (-20037508.34, -10018754.17, 20037508.34, 10018754.17) ... ) >>> filter = np.array([[1, 1, 1, 1, 0, 0, 0, 0], ... [1, 1, 1, 1, 0, 0, 0, 0], ... [1, 1, 1, 1, 0, 0, 0, 0], ... [1, 1, 1, 1, 0, 0, 0, 0], ... [0, 0, 0, 0, 1, 1, 1, 1], ... [0, 0, 0, 0, 1, 1, 1, 1], ... [0, 0, 0, 0, 1, 1, 1, 1], ... [0, 0, 0, 0, 1, 1, 1, 1], ... ]) >>> grid_filter = geo_filter.GridFilter(filter_area, filter) >>> swath_def_filtered, data_filtered = grid_filter.filter(swath_def, data) Input swath_def and data must match as described in :ref:`swath`. The returned data will always have a 1D geometry_def and if multiple channels are present the filtered data will have the shape (number_of_points, channels).pyresample-1.2.9/docs/source/grid.rst000066400000000000000000000172671302372600000176210ustar00rootroot00000000000000Resampling of gridded data ========================== Pyresample can be used to resample from an existing grid to another. Nearest neighbour resampling is used. pyresample.image ---------------- A grid can be stored in an object of type **ImageContainer** along with its area definition. An object of type **ImageContainer** allows for calculating resampling using preprocessed arrays using the method **get_array_from_linesample** Resampling can be done using descendants of **ImageContainer** and calling their **resample** method. An **ImageContainerQuick** object allows for the grid to be resampled to a new area defintion using an approximate (but fast) nearest neighbour method. Resampling an object of type **ImageContainerQuick** returns a new object of type **ImageContainerQuick**. An **ImageContainerNearest** object allows for the grid to be resampled to a new area defintion (or swath definition) using an accurate kd-tree method. Resampling an object of type **ImageContainerNearest** returns a new object of type **ImageContainerNearest**. .. doctest:: >>> import numpy as np >>> from pyresample import image, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> msg_area = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', ... 'msg_full', ... {'a': '6378169.0', 'b': '6356584.0', ... 'h': '35785831.0', 'lon_0': '0', ... 'proj': 'geos'}, ... 3712, 3712, ... [-5568742.4, -5568742.4, ... 5568742.4, 5568742.4]) >>> data = np.ones((3712, 3712)) >>> msg_con_quick = image.ImageContainerQuick(data, msg_area) >>> area_con_quick = msg_con_quick.resample(area_def) >>> result_data_quick = area_con_quick.image_data >>> msg_con_nn = image.ImageContainerNearest(data, msg_area, radius_of_influence=50000) >>> area_con_nn = msg_con_nn.resample(area_def) >>> result_data_nn = area_con_nn.image_data Data is assumed to be a numpy array of shape (rows, cols) or (rows, cols, channels). Masked arrays can be used as data input. In order to have undefined pixels masked out instead of assigned a fill value set **fill_value=None** when calling **resample_area_***. Using **ImageContainerQuick** the risk of image artifacts increases as the distance from source projection center increases. The constructor argument **radius_of_influence** to **ImageContainerNearest** specifices the maximum distance to search for a neighbour for each point in the target grid. The unit is meters. The constructor arguments of an ImageContainer object can be changed as attributes later .. doctest:: >>> import numpy as np >>> from pyresample import image, geometry >>> msg_area = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', ... 'msg_full', ... {'a': '6378169.0', 'b': '6356584.0', ... 'h': '35785831.0', 'lon_0': '0', ... 'proj': 'geos'}, ... 3712, 3712, ... [-5568742.4, -5568742.4, ... 5568742.4, 5568742.4]) >>> data = np.ones((3712, 3712)) >>> msg_con_nn = image.ImageContainerNearest(data, msg_area, radius_of_influence=50000) >>> msg_con_nn.radius_of_influence = 45000 >>> msg_con_nn.fill_value = -99 Multi channel images ******************** If the dataset has several channels the last index of the data array specifies the channels .. doctest:: >>> import numpy as np >>> from pyresample import image, geometry >>> msg_area = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', ... 'msg_full', ... {'a': '6378169.0', 'b': '6356584.0', ... 'h': '35785831.0', 'lon_0': '0', ... 'proj': 'geos'}, ... 3712, 3712, ... [-5568742.4, -5568742.4, ... 5568742.4, 5568742.4]) >>> channel1 = np.ones((3712, 3712)) >>> channel2 = np.ones((3712, 3712)) * 2 >>> channel3 = np.ones((3712, 3712)) * 3 >>> data = np.dstack((channel1, channel2, channel3)) >>> msg_con_nn = image.ImageContainerNearest(data, msg_area, radius_of_influence=50000) Segmented resampling ******************** Pyresample calculates the result in segments in order to reduce memory footprint. This is controlled by the **segments** contructor keyword argument. If no **segments** argument is given pyresample will estimate the number of segments to use. Forcing quick resampling to use 4 resampling segments: .. doctest:: >>> import numpy as np >>> from pyresample import image, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> msg_area = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', ... 'msg_full', ... {'a': '6378169.0', 'b': '6356584.0', ... 'h': '35785831.0', 'lon_0': '0', ... 'proj': 'geos'}, ... 3712, 3712, ... [-5568742.4, -5568742.4, ... 5568742.4, 5568742.4]) >>> data = np.ones((3712, 3712)) >>> msg_con_quick = image.ImageContainerQuick(data, msg_area, segments=4) >>> area_con_quick = msg_con_quick.resample(area_def) Constructor arguments ********************* The full list of constructor arguments: **ImageContainerQuick**: * image_data : Dataset. Masked arrays can be used. * image_data : Geometry definition. * fill_value (optional) : Fill value for undefined pixels. Defaults to 0. If set to **None** they will be masked out. * nprocs (optional) : Number of processor cores to use. Defaults to 1. * segments (optional) : Number of segments to split resampling in. Defaults to auto estimation. **ImageContainerNearest**: * image_data : Dataset. Masked arrays can be used. * image_data : Geometry definition. * radius_of_influence : Cut off radius in meters when considering neighbour pixels. * epsilon (optional) : The distance to a found value is guaranteed to be no further than (1 + eps) times the distance to the correct neighbour. * fill_value (optional) : Fill value for undefined pixels. Defaults to 0. If set to **None** they will be masked out. * reduce_data (optional) : Apply geographic reduction of dataset before resampling. Defaults to True * nprocs (optional) : Number of processor cores to use. Defaults to 1. * segments (optional) : Number of segments to split resampling in. Defaults to auto estimation. Preprocessing of grid resampling ********************************* For preprocessing of grid resampling see :ref:`preproc` pyresample-1.2.9/docs/source/index.rst000066400000000000000000000013671302372600000177750ustar00rootroot00000000000000.. pyresample documentation master file, created by sphinx-quickstart on Tue Jan 5 13:01:32 2010. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Pyresample ====================================== Pyresample is a Python package for resampling (reprojection) of earth observing satellite data. Pyresample handles both resampling of gridded data (e.g. geostationary satellites) and swath data (polar orbiting satellites). Pyresample can use multiple processor cores for resampling. Pyresample supports masked arrays. Documentation ------------- .. toctree:: :maxdepth: 2 installation geo_def geo_filter grid swath multi preproc plot data_reduce API pyresample-1.2.9/docs/source/installation.rst000066400000000000000000000045311302372600000213630ustar00rootroot00000000000000Installing Pyresample ===================== Pyresample depends on pyproj, numpy(>= 1.3), scipy(>= 0.7), multiprocessing (builtin package for Python > 2.5) and configobj. Optionally pykdtree can be used instead of scipy from v0.8.0. The correct version of the packages should be installed on your system (refer to numpy and scipy installation instructions) or use easy_install to handle dependencies automatically. In order to use the pyresample plotting functionality Basemap and matplotlib (>= 0.98) must be installed. These packages are not a prerequisite for using any other pyresample functionality. Package test ************ Test the package (requires nose): .. code-block:: bash $ tar -zxvf pyresample-.tar.gz $ cd pyresample- $ nosetests If all the tests passes the functionality of all pyresample functions on the system has been verified. Package installation ******************** A sandbox environment can be created for pyresample using `Virtualenv `_ Pyresample is available from pypi. Install Pyresample using pip: .. code-block:: bash $ pip install pyresample Alternatively install from tarball: .. code-block:: bash $ tar -zxvf pyresample-.tar.gz $ cd pyresample- $ python setup.py install Using pykdtree ************** As of pyresample v0.8.0 pykdtree can be used as backend instead of scipy. This enables significant speedups for large datasets. pykdtree is used as a drop-in replacement for scipy. If it's available it will be used otherwise scipy will be used. To check which backend is active for your pyresample installation do: >>> import pyresample as pr >>> pr.kd_tree.which_kdtree() which returns either 'pykdtree' or 'scipy.spatial'. Please refere to pykdtree_ for installation description. If pykdtree is built with OpenMP support the number of threads is controlled with the standard OpenMP environment variable OMP_NUM_THREADS. The *nprocs* argument has no effect on pykdtree. Using numexpr ************* As of pyresample v1.0.0 numexpr_ will be used for minor bottleneck optimization if available Show active plugins ******************* The active drop-in plugins can be show using: >>> import pyresample as pr >>> pr.get_capabilities() .. _pykdtree: https://github.com/storpipfugl/pykdtree .. _numexpr: https://code.google.com/p/numexpr/ pyresample-1.2.9/docs/source/multi.rst000066400000000000000000000035771302372600000200250ustar00rootroot00000000000000.. _multi: Using multiple processor cores ============================== Multi core processing ********************* Bottlenecks of pyresample can be executed in parallel. Parallel computing can be executed if the pyresample function has the **nprocs** keyword argument. **nprocs** specifies the number of processes to be used for calculation. If a class takes the constructor argument **nprocs** this sets **nprocs** for all methods of this class Example of resampling in parallel using 4 processes: .. doctest:: >>> import numpy >>> from pyresample import kd_tree, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = numpy.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) >>> result = kd_tree.resample_nearest(swath_def, data.ravel(), ... area_def, radius_of_influence=50000, nprocs=4) Note: Do not use more processes than available processor cores. As there is a process creation overhead there might be neglible performance improvement using say 8 compared to 4 processor cores. Test on the actual system to determine the most sensible number of processes to use. Here is an example of the performance for a varying number of processors on a 64-bit ubuntu 14.04, 32 GB RAM, 2 x Intel Xeon E5-2630 with 6 physical cores each: .. image:: _static/images/time_vs_nproc_1-12.png pyresample-1.2.9/docs/source/plot.rst000066400000000000000000000130701302372600000176360ustar00rootroot00000000000000.. _plot: Plotting with pyresample and Basemap ==================================== Pyresample supports basic integration with Basemap (http://matplotlib.sourceforge.net/basemap). Displaying data quickly ----------------------- Pyresample has some convenience functions for displaying data from a single channel. The function **plot.show_quicklook** shows a Basemap image of a dataset for a specified AreaDefinition. The function **plot.save_quicklook** saves the Basemap image directly to file. **Example usage:** .. doctest:: >>> import numpy as np >>> import pyresample as pr >>> lons = np.zeros(1000) >>> lats = np.arange(-80, -90, -0.01) >>> tb37v = np.arange(1000) >>> area_def = pr.utils.load_area('areas.cfg', 'ease_sh') >>> swath_def = pr.geometry.SwathDefinition(lons, lats) >>> result = pr.kd_tree.resample_nearest(swath_def, tb37v, area_def, ... radius_of_influence=20000, fill_value=None) >>> pr.plot.save_quicklook('tb37v_quick.png', area_def, result, label='Tb 37v (K)') Assuming **lons**, **lats** and **tb37v** are initialized with real data the result might look something like this: .. image:: _static/images/tb37v_quick.png The data passed to the functions is a 2D array matching the AreaDefinition. The Plate Carree projection +++++++++++++++++++++++++++ The Plate Carree projection (regular lon/lat grid) is named **eqc** in Proj.4 and **cyl** in Basemap. pyresample uses the Proj.4 name. Assuming the file **areas.cfg** has the following area definition: .. code-block:: bash REGION: pc_world { NAME: Plate Carree world map PCS_ID: pc_world PCS_DEF: proj=eqc XSIZE: 640 YSIZE: 480 AREA_EXTENT: (-20037508.34, -10018754.17, 20037508.34, 10018754.17) }; **Example usage:** >>> import numpy as np >>> import pyresample as pr >>> lons = np.zeros(1000) >>> lats = np.arange(-80, -90, -0.01) >>> tb37v = np.arange(1000) >>> area_def = pr.utils.load_area('areas.cfg', 'pc_world') >>> swath_def = pr.geometry.SwathDefinition(lons, lats) >>> result = pr.kd_tree.resample_nearest(swath_def, tb37v, area_def, radius_of_influence=20000, fill_value=None) >>> pr.plot.save_quicklook('tb37v_pc.png', area_def, result, num_meridians=0, num_parallels=0, label='Tb 37v (K)') Assuming **lons**, **lats** and **tb37v** are initialized with real data the result might look something like this: .. image:: _static/images/tb37v_pc.png The Globe projections +++++++++++++++++++++ From v0.7.12 pyresample can use the geos, ortho and nsper projections with Basemap. Assuming the file **areas.cfg** has the following area definition for an ortho projection area: .. code-block:: bash REGION: ortho { NAME: Ortho globe PCS_ID: ortho_globe PCS_DEF: proj=ortho, a=6370997.0, lon_0=40, lat_0=-40 XSIZE: 640 YSIZE: 480 AREA_EXTENT: (-10000000, -10000000, 10000000, 10000000) }; **Example usage:** >>> import numpy as np >>> import pyresample as pr >>> lons = np.zeros(1000) >>> lats = np.arange(-80, -90, -0.01) >>> tb37v = np.arange(1000) >>> area_def = pr.utils.load_area('areas.cfg', 'ortho') >>> swath_def = pr.geometry.SwathDefinition(lons, lats) >>> result = pr.kd_tree.resample_nearest(swath_def, tb37v, area_def, radius_of_influence=20000, fill_value=None) >>> pr.plot.save_quicklook('tb37v_ortho.png', area_def, result, num_meridians=0, num_parallels=0, label='Tb 37v (K)') Assuming **lons**, **lats** and **tb37v** are initialized with real data the result might look something like this: .. image:: _static/images/tb37v_ortho.png Getting a Basemap object ------------------------ In order to make more advanced plots than the preconfigured quicklooks a Basemap object can be generated from an AreaDefintion using the **plot.area_def2basemap(area_def, **kwargs)** function. **Example usage:** .. doctest:: >>> import numpy as np >>> import matplotlib.pyplot as plt >>> import pyresample as pr >>> lons = np.zeros(1000) >>> lats = np.arange(-80, -90, -0.01) >>> tb37v = np.arange(1000) >>> area_def = pr.utils.load_area('areas.cfg', 'ease_sh') >>> swath_def = pr.geometry.SwathDefinition(lons, lats) >>> result = pr.kd_tree.resample_nearest(swath_def, tb37v, area_def, ... radius_of_influence=20000, fill_value=None) >>> bmap = pr.plot.area_def2basemap(area_def) >>> bmng = bmap.bluemarble() >>> col = bmap.imshow(result, origin='upper') >>> plt.savefig('tb37v_bmng.png', bbox_inches='tight') Assuming **lons**, **lats** and **tb37v** are initialized with real data the result might look something like this: .. image:: _static/images/tb37v_bmng.png Any keyword arguments (not concerning the projection) passed to **plot.area_def2basemap** will be passed directly to the Basemap initialization. For more information on how to plot with Basemap please refer to the Basemap and matplotlib documentation. Limitations ----------- The pyresample use of Basemap is basically a conversion from a pyresample AreaDefintion to a Basemap object which allows for correct plotting of a resampled dataset using the **basemap.imshow** function. Currently only the following set of Proj.4 arguments can be interpreted in the conversion: {'proj', 'a', 'b', 'ellps', 'lon_0', 'lat_0', 'lon_1', 'lat_1', 'lon_2', 'lat_2', 'lat_ts'} Any other Proj.4 parameters will be ignored. If the ellipsoid is not defined in terms of 'ellps', 'a' or ('a', 'b') it will default to WGS84. The xsize and ysize in an AreaDefinition will only be used during resampling when the image data for use in **basemap.imshow** is created. The actual size and shape of the final plot is handled by matplotlib. pyresample-1.2.9/docs/source/preproc.rst000066400000000000000000000044751302372600000203430ustar00rootroot00000000000000.. _preproc: Preprocessing of grids ====================== When resampling is performed repeatedly to the same grid significant execution time can be save by preprocessing grid information. Preprocessing for grid resampling --------------------------------- Using the function **generate_quick_linesample_arrays** or **generate_nearest_neighbour_linesample_arrays** from **pyresample.utils** arrays containing the rows and cols indices used to calculate the result in **image.resample_area_quick** or **resample_area_nearest_neighbour** can be obtained. These can be fed to the method **get_array_from_linesample** of an **ImageContainer** object to obtain the resample result. .. doctest:: >>> import numpy >>> from pyresample import utils, image, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> msg_area = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', ... 'msg_full', ... {'a': '6378169.0', 'b': '6356584.0', ... 'h': '35785831.0', 'lon_0': '0', ... 'proj': 'geos'}, ... 3712, 3712, ... [-5568742.4, -5568742.4, ... 5568742.4, 5568742.4]) >>> data = numpy.ones((3712, 3712)) >>> msg_con = image.ImageContainer(data, msg_area) >>> row_indices, col_indices = \ ... utils.generate_nearest_neighbour_linesample_arrays(msg_area, area_def, 50000) >>> result = msg_con.get_array_from_linesample(row_indices, col_indices) The numpy arrays returned by **generate_*_linesample_arrays** can be and used with the **ImageContainer.get_array_from_linesample** method when the same resampling is to be performed again thus eliminating the need for calculating the reprojection. Numpy arrays can be saved and loaded using **numpy.save** and **numpy.load**. pyresample-1.2.9/docs/source/swath.rst000066400000000000000000000422721302372600000200140ustar00rootroot00000000000000.. _swath: Resampling of swath data ======================== Pyresample can be used to resample a swath dataset to a grid, a grid to a swath or a swath to another swath. Resampling can be done using nearest neighbour method, Guassian weighting, weighting with an arbitrary radial function. pyresample.image ---------------- The ImageContainerNearest class can be used for nearest neighbour resampling of swaths as well as grids. .. doctest:: >>> import numpy as np >>> from pyresample import image, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) >>> swath_con = image.ImageContainerNearest(data, swath_def, radius_of_influence=5000) >>> area_con = swath_con.resample(area_def) >>> result = area_con.image_data For other resampling types or splitting the process in two steps use the functions in **pyresample.kd_tree** described below. pyresample.kd_tree ------------------ This module contains several functions for resampling swath data. Note distance calculation is approximated with cartesian distance. Masked arrays can be used as data input. In order to have undefined pixels masked out instead of assigned a fill value set **fill_value=None** when calling the **resample_*** function. resample_nearest **************** Function for resampling using nearest neighbour method. Example showing how to resample a generated swath dataset to a grid using nearest neighbour method: .. doctest:: >>> import numpy as np >>> from pyresample import kd_tree, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) >>> result = kd_tree.resample_nearest(swath_def, data, ... area_def, radius_of_influence=50000, epsilon=0.5) If the arguments **swath_def** and **area_def** where switched (and **data** matched the dimensions of **area_def**) the grid of **area_def** would be resampled to the swath defined by **swath_def**. Note the keyword arguments: * **radius_of_influence**: The radius around each grid pixel in meters to search for neighbours in the swath. * **epsilon**: The distance to a found value is guaranteed to be no further than (1 + eps) times the distance to the correct neighbour. Allowing for uncertanty decreases execution time. If **data** is a masked array the mask will follow the neighbour pixel assignment. If there are multiple channels in the dataset the **data** argument should be of the shape of the lons and lat arrays with the channels along the last axis e.g. (rows, cols, channels). Note: the convention of pyresample < 0.7.4 is to pass **data** in the form of (number_of_data_points, channels) is still accepted. .. doctest:: >>> import numpy as np >>> from pyresample import kd_tree, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> channel1 = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> channel2 = np.fromfunction(lambda y, x: y*x, (50, 10)) * 2 >>> channel3 = np.fromfunction(lambda y, x: y*x, (50, 10)) * 3 >>> data = np.dstack((channel1, channel2, channel3)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) >>> result = kd_tree.resample_nearest(swath_def, data, ... area_def, radius_of_influence=50000) For nearest neighbour resampling the class **image.ImageContainerNearest** can be used as well as **kd_tree.resample_nearest** resample_gauss ************** Function for resampling using nearest Gussian weighting. The Gauss weigh function is defined as exp(-dist^2/sigma^2). Note the pyresample sigma is **not** the standard deviation of the gaussian. Example showing how to resample a generated swath dataset to a grid using Gaussian weighting: .. doctest:: >>> import numpy as np >>> from pyresample import kd_tree, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) >>> result = kd_tree.resample_gauss(swath_def, data, ... area_def, radius_of_influence=50000, sigmas=25000) If more channels are present in **data** the keyword argument **sigmas** must be a list containing a sigma for each channel. If **data** is a masked array any pixel in the result data that has been "contaminated" by weighting of a masked pixel is masked. Using the function **utils.fwhm2sigma** the sigma argument to the gauss resampling can be calculated from 3 dB FOV levels. resample_custom *************** Function for resampling using arbitrary radial weight functions. Example showing how to resample a generated swath dataset to a grid using an arbitrary radial weight function: .. doctest:: >>> import numpy as np >>> from pyresample import kd_tree, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) >>> wf = lambda r: 1 - r/100000.0 >>> result = kd_tree.resample_custom(swath_def, data, ... area_def, radius_of_influence=50000, weight_funcs=wf) If more channels are present in **data** the keyword argument **weight_funcs** must be a list containing a radial function for each channel. If **data** is a masked array any pixel in the result data that has been "contaminated" by weighting of a masked pixel is masked. Uncertainty estimates ********************* Uncertainty estimates in the form of weighted standard deviation can be obtained from the **resample_custom** and **resample_gauss** functions. By default the functions return the result of the resampling as a single numpy array. If the functions are given the keyword argument **with_uncert=True** then the following list of numpy arrays will be returned instead: **(result, stddev, count)**. **result** is the usual result. **stddev** is the weighted standard deviation for each element in the result. **count** is the number of data values used in the weighting for each element in the result. The principle is to view the calculated value for each element in the result as a weighted average of values sampled from a statistical variable. An estimate of the standard deviation of the distribution is calculated using the unbiased weighted estimator given as **stddev = sqrt((V1 / (V1 ** 2 + V2)) * sum(wi * (xi - result) ** 2))** where **result** is the result of the resampling. **xi** is the value of a contributing neighbour and **wi** is the corresponding weight. The coefficients are given as **V1 = sum(wi)** and **V2 = sum(wi ** 2)**. The standard deviation is only calculated for elements in the result where more than one neighbour has contributed to the weighting. The **count** numpy array can be used for filtering at a higher number of contributing neigbours. Usage only differs in the number of return values from **resample_gauss** and **resample_custom**. E.g.: >>> result, stddev, count = pr.kd_tree.resample_gauss(swath_def, ice_conc, area_def, ... radius_of_influence=20000, ... sigmas=pr.utils.fwhm2sigma(35000), ... fill_value=None, with_uncert=True) Below is shown a plot of the result of the resampling using a real data set: .. image:: _static/images/uncert_conc_nh.png The corresponding standard deviations: .. image:: _static/images/uncert_stddev_nh.png And the number of contributing neighbours for each element: .. image:: _static/images/uncert_count_nh.png Notice the standard deviation is only calculated where there are more than one contributing neighbour. Resampling from neighbour info ****************************** The resampling can be split in two steps: First get arrays containing information about the nearest neighbours to each grid point. Then use these arrays to retrive the resampling result. This approch can be useful if several datasets based on the same swath are to be resampled. The computational heavy task of calculating the neighbour information can be done once and the result can be used to retrieve the resampled data from each of the datasets fast. .. doctest:: >>> import numpy as np >>> from pyresample import kd_tree, geometry >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) >>> valid_input_index, valid_output_index, index_array, distance_array = \ ... kd_tree.get_neighbour_info(swath_def, ... area_def, 50000, ... neighbours=1) >>> res = kd_tree.get_sample_from_neighbour_info('nn', area_def.shape, data, ... valid_input_index, valid_output_index, ... index_array) Note the keyword argument **neighbours=1**. This specifies only to consider one neighbour for each grid point (the nearest neighbour). Also note **distance_array** is not a required argument for **get_sample_from_neighbour_info** when using nearest neighbour resampling Segmented resampling ******************** Whenever a resampling function takes the keyword argument **segments** the number of segments to split the resampling process in can be specified. This affects the memory footprint of pyresample. If the value of **segments** is left to default pyresample will estimate the number of segments to use. Speedup using pykdtree ********************** pykdtree can be used instead of scipy to gain significant speedup for large datasets. See :ref:`multi`. pyresample.ewa -------------- Pyresample makes it possible to resample swath data to a uniform grid using an Elliptical Weighted Averaging algorithm or EWA for short. This algorithm behaves differently than the KDTree based resampling algorithms that pyresample provides. The KDTree-based algorithms process each output grid pixel by searching for all "nearby" input pixels and applying a certain interpolation (nearest neighbor, gaussian, etc). The EWA algorithm processes each input pixel mapping it to one or more output pixels. Once each input pixel has been analyzed the intermediate results are averaged to produce the final gridded result. The EWA algorithm also has limitations on how the input data is structured compared to the generic KDTree algorithms. EWA assumes that data in the array is organized geographically; adjacent data in the array is adjacent data geographically. The algorithm uses this to configure parameters based on the size and location of the swath pixels. The EWA algorithm consists of two steps: ll2cr and fornav. The algorithm was originally part of the MODIS Swath to Grid Toolbox (ms2gt) created by the NASA National Snow & Ice Data Center (NSIDC). Its default parameters work best with MODIS L1B data, but it has been proven to produce high quality images from VIIRS and AVHRR data with the right parameters. .. note:: This code was originally part of the Polar2Grid project. This documentation and the API documentation for this algorithm may still use references or concepts from Polar2Grid until everything can be updated. Gridding ******** The first step is called 'll2cr' which stands for "longitude/latitude to column/row". This step maps the pixel location (lon/lat space) into area (grid) space. Areas in pyresample are defined by a PROJ.4 projection specification. An area is defined by the following parameters: - Grid Name - PROJ.4 String (either lat/lon or metered projection space) - Width (number of pixels in the X direction) - Height (number of pixels in the Y direction) - Cell Width (pixel size in the X direction in grid units) - Cell Height (pixel size in the Y direction in grid units) - X Origin (upper-left X coordinate in grid units) - Y Origin (upper-left Y coordinate in grid units) Resampling ********** The second step of EWA remapping is called "fornav", short for "forward navigation". This EWA algorithm processes one input scan line at a time. The algorithm weights the effect of an input pixel on an output pixel based on its location in the scan line and other calculated coefficients. It can also handle swaths that are not scan based by specifying `rows_per_scan` as the number of rows in the entire swath. How the algorithm treats the data can be configured with various keyword arguments, see the API documentation for more information. Both steps provide additional information to inform the user how much data was used in the result. The first returned value of ll2cr tells you how many of the input swath pixels overlap the grid. The first returned value of fornav tells you how many grid points have valid data values in them. Example ******* .. note:: EWA resampling in pyresample is still in an alpha stage. As development continues, EWA resampling may be called differently. .. doctest:: >>> import numpy as np >>> from pyresample.ewa import ll2cr, fornav >>> area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', ... {'a': '6378144.0', 'b': '6356759.0', ... 'lat_0': '50.00', 'lat_ts': '50.00', ... 'lon_0': '8.00', 'proj': 'stere'}, ... 800, 800, ... [-1370912.72, -909968.64, ... 1029087.28, 1490031.36]) >>> data = np.fromfunction(lambda y, x: y*x, (50, 10)) >>> lons = np.fromfunction(lambda y, x: 3 + x, (50, 10)) >>> lats = np.fromfunction(lambda y, x: 75 - y, (50, 10)) >>> swath_def = geometry.SwathDefinition(lons=lons, lats=lats) >>> # ll2cr converts swath longitudes and latitudes to grid columns and rows >>> swath_points_in_grid, cols, rows = ll2cr(swath_def, area_def) >>> # if the data is scan based, specify how many data rows make up one scan >>> rows_per_scan = 5 >>> # fornav resamples the swath data to the gridded area >>> num_valid_points, gridded_data = fornav(cols, rows, area_def, data, rows_per_scan=rows_per_scan) pyresample-1.2.9/pyresample/000077500000000000000000000000001302372600000160565ustar00rootroot00000000000000pyresample-1.2.9/pyresample/__init__.py000066400000000000000000000026421302372600000201730ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2014, 2015 Esben S. Nielsen # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . from __future__ import absolute_import from pyresample.version import __version__ from pyresample import geometry from pyresample import grid from pyresample import image from pyresample import kd_tree from pyresample import utils from pyresample import plot __all__ = ['grid', 'image', 'kd_tree', 'utils', 'plot', 'geo_filter', 'geometry'] def get_capabilities(): cap = {} try: from pykdtree.kdtree import KDTree cap['pykdtree'] = True except ImportError: cap['pykdtree'] = False try: import numexpr cap['numexpr'] = True except ImportError: cap['numexpr'] = False return cap pyresample-1.2.9/pyresample/_multi_proc.py000066400000000000000000000066321302372600000207530ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2015 Esben S. Nielsen # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . from __future__ import absolute_import import ctypes import multiprocessing as mp import numpy as np class Scheduler(object): def __init__(self, ndata, nprocs, chunk=None, schedule='guided'): if not schedule in ['guided', 'dynamic', 'static']: raise ValueError('unknown scheduling strategy') self._ndata = mp.RawValue(ctypes.c_int, ndata) self._start = mp.RawValue(ctypes.c_int, 0) self._lock = mp.Lock() self._schedule = schedule self._nprocs = nprocs if schedule == 'guided' or schedule == 'dynamic': min_chunk = ndata // (10 * nprocs) if chunk: min_chunk = chunk min_chunk = max(min_chunk, 1) self._chunk = min_chunk elif schedule == 'static': min_chunk = ndata // nprocs if chunk: min_chunk = max(chunk, min_chunk) min_chunk = max(min_chunk, 1) self._chunk = min_chunk def __iter__(self): while True: self._lock.acquire() ndata = self._ndata.value nprocs = self._nprocs start = self._start.value if self._schedule == 'guided': _chunk = ndata // nprocs chunk = max(self._chunk, _chunk) else: chunk = self._chunk if ndata: if chunk > ndata: s0 = start s1 = start + ndata self._ndata.value = 0 else: s0 = start s1 = start + chunk self._ndata.value = ndata - chunk self._start.value = start + chunk self._lock.release() yield slice(s0, s1) else: self._lock.release() raise StopIteration def shmem_as_ndarray(raw_array): _ctypes_to_numpy = { ctypes.c_char: np.int8, ctypes.c_wchar: np.int16, ctypes.c_byte: np.int8, ctypes.c_ubyte: np.uint8, ctypes.c_short: np.int16, ctypes.c_ushort: np.uint16, ctypes.c_int: np.int32, ctypes.c_uint: np.int32, ctypes.c_long: np.int32, ctypes.c_ulong: np.int32, ctypes.c_float: np.float32, ctypes.c_double: np.float64 } dtype = _ctypes_to_numpy[raw_array._type_] # The following works too, but occasionally raises # RuntimeWarning: Item size computed from the PEP 3118 buffer format string does not match the actual item size. # and appears to be slower. # return np.ctypeslib.as_array(raw_array) return np.frombuffer(raw_array, dtype=dtype) pyresample-1.2.9/pyresample/_spatial_mp.py000066400000000000000000000236631302372600000207320ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2013, 2015 Esben S. Nielsen, Martin Raspaud # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . from __future__ import absolute_import import ctypes import numpy as np import pyproj #import scipy.spatial as sp import multiprocessing as mp try: import numexpr as ne except ImportError: ne = None from ._multi_proc import shmem_as_ndarray, Scheduler # Earth radius R = 6370997.0 class cKDTree_MP(object): ''' Multiprocessing cKDTree subclass, shared memory ''' def __init__(self, data, leafsize=10, nprocs=2, chunk=None, schedule='guided'): ''' Same as cKDTree.__init__ except that an internal copy of data to shared memory is made. Extra keyword arguments: chunk : Minimum chunk size for the load balancer. schedule: Strategy for balancing work load ('static', 'dynamic' or 'guided'). ''' self.n, self.m = data.shape # Allocate shared memory for data self.shmem_data = mp.RawArray(ctypes.c_double, self.n * self.m) # View shared memory as ndarray, and copy over the data. # The RawArray objects have information about the dtype and # buffer size. _data = shmem_as_ndarray(self.shmem_data).reshape((self.n, self.m)) _data[:,:] = data # Initialize parent, we must do this last because # cKDTree stores a reference to the data array. We pass in # the copy in shared memory rather than the origial data. self.leafsize = leafsize self._nprocs = nprocs self._chunk = chunk self._schedule = schedule def query(self, x, k=1, eps=0, p=2, distance_upper_bound=np.inf): ''' Same as cKDTree.query except parallelized with multiple processes and shared memory. ''' # allocate shared memory for x and result nx = x.shape[0] shmem_x = mp.RawArray(ctypes.c_double, nx * self.m) shmem_d = mp.RawArray(ctypes.c_double, nx * k) shmem_i = mp.RawArray(ctypes.c_int, nx * k) # view shared memory as ndarrays _x = shmem_as_ndarray(shmem_x).reshape((nx, self.m)) if k == 1: _d = shmem_as_ndarray(shmem_d) _i = shmem_as_ndarray(shmem_i) else: _d = shmem_as_ndarray(shmem_d).reshape((nx, k)) _i = shmem_as_ndarray(shmem_i).reshape((nx, k)) # copy x to shared memory _x[:] = x # set up a scheduler to load balance the query scheduler = Scheduler(nx, self._nprocs, chunk=self._chunk, schedule=self._schedule) # query with multiple processes query_args = [scheduler, self.shmem_data, self.n, self.m, self.leafsize, shmem_x, nx, shmem_d, shmem_i, k, eps, p, distance_upper_bound] _run_jobs(_parallel_query, query_args, self._nprocs) # return results (private memory) return _d.copy(), _i.copy() class Proj(pyproj.Proj): def __call__(self, data1, data2, inverse=False, radians=False, errcheck=False, nprocs=1): if self.is_latlong(): return data1, data2 return super(Proj, self).__call__(data1, data2, inverse=inverse, radians=radians, errcheck=errcheck) class Proj_MP(pyproj.Proj): def __init__(self, *args, **kwargs): self._args = args self._kwargs = kwargs def __call__(self, data1, data2, inverse=False, radians=False, errcheck=False, nprocs=2, chunk=None, schedule='guided'): if self.is_latlong(): return data1, data2 grid_shape = data1.shape n = data1.size # Create shared memory shmem_data1 = mp.RawArray(ctypes.c_double, n) shmem_data2 = mp.RawArray(ctypes.c_double, n) shmem_res1 = mp.RawArray(ctypes.c_double, n) shmem_res2 = mp.RawArray(ctypes.c_double, n) # view shared memory as ndarrays _data1 = shmem_as_ndarray(shmem_data1) _data2 = shmem_as_ndarray(shmem_data2) _res1 = shmem_as_ndarray(shmem_res1) _res2 = shmem_as_ndarray(shmem_res2) # copy input data to shared memory _data1[:] = data1.ravel() _data2[:] = data2.ravel() # set up a scheduler to load balance the query scheduler = Scheduler(n, nprocs, chunk=chunk, schedule=schedule) # Projection with multiple processes proj_call_args = [scheduler, shmem_data1, shmem_data2, shmem_res1, shmem_res2, self._args, self._kwargs, inverse, radians, errcheck] _run_jobs(_parallel_proj, proj_call_args, nprocs) return _res1.copy().reshape(grid_shape), _res2.copy().reshape(grid_shape) class Cartesian(object): def __init__(self, *args, **kwargs): pass def transform_lonlats(self, lons, lats): coords = np.zeros((lons.size, 3), dtype=lons.dtype) deg2rad = lons.dtype.type(np.pi / 180) if ne: coords[:, 0] = ne.evaluate("R*cos(lats*deg2rad)*cos(lons*deg2rad)") coords[:, 1] = ne.evaluate("R*cos(lats*deg2rad)*sin(lons*deg2rad)") coords[:, 2] = ne.evaluate("R*sin(lats*deg2rad)") else: coords[:, 0] = R * np.cos(lats * deg2rad) * np.cos(lons * deg2rad) coords[:, 1] = R * np.cos(lats * deg2rad) * np.sin(lons * deg2rad) coords[:, 2] = R * np.sin(lats * deg2rad) return coords Cartesian_MP = Cartesian def _run_jobs(target, args, nprocs): """Run process pool """ # return status in shared memory # access to these values are serialized automatically ierr = mp.Value(ctypes.c_int, 0) err_msg = mp.Array(ctypes.c_char, 1024) args.extend((ierr, err_msg)) pool = [mp.Process(target=target, args=args) for n in range(nprocs)] for p in pool: p.start() for p in pool: p.join() if ierr.value != 0: raise RuntimeError('%d errors in worker processes. Last one reported:\n%s' % (ierr.value, err_msg.value.decode())) # This is executed in an external process: def _parallel_query(scheduler, # scheduler for load balancing # data needed to reconstruct the kd-tree data, ndata, ndim, leafsize, x, nx, d, i, # query data and results k, eps, p, dub, # auxillary query parameters ierr, err_msg): # return values (0 on success) try: # View shared memory as ndarrays. _data = shmem_as_ndarray(data).reshape((ndata, ndim)) _x = shmem_as_ndarray(x).reshape((nx, ndim)) if k == 1: _d = shmem_as_ndarray(d) _i = shmem_as_ndarray(i) else: _d = shmem_as_ndarray(d).reshape((nx, k)) _i = shmem_as_ndarray(i).reshape((nx, k)) # Reconstruct the kd-tree from the data. import scipy.spatial as sp kdtree = sp.cKDTree(_data, leafsize=leafsize) # Query for nearest neighbours, using slice ranges, # from the load balancer. for s in scheduler: if k == 1: _d[s], _i[s] = kdtree.query(_x[s,:], k=1, eps=eps, p=p,\ distance_upper_bound=dub) else: _d[s,:], _i[s,:] = kdtree.query(_x[s,:], k=k, eps=eps, p=p,\ distance_upper_bound=dub) # An error occured, increment the return value ierr. # Access to ierr is serialized by multiprocessing. except Exception as e: ierr.value += 1 err_msg.value = str(e).encode() def _parallel_proj(scheduler, data1, data2, res1, res2, proj_args, proj_kwargs, inverse, radians, errcheck, ierr, err_msg): try: # View shared memory as ndarrays. _data1 = shmem_as_ndarray(data1) _data2 = shmem_as_ndarray(data2) _res1 = shmem_as_ndarray(res1) _res2 = shmem_as_ndarray(res2) # Initialise pyproj proj = pyproj.Proj(*proj_args, **proj_kwargs) # Reproject data segment for s in scheduler: _res1[s], _res2[s] = proj(_data1[s], _data2[s], inverse=inverse, radians=radians, errcheck=errcheck) # An error occured, increment the return value ierr. # Access to ierr is serialized by multiprocessing. except Exception as e: ierr.value += 1 err_msg.value = str(e).encode() def _parallel_transform(scheduler, lons, lats, n, coords, ierr, err_msg): try: # View shared memory as ndarrays. _lons = shmem_as_ndarray(lons) _lats = shmem_as_ndarray(lats) _coords = shmem_as_ndarray(coords).reshape((n, 3)) # Transform to cartesian coordinates for s in scheduler: _coords[s, 0] = R * \ np.cos(np.radians(_lats[s])) * np.cos(np.radians(_lons[s])) _coords[s, 1] = R * \ np.cos(np.radians(_lats[s])) * np.sin(np.radians(_lons[s])) _coords[s, 2] = R * np.sin(np.radians(_lats[s])) # An error occured, increment the return value ierr. # Access to ierr is serialized by multiprocessing. except Exception as e: ierr.value += 1 err_msg.value = str(e).encode() pyresample-1.2.9/pyresample/data_reduce.py000066400000000000000000000254511302372600000206770ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2015 Esben S. Nielsen # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """Reduce data sets based on geographical information""" from __future__ import absolute_import import numpy as np # Earth radius R = 6370997.0 def swath_from_cartesian_grid(cart_grid, lons, lats, data, radius_of_influence): """Makes coarse data reduction of swath data by comparison with cartesian grid Parameters ---------- chart_grid : numpy array Grid of area cartesian coordinates lons : numpy array Swath lons lats : numpy array Swath lats data : numpy array Swath data radius_of_influence : float Cut off distance in meters Returns ------- (lons, lats, data) : list of numpy arrays Reduced swath data and coordinate set """ valid_index = get_valid_index_from_cartesian_grid(cart_grid, lons, lats, radius_of_influence) lons = lons[valid_index] lats = lats[valid_index] data = data[valid_index] return lons, lats, data def get_valid_index_from_cartesian_grid(cart_grid, lons, lats, radius_of_influence): """Calculates relevant data indices using coarse data reduction of swath data by comparison with cartesian grid Parameters ---------- chart_grid : numpy array Grid of area cartesian coordinates lons : numpy array Swath lons lats : numpy array Swath lats data : numpy array Swath data radius_of_influence : float Cut off distance in meters Returns ------- valid_index : numpy array Boolean array of same size as lons and lats indicating relevant indices """ def _get_lons(x, y): return np.rad2deg(np.arccos(x / np.sqrt(x ** 2 + y ** 2))) * np.sign(y) def _get_lats(z): return 90 - np.rad2deg(np.arccos(z / R)) # Get sides of target grid and transform to lon lats lons_side1 = _get_lons(cart_grid[0, :, 0], cart_grid[0, :, 1]) lons_side2 = _get_lons(cart_grid[:, -1, 0], cart_grid[:, -1, 1]) lons_side3 = _get_lons(cart_grid[-1, ::-1, 0], cart_grid[-1, ::-1, 1]) lons_side4 = _get_lons(cart_grid[::-1, 0, 0], cart_grid[::-1, 0, 1]) lats_side1 = _get_lats(cart_grid[0, :, 2]) lats_side2 = _get_lats(cart_grid[:, -1, 2]) lats_side3 = _get_lats(cart_grid[-1, ::-1, 2]) lats_side4 = _get_lats(cart_grid[::-1, 0, 2]) valid_index = _get_valid_index(lons_side1, lons_side2, lons_side3, lons_side4, lats_side1, lats_side2, lats_side3, lats_side4, lons, lats, radius_of_influence) return valid_index def swath_from_lonlat_grid(grid_lons, grid_lats, lons, lats, data, radius_of_influence): """Makes coarse data reduction of swath data by comparison with lon lat grid Parameters ---------- grid_lons : numpy array Grid of area lons grid_lats : numpy array Grid of area lats lons : numpy array Swath lons lats : numpy array Swath lats data : numpy array Swath data radius_of_influence : float Cut off distance in meters Returns ------- (lons, lats, data) : list of numpy arrays Reduced swath data and coordinate set """ valid_index = get_valid_index_from_lonlat_grid( grid_lons, grid_lats, lons, lats, radius_of_influence) lons = lons[valid_index] lats = lats[valid_index] data = data[valid_index] return lons, lats, data def swath_from_lonlat_boundaries(boundary_lons, boundary_lats, lons, lats, data, radius_of_influence): """Makes coarse data reduction of swath data by comparison with lon lat boundary Parameters ---------- boundary_lons : numpy array Grid of area lons boundary_lats : numpy array Grid of area lats lons : numpy array Swath lons lats : numpy array Swath lats data : numpy array Swath data radius_of_influence : float Cut off distance in meters Returns ------- (lons, lats, data) : list of numpy arrays Reduced swath data and coordinate set """ valid_index = get_valid_index_from_lonlat_boundaries(boundary_lons, boundary_lats, lons, lats, radius_of_influence) lons = lons[valid_index] lats = lats[valid_index] data = data[valid_index] return lons, lats, data def get_valid_index_from_lonlat_grid(grid_lons, grid_lats, lons, lats, radius_of_influence): """Calculates relevant data indices using coarse data reduction of swath data by comparison with lon lat grid Parameters ---------- chart_grid : numpy array Grid of area cartesian coordinates lons : numpy array Swath lons lats : numpy array Swath lats data : numpy array Swath data radius_of_influence : float Cut off distance in meters Returns ------- valid_index : numpy array Boolean array of same size as lon and lat indicating relevant indices """ # Get sides of target grid lons_side1 = grid_lons[0, :] lons_side2 = grid_lons[:, -1] lons_side3 = grid_lons[-1, ::-1] lons_side4 = grid_lons[::-1, 0] lats_side1 = grid_lats[0, :] lats_side2 = grid_lats[:, -1] lats_side3 = grid_lats[-1, :] lats_side4 = grid_lats[:, 0] valid_index = _get_valid_index(lons_side1, lons_side2, lons_side3, lons_side4, lats_side1, lats_side2, lats_side3, lats_side4, lons, lats, radius_of_influence) return valid_index def get_valid_index_from_lonlat_boundaries(boundary_lons, boundary_lats, lons, lats, radius_of_influence): """Find relevant indices from grid boundaries using the winding number theorem""" valid_index = _get_valid_index(boundary_lons.side1, boundary_lons.side2, boundary_lons.side3, boundary_lons.side4, boundary_lats.side1, boundary_lats.side2, boundary_lats.side3, boundary_lats.side4, lons, lats, radius_of_influence) return valid_index def _get_valid_index(lons_side1, lons_side2, lons_side3, lons_side4, lats_side1, lats_side2, lats_side3, lats_side4, lons, lats, radius_of_influence): """Find relevant indices from grid boundaries using the winding number theorem""" # Coarse reduction of data based on extrema analysis of the boundary # lon lat values of the target grid illegal_lons = (((lons_side1 < -180) | (lons_side1 > 180)).any() or ((lons_side2 < -180) | (lons_side2 > 180)).any() or ((lons_side3 < -180) | (lons_side3 > 180)).any() or ((lons_side4 < -180) | (lons_side4 > 180)).any()) illegal_lats = (((lats_side1 < -90) | (lats_side1 > 90)).any() or ((lats_side2 < -90) | (lats_side2 > 90)).any() or ((lats_side3 < -90) | (lats_side3 > 90)).any() or ((lats_side4 < -90) | (lats_side4 > 90)).any()) if illegal_lons or illegal_lats: # Grid boundaries are not safe to operate on return np.ones(lons.size, dtype=np.bool) # Find sum angle sum of grid boundary angle_sum = 0 for side in (lons_side1, lons_side2, lons_side3, lons_side4): prev = None side_sum = 0 for lon in side: if prev: delta = lon - prev if abs(delta) > 180: delta = (abs(delta) - 360) * (delta // abs(delta)) angle_sum += delta side_sum += delta prev = lon # Buffer min and max lon and lat of interest with radius of interest lat_min = min(lats_side1.min(), lats_side2.min(), lats_side3.min(), lats_side4.min()) lat_min_buffered = lat_min - float(radius_of_influence) / R lat_max = max(lats_side1.max(), lats_side2.max(), lats_side3.max(), lats_side4.max()) lat_max_buffered = lat_max + float(radius_of_influence) / R max_angle_s2 = max(abs(lats_side2.max()), abs(lats_side2.min())) max_angle_s4 = max(abs(lats_side4.max()), abs(lats_side4.min())) lon_min_buffered = (lons_side4.min() - float(radius_of_influence) / (np.sin(np.radians(max_angle_s4)) * R)) lon_max_buffered = (lons_side2.max() + float(radius_of_influence) / (np.sin(np.radians(max_angle_s2)) * R)) # From the winding number theorem follows: # angle_sum possiblilities: #-360: area covers north pole # 360: area covers south pole # 0: area covers no poles # else: area covers both poles if round(angle_sum) == -360: # Covers NP valid_index = (lats >= lat_min_buffered) elif round(angle_sum) == 360: # Covers SP valid_index = (lats <= lat_max_buffered) elif round(angle_sum) == 0: # Covers no poles valid_lats = (lats >= lat_min_buffered) * (lats <= lat_max_buffered) if lons_side2.min() > lons_side4.max(): # No date line crossing valid_lons = (lons >= lon_min_buffered) * \ (lons <= lon_max_buffered) else: # Date line crossing seg1 = (lons >= lon_min_buffered) * (lons <= 180) seg2 = (lons <= lon_max_buffered) * (lons >= -180) valid_lons = seg1 + seg2 valid_index = valid_lats * valid_lons else: # Covers both poles don't reduce valid_index = np.ones(lons.size, dtype=np.bool) return valid_index pyresample-1.2.9/pyresample/ewa/000077500000000000000000000000001302372600000166325ustar00rootroot00000000000000pyresample-1.2.9/pyresample/ewa/__init__.py000066400000000000000000000236671302372600000207610ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2016 # Author(s): # David Hoese # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # You should have received a copy of the GNU General Public License # along with this program. If not, see . """Code for resampling using the Elliptical Weighted Averaging (EWA) algorithm. The logic and original code for this algorithm were translated from the software package "MODIS Swath 2 Grid Toolbox" or "ms2gt" created by the NASA National Snow & Ice Data Center (NSIDC): https://nsidc.org/data/modis/ms2gt/index.html Since the project has slowed down, Terry Haran has maintained the package and made updates available: http://cires1.colorado.edu/~tharan/ms2gt/ The ms2gt C executables "ll2cr" and "fornav" were rewritten for the Polar2Grid software package created by the Space Science Engineering Center (SSEC)/Cooperative Institute for Meteorological Satellite Studies. They were rewritten as a combination of C++ and Cython to make them more python friendly by David Hoese and were then copied and modified here in pyresample. The rewrite of "ll2cr" also included an important switch from using the "mapx" library to using the more popular and capable pyproj (PROJ.4) library. The EWA algorithm consists of two parts "ll2cr" and "fornav" and are described below. ll2cr ----- The "ll2cr" process is the first step in the EWA algorithm. It stands for "latitude/longitude to column/row". Its main purpose is to convert input longitude and latitude coordinates to column and row coordinates of the destination grid. These coordinates are then used in the next step "fornav". fornav ------ The "fornav" or "Forward Navigation" step of the EWA algorithm is where the actual Elliptical Weighted Averaging algorithm is run. The algorithm maps input swath pixels to output grid pixels by averaging multiple input pixels based on an elliptical region and other coefficients, some of which are determined at run time. For more information on these steps see the documentation for the corresponding modules. """ import logging import numpy as np from pyresample.ewa import _ll2cr, _fornav LOG = logging.getLogger(__name__) def ll2cr(swath_def, area_def, fill=np.nan, copy=True): """Map input swath pixels to output grid column and rows. Parameters ---------- swath_def : SwathDefinition Navigation definition for swath data to remap area_def : AreaDefinition Grid definition to be mapped to fill : float, optional Fill value used in longitude and latitude arrays copy : bool, optional Create a copy of the longitude and latitude arrays (default: True) Returns ------- (swath_points_in_grid, cols, rows) : tuple of integer, numpy array, numpy array Number of points from the input swath overlapping the destination area and the column and row arrays to pass to `fornav`. .. note:: ll2cr uses the pyproj library which is limited to 64-bit float navigation arrays in order to not do additional copying or casting of data types. """ lons, lats = swath_def.get_lonlats() # ll2cr requires 64-bit floats due to pyproj limitations # also need a copy of lons, lats since they are written to in-place lons = lons.astype(np.float64, copy=copy) lats = lats.astype(np.float64, copy=copy) # Break the input area up in to the expected parameters for ll2cr p = area_def.proj4_string cw = area_def.pixel_size_x # cell height must be negative for this to work as expected ch = -abs(area_def.pixel_size_y) w = area_def.x_size h = area_def.y_size ox = area_def.area_extent[0] + cw / 2. oy = area_def.area_extent[3] + ch / 2. swath_points_in_grid = _ll2cr.ll2cr_static(lons, lats, fill, p, cw, ch, w, h, ox, oy) return swath_points_in_grid, lons, lats def fornav(cols, rows, area_def, data_in, rows_per_scan=None, fill=None, out=None, weight_count=10000, weight_min=0.01, weight_distance_max=1.0, weight_delta_max=10.0, weight_sum_min=-1.0, maximum_weight_mode=False): """Remap data in to output grid using elliptical weighted averaging. This algorithm works under the assumption that the data is observed one scan line at a time. However, good results can still be achieved for non-scan based data is provided if `rows_per_scan` is set to the number of rows in the entire swath or by setting it to `None`. Parameters ---------- cols : numpy array Column location for each input swath pixel (from `ll2cr`) rows : numpy array Row location for each input swath pixel (from `ll2cr`) area_def : AreaDefinition Grid definition to be mapped to data_in : numpy array or tuple of numpy arrays Swath data to be remapped to output grid rows_per_scan : int or None, optional Number of data rows for every observed scanline. If None then the entire swath is treated as one large scanline. fill : float/int or None, optional If `data_in` is made of numpy arrays then this represents the fill value used to mark invalid data pixels. This value will also be used in the output array(s). If None, then np.nan will be used for float arrays and -999 will be used for integer arrays. out : numpy array or tuple of numpy arrays, optional Specify a numpy array to be written to for each input array. This can be used as an optimization by providing `np.memmap` arrays or other array-like objects. weight_count : int, optional number of elements to create in the gaussian weight table. Default is 10000. Must be at least 2 weight_min : float, optional the minimum value to store in the last position of the weight table. Default is 0.01, which, with a `weight_distance_max` of 1.0 produces a weight of 0.01 at a grid cell distance of 1.0. Must be greater than 0. weight_distance_max : float, optional distance in grid cell units at which to apply a weight of `weight_min`. Default is 1.0. Must be greater than 0. weight_delta_max : float, optional maximum distance in grid cells in each grid dimension over which to distribute a single swath cell. Default is 10.0. weight_sum_min : float, optional minimum weight sum value. Cells whose weight sums are less than `weight_sum_min` are set to the grid fill value. Default is EPSILON. maximum_weight_mode : bool, optional If False (default), a weighted average of all swath cells that map to a particular grid cell is used. If True, the swath cell having the maximum weight of all swath cells that map to a particular grid cell is used. This option should be used for coded/category data, i.e. snow cover. Returns ------- (valid grid points, output arrays): tuple of integer tuples and numpy array tuples The valid_grid_points tuple holds the number of output grid pixels that were written with valid data. The second element in the tuple is a tuple of output grid numpy arrays for each input array. If there was only one input array provided then the returned tuple is simply the singe points integer and single output grid array. 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static int __Pyx_init_sys_getdefaultencoding_params(void) { PyObject* sys; PyObject* default_encoding = NULL; char* default_encoding_c; sys = PyImport_ImportModule("sys"); if (!sys) goto bad; default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); Py_DECREF(sys); if (!default_encoding) goto bad; default_encoding_c = PyBytes_AsString(default_encoding); if (!default_encoding_c) goto bad; __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c)); if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); Py_DECREF(default_encoding); return 0; bad: Py_XDECREF(default_encoding); return -1; } #endif #endif /* Test for GCC > 2.95 */ #if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) #define likely(x) __builtin_expect(!!(x), 1) #define unlikely(x) __builtin_expect(!!(x), 0) #else /* !__GNUC__ or GCC < 2.95 */ #define likely(x) (x) #define unlikely(x) (x) #endif /* __GNUC__ */ static PyObject *__pyx_m; static PyObject *__pyx_d; static PyObject *__pyx_b; static PyObject *__pyx_empty_tuple; static PyObject *__pyx_empty_bytes; static PyObject *__pyx_empty_unicode; static int __pyx_lineno; static int __pyx_clineno = 0; static const char * __pyx_cfilenm= __FILE__; static const char *__pyx_filename; /* None.proto */ #if !defined(CYTHON_CCOMPLEX) #if defined(__cplusplus) #define CYTHON_CCOMPLEX 1 #elif defined(_Complex_I) #define CYTHON_CCOMPLEX 1 #else #define CYTHON_CCOMPLEX 0 #endif #endif #if CYTHON_CCOMPLEX #ifdef __cplusplus #include #else #include #endif #endif #if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) #undef _Complex_I #define _Complex_I 1.0fj #endif static const char *__pyx_f[] = { "pyresample/ewa/_fornav.pyx", "__init__.pxd", "stringsource", "type.pxd", "bool.pxd", "complex.pxd", }; /* BufferFormatStructs.proto */ #define IS_UNSIGNED(type) (((type) -1) > 0) struct __Pyx_StructField_; #define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) typedef struct { const char* name; struct __Pyx_StructField_* fields; size_t size; size_t arraysize[8]; int ndim; char typegroup; char is_unsigned; int flags; } __Pyx_TypeInfo; typedef struct __Pyx_StructField_ { __Pyx_TypeInfo* type; const char* name; size_t offset; } __Pyx_StructField; typedef struct { __Pyx_StructField* field; size_t parent_offset; } __Pyx_BufFmt_StackElem; typedef struct { __Pyx_StructField root; __Pyx_BufFmt_StackElem* head; size_t fmt_offset; size_t new_count, enc_count; size_t struct_alignment; int is_complex; char enc_type; char new_packmode; char enc_packmode; char is_valid_array; } __Pyx_BufFmt_Context; /* Atomics.proto */ #include #ifndef CYTHON_ATOMICS #define CYTHON_ATOMICS 1 #endif #define __pyx_atomic_int_type int #if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ !defined(__i386__) #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) #ifdef __PYX_DEBUG_ATOMICS #warning "Using GNU atomics" #endif #elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 #include #undef __pyx_atomic_int_type #define __pyx_atomic_int_type LONG #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) #ifdef __PYX_DEBUG_ATOMICS #pragma message ("Using MSVC atomics") #endif #elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) #ifdef __PYX_DEBUG_ATOMICS #warning "Using Intel atomics" #endif #else #undef CYTHON_ATOMICS #define CYTHON_ATOMICS 0 #ifdef __PYX_DEBUG_ATOMICS #warning "Not using atomics" #endif #endif typedef volatile __pyx_atomic_int_type __pyx_atomic_int; #if CYTHON_ATOMICS #define __pyx_add_acquisition_count(memview)\ __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #define __pyx_sub_acquisition_count(memview)\ __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #else #define __pyx_add_acquisition_count(memview)\ __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #define __pyx_sub_acquisition_count(memview)\ __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #endif /* MemviewSliceStruct.proto */ struct __pyx_memoryview_obj; typedef struct { struct __pyx_memoryview_obj *memview; char *data; Py_ssize_t shape[8]; Py_ssize_t strides[8]; Py_ssize_t suboffsets[8]; } __Pyx_memviewslice; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t */ typedef npy_int8 __pyx_t_5numpy_int8_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t */ typedef npy_int16 __pyx_t_5numpy_int16_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":727 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< * ctypedef npy_int64 int64_t * #ctypedef npy_int96 int96_t */ typedef npy_int32 __pyx_t_5numpy_int32_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":728 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< * #ctypedef npy_int96 int96_t * #ctypedef npy_int128 int128_t */ typedef npy_int64 __pyx_t_5numpy_int64_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":734 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< * ctypedef npy_uint64 uint64_t * #ctypedef npy_uint96 uint96_t */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":735 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< * #ctypedef npy_uint96 uint96_t * #ctypedef npy_uint128 uint128_t */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":739 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< * ctypedef npy_float64 float64_t * #ctypedef npy_float80 float80_t */ typedef npy_float32 __pyx_t_5numpy_float32_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":740 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< * #ctypedef npy_float80 float80_t * #ctypedef npy_float128 float128_t */ typedef npy_float64 __pyx_t_5numpy_float64_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t */ typedef npy_long __pyx_t_5numpy_int_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":750 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< * ctypedef npy_longlong longlong_t * */ typedef npy_longlong __pyx_t_5numpy_long_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< * * ctypedef npy_ulong uint_t */ typedef npy_longlong __pyx_t_5numpy_longlong_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t */ typedef npy_ulong __pyx_t_5numpy_uint_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":754 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< * ctypedef npy_ulonglong ulonglong_t * */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< * * ctypedef npy_intp intp_t */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":757 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< * ctypedef npy_uintp uintp_t * */ typedef npy_intp __pyx_t_5numpy_intp_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< * * ctypedef npy_double float_t */ typedef npy_uintp __pyx_t_5numpy_uintp_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t */ typedef npy_double __pyx_t_5numpy_float_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":761 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< * ctypedef npy_longdouble longdouble_t * */ typedef npy_double __pyx_t_5numpy_double_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< * * ctypedef npy_cfloat cfloat_t */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; /* None.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus typedef ::std::complex< float > __pyx_t_float_complex; #else typedef float _Complex __pyx_t_float_complex; #endif #else typedef struct { float real, imag; } __pyx_t_float_complex; #endif /* None.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus typedef ::std::complex< double > __pyx_t_double_complex; #else typedef double _Complex __pyx_t_double_complex; #endif #else typedef struct { double real, imag; } __pyx_t_double_complex; #endif /*--- Type declarations ---*/ struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct____pyx_fuse_0fornav_wrapper; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr; struct __pyx_array_obj; struct __pyx_MemviewEnum_obj; struct __pyx_memoryview_obj; struct __pyx_memoryviewslice_obj; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":764 * ctypedef npy_longdouble longdouble_t * * ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<< * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t */ typedef npy_cfloat __pyx_t_5numpy_cfloat_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":765 * * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<< * ctypedef npy_clongdouble clongdouble_t * */ typedef npy_cdouble __pyx_t_5numpy_cdouble_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":766 * ctypedef npy_cfloat cfloat_t * ctypedef npy_cdouble cdouble_t * ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<< * * ctypedef npy_cdouble complex_t */ typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":768 * ctypedef npy_clongdouble clongdouble_t * * ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<< * * cdef inline object PyArray_MultiIterNew1(a): */ typedef npy_cdouble __pyx_t_5numpy_complex_t; struct __pyx_defaults; typedef struct __pyx_defaults __pyx_defaults; struct __pyx_defaults1; typedef struct __pyx_defaults1 __pyx_defaults1; struct __pyx_defaults2; typedef struct __pyx_defaults2 __pyx_defaults2; struct __pyx_defaults3; typedef struct __pyx_defaults3 __pyx_defaults3; struct __pyx_defaults { PyBoolObject *__pyx_arg_maximum_weight_mode; unsigned int __pyx_arg_weight_count; weight_type __pyx_arg_weight_min; weight_type __pyx_arg_weight_distance_max; weight_type __pyx_arg_weight_delta_max; weight_type __pyx_arg_weight_sum_min; }; struct __pyx_defaults1 { PyBoolObject *__pyx_arg_maximum_weight_mode; unsigned int __pyx_arg_weight_count; weight_type __pyx_arg_weight_min; weight_type __pyx_arg_weight_distance_max; weight_type __pyx_arg_weight_delta_max; weight_type __pyx_arg_weight_sum_min; }; struct __pyx_defaults2 { PyBoolObject *__pyx_arg_maximum_weight_mode; unsigned int __pyx_arg_weight_count; weight_type __pyx_arg_weight_min; weight_type __pyx_arg_weight_distance_max; weight_type __pyx_arg_weight_delta_max; weight_type __pyx_arg_weight_sum_min; }; struct __pyx_defaults3 { PyBoolObject *__pyx_arg_maximum_weight_mode; unsigned int __pyx_arg_weight_count; weight_type __pyx_arg_weight_min; weight_type __pyx_arg_weight_distance_max; weight_type __pyx_arg_weight_delta_max; weight_type __pyx_arg_weight_sum_min; }; /* "pyresample/ewa/_fornav.pyx":199 * @cython.boundscheck(False) * @cython.wraparound(False) * def fornav_wrapper(numpy.ndarray[cr_dtype, ndim=2, mode='c'] cols_array, # <<<<<<<<<<<<<< * numpy.ndarray[cr_dtype, ndim=2, mode='c'] rows_array, * tuple input_arrays, tuple output_arrays, input_fill, output_fill, */ struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct____pyx_fuse_0fornav_wrapper { PyObject_HEAD PyArray_Descr *__pyx_v_in_type; PyObject *__pyx_v_input_arrays; PyArray_Descr *__pyx_v_out_type; PyObject *__pyx_v_output_arrays; }; /* "pyresample/ewa/_fornav.pyx":265 * if in_type != out_type: * raise ValueError("Input and Output must be of the same type") * if not all(input_array.dtype == in_type for input_array in input_arrays): # <<<<<<<<<<<<<< * raise ValueError("Input arrays must all be of the same data type") * if not all(output_array.dtype == out_type for output_array in output_arrays): */ struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr { PyObject_HEAD struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct____pyx_fuse_0fornav_wrapper *__pyx_outer_scope; PyObject *__pyx_v_input_array; }; /* "pyresample/ewa/_fornav.pyx":267 * if not all(input_array.dtype == in_type for input_array in input_arrays): * raise ValueError("Input arrays must all be of the same data type") * if not all(output_array.dtype == out_type for output_array in output_arrays): # <<<<<<<<<<<<<< * raise ValueError("Input arrays must all be of the same data type") * */ struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr { PyObject_HEAD struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct____pyx_fuse_0fornav_wrapper *__pyx_outer_scope; PyObject *__pyx_v_output_array; }; /* "pyresample/ewa/_fornav.pyx":199 * @cython.boundscheck(False) * @cython.wraparound(False) * def fornav_wrapper(numpy.ndarray[cr_dtype, ndim=2, mode='c'] cols_array, # <<<<<<<<<<<<<< * numpy.ndarray[cr_dtype, ndim=2, mode='c'] rows_array, * tuple input_arrays, tuple output_arrays, input_fill, output_fill, */ struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper { PyObject_HEAD PyArray_Descr *__pyx_v_in_type; PyObject *__pyx_v_input_arrays; PyArray_Descr *__pyx_v_out_type; PyObject *__pyx_v_output_arrays; }; /* "pyresample/ewa/_fornav.pyx":265 * if in_type != out_type: * raise ValueError("Input and Output must be of the same type") * if not all(input_array.dtype == in_type for input_array in input_arrays): # <<<<<<<<<<<<<< * raise ValueError("Input arrays must all be of the same data type") * if not all(output_array.dtype == out_type for output_array in output_arrays): */ struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr { PyObject_HEAD struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *__pyx_outer_scope; 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return unlikely(result < 0) ? result : (result == (eq == Py_EQ)); } /* DictGetItem.proto */ #if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key) { PyObject *value; value = PyDict_GetItemWithError(d, key); if (unlikely(!value)) { if (!PyErr_Occurred()) { PyObject* args = PyTuple_Pack(1, key); if (likely(args)) PyErr_SetObject(PyExc_KeyError, args); Py_XDECREF(args); } return NULL; } Py_INCREF(value); return value; } #else #define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) #endif /* UnicodeAsUCS4.proto */ static CYTHON_INLINE Py_UCS4 __Pyx_PyUnicode_AsPy_UCS4(PyObject*); /* object_ord.proto */ #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyObject_Ord(c)\ (likely(PyUnicode_Check(c)) ? 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(PyErr_SetString(PyExc_IndexError, "list assignment index out of range"), -1) :\ __Pyx_SetItemInt_Generic(o, to_py_func(i), v))) static CYTHON_INLINE int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v); static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list, int wraparound, int boundscheck); /* IterFinish.proto */ static CYTHON_INLINE int __Pyx_IterFinish(void); /* PyObjectCallMethO.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); #endif /* PyObjectCallNoArg.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func); #else #define __Pyx_PyObject_CallNoArg(func) __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL) #endif /* PyObjectCallOneArg.proto */ static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); /* PyObjectCallMethod0.proto */ static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name); /* RaiseNeedMoreValuesToUnpack.proto */ static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index); /* RaiseTooManyValuesToUnpack.proto */ static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected); /* UnpackItemEndCheck.proto */ static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected); /* RaiseNoneIterError.proto */ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void); /* UnpackTupleError.proto */ static void __Pyx_UnpackTupleError(PyObject *, Py_ssize_t index); /* UnpackTuple2.proto */ static CYTHON_INLINE int __Pyx_unpack_tuple2(PyObject* tuple, PyObject** value1, PyObject** value2, int is_tuple, int has_known_size, int decref_tuple); /* dict_iter.proto */ static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* dict, int is_dict, PyObject* method_name, Py_ssize_t* p_orig_length, int* p_is_dict); static CYTHON_INLINE int __Pyx_dict_iter_next(PyObject* dict_or_iter, Py_ssize_t orig_length, Py_ssize_t* ppos, PyObject** pkey, PyObject** pvalue, PyObject** pitem, int is_dict); /* ListAppend.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { PyListObject* L = (PyListObject*) list; Py_ssize_t len = Py_SIZE(list); if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); Py_SIZE(list) = len+1; return 0; } return PyList_Append(list, x); } #else #define __Pyx_PyList_Append(L,x) PyList_Append(L,x) #endif /* ArgTypeTest.proto */ static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, const char *name, int exact); /* None.proto */ static CYTHON_INLINE void __Pyx_RaiseClosureNameError(const char *varname); /* BufferFormatCheck.proto */ static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, __Pyx_BufFmt_StackElem* stack, __Pyx_TypeInfo* type); // PROTO /* GetItemInt.proto */ #define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ __Pyx_GetItemInt_Generic(o, to_py_func(i)))) #define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); #define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, int wraparound, int boundscheck); /* ExtTypeTest.proto */ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); #define __Pyx_BufPtrCContig2d(type, buf, i0, s0, i1, s1) ((type)((char*)buf + i0 * s0) + i1) /* GetModuleGlobalName.proto */ static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name); /* BufferFallbackError.proto */ static void __Pyx_RaiseBufferFallbackError(void); #define __Pyx_BufPtrStrided2d(type, buf, i0, s0, i1, s1) (type)((char*)buf + i0 * s0 + i1 * s1) /* IncludeStringH.proto */ #include /* BytesEquals.proto */ static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); /* UnicodeEquals.proto */ static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); /* StrEquals.proto */ #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals #else #define __Pyx_PyString_Equals __Pyx_PyBytes_Equals #endif /* None.proto */ static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* UnaryNegOverflows.proto */ #define UNARY_NEG_WOULD_OVERFLOW(x)\ (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ /* GetAttr.proto */ static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); /* decode_c_string.proto */ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( const char* cstring, Py_ssize_t start, Py_ssize_t stop, const char* encoding, const char* errors, PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); /* SwapException.proto */ #if CYTHON_COMPILING_IN_CPYTHON #define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); #else static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); #endif static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ /* ListCompAppend.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { PyListObject* L = (PyListObject*) list; Py_ssize_t len = Py_SIZE(list); if (likely(L->allocated > len)) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); Py_SIZE(list) = len+1; return 0; } return PyList_Append(list, x); } #else #define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) #endif /* PyIntBinop.proto */ #if CYTHON_COMPILING_IN_CPYTHON static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace); #else #define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\ (inplace ? PyNumber_InPlaceAdd(op1, op2) : PyNumber_Add(op1, op2)) #endif /* ListExtend.proto */ static CYTHON_INLINE int __Pyx_PyList_Extend(PyObject* L, PyObject* v) { #if CYTHON_COMPILING_IN_CPYTHON PyObject* none = _PyList_Extend((PyListObject*)L, v); if (unlikely(!none)) return -1; Py_DECREF(none); return 0; #else return PyList_SetSlice(L, PY_SSIZE_T_MAX, PY_SSIZE_T_MAX, v); #endif } /* None.proto */ static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname); /* ForceInitThreads.proto */ #ifndef __PYX_FORCE_INIT_THREADS #define __PYX_FORCE_INIT_THREADS 0 #endif /* None.proto */ static CYTHON_INLINE long __Pyx_div_long(long, long); /* WriteUnraisableException.proto */ static void __Pyx_WriteUnraisable(const char *name, int clineno, int lineno, const char *filename, int full_traceback, int nogil); /* SetVTable.proto */ static int __Pyx_SetVtable(PyObject *dict, void *vtable); /* FetchCommonType.proto */ static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type); /* CythonFunction.proto */ #define __Pyx_CyFunction_USED 1 #include #define __Pyx_CYFUNCTION_STATICMETHOD 0x01 #define __Pyx_CYFUNCTION_CLASSMETHOD 0x02 #define __Pyx_CYFUNCTION_CCLASS 0x04 #define __Pyx_CyFunction_GetClosure(f)\ (((__pyx_CyFunctionObject *) (f))->func_closure) #define __Pyx_CyFunction_GetClassObj(f)\ (((__pyx_CyFunctionObject *) (f))->func_classobj) #define __Pyx_CyFunction_Defaults(type, f)\ ((type *)(((__pyx_CyFunctionObject *) (f))->defaults)) #define __Pyx_CyFunction_SetDefaultsGetter(f, g)\ ((__pyx_CyFunctionObject *) (f))->defaults_getter = (g) typedef struct { PyCFunctionObject func; #if PY_VERSION_HEX < 0x030500A0 PyObject *func_weakreflist; #endif PyObject *func_dict; PyObject *func_name; PyObject *func_qualname; PyObject *func_doc; PyObject *func_globals; PyObject *func_code; PyObject *func_closure; PyObject *func_classobj; void *defaults; int defaults_pyobjects; int flags; PyObject *defaults_tuple; PyObject *defaults_kwdict; PyObject *(*defaults_getter)(PyObject *); PyObject *func_annotations; } __pyx_CyFunctionObject; static PyTypeObject *__pyx_CyFunctionType = 0; #define __Pyx_CyFunction_NewEx(ml, flags, qualname, self, module, globals, code)\ __Pyx_CyFunction_New(__pyx_CyFunctionType, ml, flags, qualname, self, module, globals, code) static PyObject *__Pyx_CyFunction_New(PyTypeObject *, PyMethodDef *ml, int flags, PyObject* qualname, PyObject *self, PyObject *module, PyObject *globals, PyObject* code); static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *m, size_t size, int pyobjects); static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *m, PyObject *tuple); static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *m, PyObject *dict); static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *m, PyObject *dict); static int __pyx_CyFunction_init(void); /* FusedFunction.proto */ typedef struct { __pyx_CyFunctionObject func; PyObject *__signatures__; PyObject *type; PyObject *self; } __pyx_FusedFunctionObject; #define __pyx_FusedFunction_NewEx(ml, flags, qualname, self, module, globals, code)\ __pyx_FusedFunction_New(__pyx_FusedFunctionType, ml, flags, qualname, self, module, globals, code) static PyObject *__pyx_FusedFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags, PyObject *qualname, PyObject *self, PyObject *module, PyObject *globals, PyObject *code); static int __pyx_FusedFunction_clear(__pyx_FusedFunctionObject *self); static PyTypeObject *__pyx_FusedFunctionType = NULL; static int __pyx_FusedFunction_init(void); #define __Pyx_FusedFunction_USED /* CodeObjectCache.proto */ typedef struct { PyCodeObject* code_object; int code_line; } __Pyx_CodeObjectCacheEntry; struct __Pyx_CodeObjectCache { int count; int max_count; __Pyx_CodeObjectCacheEntry* entries; }; static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); static PyCodeObject *__pyx_find_code_object(int code_line); static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); /* AddTraceback.proto */ static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename); #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); static void __Pyx_ReleaseBuffer(Py_buffer *view); #else #define __Pyx_GetBuffer PyObject_GetBuffer #define __Pyx_ReleaseBuffer PyBuffer_Release #endif /* BufferStructDeclare.proto */ typedef struct { Py_ssize_t shape, strides, suboffsets; } __Pyx_Buf_DimInfo; typedef struct { size_t refcount; Py_buffer pybuffer; } __Pyx_Buffer; typedef struct { __Pyx_Buffer *rcbuffer; char *data; __Pyx_Buf_DimInfo diminfo[8]; } __Pyx_LocalBuf_ND; /* None.proto */ static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0}; static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1}; /* MemviewSliceIsContig.proto */ static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); /* OverlappingSlices.proto */ static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, __Pyx_memviewslice *slice2, int ndim, size_t itemsize); /* Capsule.proto */ static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); /* TypeInfoCompare.proto */ static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); /* MemviewSliceValidateAndInit.proto */ static int __Pyx_ValidateAndInit_memviewslice( int *axes_specs, int c_or_f_flag, int buf_flags, int ndim, __Pyx_TypeInfo *dtype, __Pyx_BufFmt_StackElem stack[], __Pyx_memviewslice *memviewslice, PyObject *original_obj); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5numpy_float32_t(PyObject *); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5numpy_float64_t(PyObject *); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_int(unsigned int value); /* BytesContains.proto */ static CYTHON_INLINE int __Pyx_BytesContains(PyObject* bytes, char character); /* None.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus #define __Pyx_CREAL(z) ((z).real()) #define __Pyx_CIMAG(z) ((z).imag()) #else #define __Pyx_CREAL(z) (__real__(z)) #define __Pyx_CIMAG(z) (__imag__(z)) #endif #else #define __Pyx_CREAL(z) ((z).real) #define __Pyx_CIMAG(z) ((z).imag) #endif #if defined(__cplusplus) && CYTHON_CCOMPLEX && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) #define __Pyx_SET_CREAL(z,x) ((z).real(x)) #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) #else #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) #endif /* None.proto */ static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); /* None.proto */ #if CYTHON_CCOMPLEX #define __Pyx_c_eqf(a, b) ((a)==(b)) #define __Pyx_c_sumf(a, b) ((a)+(b)) #define __Pyx_c_difff(a, b) ((a)-(b)) #define __Pyx_c_prodf(a, b) ((a)*(b)) #define __Pyx_c_quotf(a, b) ((a)/(b)) #define __Pyx_c_negf(a) (-(a)) #ifdef __cplusplus #define __Pyx_c_is_zerof(z) ((z)==(float)0) #define __Pyx_c_conjf(z) (::std::conj(z)) #if 1 #define __Pyx_c_absf(z) (::std::abs(z)) #define __Pyx_c_powf(a, b) (::std::pow(a, b)) #endif #else #define __Pyx_c_is_zerof(z) ((z)==0) #define __Pyx_c_conjf(z) (conjf(z)) #if 1 #define __Pyx_c_absf(z) (cabsf(z)) #define __Pyx_c_powf(a, b) (cpowf(a, b)) #endif #endif #else static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex); static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex); #if 1 static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex, __pyx_t_float_complex); #endif #endif /* None.proto */ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); /* None.proto */ #if CYTHON_CCOMPLEX #define __Pyx_c_eq(a, b) ((a)==(b)) #define __Pyx_c_sum(a, b) ((a)+(b)) #define __Pyx_c_diff(a, b) ((a)-(b)) #define __Pyx_c_prod(a, b) ((a)*(b)) #define __Pyx_c_quot(a, b) ((a)/(b)) #define __Pyx_c_neg(a) (-(a)) #ifdef __cplusplus #define __Pyx_c_is_zero(z) ((z)==(double)0) #define __Pyx_c_conj(z) (::std::conj(z)) #if 1 #define __Pyx_c_abs(z) (::std::abs(z)) #define __Pyx_c_pow(a, b) (::std::pow(a, b)) #endif #else #define __Pyx_c_is_zero(z) ((z)==0) #define __Pyx_c_conj(z) (conj(z)) #if 1 #define __Pyx_c_abs(z) (cabs(z)) #define __Pyx_c_pow(a, b) (cpow(a, b)) #endif #endif #else static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex); static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex); #if 1 static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex, __pyx_t_double_complex); #endif #endif /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); /* MemviewSliceCopyTemplate.proto */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, const char *mode, int ndim, size_t sizeof_dtype, int contig_flag, int dtype_is_object); /* MemviewSliceInit.proto */ #define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d #define __Pyx_MEMVIEW_DIRECT 1 #define __Pyx_MEMVIEW_PTR 2 #define __Pyx_MEMVIEW_FULL 4 #define __Pyx_MEMVIEW_CONTIG 8 #define __Pyx_MEMVIEW_STRIDED 16 #define __Pyx_MEMVIEW_FOLLOW 32 #define __Pyx_IS_C_CONTIG 1 #define __Pyx_IS_F_CONTIG 2 static int __Pyx_init_memviewslice( struct __pyx_memoryview_obj *memview, int ndim, __Pyx_memviewslice *memviewslice, int memview_is_new_reference); static CYTHON_INLINE int __pyx_add_acquisition_count_locked( __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); #define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) #define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) #define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) #define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); /* CIntFromPy.proto */ static CYTHON_INLINE size_t __Pyx_PyInt_As_size_t(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE npy_int8 __Pyx_PyInt_As_npy_int8(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); /* PyObjectCallMethod1.proto */ static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg); /* CoroutineBase.proto */ typedef PyObject *(*__pyx_coroutine_body_t)(PyObject *, PyObject *); typedef struct { PyObject_HEAD __pyx_coroutine_body_t body; PyObject *closure; PyObject *exc_type; PyObject *exc_value; PyObject *exc_traceback; PyObject *gi_weakreflist; PyObject *classobj; PyObject *yieldfrom; PyObject *gi_name; PyObject *gi_qualname; int resume_label; char is_running; } __pyx_CoroutineObject; static __pyx_CoroutineObject *__Pyx__Coroutine_New(PyTypeObject *type, __pyx_coroutine_body_t body, PyObject *closure, PyObject *name, PyObject *qualname); static int __Pyx_Coroutine_clear(PyObject *self); #if 1 || PY_VERSION_HEX < 0x030300B0 static int __Pyx_PyGen_FetchStopIterationValue(PyObject **pvalue); #else #define __Pyx_PyGen_FetchStopIterationValue(pvalue) PyGen_FetchStopIterationValue(pvalue) #endif /* PatchModuleWithCoroutine.proto */ static PyObject* __Pyx_Coroutine_patch_module(PyObject* module, const char* py_code); /* PatchGeneratorABC.proto */ static int __Pyx_patch_abc(void); /* Generator.proto */ #define __Pyx_Generator_USED static PyTypeObject *__pyx_GeneratorType = 0; #define __Pyx_Generator_CheckExact(obj) (Py_TYPE(obj) == __pyx_GeneratorType) #define __Pyx_Generator_New(body, closure, name, qualname)\ __Pyx__Coroutine_New(__pyx_GeneratorType, body, closure, name, qualname) static PyObject *__Pyx_Generator_Next(PyObject *self); static int __pyx_Generator_init(void); /* CheckBinaryVersion.proto */ static int __Pyx_check_binary_version(void); /* PyIdentifierFromString.proto */ #if !defined(__Pyx_PyIdentifier_FromString) #if PY_MAJOR_VERSION < 3 #define __Pyx_PyIdentifier_FromString(s) PyString_FromString(s) #else #define __Pyx_PyIdentifier_FromString(s) PyUnicode_FromString(s) #endif #endif /* ModuleImport.proto */ static PyObject *__Pyx_ImportModule(const char *name); /* TypeImport.proto */ static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict); /* InitStrings.proto */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ /* Module declarations from 'cython' */ /* Module declarations from 'cpython.buffer' */ /* Module declarations from 'libc.string' */ /* Module declarations from 'libc.stdio' */ /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.type' */ static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; /* Module declarations from 'cpython.version' */ /* Module declarations from 'cpython.exc' */ /* Module declarations from 'cpython.module' */ /* Module declarations from 'cpython.mem' */ /* Module declarations from 'cpython.tuple' */ /* Module declarations from 'cpython.list' */ /* Module declarations from 'cpython.sequence' */ /* Module declarations from 'cpython.mapping' */ /* Module declarations from 'cpython.iterator' */ /* Module declarations from 'cpython.number' */ /* Module declarations from 'cpython.int' */ /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.bool' */ static PyTypeObject *__pyx_ptype_7cpython_4bool_bool = 0; /* Module declarations from 'cpython.long' */ /* Module declarations from 'cpython.float' */ /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.complex' */ static PyTypeObject *__pyx_ptype_7cpython_7complex_complex = 0; /* Module declarations from 'cpython.string' */ /* Module declarations from 'cpython.unicode' */ /* Module declarations from 'cpython.dict' */ /* Module declarations from 'cpython.instance' */ /* Module declarations from 'cpython.function' */ /* Module declarations from 'cpython.method' */ /* Module declarations from 'cpython.weakref' */ /* Module declarations from 'cpython.getargs' */ /* Module declarations from 'cpython.pythread' */ /* Module declarations from 'cpython.pystate' */ /* Module declarations from 'cpython.cobject' */ /* Module declarations from 'cpython.oldbuffer' */ /* Module declarations from 'cpython.set' */ /* Module declarations from 'cpython.bytes' */ /* Module declarations from 'cpython.pycapsule' */ /* Module declarations from 'cpython' */ /* Module declarations from 'cpython.object' */ /* Module declarations from 'cpython.ref' */ /* Module declarations from 'libc.stdlib' */ /* Module declarations from 'numpy' */ /* Module declarations from 'numpy' */ static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ /* Module declarations from 'pyresample.ewa._fornav' */ static PyTypeObject *__pyx_ptype_10pyresample_3ewa_7_fornav___pyx_scope_struct____pyx_fuse_0fornav_wrapper = 0; static PyTypeObject *__pyx_ptype_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr = 0; static PyTypeObject *__pyx_ptype_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr = 0; static PyTypeObject *__pyx_ptype_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper = 0; static PyTypeObject *__pyx_ptype_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr = 0; static PyTypeObject *__pyx_ptype_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr = 0; static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; static PyTypeObject *__pyx_memoryview_type = 0; static PyTypeObject *__pyx_memoryviewslice_type = 0; static PyObject *generic = 0; static PyObject *strided = 0; static PyObject *indirect = 0; static PyObject *contiguous = 0; static PyObject *indirect_contiguous = 0; static int __pyx_memoryview_thread_locks_used; static PyThread_type_lock __pyx_memoryview_thread_locks[8]; static int __pyx_fuse_0_0_0__pyx_f_10pyresample_3ewa_7_fornav_fornav(unsigned int *, size_t, size_t, size_t, size_t, size_t, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t **, __pyx_t_5numpy_float32_t **, __pyx_t_5numpy_float32_t, __pyx_t_5numpy_float32_t, size_t, unsigned int, float, float, float, float, int); /*proto*/ static int __pyx_fuse_0_1_1__pyx_f_10pyresample_3ewa_7_fornav_fornav(unsigned int *, size_t, size_t, size_t, size_t, size_t, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float64_t **, __pyx_t_5numpy_float64_t **, __pyx_t_5numpy_float64_t, __pyx_t_5numpy_float64_t, size_t, unsigned int, float, float, float, float, int); /*proto*/ static int __pyx_fuse_0_2_2__pyx_f_10pyresample_3ewa_7_fornav_fornav(unsigned int *, size_t, size_t, size_t, size_t, size_t, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_float32_t *, __pyx_t_5numpy_int8_t **, __pyx_t_5numpy_int8_t **, __pyx_t_5numpy_int8_t, __pyx_t_5numpy_int8_t, size_t, unsigned int, float, float, float, float, int); /*proto*/ static int __pyx_fuse_1_0_0__pyx_f_10pyresample_3ewa_7_fornav_fornav(unsigned int *, size_t, size_t, size_t, size_t, size_t, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float32_t **, __pyx_t_5numpy_float32_t **, __pyx_t_5numpy_float32_t, __pyx_t_5numpy_float32_t, size_t, unsigned int, float, float, float, float, int); /*proto*/ static int __pyx_fuse_1_1_1__pyx_f_10pyresample_3ewa_7_fornav_fornav(unsigned int *, size_t, size_t, size_t, size_t, size_t, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t **, __pyx_t_5numpy_float64_t **, __pyx_t_5numpy_float64_t, __pyx_t_5numpy_float64_t, size_t, unsigned int, float, float, float, float, int); /*proto*/ static int __pyx_fuse_1_2_2__pyx_f_10pyresample_3ewa_7_fornav_fornav(unsigned int *, size_t, size_t, size_t, size_t, size_t, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_float64_t *, __pyx_t_5numpy_int8_t **, __pyx_t_5numpy_int8_t **, __pyx_t_5numpy_int8_t, __pyx_t_5numpy_int8_t, size_t, unsigned int, float, float, float, float, int); /*proto*/ static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ static void *__pyx_align_pointer(void *, size_t); /*proto*/ static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ static PyObject *_unellipsify(PyObject *, int); /*proto*/ static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t = { "float32_t", NULL, sizeof(__pyx_t_5numpy_float32_t), { 0 }, 0, 'R', 0, 0 }; static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t = { "float64_t", NULL, sizeof(__pyx_t_5numpy_float64_t), { 0 }, 0, 'R', 0, 0 }; static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_int8_t = { "int8_t", NULL, sizeof(__pyx_t_5numpy_int8_t), { 0 }, 0, IS_UNSIGNED(__pyx_t_5numpy_int8_t) ? 'U' : 'I', IS_UNSIGNED(__pyx_t_5numpy_int8_t), 0 }; #define __Pyx_MODULE_NAME "pyresample.ewa._fornav" int __pyx_module_is_main_pyresample__ewa___fornav = 0; /* Implementation of 'pyresample.ewa._fornav' */ static PyObject *__pyx_builtin_RuntimeError; static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_ImportError; static PyObject *__pyx_builtin_AttributeError; static PyObject *__pyx_builtin_TypeError; static PyObject *__pyx_builtin_zip; static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_enumerate; static PyObject *__pyx_builtin_Ellipsis; static PyObject *__pyx_builtin_id; static PyObject *__pyx_builtin_IndexError; static const char __pyx_k_O[] = "O"; static const char __pyx_k_c[] = "c"; static const char __pyx_k_i[] = "i"; static const char __pyx_k_id[] = "id"; static const char __pyx_k__13[] = "()"; static const char __pyx_k__15[] = "|"; static const char __pyx_k_obj[] = "obj"; static const char __pyx_k_zip[] = "zip"; static const char __pyx_k_args[] = "args"; static const char __pyx_k_base[] = "base"; static const char __pyx_k_int8[] = "int8"; static const char __pyx_k_kind[] = "kind"; static const char __pyx_k_main[] = "__main__"; static const char __pyx_k_mode[] = "mode"; static const char __pyx_k_name[] = "name"; static const char __pyx_k_ndim[] = "ndim"; static const char __pyx_k_pack[] = "pack"; static const char __pyx_k_send[] = "send"; static const char __pyx_k_size[] = "size"; static const char __pyx_k_step[] = "step"; static const char __pyx_k_stop[] = "stop"; static const char __pyx_k_test[] = "__test__"; static const char __pyx_k_ASCII[] = "ASCII"; static const char __pyx_k_class[] = "__class__"; static const char __pyx_k_close[] = "close"; static const char __pyx_k_dtype[] = "dtype"; static const char __pyx_k_error[] = "error"; static const char __pyx_k_flags[] = "flags"; static const char __pyx_k_numpy[] = "numpy"; static const char __pyx_k_range[] = "range"; static const char __pyx_k_shape[] = "shape"; static const char __pyx_k_split[] = "split"; static const char __pyx_k_start[] = "start"; static const char __pyx_k_strip[] = "strip"; static const char __pyx_k_throw[] = "throw"; static const char __pyx_k_encode[] = "encode"; static const char __pyx_k_format[] = "format"; static const char __pyx_k_import[] = "__import__"; static const char __pyx_k_kwargs[] = "kwargs"; static const char __pyx_k_name_2[] = "__name__"; static const char __pyx_k_struct[] = "struct"; static const char __pyx_k_unpack[] = "unpack"; static const char __pyx_k_float32[] = "float32"; static const char __pyx_k_float64[] = "float64"; static const char __pyx_k_fortran[] = "fortran"; static const char __pyx_k_genexpr[] = "genexpr"; static const char __pyx_k_in_type[] = "in_type"; static const char __pyx_k_memview[] = "memview"; static const char __pyx_k_ndarray[] = "ndarray"; static const char __pyx_k_Ellipsis[] = "Ellipsis"; static const char __pyx_k_defaults[] = "defaults"; static const char __pyx_k_itemsize[] = "itemsize"; static const char __pyx_k_out_type[] = "out_type"; static const char __pyx_k_TypeError[] = "TypeError"; static const char __pyx_k_docformat[] = "__docformat__"; static const char __pyx_k_enumerate[] = "enumerate"; static const char __pyx_k_float32_t[] = "float32_t"; static const char __pyx_k_float64_t[] = "float64_t"; static const char __pyx_k_grid_cols[] = "grid_cols"; static const char __pyx_k_grid_rows[] = "grid_rows"; static const char __pyx_k_num_items[] = "num_items"; static const char __pyx_k_valid_arr[] = "valid_arr"; static const char __pyx_k_IndexError[] = "IndexError"; static const char __pyx_k_ValueError[] = "ValueError"; static const char __pyx_k_cols_array[] = "cols_array"; static const char __pyx_k_input_fill[] = "input_fill"; static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; static const char __pyx_k_rows_array[] = "rows_array"; static const char __pyx_k_signatures[] = "signatures"; static const char __pyx_k_swath_cols[] = "swath_cols"; static const char __pyx_k_swath_rows[] = "swath_rows"; static const char __pyx_k_tmp_arr_i8[] = "tmp_arr_i8"; static const char __pyx_k_valid_list[] = "valid_list"; static const char __pyx_k_weight_min[] = "weight_min"; static const char __pyx_k_ImportError[] = "ImportError"; static const char __pyx_k_MemoryError[] = "MemoryError"; static const char __pyx_k_func_result[] = "func_result"; static const char __pyx_k_num_outputs[] = "num_outputs"; static const char __pyx_k_output_fill[] = "output_fill"; static const char __pyx_k_tmp_arr_f32[] = "tmp_arr_f32"; static const char __pyx_k_tmp_arr_f64[] = "tmp_arr_f64"; static const char __pyx_k_RuntimeError[] = "RuntimeError"; static const char __pyx_k_cols_pointer[] = "cols_pointer"; static const char __pyx_k_input_arrays[] = "input_arrays"; static const char __pyx_k_rows_pointer[] = "rows_pointer"; static const char __pyx_k_weight_count[] = "weight_count"; static const char __pyx_k_input_pointer[] = "input_pointer"; static const char __pyx_k_output_arrays[] = "output_arrays"; static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; static const char __pyx_k_rows_per_scan[] = "rows_per_scan"; static const char __pyx_k_AttributeError[] = "AttributeError"; static const char __pyx_k_fornav_wrapper[] = "fornav_wrapper"; static const char __pyx_k_output_pointer[] = "output_pointer"; static const char __pyx_k_weight_sum_min[] = "weight_sum_min"; static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; static const char __pyx_k_weight_delta_max[] = "weight_delta_max"; static const char __pyx_k_strided_and_direct[] = ""; static const char __pyx_k_maximum_weight_mode[] = "maximum_weight_mode"; static const char __pyx_k_restructuredtext_en[] = "restructuredtext en"; static const char __pyx_k_weight_distance_max[] = "weight_distance_max"; static const char __pyx_k_strided_and_indirect[] = ""; static const char __pyx_k_No_input_arrays_given[] = "No input arrays given"; static const char __pyx_k_contiguous_and_direct[] = ""; static const char __pyx_k_MemoryView_of_r_object[] = ""; static const char __pyx_k_pyresample_ewa__fornav[] = "pyresample.ewa._fornav"; static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; static const char __pyx_k_contiguous_and_indirect[] = ""; static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; static const char __pyx_k_No_matching_signature_found[] = "No matching signature found"; static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; static const char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static const char __pyx_k_Expected_at_least_d_arguments[] = "Expected at least %d arguments"; static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static const char __pyx_k_pyx_fuse_0fornav_wrapper_local[] = "__pyx_fuse_0fornav_wrapper..genexpr"; static const char __pyx_k_pyx_fuse_1fornav_wrapper_local[] = "__pyx_fuse_1fornav_wrapper..genexpr"; static const char __pyx_k_strided_and_direct_or_indirect[] = ""; static const char __pyx_k_EWA_requires_2_or_more_rows_per[] = "EWA requires 2 or more rows_per_scan and must be a factor of the total number of input rows"; static const char __pyx_k_Input_and_Output_must_be_of_the[] = "Input and Output must be of the same type"; static const char __pyx_k_Input_arrays_must_all_be_of_the[] = "Input arrays must all be of the same data type"; static const char __pyx_k_Must_have_same_number_of_inputs[] = "Must have same number of inputs and outputs"; static const char __pyx_k_Users_davidh_repos_git_pyresamp[] = "/Users/davidh/repos/git/pyresample/pyresample/ewa/_fornav.pyx"; static const char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; static const char __pyx_k_Could_not_initialize_weight_stru[] = "Could not initialize weight structure for EWA resampling"; static const char __pyx_k_EWA_Resampling_No_swath_pixels_f[] = "EWA Resampling: No swath pixels found inside grid to be resampled"; static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; static const char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; static const char __pyx_k_Function_call_with_ambiguous_arg[] = "Function call with ambiguous argument types"; static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; static const char __pyx_k_Resampling_swath_data_to_uniform[] = "Resampling swath data to uniform grid using an Elliptical Weighted\nAveraging (EWA) algorithm.\n"; static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; static const char __pyx_k_Unknown_input_and_output_data_ty[] = "Unknown input and output data type"; static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; static const char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; static PyObject *__pyx_n_s_ASCII; static PyObject *__pyx_n_s_AttributeError; static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; static PyObject *__pyx_kp_s_Cannot_index_with_type_s; static PyObject *__pyx_kp_s_Could_not_initialize_weight_stru; static PyObject *__pyx_kp_s_EWA_Resampling_No_swath_pixels_f; static PyObject *__pyx_kp_s_EWA_requires_2_or_more_rows_per; static PyObject *__pyx_n_s_Ellipsis; static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; static PyObject *__pyx_kp_s_Expected_at_least_d_arguments; static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_kp_s_Function_call_with_ambiguous_arg; static PyObject *__pyx_n_s_ImportError; static PyObject *__pyx_n_s_IndexError; static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; static PyObject *__pyx_kp_s_Input_and_Output_must_be_of_the; static PyObject *__pyx_kp_s_Input_arrays_must_all_be_of_the; static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; static PyObject *__pyx_n_s_MemoryError; static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; static PyObject *__pyx_kp_s_MemoryView_of_r_object; static PyObject *__pyx_kp_s_Must_have_same_number_of_inputs; static PyObject *__pyx_kp_s_No_input_arrays_given; static PyObject *__pyx_kp_s_No_matching_signature_found; static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; static PyObject *__pyx_n_b_O; static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_RuntimeError; static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_kp_s_Unknown_input_and_output_data_ty; static PyObject *__pyx_kp_s_Users_davidh_repos_git_pyresamp; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_kp_s__13; static PyObject *__pyx_kp_s__15; static PyObject *__pyx_n_s_allocate_buffer; static PyObject *__pyx_n_s_args; static PyObject *__pyx_n_s_base; static PyObject *__pyx_n_s_c; static PyObject *__pyx_n_u_c; static PyObject *__pyx_n_s_class; static PyObject *__pyx_n_s_close; static PyObject *__pyx_n_s_cols_array; static PyObject *__pyx_n_s_cols_pointer; static PyObject *__pyx_kp_s_contiguous_and_direct; static PyObject *__pyx_kp_s_contiguous_and_indirect; static PyObject *__pyx_n_s_defaults; static PyObject *__pyx_n_s_docformat; static PyObject *__pyx_n_s_dtype; static PyObject *__pyx_n_s_dtype_is_object; static PyObject *__pyx_n_s_encode; static PyObject *__pyx_n_s_enumerate; static PyObject *__pyx_n_s_error; static PyObject *__pyx_n_s_flags; static PyObject *__pyx_n_s_float32; static PyObject *__pyx_n_s_float32_t; static PyObject *__pyx_n_s_float64; static PyObject *__pyx_n_s_float64_t; static PyObject *__pyx_n_s_format; static PyObject *__pyx_n_s_fornav_wrapper; static PyObject *__pyx_n_s_fortran; static PyObject *__pyx_n_u_fortran; static PyObject *__pyx_n_s_func_result; static PyObject *__pyx_n_s_genexpr; static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; static PyObject *__pyx_n_s_grid_cols; static PyObject *__pyx_n_s_grid_rows; static PyObject *__pyx_n_s_i; static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_in_type; static PyObject *__pyx_n_s_input_arrays; static PyObject *__pyx_n_s_input_fill; static PyObject *__pyx_n_s_input_pointer; static PyObject *__pyx_n_s_int8; static PyObject *__pyx_n_s_itemsize; static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; static PyObject *__pyx_n_s_kind; static PyObject *__pyx_n_s_kwargs; static PyObject *__pyx_n_s_main; static PyObject *__pyx_n_s_maximum_weight_mode; static PyObject *__pyx_n_s_memview; static PyObject *__pyx_n_s_mode; static PyObject *__pyx_n_s_name; static PyObject *__pyx_n_s_name_2; static PyObject *__pyx_n_s_ndarray; static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous; static PyObject *__pyx_kp_u_ndarray_is_not_Fortran_contiguou; static PyObject *__pyx_n_s_ndim; static PyObject *__pyx_n_s_num_items; static PyObject *__pyx_n_s_num_outputs; static PyObject *__pyx_n_s_numpy; static PyObject *__pyx_n_s_obj; static PyObject *__pyx_n_s_out_type; static PyObject *__pyx_n_s_output_arrays; static PyObject *__pyx_n_s_output_fill; static PyObject *__pyx_n_s_output_pointer; static PyObject *__pyx_n_s_pack; static PyObject *__pyx_n_s_pyresample_ewa__fornav; static PyObject *__pyx_n_s_pyx_fuse_0fornav_wrapper_local; static PyObject *__pyx_n_s_pyx_fuse_1fornav_wrapper_local; static PyObject *__pyx_n_s_pyx_getbuffer; static PyObject *__pyx_n_s_pyx_vtable; static PyObject *__pyx_n_s_range; static PyObject *__pyx_kp_s_restructuredtext_en; static PyObject *__pyx_n_s_rows_array; static PyObject *__pyx_n_s_rows_per_scan; static PyObject *__pyx_n_s_rows_pointer; static PyObject *__pyx_n_s_send; static PyObject *__pyx_n_s_shape; static PyObject *__pyx_n_s_signatures; static PyObject *__pyx_n_s_size; static PyObject *__pyx_n_s_split; static PyObject *__pyx_n_s_start; static PyObject *__pyx_n_s_step; static PyObject *__pyx_n_s_stop; static PyObject *__pyx_kp_s_strided_and_direct; static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; static PyObject *__pyx_kp_s_strided_and_indirect; static PyObject *__pyx_n_s_strip; static PyObject *__pyx_n_s_struct; static PyObject *__pyx_n_s_swath_cols; static PyObject *__pyx_n_s_swath_rows; static PyObject *__pyx_n_s_test; static PyObject *__pyx_n_s_throw; static PyObject *__pyx_n_s_tmp_arr_f32; static PyObject *__pyx_n_s_tmp_arr_f64; static PyObject *__pyx_n_s_tmp_arr_i8; static PyObject *__pyx_kp_s_unable_to_allocate_array_data; static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; static PyObject *__pyx_n_s_unpack; static PyObject *__pyx_n_s_valid_arr; static PyObject *__pyx_n_s_valid_list; static PyObject *__pyx_n_s_weight_count; static PyObject *__pyx_n_s_weight_delta_max; static PyObject *__pyx_n_s_weight_distance_max; static PyObject *__pyx_n_s_weight_min; static PyObject *__pyx_n_s_weight_sum_min; static PyObject *__pyx_n_s_zip; static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_fornav_wrapper(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_signatures, PyObject *__pyx_v_args, PyObject *__pyx_v_kwargs, CYTHON_UNUSED PyObject *__pyx_v_defaults); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_12__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_14fornav_wrapper_genexpr(PyObject *__pyx_self); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_14fornav_wrapper_3genexpr(PyObject *__pyx_self); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_2fornav_wrapper(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_cols_array, PyArrayObject *__pyx_v_rows_array, PyObject *__pyx_v_input_arrays, PyObject *__pyx_v_output_arrays, PyObject *__pyx_v_input_fill, PyObject *__pyx_v_output_fill, size_t __pyx_v_rows_per_scan, unsigned int __pyx_v_weight_count, weight_type __pyx_v_weight_min, weight_type __pyx_v_weight_distance_max, weight_type __pyx_v_weight_delta_max, weight_type __pyx_v_weight_sum_min, PyBoolObject *__pyx_v_maximum_weight_mode); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_14__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_14fornav_wrapper_6genexpr(PyObject *__pyx_self); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_14fornav_wrapper_9genexpr(PyObject *__pyx_self); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_7_fornav_4fornav_wrapper(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_cols_array, PyArrayObject *__pyx_v_rows_array, PyObject *__pyx_v_input_arrays, PyObject *__pyx_v_output_arrays, PyObject *__pyx_v_input_fill, PyObject *__pyx_v_output_fill, size_t __pyx_v_rows_per_scan, unsigned int __pyx_v_weight_count, weight_type __pyx_v_weight_min, weight_type __pyx_v_weight_distance_max, weight_type __pyx_v_weight_delta_max, weight_type __pyx_v_weight_sum_min, PyBoolObject *__pyx_v_maximum_weight_mode); /* proto */ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct____pyx_fuse_0fornav_wrapper(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new__memoryviewslice(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_int_0; static PyObject *__pyx_int_1; static PyObject *__pyx_int_neg_1; static PyObject *__pyx_tuple_; static PyObject *__pyx_tuple__2; static PyObject *__pyx_tuple__3; static PyObject *__pyx_tuple__4; static PyObject *__pyx_tuple__5; static PyObject *__pyx_tuple__6; static PyObject *__pyx_tuple__7; static PyObject *__pyx_tuple__8; static PyObject *__pyx_tuple__9; static PyObject *__pyx_slice__48; static PyObject *__pyx_slice__49; static PyObject *__pyx_slice__50; static PyObject *__pyx_tuple__10; static PyObject *__pyx_tuple__11; static PyObject *__pyx_tuple__12; static PyObject *__pyx_tuple__14; static PyObject *__pyx_tuple__16; static PyObject *__pyx_tuple__17; static PyObject *__pyx_tuple__18; static PyObject *__pyx_tuple__19; static PyObject *__pyx_tuple__20; static PyObject *__pyx_tuple__21; static PyObject *__pyx_tuple__22; static PyObject *__pyx_tuple__23; static PyObject *__pyx_tuple__24; static PyObject *__pyx_tuple__25; static PyObject *__pyx_tuple__26; static PyObject *__pyx_tuple__27; static PyObject *__pyx_tuple__28; static PyObject *__pyx_tuple__29; static PyObject *__pyx_tuple__30; static PyObject *__pyx_tuple__31; static PyObject *__pyx_tuple__32; static PyObject *__pyx_tuple__33; static PyObject *__pyx_tuple__34; static PyObject *__pyx_tuple__35; static PyObject *__pyx_tuple__36; static PyObject *__pyx_tuple__37; static PyObject *__pyx_tuple__38; static PyObject *__pyx_tuple__39; static PyObject *__pyx_tuple__40; static PyObject *__pyx_tuple__41; static PyObject *__pyx_tuple__42; static PyObject *__pyx_tuple__43; static PyObject *__pyx_tuple__44; static PyObject *__pyx_tuple__45; static PyObject *__pyx_tuple__46; static PyObject *__pyx_tuple__47; static PyObject *__pyx_tuple__51; static PyObject *__pyx_tuple__52; static PyObject *__pyx_tuple__54; static PyObject *__pyx_tuple__55; static PyObject *__pyx_tuple__56; static PyObject *__pyx_tuple__57; static PyObject *__pyx_tuple__58; static PyObject *__pyx_codeobj__53; /* "pyresample/ewa/_fornav.pyx":110 * @cython.boundscheck(False) * @cython.wraparound(False) * cdef int fornav(unsigned int *valid_list, size_t chan_count, size_t swath_cols, size_t swath_rows, size_t grid_cols, size_t grid_rows, # <<<<<<<<<<<<<< * cr_dtype *cols_pointer, cr_dtype *rows_pointer, * image_dtype **input_arrays, grid_dtype **output_arrays, */ static int __pyx_fuse_0_0_0__pyx_f_10pyresample_3ewa_7_fornav_fornav(unsigned int *__pyx_v_valid_list, size_t __pyx_v_chan_count, size_t __pyx_v_swath_cols, size_t __pyx_v_swath_rows, size_t __pyx_v_grid_cols, size_t __pyx_v_grid_rows, __pyx_t_5numpy_float32_t *__pyx_v_cols_pointer, __pyx_t_5numpy_float32_t *__pyx_v_rows_pointer, __pyx_t_5numpy_float32_t **__pyx_v_input_arrays, __pyx_t_5numpy_float32_t **__pyx_v_output_arrays, __pyx_t_5numpy_float32_t __pyx_v_input_fill, __pyx_t_5numpy_float32_t __pyx_v_output_fill, size_t __pyx_v_rows_per_scan, unsigned int __pyx_v_weight_count, float __pyx_v_weight_min, float __pyx_v_weight_distance_max, float __pyx_v_weight_delta_max, float __pyx_v_weight_sum_min, int __pyx_v_maximum_weight_mode) { unsigned int __pyx_v_row_idx; unsigned int __pyx_v_idx; int __pyx_v_got_point; int __pyx_v_tmp_got_point; int __pyx_v_func_result; __pyx_t_5numpy_float32_t *__pyx_v_tmp_cols_pointer; __pyx_t_5numpy_float32_t *__pyx_v_tmp_rows_pointer; __pyx_t_5numpy_float32_t **__pyx_v_input_images; ewa_weight __pyx_v_ewaw; ewa_parameters *__pyx_v_ewap; accum_type **__pyx_v_grid_accums; weight_type **__pyx_v_grid_weights; int __pyx_r; __Pyx_RefNannyDeclarations int __pyx_t_1; PyObject *__pyx_t_2 = NULL; size_t __pyx_t_3; size_t __pyx_t_4; size_t __pyx_t_5; unsigned int __pyx_t_6; int __pyx_t_7; __Pyx_RefNannySetupContext("__pyx_fuse_0_0_0fornav", 0); /* "pyresample/ewa/_fornav.pyx":118 * cdef unsigned int row_idx * cdef unsigned int idx * cdef bint got_point = 0 # <<<<<<<<<<<<<< * cdef bint tmp_got_point * cdef int func_result */ __pyx_v_got_point = 0; /* "pyresample/ewa/_fornav.pyx":128 * * # other defaults * if weight_sum_min == -1.0: # <<<<<<<<<<<<<< * weight_sum_min = weight_min * */ __pyx_t_1 = ((__pyx_v_weight_sum_min == -1.0) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":129 * # other defaults * if weight_sum_min == -1.0: * weight_sum_min = weight_min # <<<<<<<<<<<<<< * * func_result = initialize_weight(chan_count, weight_count, weight_min, weight_distance_max, weight_delta_max, */ __pyx_v_weight_sum_min = __pyx_v_weight_min; /* "pyresample/ewa/_fornav.pyx":128 * * # other defaults * if weight_sum_min == -1.0: # <<<<<<<<<<<<<< * weight_sum_min = weight_min * */ } /* "pyresample/ewa/_fornav.pyx":131 * weight_sum_min = weight_min * * func_result = initialize_weight(chan_count, weight_count, weight_min, weight_distance_max, weight_delta_max, # <<<<<<<<<<<<<< * weight_sum_min, &ewaw) * if func_result < 0: */ __pyx_v_func_result = initialize_weight(__pyx_v_chan_count, __pyx_v_weight_count, __pyx_v_weight_min, __pyx_v_weight_distance_max, __pyx_v_weight_delta_max, __pyx_v_weight_sum_min, (&__pyx_v_ewaw)); /* "pyresample/ewa/_fornav.pyx":133 * func_result = initialize_weight(chan_count, weight_count, weight_min, weight_distance_max, weight_delta_max, * weight_sum_min, &ewaw) * if func_result < 0: # <<<<<<<<<<<<<< * raise RuntimeError("Could not initialize weight structure for EWA resampling") * */ __pyx_t_1 = ((__pyx_v_func_result < 0) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":134 * weight_sum_min, &ewaw) * if func_result < 0: * raise RuntimeError("Could not initialize weight structure for EWA resampling") # <<<<<<<<<<<<<< * * # Allocate location for storing the sum of all of the pixels involved in each grid cell */ __pyx_t_2 = __Pyx_PyObject_Call(__pyx_builtin_RuntimeError, __pyx_tuple_, NULL); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 134, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_Raise(__pyx_t_2, 0, 0, 0); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __PYX_ERR(0, 134, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":133 * func_result = initialize_weight(chan_count, weight_count, weight_min, weight_distance_max, weight_delta_max, * weight_sum_min, &ewaw) * if func_result < 0: # <<<<<<<<<<<<<< * raise RuntimeError("Could not initialize weight structure for EWA resampling") * */ } /* "pyresample/ewa/_fornav.pyx":138 * # Allocate location for storing the sum of all of the pixels involved in each grid cell * # XXX: Do these need to be initialized to a fill value? * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) # <<<<<<<<<<<<<< * if grid_accums is NULL: * raise MemoryError() */ __pyx_v_grid_accums = initialize_grid_accums(__pyx_v_chan_count, __pyx_v_grid_cols, __pyx_v_grid_rows); /* "pyresample/ewa/_fornav.pyx":139 * # XXX: Do these need to be initialized to a fill value? * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) */ __pyx_t_1 = ((__pyx_v_grid_accums == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":140 * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: */ PyErr_NoMemory(); __PYX_ERR(0, 140, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":139 * # XXX: Do these need to be initialized to a fill value? * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) */ } /* "pyresample/ewa/_fornav.pyx":141 * if grid_accums is NULL: * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) # <<<<<<<<<<<<<< * if grid_weights is NULL: * raise MemoryError() */ __pyx_v_grid_weights = initialize_grid_weights(__pyx_v_chan_count, __pyx_v_grid_cols, __pyx_v_grid_rows); /* "pyresample/ewa/_fornav.pyx":142 * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate memory for the parameters specific to each column */ __pyx_t_1 = ((__pyx_v_grid_weights == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":143 * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) */ PyErr_NoMemory(); __PYX_ERR(0, 143, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":142 * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate memory for the parameters specific to each column */ } /* "pyresample/ewa/_fornav.pyx":145 * raise MemoryError() * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) # <<<<<<<<<<<<<< * if ewap is NULL: * raise MemoryError() */ __pyx_v_ewap = ((ewa_parameters *)malloc((__pyx_v_swath_cols * (sizeof(ewa_parameters))))); /* "pyresample/ewa/_fornav.pyx":146 * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use */ __pyx_t_1 = ((__pyx_v_ewap == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":147 * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) */ PyErr_NoMemory(); __PYX_ERR(0, 147, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":146 * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use */ } /* "pyresample/ewa/_fornav.pyx":149 * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) # <<<<<<<<<<<<<< * if input_images is NULL: * raise MemoryError() */ __pyx_v_input_images = ((__pyx_t_5numpy_float32_t **)malloc((__pyx_v_chan_count * (sizeof(__pyx_t_5numpy_float32_t *))))); /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ __pyx_t_1 = ((__pyx_v_input_images == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":151 * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * * */ PyErr_NoMemory(); __PYX_ERR(0, 151, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ } /* "pyresample/ewa/_fornav.pyx":155 * * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: # <<<<<<<<<<<<<< * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] */ __pyx_t_3 = __pyx_v_swath_rows; __pyx_t_4 = __pyx_v_rows_per_scan; for (__pyx_v_row_idx = 0; __pyx_v_row_idx < __pyx_t_3; __pyx_v_row_idx+=__pyx_t_4) { /* "pyresample/ewa/_fornav.pyx":156 * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] # <<<<<<<<<<<<<< * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] * # print "Current cols pointer: %d" % (tmp_cols_pointer,) */ __pyx_v_tmp_cols_pointer = (&(__pyx_v_cols_pointer[(__pyx_v_row_idx * __pyx_v_swath_cols)])); /* "pyresample/ewa/_fornav.pyx":157 * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] # <<<<<<<<<<<<<< * # print "Current cols pointer: %d" % (tmp_cols_pointer,) * */ __pyx_v_tmp_rows_pointer = (&(__pyx_v_rows_pointer[(__pyx_v_row_idx * __pyx_v_swath_cols)])); /* "pyresample/ewa/_fornav.pyx":161 * * # Assign the python/numpy array objects to a pointer location for the rest of the functions * for idx in range(chan_count): # <<<<<<<<<<<<<< * input_images[idx] = &input_arrays[idx][row_idx * swath_cols] * # print "Current input 0 pointer: %d" % (input_images[idx],) */ __pyx_t_5 = __pyx_v_chan_count; for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_idx = __pyx_t_6; /* "pyresample/ewa/_fornav.pyx":162 * # Assign the python/numpy array objects to a pointer location for the rest of the functions * for idx in range(chan_count): * input_images[idx] = &input_arrays[idx][row_idx * swath_cols] # <<<<<<<<<<<<<< * # print "Current input 0 pointer: %d" % (input_images[idx],) * */ (__pyx_v_input_images[__pyx_v_idx]) = (&((__pyx_v_input_arrays[__pyx_v_idx])[(__pyx_v_row_idx * __pyx_v_swath_cols)])); } /* "pyresample/ewa/_fornav.pyx":166 * * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) # <<<<<<<<<<<<<< * if func_result < 0: * got_point = got_point or 0 */ __pyx_v_func_result = compute_ewa_parameters<__pyx_t_5numpy_float32_t>(__pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, (&__pyx_v_ewaw), __pyx_v_ewap); /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ __pyx_t_1 = ((__pyx_v_func_result < 0) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":168 * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: * got_point = got_point or 0 # <<<<<<<<<<<<<< * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue */ __pyx_t_7 = (__pyx_v_got_point != 0); if (!__pyx_t_7) { } else { __pyx_t_1 = __pyx_t_7; goto __pyx_L14_bool_binop_done; } __pyx_t_1 = 0; __pyx_L14_bool_binop_done:; __pyx_v_got_point = __pyx_t_1; /* "pyresample/ewa/_fornav.pyx":170 * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue # <<<<<<<<<<<<<< * * # NOTE: In the C version this is where the image array data is loaded */ goto __pyx_L9_continue; /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ } /* "pyresample/ewa/_fornav.pyx":173 * * # NOTE: In the C version this is where the image array data is loaded * tmp_got_point = compute_ewa(chan_count, maximum_weight_mode, # <<<<<<<<<<<<<< * swath_cols, rows_per_scan, grid_cols, grid_rows, * tmp_cols_pointer, tmp_rows_pointer, */ __pyx_v_tmp_got_point = compute_ewa<__pyx_t_5numpy_float32_t,__pyx_t_5numpy_float32_t>(__pyx_v_chan_count, __pyx_v_maximum_weight_mode, __pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_grid_cols, __pyx_v_grid_rows, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, __pyx_v_input_images, __pyx_v_input_fill, __pyx_v_grid_accums, __pyx_v_grid_weights, (&__pyx_v_ewaw), __pyx_v_ewap); /* "pyresample/ewa/_fornav.pyx":178 * input_images, input_fill, grid_accums, grid_weights, &ewaw, ewap) * * got_point = got_point or tmp_got_point # <<<<<<<<<<<<<< * * free(input_images) */ __pyx_t_7 = (__pyx_v_got_point != 0); if (!__pyx_t_7) { } else { __pyx_t_1 = __pyx_t_7; goto __pyx_L16_bool_binop_done; } __pyx_t_7 = (__pyx_v_tmp_got_point != 0); __pyx_t_1 = __pyx_t_7; __pyx_L16_bool_binop_done:; __pyx_v_got_point = __pyx_t_1; __pyx_L9_continue:; } /* "pyresample/ewa/_fornav.pyx":180 * got_point = got_point or tmp_got_point * * free(input_images) # <<<<<<<<<<<<<< * free(ewap) * */ free(__pyx_v_input_images); /* "pyresample/ewa/_fornav.pyx":181 * * free(input_images) * free(ewap) # <<<<<<<<<<<<<< * * if not got_point: */ free(__pyx_v_ewap); /* "pyresample/ewa/_fornav.pyx":183 * free(ewap) * * if not got_point: # <<<<<<<<<<<<<< * raise RuntimeError("EWA Resampling: No swath pixels found inside grid to be resampled") * */ __pyx_t_1 = ((!(__pyx_v_got_point != 0)) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":184 * * if not got_point: * raise RuntimeError("EWA Resampling: No swath pixels found inside grid to be resampled") # <<<<<<<<<<<<<< * * for idx in range(chan_count): */ __pyx_t_2 = __Pyx_PyObject_Call(__pyx_builtin_RuntimeError, __pyx_tuple__2, NULL); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 184, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_2); __Pyx_Raise(__pyx_t_2, 0, 0, 0); __Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0; __PYX_ERR(0, 184, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":183 * free(ewap) * * if not got_point: # <<<<<<<<<<<<<< * raise RuntimeError("EWA Resampling: No swath pixels found inside grid to be resampled") * */ } /* "pyresample/ewa/_fornav.pyx":186 * raise RuntimeError("EWA Resampling: No swath pixels found inside grid to be resampled") * * for idx in range(chan_count): # <<<<<<<<<<<<<< * valid_list[idx] = write_grid_image(output_arrays[idx], output_fill, grid_cols, grid_rows, * grid_accums[idx], grid_weights[idx], maximum_weight_mode, weight_sum_min) */ __pyx_t_4 = __pyx_v_chan_count; for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_4; __pyx_t_6+=1) { __pyx_v_idx = __pyx_t_6; /* "pyresample/ewa/_fornav.pyx":187 * * for idx in range(chan_count): * valid_list[idx] = write_grid_image(output_arrays[idx], output_fill, grid_cols, grid_rows, # <<<<<<<<<<<<<< * grid_accums[idx], grid_weights[idx], maximum_weight_mode, weight_sum_min) * */ (__pyx_v_valid_list[__pyx_v_idx]) = write_grid_image((__pyx_v_output_arrays[__pyx_v_idx]), __pyx_v_output_fill, __pyx_v_grid_cols, __pyx_v_grid_rows, (__pyx_v_grid_accums[__pyx_v_idx]), (__pyx_v_grid_weights[__pyx_v_idx]), __pyx_v_maximum_weight_mode, __pyx_v_weight_sum_min); } /* "pyresample/ewa/_fornav.pyx":191 * * # free(grid_accums) * deinitialize_weight(&ewaw) # <<<<<<<<<<<<<< * deinitialize_grids(chan_count, grid_accums) * deinitialize_grids(chan_count, grid_weights) */ deinitialize_weight((&__pyx_v_ewaw)); /* "pyresample/ewa/_fornav.pyx":192 * # free(grid_accums) * deinitialize_weight(&ewaw) * deinitialize_grids(chan_count, grid_accums) # <<<<<<<<<<<<<< * deinitialize_grids(chan_count, grid_weights) * */ deinitialize_grids(__pyx_v_chan_count, ((void **)__pyx_v_grid_accums)); /* "pyresample/ewa/_fornav.pyx":193 * deinitialize_weight(&ewaw) * deinitialize_grids(chan_count, grid_accums) * deinitialize_grids(chan_count, grid_weights) # <<<<<<<<<<<<<< * * return 0 */ deinitialize_grids(__pyx_v_chan_count, ((void **)__pyx_v_grid_weights)); /* "pyresample/ewa/_fornav.pyx":195 * deinitialize_grids(chan_count, grid_weights) * * return 0 # <<<<<<<<<<<<<< * * @cython.boundscheck(False) */ __pyx_r = 0; goto __pyx_L0; /* "pyresample/ewa/_fornav.pyx":110 * @cython.boundscheck(False) * @cython.wraparound(False) * cdef int fornav(unsigned int *valid_list, size_t chan_count, size_t swath_cols, size_t swath_rows, size_t grid_cols, size_t grid_rows, # <<<<<<<<<<<<<< * cr_dtype *cols_pointer, cr_dtype *rows_pointer, * image_dtype **input_arrays, grid_dtype **output_arrays, */ /* function exit code */ __pyx_L1_error:; 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if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":140 * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: */ PyErr_NoMemory(); __PYX_ERR(0, 140, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":139 * # XXX: Do these need to be initialized to a fill value? * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) */ } /* "pyresample/ewa/_fornav.pyx":141 * if grid_accums is NULL: * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) # <<<<<<<<<<<<<< * if grid_weights is NULL: * raise MemoryError() */ __pyx_v_grid_weights = initialize_grid_weights(__pyx_v_chan_count, __pyx_v_grid_cols, __pyx_v_grid_rows); /* "pyresample/ewa/_fornav.pyx":142 * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate memory for the parameters specific to each column */ __pyx_t_1 = ((__pyx_v_grid_weights == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":143 * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) */ PyErr_NoMemory(); __PYX_ERR(0, 143, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":142 * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate memory for the parameters specific to each column */ } /* "pyresample/ewa/_fornav.pyx":145 * raise MemoryError() * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) # <<<<<<<<<<<<<< * if ewap is NULL: * raise MemoryError() */ __pyx_v_ewap = ((ewa_parameters *)malloc((__pyx_v_swath_cols * (sizeof(ewa_parameters))))); /* "pyresample/ewa/_fornav.pyx":146 * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use */ __pyx_t_1 = ((__pyx_v_ewap == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":147 * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) */ PyErr_NoMemory(); __PYX_ERR(0, 147, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":146 * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use */ } /* "pyresample/ewa/_fornav.pyx":149 * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) # <<<<<<<<<<<<<< * if input_images is NULL: * raise MemoryError() */ __pyx_v_input_images = ((__pyx_t_5numpy_float64_t **)malloc((__pyx_v_chan_count * (sizeof(__pyx_t_5numpy_float64_t *))))); /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ __pyx_t_1 = ((__pyx_v_input_images == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":151 * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * * */ PyErr_NoMemory(); __PYX_ERR(0, 151, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ } /* "pyresample/ewa/_fornav.pyx":155 * * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: # <<<<<<<<<<<<<< * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] */ __pyx_t_3 = __pyx_v_swath_rows; __pyx_t_4 = __pyx_v_rows_per_scan; for (__pyx_v_row_idx = 0; __pyx_v_row_idx < __pyx_t_3; __pyx_v_row_idx+=__pyx_t_4) { /* "pyresample/ewa/_fornav.pyx":156 * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] # <<<<<<<<<<<<<< * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] * # print "Current cols pointer: %d" % (tmp_cols_pointer,) */ __pyx_v_tmp_cols_pointer = (&(__pyx_v_cols_pointer[(__pyx_v_row_idx * __pyx_v_swath_cols)])); /* "pyresample/ewa/_fornav.pyx":157 * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] # <<<<<<<<<<<<<< * # print "Current cols pointer: %d" % (tmp_cols_pointer,) * */ __pyx_v_tmp_rows_pointer = (&(__pyx_v_rows_pointer[(__pyx_v_row_idx * __pyx_v_swath_cols)])); /* "pyresample/ewa/_fornav.pyx":161 * * # Assign the python/numpy array objects to a pointer location for the rest of the functions * for idx in range(chan_count): # <<<<<<<<<<<<<< * input_images[idx] = &input_arrays[idx][row_idx * swath_cols] * # print "Current input 0 pointer: %d" % (input_images[idx],) */ __pyx_t_5 = __pyx_v_chan_count; for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_idx = __pyx_t_6; /* "pyresample/ewa/_fornav.pyx":162 * # Assign the python/numpy array objects to a pointer location for the rest of the functions * for idx in range(chan_count): * input_images[idx] = &input_arrays[idx][row_idx * swath_cols] # <<<<<<<<<<<<<< * # print "Current input 0 pointer: %d" % (input_images[idx],) * */ (__pyx_v_input_images[__pyx_v_idx]) = (&((__pyx_v_input_arrays[__pyx_v_idx])[(__pyx_v_row_idx * __pyx_v_swath_cols)])); } /* "pyresample/ewa/_fornav.pyx":166 * * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) # <<<<<<<<<<<<<< * if func_result < 0: * got_point = got_point or 0 */ __pyx_v_func_result = compute_ewa_parameters<__pyx_t_5numpy_float32_t>(__pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, (&__pyx_v_ewaw), __pyx_v_ewap); /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ __pyx_t_1 = ((__pyx_v_func_result < 0) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":168 * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: * got_point = got_point or 0 # <<<<<<<<<<<<<< * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue */ __pyx_t_7 = (__pyx_v_got_point != 0); if (!__pyx_t_7) { } else { __pyx_t_1 = __pyx_t_7; goto __pyx_L14_bool_binop_done; } __pyx_t_1 = 0; __pyx_L14_bool_binop_done:; __pyx_v_got_point = __pyx_t_1; /* "pyresample/ewa/_fornav.pyx":170 * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue # <<<<<<<<<<<<<< * * # NOTE: In the C version this is where the image array data is loaded */ goto __pyx_L9_continue; /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ } /* "pyresample/ewa/_fornav.pyx":173 * * # NOTE: In the C version this is where the image array data is loaded * tmp_got_point = compute_ewa(chan_count, maximum_weight_mode, # <<<<<<<<<<<<<< * swath_cols, rows_per_scan, grid_cols, grid_rows, * tmp_cols_pointer, tmp_rows_pointer, */ __pyx_v_tmp_got_point = compute_ewa<__pyx_t_5numpy_float32_t,__pyx_t_5numpy_float64_t>(__pyx_v_chan_count, __pyx_v_maximum_weight_mode, __pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_grid_cols, __pyx_v_grid_rows, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, __pyx_v_input_images, __pyx_v_input_fill, __pyx_v_grid_accums, __pyx_v_grid_weights, (&__pyx_v_ewaw), __pyx_v_ewap); 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if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":140 * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: */ PyErr_NoMemory(); __PYX_ERR(0, 140, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":139 * # XXX: Do these need to be initialized to a fill value? * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) */ } /* "pyresample/ewa/_fornav.pyx":141 * if grid_accums is NULL: * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) # <<<<<<<<<<<<<< * if grid_weights is NULL: * raise MemoryError() */ __pyx_v_grid_weights = initialize_grid_weights(__pyx_v_chan_count, __pyx_v_grid_cols, __pyx_v_grid_rows); /* "pyresample/ewa/_fornav.pyx":142 * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate memory for the parameters specific to each column */ __pyx_t_1 = ((__pyx_v_grid_weights == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":143 * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) */ PyErr_NoMemory(); __PYX_ERR(0, 143, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":142 * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate memory for the parameters specific to each column */ } /* "pyresample/ewa/_fornav.pyx":145 * raise MemoryError() * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) # <<<<<<<<<<<<<< * if ewap is NULL: * raise MemoryError() */ __pyx_v_ewap = ((ewa_parameters *)malloc((__pyx_v_swath_cols * (sizeof(ewa_parameters))))); /* "pyresample/ewa/_fornav.pyx":146 * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use */ __pyx_t_1 = ((__pyx_v_ewap == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":147 * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) */ PyErr_NoMemory(); __PYX_ERR(0, 147, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":146 * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use */ } /* "pyresample/ewa/_fornav.pyx":149 * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) # <<<<<<<<<<<<<< * if input_images is NULL: * raise MemoryError() */ __pyx_v_input_images = ((__pyx_t_5numpy_int8_t **)malloc((__pyx_v_chan_count * (sizeof(__pyx_t_5numpy_int8_t *))))); /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ __pyx_t_1 = ((__pyx_v_input_images == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":151 * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * * */ PyErr_NoMemory(); __PYX_ERR(0, 151, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ } /* "pyresample/ewa/_fornav.pyx":155 * * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: # <<<<<<<<<<<<<< * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] */ __pyx_t_3 = __pyx_v_swath_rows; __pyx_t_4 = __pyx_v_rows_per_scan; for (__pyx_v_row_idx = 0; __pyx_v_row_idx < __pyx_t_3; __pyx_v_row_idx+=__pyx_t_4) { /* "pyresample/ewa/_fornav.pyx":156 * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] # <<<<<<<<<<<<<< * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] * # print "Current cols pointer: %d" % (tmp_cols_pointer,) */ __pyx_v_tmp_cols_pointer = (&(__pyx_v_cols_pointer[(__pyx_v_row_idx * __pyx_v_swath_cols)])); /* "pyresample/ewa/_fornav.pyx":157 * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] # <<<<<<<<<<<<<< * # print "Current cols pointer: %d" % (tmp_cols_pointer,) * */ __pyx_v_tmp_rows_pointer = (&(__pyx_v_rows_pointer[(__pyx_v_row_idx * __pyx_v_swath_cols)])); /* "pyresample/ewa/_fornav.pyx":161 * * # Assign the python/numpy array objects to a pointer location for the rest of the functions * for idx in range(chan_count): # <<<<<<<<<<<<<< * input_images[idx] = &input_arrays[idx][row_idx * swath_cols] * # print "Current input 0 pointer: %d" % (input_images[idx],) */ __pyx_t_5 = __pyx_v_chan_count; for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_idx = __pyx_t_6; /* "pyresample/ewa/_fornav.pyx":162 * # Assign the python/numpy array objects to a pointer location for the rest of the functions * for idx in range(chan_count): * input_images[idx] = &input_arrays[idx][row_idx * swath_cols] # <<<<<<<<<<<<<< * # print "Current input 0 pointer: %d" % (input_images[idx],) * */ (__pyx_v_input_images[__pyx_v_idx]) = (&((__pyx_v_input_arrays[__pyx_v_idx])[(__pyx_v_row_idx * __pyx_v_swath_cols)])); } /* "pyresample/ewa/_fornav.pyx":166 * * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) # <<<<<<<<<<<<<< * if func_result < 0: * got_point = got_point or 0 */ __pyx_v_func_result = compute_ewa_parameters<__pyx_t_5numpy_float32_t>(__pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, (&__pyx_v_ewaw), __pyx_v_ewap); /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ __pyx_t_1 = ((__pyx_v_func_result < 0) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":168 * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: * got_point = got_point or 0 # <<<<<<<<<<<<<< * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue */ __pyx_t_7 = (__pyx_v_got_point != 0); if (!__pyx_t_7) { } else { __pyx_t_1 = __pyx_t_7; goto __pyx_L14_bool_binop_done; } __pyx_t_1 = 0; __pyx_L14_bool_binop_done:; __pyx_v_got_point = __pyx_t_1; /* "pyresample/ewa/_fornav.pyx":170 * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue # <<<<<<<<<<<<<< * * # NOTE: In the C version this is where the image array data is loaded */ goto __pyx_L9_continue; /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ } /* "pyresample/ewa/_fornav.pyx":173 * * # NOTE: In the C version this is where the image array data is loaded * tmp_got_point = compute_ewa(chan_count, maximum_weight_mode, # <<<<<<<<<<<<<< * swath_cols, rows_per_scan, grid_cols, grid_rows, * tmp_cols_pointer, tmp_rows_pointer, */ __pyx_v_tmp_got_point = compute_ewa<__pyx_t_5numpy_float32_t,__pyx_t_5numpy_int8_t>(__pyx_v_chan_count, __pyx_v_maximum_weight_mode, __pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_grid_cols, __pyx_v_grid_rows, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, __pyx_v_input_images, __pyx_v_input_fill, __pyx_v_grid_accums, __pyx_v_grid_weights, (&__pyx_v_ewaw), __pyx_v_ewap); 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int __pyx_v_tmp_got_point; int __pyx_v_func_result; __pyx_t_5numpy_float64_t *__pyx_v_tmp_cols_pointer; __pyx_t_5numpy_float64_t *__pyx_v_tmp_rows_pointer; __pyx_t_5numpy_float32_t **__pyx_v_input_images; ewa_weight __pyx_v_ewaw; ewa_parameters *__pyx_v_ewap; accum_type **__pyx_v_grid_accums; weight_type **__pyx_v_grid_weights; int __pyx_r; __Pyx_RefNannyDeclarations int __pyx_t_1; PyObject *__pyx_t_2 = NULL; size_t __pyx_t_3; size_t __pyx_t_4; size_t __pyx_t_5; unsigned int __pyx_t_6; int __pyx_t_7; __Pyx_RefNannySetupContext("__pyx_fuse_1_0_0fornav", 0); /* "pyresample/ewa/_fornav.pyx":118 * cdef unsigned int row_idx * cdef unsigned int idx * cdef bint got_point = 0 # <<<<<<<<<<<<<< * cdef bint tmp_got_point * cdef int func_result */ __pyx_v_got_point = 0; /* "pyresample/ewa/_fornav.pyx":128 * * # other defaults * if weight_sum_min == -1.0: # <<<<<<<<<<<<<< * weight_sum_min = weight_min * */ __pyx_t_1 = ((__pyx_v_weight_sum_min == -1.0) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":129 * # other defaults * if weight_sum_min == -1.0: * weight_sum_min = weight_min # <<<<<<<<<<<<<< * * func_result = initialize_weight(chan_count, weight_count, weight_min, weight_distance_max, weight_delta_max, */ __pyx_v_weight_sum_min = __pyx_v_weight_min; 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if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":140 * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: */ PyErr_NoMemory(); __PYX_ERR(0, 140, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":139 * # XXX: Do these need to be initialized to a fill value? * cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) * if grid_accums is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) */ } /* "pyresample/ewa/_fornav.pyx":141 * if grid_accums is NULL: * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) # <<<<<<<<<<<<<< * if grid_weights is NULL: * raise MemoryError() */ __pyx_v_grid_weights = initialize_grid_weights(__pyx_v_chan_count, __pyx_v_grid_cols, __pyx_v_grid_rows); /* "pyresample/ewa/_fornav.pyx":142 * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate memory for the parameters specific to each column */ __pyx_t_1 = ((__pyx_v_grid_weights == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":143 * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) */ PyErr_NoMemory(); __PYX_ERR(0, 143, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":142 * raise MemoryError() * cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) * if grid_weights is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate memory for the parameters specific to each column */ } /* "pyresample/ewa/_fornav.pyx":145 * raise MemoryError() * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) # <<<<<<<<<<<<<< * if ewap is NULL: * raise MemoryError() */ __pyx_v_ewap = ((ewa_parameters *)malloc((__pyx_v_swath_cols * (sizeof(ewa_parameters))))); /* "pyresample/ewa/_fornav.pyx":146 * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use */ __pyx_t_1 = ((__pyx_v_ewap == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":147 * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) */ PyErr_NoMemory(); __PYX_ERR(0, 147, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":146 * # Allocate memory for the parameters specific to each column * ewap = malloc(swath_cols * sizeof(ewa_parameters)) * if ewap is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use */ } /* "pyresample/ewa/_fornav.pyx":149 * raise MemoryError() * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) # <<<<<<<<<<<<<< * if input_images is NULL: * raise MemoryError() */ __pyx_v_input_images = ((__pyx_t_5numpy_float32_t **)malloc((__pyx_v_chan_count * (sizeof(__pyx_t_5numpy_float32_t *))))); /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ __pyx_t_1 = ((__pyx_v_input_images == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":151 * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * * */ PyErr_NoMemory(); __PYX_ERR(0, 151, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ } /* "pyresample/ewa/_fornav.pyx":155 * * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: # <<<<<<<<<<<<<< * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] */ __pyx_t_3 = __pyx_v_swath_rows; __pyx_t_4 = __pyx_v_rows_per_scan; for (__pyx_v_row_idx = 0; __pyx_v_row_idx < __pyx_t_3; __pyx_v_row_idx+=__pyx_t_4) { /* "pyresample/ewa/_fornav.pyx":156 * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] # <<<<<<<<<<<<<< * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] * # print "Current cols pointer: %d" % (tmp_cols_pointer,) */ __pyx_v_tmp_cols_pointer = (&(__pyx_v_cols_pointer[(__pyx_v_row_idx * __pyx_v_swath_cols)])); /* "pyresample/ewa/_fornav.pyx":157 * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] # <<<<<<<<<<<<<< * # print "Current cols pointer: %d" % (tmp_cols_pointer,) * */ __pyx_v_tmp_rows_pointer = (&(__pyx_v_rows_pointer[(__pyx_v_row_idx * __pyx_v_swath_cols)])); /* "pyresample/ewa/_fornav.pyx":161 * * # Assign the python/numpy array objects to a pointer location for the rest of the functions * for idx in range(chan_count): # <<<<<<<<<<<<<< * input_images[idx] = &input_arrays[idx][row_idx * swath_cols] * # print "Current input 0 pointer: %d" % (input_images[idx],) */ __pyx_t_5 = __pyx_v_chan_count; for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) { __pyx_v_idx = __pyx_t_6; /* "pyresample/ewa/_fornav.pyx":162 * # Assign the python/numpy array objects to a pointer location for the rest of the functions * for idx in range(chan_count): * input_images[idx] = &input_arrays[idx][row_idx * swath_cols] # <<<<<<<<<<<<<< * # print "Current input 0 pointer: %d" % (input_images[idx],) * */ (__pyx_v_input_images[__pyx_v_idx]) = (&((__pyx_v_input_arrays[__pyx_v_idx])[(__pyx_v_row_idx * __pyx_v_swath_cols)])); } /* "pyresample/ewa/_fornav.pyx":166 * * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) # <<<<<<<<<<<<<< * if func_result < 0: * got_point = got_point or 0 */ __pyx_v_func_result = compute_ewa_parameters<__pyx_t_5numpy_float64_t>(__pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, (&__pyx_v_ewaw), __pyx_v_ewap); /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ __pyx_t_1 = ((__pyx_v_func_result < 0) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":168 * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: * got_point = got_point or 0 # <<<<<<<<<<<<<< * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue */ __pyx_t_7 = (__pyx_v_got_point != 0); if (!__pyx_t_7) { } else { __pyx_t_1 = __pyx_t_7; goto __pyx_L14_bool_binop_done; } __pyx_t_1 = 0; __pyx_L14_bool_binop_done:; __pyx_v_got_point = __pyx_t_1; /* "pyresample/ewa/_fornav.pyx":170 * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue # <<<<<<<<<<<<<< * * # NOTE: In the C version this is where the image array data is loaded */ goto __pyx_L9_continue; /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ } /* "pyresample/ewa/_fornav.pyx":173 * * # NOTE: In the C version this is where the image array data is loaded * tmp_got_point = compute_ewa(chan_count, maximum_weight_mode, # <<<<<<<<<<<<<< * swath_cols, rows_per_scan, grid_cols, grid_rows, * tmp_cols_pointer, tmp_rows_pointer, */ __pyx_v_tmp_got_point = compute_ewa<__pyx_t_5numpy_float64_t,__pyx_t_5numpy_float32_t>(__pyx_v_chan_count, __pyx_v_maximum_weight_mode, __pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_grid_cols, __pyx_v_grid_rows, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, __pyx_v_input_images, __pyx_v_input_fill, __pyx_v_grid_accums, __pyx_v_grid_weights, (&__pyx_v_ewaw), __pyx_v_ewap); 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if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":168 * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: * got_point = got_point or 0 # <<<<<<<<<<<<<< * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue */ __pyx_t_7 = (__pyx_v_got_point != 0); if (!__pyx_t_7) { } else { __pyx_t_1 = __pyx_t_7; goto __pyx_L14_bool_binop_done; } __pyx_t_1 = 0; __pyx_L14_bool_binop_done:; __pyx_v_got_point = __pyx_t_1; /* "pyresample/ewa/_fornav.pyx":170 * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") * continue # <<<<<<<<<<<<<< * * # NOTE: In the C version this is where the image array data is loaded */ goto __pyx_L9_continue; /* "pyresample/ewa/_fornav.pyx":167 * # Calculate EWA parameters for each column index * func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) * if func_result < 0: # <<<<<<<<<<<<<< * got_point = got_point or 0 * # raise RuntimeError("Could compute EWA parameters for EWA resampling") */ } /* "pyresample/ewa/_fornav.pyx":173 * * # NOTE: In the C version this is where the image array data is loaded * tmp_got_point = compute_ewa(chan_count, maximum_weight_mode, # <<<<<<<<<<<<<< * swath_cols, rows_per_scan, grid_cols, grid_rows, * tmp_cols_pointer, tmp_rows_pointer, */ __pyx_v_tmp_got_point = compute_ewa<__pyx_t_5numpy_float64_t,__pyx_t_5numpy_float64_t>(__pyx_v_chan_count, __pyx_v_maximum_weight_mode, __pyx_v_swath_cols, __pyx_v_rows_per_scan, __pyx_v_grid_cols, __pyx_v_grid_rows, __pyx_v_tmp_cols_pointer, __pyx_v_tmp_rows_pointer, __pyx_v_input_images, __pyx_v_input_fill, __pyx_v_grid_accums, __pyx_v_grid_weights, (&__pyx_v_ewaw), __pyx_v_ewap); 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/* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ __pyx_t_1 = ((__pyx_v_input_images == NULL) != 0); if (__pyx_t_1) { /* "pyresample/ewa/_fornav.pyx":151 * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: * raise MemoryError() # <<<<<<<<<<<<<< * * */ PyErr_NoMemory(); __PYX_ERR(0, 151, __pyx_L1_error) /* "pyresample/ewa/_fornav.pyx":150 * # Allocate pointers to the correct portion of the data arrays that we will use * input_images = malloc(chan_count * sizeof(image_dtype *)) * if input_images is NULL: # <<<<<<<<<<<<<< * raise MemoryError() * */ } /* "pyresample/ewa/_fornav.pyx":155 * * # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps * for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: # <<<<<<<<<<<<<< * tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] * tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] */ __pyx_t_3 = __pyx_v_swath_rows; 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= mslice.strides[i] */ __pyx_t_1 = __pyx_v_ndim; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* "View.MemoryView":1113 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * f_stride = mslice.strides[i] * break */ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { /* "View.MemoryView":1114 * for i in range(ndim): * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< * break * */ __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); /* "View.MemoryView":1115 * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): */ goto __pyx_L7_break; /* "View.MemoryView":1113 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * f_stride = mslice.strides[i] * break */ } } __pyx_L7_break:; /* "View.MemoryView":1117 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< * return 'C' * else: */ __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); if (__pyx_t_2) { /* "View.MemoryView":1118 * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): * return 'C' # <<<<<<<<<<<<<< * else: * return 'F' */ __pyx_r = 'C'; goto __pyx_L0; /* "View.MemoryView":1117 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< * return 'C' * else: */ } /* "View.MemoryView":1120 * return 'C' * else: * return 'F' # <<<<<<<<<<<<<< * * @cython.cdivision(True) */ /*else*/ { __pyx_r = 'F'; goto __pyx_L0; } /* "View.MemoryView":1099 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< * """ * Figure out the best memory access order for a given slice. */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1123 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< * char *dst_data, Py_ssize_t *dst_strides, * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, */ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { CYTHON_UNUSED Py_ssize_t __pyx_v_i; CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; Py_ssize_t __pyx_v_dst_extent; Py_ssize_t __pyx_v_src_stride; Py_ssize_t __pyx_v_dst_stride; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; Py_ssize_t __pyx_t_4; Py_ssize_t __pyx_t_5; /* "View.MemoryView":1130 * * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] */ __pyx_v_src_extent = (__pyx_v_src_shape[0]); /* "View.MemoryView":1131 * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] */ __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); /* "View.MemoryView":1132 * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t dst_stride = dst_strides[0] * */ __pyx_v_src_stride = (__pyx_v_src_strides[0]); /* "View.MemoryView":1133 * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< * * if ndim == 1: */ __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); /* "View.MemoryView":1135 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): */ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { /* "View.MemoryView":1136 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); if (__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); if (__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } /* "View.MemoryView":1137 * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< * memcpy(dst_data, src_data, itemsize * dst_extent) * else: */ __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); if (__pyx_t_2) { __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); } __pyx_t_3 = (__pyx_t_2 != 0); __pyx_t_1 = __pyx_t_3; __pyx_L5_bool_binop_done:; /* "View.MemoryView":1136 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ if (__pyx_t_1) { /* "View.MemoryView":1138 * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< * else: * for i in range(dst_extent): */ memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent)); /* "View.MemoryView":1136 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ goto __pyx_L4; } /* "View.MemoryView":1140 * memcpy(dst_data, src_data, itemsize * dst_extent) * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< * memcpy(dst_data, src_data, itemsize) * src_data += src_stride */ /*else*/ { __pyx_t_4 = __pyx_v_dst_extent; for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; /* "View.MemoryView":1141 * else: * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< * src_data += src_stride * dst_data += dst_stride */ memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize); /* "View.MemoryView":1142 * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< * dst_data += dst_stride * else: */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); /* "View.MemoryView":1143 * memcpy(dst_data, src_data, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< * else: * for i in range(dst_extent): */ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); } } __pyx_L4:; /* "View.MemoryView":1135 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): */ goto __pyx_L3; } /* "View.MemoryView":1145 * dst_data += dst_stride * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< * _copy_strided_to_strided(src_data, src_strides + 1, * dst_data, dst_strides + 1, */ /*else*/ { __pyx_t_4 = __pyx_v_dst_extent; for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; /* "View.MemoryView":1146 * else: * for i in range(dst_extent): * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< * dst_data, dst_strides + 1, * src_shape + 1, dst_shape + 1, */ _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); /* "View.MemoryView":1150 * src_shape + 1, dst_shape + 1, * ndim - 1, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< * dst_data += dst_stride * */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); /* "View.MemoryView":1151 * ndim - 1, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, */ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); } } __pyx_L3:; /* "View.MemoryView":1123 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< * char *dst_data, Py_ssize_t *dst_strides, * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, */ /* function exit code */ } /* "View.MemoryView":1153 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: */ static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { /* "View.MemoryView":1156 * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< * src.shape, dst.shape, ndim, itemsize) * */ _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); /* "View.MemoryView":1153 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: */ /* function exit code */ } /* "View.MemoryView":1160 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< * "Return the size of the memory occupied by the slice in number of bytes" * cdef int i */ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { int __pyx_v_i; Py_ssize_t __pyx_v_size; Py_ssize_t __pyx_r; Py_ssize_t __pyx_t_1; int __pyx_t_2; int __pyx_t_3; /* "View.MemoryView":1163 * "Return the size of the memory occupied by the slice in number of bytes" * cdef int i * cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<< * * for i in range(ndim): */ __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_size = __pyx_t_1; /* "View.MemoryView":1165 * cdef Py_ssize_t size = src.memview.view.itemsize * * for i in range(ndim): # <<<<<<<<<<<<<< * size *= src.shape[i] * */ __pyx_t_2 = __pyx_v_ndim; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* "View.MemoryView":1166 * * for i in range(ndim): * size *= src.shape[i] # <<<<<<<<<<<<<< * * return size */ __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i])); } /* "View.MemoryView":1168 * size *= src.shape[i] * * return size # <<<<<<<<<<<<<< * * @cname('__pyx_fill_contig_strides_array') */ __pyx_r = __pyx_v_size; goto __pyx_L0; /* "View.MemoryView":1160 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< * "Return the size of the memory occupied by the slice in number of bytes" * cdef int i */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1171 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, * int ndim, char order) nogil: */ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { int __pyx_v_idx; Py_ssize_t __pyx_r; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; /* "View.MemoryView":1180 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< * for idx in range(ndim): * strides[idx] = stride */ __pyx_t_1 = ((__pyx_v_order == 'F') != 0); if (__pyx_t_1) { /* "View.MemoryView":1181 * * if order == 'F': * for idx in range(ndim): # <<<<<<<<<<<<<< * strides[idx] = stride * stride = stride * shape[idx] */ __pyx_t_2 = __pyx_v_ndim; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_idx = __pyx_t_3; /* "View.MemoryView":1182 * if order == 'F': * for idx in range(ndim): * strides[idx] = stride # <<<<<<<<<<<<<< * stride = stride * shape[idx] * else: */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; /* "View.MemoryView":1183 * for idx in range(ndim): * strides[idx] = stride * stride = stride * shape[idx] # <<<<<<<<<<<<<< * else: * for idx in range(ndim - 1, -1, -1): */ __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); } /* "View.MemoryView":1180 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< * for idx in range(ndim): * strides[idx] = stride */ goto __pyx_L3; } /* "View.MemoryView":1185 * stride = stride * shape[idx] * else: * for idx in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< * strides[idx] = stride * stride = stride * shape[idx] */ /*else*/ { for (__pyx_t_2 = (__pyx_v_ndim - 1); __pyx_t_2 > -1L; __pyx_t_2-=1) { __pyx_v_idx = __pyx_t_2; /* "View.MemoryView":1186 * else: * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride # <<<<<<<<<<<<<< * stride = stride * shape[idx] * */ (__pyx_v_strides[__pyx_v_idx]) = __pyx_v_stride; /* "View.MemoryView":1187 * for idx in range(ndim - 1, -1, -1): * strides[idx] = stride * stride = stride * shape[idx] # <<<<<<<<<<<<<< * * return stride */ __pyx_v_stride = (__pyx_v_stride * (__pyx_v_shape[__pyx_v_idx])); } } __pyx_L3:; /* "View.MemoryView":1189 * stride = stride * shape[idx] * * return stride # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_copy_data_to_temp') */ __pyx_r = __pyx_v_stride; goto __pyx_L0; /* "View.MemoryView":1171 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, * int ndim, char order) nogil: */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1192 * * @cname('__pyx_memoryview_copy_data_to_temp') * cdef void *copy_data_to_temp(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< * __Pyx_memviewslice *tmpslice, * char order, */ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_tmpslice, char __pyx_v_order, int __pyx_v_ndim) { int __pyx_v_i; void *__pyx_v_result; size_t __pyx_v_itemsize; size_t __pyx_v_size; void *__pyx_r; Py_ssize_t __pyx_t_1; int __pyx_t_2; int __pyx_t_3; struct __pyx_memoryview_obj *__pyx_t_4; int __pyx_t_5; /* "View.MemoryView":1203 * cdef void *result * * cdef size_t itemsize = src.memview.view.itemsize # <<<<<<<<<<<<<< * cdef size_t size = slice_get_size(src, ndim) * */ __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_itemsize = __pyx_t_1; /* "View.MemoryView":1204 * * cdef size_t itemsize = src.memview.view.itemsize * cdef size_t size = slice_get_size(src, ndim) # <<<<<<<<<<<<<< * * result = malloc(size) */ __pyx_v_size = __pyx_memoryview_slice_get_size(__pyx_v_src, __pyx_v_ndim); /* "View.MemoryView":1206 * cdef size_t size = slice_get_size(src, ndim) * * result = malloc(size) # <<<<<<<<<<<<<< * if not result: * _err(MemoryError, NULL) */ __pyx_v_result = malloc(__pyx_v_size); /* "View.MemoryView":1207 * * result = malloc(size) * if not result: # <<<<<<<<<<<<<< * _err(MemoryError, NULL) * */ __pyx_t_2 = ((!(__pyx_v_result != 0)) != 0); if (__pyx_t_2) { /* "View.MemoryView":1208 * result = malloc(size) * if not result: * _err(MemoryError, NULL) # <<<<<<<<<<<<<< * * */ __pyx_t_3 = __pyx_memoryview_err(__pyx_builtin_MemoryError, NULL); if (unlikely(__pyx_t_3 == -1)) __PYX_ERR(2, 1208, __pyx_L1_error) /* "View.MemoryView":1207 * * result = malloc(size) * if not result: # <<<<<<<<<<<<<< * _err(MemoryError, NULL) * */ } /* "View.MemoryView":1211 * * * tmpslice.data = result # <<<<<<<<<<<<<< * tmpslice.memview = src.memview * for i in range(ndim): */ __pyx_v_tmpslice->data = ((char *)__pyx_v_result); /* "View.MemoryView":1212 * * tmpslice.data = result * tmpslice.memview = src.memview # <<<<<<<<<<<<<< * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] */ __pyx_t_4 = __pyx_v_src->memview; __pyx_v_tmpslice->memview = __pyx_t_4; /* "View.MemoryView":1213 * tmpslice.data = result * tmpslice.memview = src.memview * for i in range(ndim): # <<<<<<<<<<<<<< * tmpslice.shape[i] = src.shape[i] * tmpslice.suboffsets[i] = -1 */ __pyx_t_3 = __pyx_v_ndim; for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_3; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; /* "View.MemoryView":1214 * tmpslice.memview = src.memview * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] # <<<<<<<<<<<<<< * tmpslice.suboffsets[i] = -1 * */ (__pyx_v_tmpslice->shape[__pyx_v_i]) = (__pyx_v_src->shape[__pyx_v_i]); /* "View.MemoryView":1215 * for i in range(ndim): * tmpslice.shape[i] = src.shape[i] * tmpslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< * * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, */ (__pyx_v_tmpslice->suboffsets[__pyx_v_i]) = -1L; } /* "View.MemoryView":1217 * tmpslice.suboffsets[i] = -1 * * fill_contig_strides_array(&tmpslice.shape[0], &tmpslice.strides[0], itemsize, # 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__pyx_memoryview_broadcast_leading((&__pyx_v_dst), __pyx_v_dst_ndim, __pyx_v_src_ndim); /* "View.MemoryView":1270 * if src_ndim < dst_ndim: * broadcast_leading(&src, src_ndim, dst_ndim) * elif dst_ndim < src_ndim: # <<<<<<<<<<<<<< * broadcast_leading(&dst, dst_ndim, src_ndim) * */ } __pyx_L3:; /* "View.MemoryView":1273 * broadcast_leading(&dst, dst_ndim, src_ndim) * * cdef int ndim = max(src_ndim, dst_ndim) # <<<<<<<<<<<<<< * * for i in range(ndim): */ __pyx_t_3 = __pyx_v_dst_ndim; __pyx_t_4 = __pyx_v_src_ndim; if (((__pyx_t_3 > __pyx_t_4) != 0)) { __pyx_t_5 = __pyx_t_3; } else { __pyx_t_5 = __pyx_t_4; } __pyx_v_ndim = __pyx_t_5; /* "View.MemoryView":1275 * cdef int ndim = max(src_ndim, dst_ndim) * * for i in range(ndim): # <<<<<<<<<<<<<< * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: */ __pyx_t_5 = __pyx_v_ndim; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_5; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* "View.MemoryView":1276 * * for i in range(ndim): * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< * if src.shape[i] == 1: * broadcasting = True */ __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) != (__pyx_v_dst.shape[__pyx_v_i])) != 0); if (__pyx_t_2) { /* "View.MemoryView":1277 * for i in range(ndim): * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: # <<<<<<<<<<<<<< * broadcasting = True * src.strides[i] = 0 */ __pyx_t_2 = (((__pyx_v_src.shape[__pyx_v_i]) == 1) != 0); if (__pyx_t_2) { /* "View.MemoryView":1278 * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: * broadcasting = True # <<<<<<<<<<<<<< * src.strides[i] = 0 * else: */ __pyx_v_broadcasting = 1; /* "View.MemoryView":1279 * if src.shape[i] == 1: * broadcasting = True * src.strides[i] = 0 # <<<<<<<<<<<<<< * else: * _err_extents(i, dst.shape[i], src.shape[i]) */ (__pyx_v_src.strides[__pyx_v_i]) = 0; /* "View.MemoryView":1277 * for i in range(ndim): * if src.shape[i] != dst.shape[i]: * if src.shape[i] == 1: # <<<<<<<<<<<<<< * broadcasting = True * src.strides[i] = 0 */ goto __pyx_L7; } /* "View.MemoryView":1281 * src.strides[i] = 0 * else: * _err_extents(i, dst.shape[i], src.shape[i]) # <<<<<<<<<<<<<< * * if src.suboffsets[i] >= 0: */ /*else*/ { __pyx_t_4 = __pyx_memoryview_err_extents(__pyx_v_i, (__pyx_v_dst.shape[__pyx_v_i]), (__pyx_v_src.shape[__pyx_v_i])); if (unlikely(__pyx_t_4 == -1)) __PYX_ERR(2, 1281, __pyx_L1_error) } __pyx_L7:; /* "View.MemoryView":1276 * * for i in range(ndim): * if src.shape[i] != dst.shape[i]: # <<<<<<<<<<<<<< * if src.shape[i] == 1: * broadcasting = True */ } /* "View.MemoryView":1283 * _err_extents(i, dst.shape[i], src.shape[i]) * * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< * _err_dim(ValueError, "Dimension %d is not direct", i) * */ __pyx_t_2 = (((__pyx_v_src.suboffsets[__pyx_v_i]) >= 0) != 0); if (__pyx_t_2) { /* "View.MemoryView":1284 * * if src.suboffsets[i] >= 0: * _err_dim(ValueError, "Dimension %d is not direct", i) # <<<<<<<<<<<<<< * * if slices_overlap(&src, &dst, ndim, itemsize): */ __pyx_t_4 = __pyx_memoryview_err_dim(__pyx_builtin_ValueError, ((char *)"Dimension %d is not direct"), __pyx_v_i); if (unlikely(__pyx_t_4 == -1)) __PYX_ERR(2, 1284, __pyx_L1_error) /* "View.MemoryView":1283 * _err_extents(i, dst.shape[i], src.shape[i]) * * if src.suboffsets[i] >= 0: # <<<<<<<<<<<<<< * _err_dim(ValueError, "Dimension %d is not direct", i) * */ } } /* "View.MemoryView":1286 * _err_dim(ValueError, "Dimension %d is not direct", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< * * if not slice_is_contig(src, order, ndim): */ __pyx_t_2 = (__pyx_slices_overlap((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize) != 0); if (__pyx_t_2) { /* "View.MemoryView":1288 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< * order = get_best_order(&dst, ndim) * */ __pyx_t_2 = ((!(__pyx_memviewslice_is_contig(__pyx_v_src, __pyx_v_order, __pyx_v_ndim) != 0)) != 0); if (__pyx_t_2) { /* "View.MemoryView":1289 * * if not slice_is_contig(src, order, ndim): * order = get_best_order(&dst, ndim) # <<<<<<<<<<<<<< * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) */ __pyx_v_order = __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim); /* "View.MemoryView":1288 * if slices_overlap(&src, &dst, ndim, itemsize): * * if not slice_is_contig(src, order, ndim): # <<<<<<<<<<<<<< * order = get_best_order(&dst, ndim) * */ } /* "View.MemoryView":1291 * order = get_best_order(&dst, ndim) * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) # <<<<<<<<<<<<<< * src = tmp * */ __pyx_t_6 = __pyx_memoryview_copy_data_to_temp((&__pyx_v_src), (&__pyx_v_tmp), __pyx_v_order, __pyx_v_ndim); if (unlikely(__pyx_t_6 == NULL)) __PYX_ERR(2, 1291, __pyx_L1_error) __pyx_v_tmpdata = __pyx_t_6; /* "View.MemoryView":1292 * * tmpdata = copy_data_to_temp(&src, &tmp, order, ndim) * src = tmp # <<<<<<<<<<<<<< * * if not broadcasting: */ __pyx_v_src = __pyx_v_tmp; /* "View.MemoryView":1286 * _err_dim(ValueError, "Dimension %d is not direct", i) * * if slices_overlap(&src, &dst, ndim, itemsize): # <<<<<<<<<<<<<< * * if not slice_is_contig(src, order, ndim): */ } /* "View.MemoryView":1294 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< * * */ __pyx_t_2 = ((!(__pyx_v_broadcasting != 0)) != 0); if (__pyx_t_2) { /* "View.MemoryView":1297 * * * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): */ __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'C', __pyx_v_ndim) != 0); if (__pyx_t_2) { /* "View.MemoryView":1298 * * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) # <<<<<<<<<<<<<< * elif slice_is_contig(src, 'F', ndim): * direct_copy = slice_is_contig(dst, 'F', ndim) */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'C', __pyx_v_ndim); /* "View.MemoryView":1297 * * * if slice_is_contig(src, 'C', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): */ goto __pyx_L12; } /* "View.MemoryView":1299 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'F', ndim) * */ __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0); if (__pyx_t_2) { /* "View.MemoryView":1300 * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< * * if direct_copy: */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); /* "View.MemoryView":1299 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'F', ndim) * */ } __pyx_L12:; /* "View.MemoryView":1302 * direct_copy = slice_is_contig(dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< * * refcount_copying(&dst, dtype_is_object, ndim, False) */ __pyx_t_2 = (__pyx_v_direct_copy != 0); if (__pyx_t_2) { /* "View.MemoryView":1304 * if direct_copy: * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); /* "View.MemoryView":1305 * * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) */ memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim)); /* "View.MemoryView":1306 * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< * free(tmpdata) * return 0 */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); /* "View.MemoryView":1307 * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) # <<<<<<<<<<<<<< * return 0 * */ free(__pyx_v_tmpdata); /* "View.MemoryView":1308 * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) * return 0 # <<<<<<<<<<<<<< * * if order == 'F' == get_best_order(&dst, ndim): */ __pyx_r = 0; goto __pyx_L0; /* "View.MemoryView":1302 * direct_copy = slice_is_contig(dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< * * refcount_copying(&dst, dtype_is_object, ndim, False) */ } /* "View.MemoryView":1294 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< * * */ } /* "View.MemoryView":1310 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< * * */ __pyx_t_2 = (__pyx_v_order == 'F'); if (__pyx_t_2) { __pyx_t_2 = ('F' == __pyx_get_best_slice_order((&__pyx_v_dst), __pyx_v_ndim)); } __pyx_t_7 = (__pyx_t_2 != 0); if (__pyx_t_7) { /* "View.MemoryView":1313 * * * transpose_memslice(&src) # <<<<<<<<<<<<<< * transpose_memslice(&dst) * */ __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_src)); if (unlikely(__pyx_t_5 == 0)) __PYX_ERR(2, 1313, __pyx_L1_error) /* "View.MemoryView":1314 * * transpose_memslice(&src) * transpose_memslice(&dst) # <<<<<<<<<<<<<< * * refcount_copying(&dst, dtype_is_object, ndim, False) */ __pyx_t_5 = __pyx_memslice_transpose((&__pyx_v_dst)); if (unlikely(__pyx_t_5 == 0)) __PYX_ERR(2, 1314, __pyx_L1_error) /* "View.MemoryView":1310 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< * * */ } /* "View.MemoryView":1316 * transpose_memslice(&dst) * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); /* "View.MemoryView":1317 * * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< * refcount_copying(&dst, dtype_is_object, ndim, True) * */ copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); /* "View.MemoryView":1318 * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< * * free(tmpdata) */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); /* "View.MemoryView":1320 * refcount_copying(&dst, dtype_is_object, ndim, True) * * free(tmpdata) # <<<<<<<<<<<<<< * return 0 * */ free(__pyx_v_tmpdata); /* "View.MemoryView":1321 * * free(tmpdata) * return 0 # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_broadcast_leading') */ __pyx_r = 0; goto __pyx_L0; /* "View.MemoryView":1252 * * @cname('__pyx_memoryview_copy_contents') * cdef int memoryview_copy_contents(__Pyx_memviewslice src, # <<<<<<<<<<<<<< * __Pyx_memviewslice dst, * int src_ndim, int dst_ndim, */ /* function exit code */ __pyx_L1_error:; { #ifdef WITH_THREAD PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); #endif __Pyx_AddTraceback("View.MemoryView.memoryview_copy_contents", __pyx_clineno, __pyx_lineno, __pyx_filename); #ifdef WITH_THREAD PyGILState_Release(__pyx_gilstate_save); #endif } __pyx_r = -1; __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1324 * * @cname('__pyx_memoryview_broadcast_leading') * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< * int ndim, * int ndim_other) nogil: */ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim, int __pyx_v_ndim_other) { int __pyx_v_i; int __pyx_v_offset; int __pyx_t_1; int __pyx_t_2; /* "View.MemoryView":1328 * int ndim_other) nogil: * cdef int i * cdef int offset = ndim_other - ndim # <<<<<<<<<<<<<< * * for i in range(ndim - 1, -1, -1): */ __pyx_v_offset = (__pyx_v_ndim_other - __pyx_v_ndim); /* "View.MemoryView":1330 * cdef int offset = ndim_other - ndim * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< * mslice.shape[i + offset] = mslice.shape[i] * mslice.strides[i + offset] = mslice.strides[i] */ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1L; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; /* "View.MemoryView":1331 * * for i in range(ndim - 1, -1, -1): * mslice.shape[i + offset] = mslice.shape[i] # <<<<<<<<<<<<<< * mslice.strides[i + offset] = mslice.strides[i] * mslice.suboffsets[i + offset] = mslice.suboffsets[i] */ (__pyx_v_mslice->shape[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->shape[__pyx_v_i]); /* "View.MemoryView":1332 * for i in range(ndim - 1, -1, -1): * mslice.shape[i + offset] = mslice.shape[i] * mslice.strides[i + offset] = mslice.strides[i] # <<<<<<<<<<<<<< * mslice.suboffsets[i + offset] = mslice.suboffsets[i] * */ (__pyx_v_mslice->strides[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->strides[__pyx_v_i]); /* "View.MemoryView":1333 * mslice.shape[i + offset] = mslice.shape[i] * mslice.strides[i + offset] = mslice.strides[i] * mslice.suboffsets[i + offset] = mslice.suboffsets[i] # <<<<<<<<<<<<<< * * for i in range(offset): */ (__pyx_v_mslice->suboffsets[(__pyx_v_i + __pyx_v_offset)]) = (__pyx_v_mslice->suboffsets[__pyx_v_i]); } /* "View.MemoryView":1335 * mslice.suboffsets[i + offset] = mslice.suboffsets[i] * * for i in range(offset): # <<<<<<<<<<<<<< * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] */ __pyx_t_1 = __pyx_v_offset; for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) { __pyx_v_i = __pyx_t_2; /* "View.MemoryView":1336 * * for i in range(offset): * mslice.shape[i] = 1 # <<<<<<<<<<<<<< * mslice.strides[i] = mslice.strides[0] * mslice.suboffsets[i] = -1 */ (__pyx_v_mslice->shape[__pyx_v_i]) = 1; /* "View.MemoryView":1337 * for i in range(offset): * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] # <<<<<<<<<<<<<< * mslice.suboffsets[i] = -1 * */ (__pyx_v_mslice->strides[__pyx_v_i]) = (__pyx_v_mslice->strides[0]); /* "View.MemoryView":1338 * mslice.shape[i] = 1 * mslice.strides[i] = mslice.strides[0] * mslice.suboffsets[i] = -1 # <<<<<<<<<<<<<< * * */ (__pyx_v_mslice->suboffsets[__pyx_v_i]) = -1L; } /* "View.MemoryView":1324 * * @cname('__pyx_memoryview_broadcast_leading') * cdef void broadcast_leading(__Pyx_memviewslice *mslice, # <<<<<<<<<<<<<< * int ndim, * int ndim_other) nogil: */ /* function exit code */ } /* "View.MemoryView":1346 * * @cname('__pyx_memoryview_refcount_copying') * cdef void refcount_copying(__Pyx_memviewslice *dst, bint dtype_is_object, # <<<<<<<<<<<<<< * int ndim, bint inc) nogil: * */ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *__pyx_v_dst, int __pyx_v_dtype_is_object, int __pyx_v_ndim, int __pyx_v_inc) { int __pyx_t_1; /* 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"pyresample.ewa._fornav.__pyx_scope_struct_1_genexpr", /*tp_name*/ sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr, /*tp_dealloc*/ 0, /*tp_print*/ 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr, /*tp_traverse*/ __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ 0, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_1_genexpr, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif }; static struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr *__pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr[8]; static int __pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr = 0; static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { PyObject *o; if (CYTHON_COMPILING_IN_CPYTHON && likely((__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr > 0) & (t->tp_basicsize == sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr)))) { o = (PyObject*)__pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr[--__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr]; memset(o, 0, sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr)); (void) PyObject_INIT(o, t); PyObject_GC_Track(o); } else { o = (*t->tp_alloc)(t, 0); if (unlikely(!o)) return 0; } return o; } static void __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr(PyObject *o) { struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr *)o; PyObject_GC_UnTrack(o); Py_CLEAR(p->__pyx_outer_scope); Py_CLEAR(p->__pyx_v_output_array); if (CYTHON_COMPILING_IN_CPYTHON && ((__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr < 8) & (Py_TYPE(o)->tp_basicsize == sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr)))) { __pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr[__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr++] = ((struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr *)o); } else { (*Py_TYPE(o)->tp_free)(o); } } static int __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr(PyObject *o, visitproc v, void *a) { int e; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr *)o; if (p->__pyx_outer_scope) { e = (*v)(((PyObject*)p->__pyx_outer_scope), a); if (e) return e; } if (p->__pyx_v_output_array) { e = (*v)(p->__pyx_v_output_array, a); if (e) return e; } return 0; } static int __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr(PyObject *o) { PyObject* tmp; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr *)o; tmp = ((PyObject*)p->__pyx_outer_scope); p->__pyx_outer_scope = ((struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct____pyx_fuse_0fornav_wrapper *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->__pyx_v_output_array); p->__pyx_v_output_array = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } static PyTypeObject __pyx_type_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr = { PyVarObject_HEAD_INIT(0, 0) "pyresample.ewa._fornav.__pyx_scope_struct_2_genexpr", /*tp_name*/ sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr, /*tp_dealloc*/ 0, /*tp_print*/ 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr, /*tp_traverse*/ __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ 0, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_2_genexpr, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif }; static struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *__pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper[8]; static int __pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper = 0; static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { PyObject *o; if (CYTHON_COMPILING_IN_CPYTHON && likely((__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper > 0) & (t->tp_basicsize == sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper)))) { o = (PyObject*)__pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper[--__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper]; memset(o, 0, sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper)); (void) PyObject_INIT(o, t); PyObject_GC_Track(o); } else { o = (*t->tp_alloc)(t, 0); if (unlikely(!o)) return 0; } return o; } static void __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper(PyObject *o) { struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *)o; PyObject_GC_UnTrack(o); Py_CLEAR(p->__pyx_v_in_type); Py_CLEAR(p->__pyx_v_input_arrays); Py_CLEAR(p->__pyx_v_out_type); Py_CLEAR(p->__pyx_v_output_arrays); if (CYTHON_COMPILING_IN_CPYTHON && ((__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper < 8) & (Py_TYPE(o)->tp_basicsize == sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper)))) { __pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper[__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper++] = ((struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *)o); } else { (*Py_TYPE(o)->tp_free)(o); } } static int __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper(PyObject *o, visitproc v, void *a) { int e; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *)o; if (p->__pyx_v_in_type) { e = (*v)(((PyObject*)p->__pyx_v_in_type), a); if (e) return e; } if (p->__pyx_v_input_arrays) { e = (*v)(p->__pyx_v_input_arrays, a); if (e) return e; } if (p->__pyx_v_out_type) { e = (*v)(((PyObject*)p->__pyx_v_out_type), a); if (e) return e; } if (p->__pyx_v_output_arrays) { e = (*v)(p->__pyx_v_output_arrays, a); if (e) return e; } return 0; } static int __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper(PyObject *o) { PyObject* tmp; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *)o; tmp = ((PyObject*)p->__pyx_v_in_type); p->__pyx_v_in_type = ((PyArray_Descr *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->__pyx_v_input_arrays); p->__pyx_v_input_arrays = ((PyObject*)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->__pyx_v_out_type); p->__pyx_v_out_type = ((PyArray_Descr *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->__pyx_v_output_arrays); p->__pyx_v_output_arrays = ((PyObject*)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } static PyTypeObject __pyx_type_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper = { PyVarObject_HEAD_INIT(0, 0) "pyresample.ewa._fornav.__pyx_scope_struct_3___pyx_fuse_1fornav_wrapper", /*tp_name*/ sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper, /*tp_dealloc*/ 0, /*tp_print*/ 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper, /*tp_traverse*/ __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ 0, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif }; static struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr *__pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr[8]; static int __pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr = 0; static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { PyObject *o; if (CYTHON_COMPILING_IN_CPYTHON && likely((__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr > 0) & (t->tp_basicsize == sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr)))) { o = (PyObject*)__pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr[--__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr]; memset(o, 0, sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr)); (void) PyObject_INIT(o, t); PyObject_GC_Track(o); } else { o = (*t->tp_alloc)(t, 0); if (unlikely(!o)) return 0; } return o; } static void __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr(PyObject *o) { struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr *)o; PyObject_GC_UnTrack(o); Py_CLEAR(p->__pyx_outer_scope); Py_CLEAR(p->__pyx_v_input_array); if (CYTHON_COMPILING_IN_CPYTHON && ((__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr < 8) & (Py_TYPE(o)->tp_basicsize == sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr)))) { __pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr[__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr++] = ((struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr *)o); } else { (*Py_TYPE(o)->tp_free)(o); } } static int __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr(PyObject *o, visitproc v, void *a) { int e; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr *)o; if (p->__pyx_outer_scope) { e = (*v)(((PyObject*)p->__pyx_outer_scope), a); if (e) return e; } if (p->__pyx_v_input_array) { e = (*v)(p->__pyx_v_input_array, a); if (e) return e; } return 0; } static int __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr(PyObject *o) { PyObject* tmp; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr *)o; tmp = ((PyObject*)p->__pyx_outer_scope); p->__pyx_outer_scope = ((struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->__pyx_v_input_array); p->__pyx_v_input_array = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } static PyTypeObject __pyx_type_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr = { PyVarObject_HEAD_INIT(0, 0) "pyresample.ewa._fornav.__pyx_scope_struct_4_genexpr", /*tp_name*/ sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr, /*tp_dealloc*/ 0, /*tp_print*/ 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr, /*tp_traverse*/ __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ 0, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_4_genexpr, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif }; static struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr *__pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr[8]; static int __pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr = 0; static PyObject *__pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { PyObject *o; if (CYTHON_COMPILING_IN_CPYTHON && likely((__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr > 0) & (t->tp_basicsize == sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr)))) { o = (PyObject*)__pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr[--__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr]; memset(o, 0, sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr)); (void) PyObject_INIT(o, t); PyObject_GC_Track(o); } else { o = (*t->tp_alloc)(t, 0); if (unlikely(!o)) return 0; } return o; } static void __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr(PyObject *o) { struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr *)o; PyObject_GC_UnTrack(o); Py_CLEAR(p->__pyx_outer_scope); Py_CLEAR(p->__pyx_v_output_array); if (CYTHON_COMPILING_IN_CPYTHON && ((__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr < 8) & (Py_TYPE(o)->tp_basicsize == sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr)))) { __pyx_freelist_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr[__pyx_freecount_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr++] = ((struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr *)o); } else { (*Py_TYPE(o)->tp_free)(o); } } static int __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr(PyObject *o, visitproc v, void *a) { int e; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr *)o; if (p->__pyx_outer_scope) { e = (*v)(((PyObject*)p->__pyx_outer_scope), a); if (e) return e; } if (p->__pyx_v_output_array) { e = (*v)(p->__pyx_v_output_array, a); if (e) return e; } return 0; } static int __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr(PyObject *o) { PyObject* tmp; struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr *p = (struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr *)o; tmp = ((PyObject*)p->__pyx_outer_scope); p->__pyx_outer_scope = ((struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_3___pyx_fuse_1fornav_wrapper *)Py_None); Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->__pyx_v_output_array); p->__pyx_v_output_array = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } static PyTypeObject __pyx_type_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr = { PyVarObject_HEAD_INIT(0, 0) "pyresample.ewa._fornav.__pyx_scope_struct_5_genexpr", /*tp_name*/ sizeof(struct __pyx_obj_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr, /*tp_dealloc*/ 0, /*tp_print*/ 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif 0, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ __pyx_tp_traverse_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr, /*tp_traverse*/ __pyx_tp_clear_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ 0, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_10pyresample_3ewa_7_fornav___pyx_scope_struct_5_genexpr, 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PyErr_ExceptionMatches(PyExc_AttributeError)) { PyErr_Clear(); v = __pyx_array___getattr__(o, n); } return v; } static PyObject *__pyx_getprop___pyx_array_memview(PyObject *o, CYTHON_UNUSED void *x) { return __pyx_pw_15View_dot_MemoryView_5array_7memview_1__get__(o); } static PyMethodDef __pyx_methods_array[] = { {"__getattr__", (PyCFunction)__pyx_array___getattr__, METH_O|METH_COEXIST, 0}, {0, 0, 0, 0} }; static struct PyGetSetDef __pyx_getsets_array[] = { {(char *)"memview", __pyx_getprop___pyx_array_memview, 0, (char *)0, 0}, {0, 0, 0, 0, 0} }; static PySequenceMethods __pyx_tp_as_sequence_array = { 0, /*sq_length*/ 0, /*sq_concat*/ 0, /*sq_repeat*/ __pyx_sq_item_array, /*sq_item*/ 0, /*sq_slice*/ 0, /*sq_ass_item*/ 0, /*sq_ass_slice*/ 0, /*sq_contains*/ 0, /*sq_inplace_concat*/ 0, /*sq_inplace_repeat*/ }; static PyMappingMethods __pyx_tp_as_mapping_array = { 0, /*mp_length*/ __pyx_array___getitem__, /*mp_subscript*/ __pyx_mp_ass_subscript_array, /*mp_ass_subscript*/ }; static 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Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/ 0, /*tp_doc*/ 0, /*tp_traverse*/ 0, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ __pyx_methods_array, /*tp_methods*/ 0, /*tp_members*/ __pyx_getsets_array, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ 0, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_array, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif }; static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) { struct __pyx_MemviewEnum_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_MemviewEnum_obj *)o); p->name = Py_None; Py_INCREF(Py_None); return o; } static void __pyx_tp_dealloc_Enum(PyObject *o) { struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; #if PY_VERSION_HEX >= 0x030400a1 if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif PyObject_GC_UnTrack(o); Py_CLEAR(p->name); (*Py_TYPE(o)->tp_free)(o); } static int __pyx_tp_traverse_Enum(PyObject *o, visitproc v, void *a) { int e; struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; if (p->name) { e = (*v)(p->name, a); if (e) return e; } return 0; } static int __pyx_tp_clear_Enum(PyObject *o) { PyObject* tmp; struct __pyx_MemviewEnum_obj *p = (struct __pyx_MemviewEnum_obj *)o; tmp = ((PyObject*)p->name); p->name = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); return 0; } static PyMethodDef __pyx_methods_Enum[] = { {0, 0, 0, 0} }; static PyTypeObject __pyx_type___pyx_MemviewEnum = { PyVarObject_HEAD_INIT(0, 0) "pyresample.ewa._fornav.Enum", /*tp_name*/ sizeof(struct __pyx_MemviewEnum_obj), /*tp_basicsize*/ 0, /*tp_itemsize*/ __pyx_tp_dealloc_Enum, /*tp_dealloc*/ 0, /*tp_print*/ 0, /*tp_getattr*/ 0, /*tp_setattr*/ #if PY_MAJOR_VERSION < 3 0, /*tp_compare*/ #endif #if PY_MAJOR_VERSION >= 3 0, /*tp_as_async*/ #endif __pyx_MemviewEnum___repr__, /*tp_repr*/ 0, /*tp_as_number*/ 0, /*tp_as_sequence*/ 0, /*tp_as_mapping*/ 0, /*tp_hash*/ 0, /*tp_call*/ 0, /*tp_str*/ 0, /*tp_getattro*/ 0, /*tp_setattro*/ 0, /*tp_as_buffer*/ Py_TPFLAGS_DEFAULT|Py_TPFLAGS_HAVE_VERSION_TAG|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ 0, /*tp_doc*/ __pyx_tp_traverse_Enum, /*tp_traverse*/ __pyx_tp_clear_Enum, /*tp_clear*/ 0, /*tp_richcompare*/ 0, /*tp_weaklistoffset*/ 0, /*tp_iter*/ 0, /*tp_iternext*/ __pyx_methods_Enum, /*tp_methods*/ 0, /*tp_members*/ 0, /*tp_getset*/ 0, /*tp_base*/ 0, /*tp_dict*/ 0, /*tp_descr_get*/ 0, /*tp_descr_set*/ 0, /*tp_dictoffset*/ __pyx_MemviewEnum___init__, /*tp_init*/ 0, /*tp_alloc*/ __pyx_tp_new_Enum, /*tp_new*/ 0, /*tp_free*/ 0, /*tp_is_gc*/ 0, /*tp_bases*/ 0, /*tp_mro*/ 0, /*tp_cache*/ 0, /*tp_subclasses*/ 0, /*tp_weaklist*/ 0, /*tp_del*/ 0, /*tp_version_tag*/ #if PY_VERSION_HEX >= 0x030400a1 0, /*tp_finalize*/ #endif }; static struct __pyx_vtabstruct_memoryview __pyx_vtable_memoryview; static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { struct __pyx_memoryview_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_memoryview_obj *)o); p->__pyx_vtab = __pyx_vtabptr_memoryview; p->obj = Py_None; Py_INCREF(Py_None); p->_size = Py_None; Py_INCREF(Py_None); p->_array_interface = Py_None; Py_INCREF(Py_None); p->view.obj = NULL; if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) { Py_DECREF(o); o = 0; } return o; } static void __pyx_tp_dealloc_memoryview(PyObject *o) { struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; #if PY_VERSION_HEX >= 0x030400a1 if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif PyObject_GC_UnTrack(o); { PyObject *etype, *eval, *etb; PyErr_Fetch(&etype, &eval, &etb); ++Py_REFCNT(o); __pyx_memoryview___dealloc__(o); --Py_REFCNT(o); PyErr_Restore(etype, eval, etb); } Py_CLEAR(p->obj); Py_CLEAR(p->_size); Py_CLEAR(p->_array_interface); (*Py_TYPE(o)->tp_free)(o); } static int __pyx_tp_traverse_memoryview(PyObject *o, visitproc v, void *a) { int e; struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; if (p->obj) { e = (*v)(p->obj, a); if (e) return e; } if (p->_size) { e = (*v)(p->_size, a); if (e) return e; } if (p->_array_interface) { e = (*v)(p->_array_interface, a); if (e) return e; } if (p->view.obj) { e = (*v)(p->view.obj, a); if (e) return e; } return 0; } static int __pyx_tp_clear_memoryview(PyObject *o) { PyObject* tmp; struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; tmp = ((PyObject*)p->obj); p->obj = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->_size); p->_size = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); tmp = ((PyObject*)p->_array_interface); p->_array_interface = Py_None; Py_INCREF(Py_None); Py_XDECREF(tmp); Py_CLEAR(p->view.obj); return 0; } static PyObject *__pyx_sq_item_memoryview(PyObject *o, Py_ssize_t i) { PyObject *r; PyObject *x = PyInt_FromSsize_t(i); if(!x) return 0; r = Py_TYPE(o)->tp_as_mapping->mp_subscript(o, x); Py_DECREF(x); return r; } static int __pyx_mp_ass_subscript_memoryview(PyObject *o, PyObject *i, PyObject *v) { if (v) { return __pyx_memoryview___setitem__(o, i, v); } else { PyErr_Format(PyExc_NotImplementedError, "Subscript deletion not 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"" : "s", num_found); } /* RaiseDoubleKeywords */ static void __Pyx_RaiseDoubleKeywordsError( const char* func_name, PyObject* kw_name) { PyErr_Format(PyExc_TypeError, #if PY_MAJOR_VERSION >= 3 "%s() got multiple values for keyword argument '%U'", func_name, kw_name); #else "%s() got multiple values for keyword argument '%s'", func_name, PyString_AsString(kw_name)); #endif } /* ParseKeywords */ static int __Pyx_ParseOptionalKeywords( PyObject *kwds, PyObject **argnames[], PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, const char* function_name) { PyObject *key = 0, *value = 0; Py_ssize_t pos = 0; PyObject*** name; PyObject*** first_kw_arg = argnames + num_pos_args; while (PyDict_Next(kwds, &pos, &key, &value)) { name = first_kw_arg; while (*name && (**name != key)) name++; if (*name) { values[name-argnames] = value; continue; } name = first_kw_arg; #if PY_MAJOR_VERSION < 3 if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) { while (*name) { if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) && _PyString_Eq(**name, key)) { values[name-argnames] = value; break; } name++; } if (*name) continue; else { PyObject*** argname = argnames; while (argname != first_kw_arg) { if ((**argname == key) || ( (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) && _PyString_Eq(**argname, key))) { goto arg_passed_twice; } argname++; } } } else #endif if (likely(PyUnicode_Check(key))) { while (*name) { int cmp = (**name == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 (PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 : #endif PyUnicode_Compare(**name, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; if (cmp == 0) { values[name-argnames] = value; break; } name++; } if (*name) continue; else { PyObject*** argname = argnames; while (argname != first_kw_arg) { int cmp = (**argname == key) ? 0 : #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 (PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 : #endif PyUnicode_Compare(**argname, key); if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; if (cmp == 0) goto arg_passed_twice; argname++; } } } else goto invalid_keyword_type; if (kwds2) { if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; } else { goto invalid_keyword; } } return 0; arg_passed_twice: __Pyx_RaiseDoubleKeywordsError(function_name, key); goto bad; invalid_keyword_type: PyErr_Format(PyExc_TypeError, "%.200s() keywords must be strings", function_name); goto bad; invalid_keyword: PyErr_Format(PyExc_TypeError, #if PY_MAJOR_VERSION < 3 "%.200s() got an unexpected keyword argument '%.200s'", function_name, PyString_AsString(key)); #else "%s() got an unexpected keyword argument '%U'", function_name, key); #endif bad: return -1; } /* Import */ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { PyObject *empty_list = 0; PyObject *module = 0; PyObject *global_dict = 0; PyObject *empty_dict = 0; PyObject *list; #if PY_VERSION_HEX < 0x03030000 PyObject *py_import; py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); if (!py_import) goto bad; #endif if (from_list) list = from_list; else { empty_list = PyList_New(0); if (!empty_list) goto bad; list = empty_list; } global_dict = PyModule_GetDict(__pyx_m); if (!global_dict) goto bad; empty_dict = PyDict_New(); if (!empty_dict) goto bad; { #if PY_MAJOR_VERSION >= 3 if (level == -1) { if (strchr(__Pyx_MODULE_NAME, '.')) { #if PY_VERSION_HEX < 0x03030000 PyObject *py_level = PyInt_FromLong(1); if (!py_level) goto bad; module = PyObject_CallFunctionObjArgs(py_import, name, global_dict, empty_dict, list, py_level, NULL); Py_DECREF(py_level); #else module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, 1); #endif if (!module) { if (!PyErr_ExceptionMatches(PyExc_ImportError)) goto bad; PyErr_Clear(); } } level = 0; } #endif if (!module) { #if PY_VERSION_HEX < 0x03030000 PyObject *py_level = PyInt_FromLong(level); if (!py_level) goto bad; module = PyObject_CallFunctionObjArgs(py_import, name, global_dict, empty_dict, list, py_level, NULL); Py_DECREF(py_level); #else module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, level); #endif } } bad: #if PY_VERSION_HEX < 0x03030000 Py_XDECREF(py_import); #endif Py_XDECREF(empty_list); Py_XDECREF(empty_dict); return module; } /* SaveResetException */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { *type = tstate->exc_type; *value = tstate->exc_value; *tb = tstate->exc_traceback; Py_XINCREF(*type); Py_XINCREF(*value); Py_XINCREF(*tb); } static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = type; tstate->exc_value = value; tstate->exc_traceback = tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); } #endif /* PyErrExceptionMatches */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err) { PyObject *exc_type = tstate->curexc_type; if (exc_type == err) return 1; if (unlikely(!exc_type)) return 0; return PyErr_GivenExceptionMatches(exc_type, err); } #endif /* GetException */ #if CYTHON_COMPILING_IN_CPYTHON static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { #else static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) { #endif PyObject *local_type, *local_value, *local_tb; #if CYTHON_COMPILING_IN_CPYTHON PyObject *tmp_type, *tmp_value, *tmp_tb; local_type = tstate->curexc_type; local_value = tstate->curexc_value; local_tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; #else PyErr_Fetch(&local_type, &local_value, &local_tb); #endif PyErr_NormalizeException(&local_type, &local_value, &local_tb); #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(tstate->curexc_type)) #else if (unlikely(PyErr_Occurred())) #endif goto bad; #if PY_MAJOR_VERSION >= 3 if (local_tb) { if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) goto bad; } #endif Py_XINCREF(local_tb); Py_XINCREF(local_type); Py_XINCREF(local_value); *type = local_type; *value = local_value; *tb = local_tb; #if CYTHON_COMPILING_IN_CPYTHON tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = local_type; tstate->exc_value = local_value; tstate->exc_traceback = local_tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); #else PyErr_SetExcInfo(local_type, local_value, local_tb); #endif return 0; bad: *type = 0; *value = 0; *tb = 0; Py_XDECREF(local_type); Py_XDECREF(local_value); Py_XDECREF(local_tb); return -1; } /* UnicodeAsUCS4 */ static CYTHON_INLINE Py_UCS4 __Pyx_PyUnicode_AsPy_UCS4(PyObject* x) { Py_ssize_t length; #if CYTHON_PEP393_ENABLED length = PyUnicode_GET_LENGTH(x); if (likely(length == 1)) { return PyUnicode_READ_CHAR(x, 0); } #else length = PyUnicode_GET_SIZE(x); if (likely(length == 1)) { return PyUnicode_AS_UNICODE(x)[0]; } #if Py_UNICODE_SIZE == 2 else if (PyUnicode_GET_SIZE(x) == 2) { Py_UCS4 high_val = PyUnicode_AS_UNICODE(x)[0]; if (high_val >= 0xD800 && high_val <= 0xDBFF) { Py_UCS4 low_val = PyUnicode_AS_UNICODE(x)[1]; if (low_val >= 0xDC00 && low_val <= 0xDFFF) { return 0x10000 + (((high_val & ((1<<10)-1)) << 10) | (low_val & ((1<<10)-1))); } } } #endif #endif PyErr_Format(PyExc_ValueError, "only single character unicode strings can be converted to Py_UCS4, " "got length %" CYTHON_FORMAT_SSIZE_T "d", length); return (Py_UCS4)-1; } /* object_ord */ static long __Pyx__PyObject_Ord(PyObject* c) { Py_ssize_t size; if (PyBytes_Check(c)) { size = PyBytes_GET_SIZE(c); if (likely(size == 1)) { return (unsigned char) PyBytes_AS_STRING(c)[0]; } #if PY_MAJOR_VERSION < 3 } else if (PyUnicode_Check(c)) { return (long)__Pyx_PyUnicode_AsPy_UCS4(c); #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) } else if (PyByteArray_Check(c)) { size = PyByteArray_GET_SIZE(c); if (likely(size == 1)) { return (unsigned char) PyByteArray_AS_STRING(c)[0]; } #endif } else { PyErr_Format(PyExc_TypeError, "ord() expected string of length 1, but %.200s found", c->ob_type->tp_name); return (long)(Py_UCS4)-1; } PyErr_Format(PyExc_TypeError, "ord() expected a character, but string of length %zd found", size); return (long)(Py_UCS4)-1; } /* SetItemInt */ static CYTHON_INLINE int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) { int r; if (!j) return -1; r = PyObject_SetItem(o, j, v); Py_DECREF(j); return r; } static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (is_list || PyList_CheckExact(o)) { Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o)); if ((!boundscheck) || likely((n >= 0) & (n < PyList_GET_SIZE(o)))) { PyObject* old = PyList_GET_ITEM(o, n); Py_INCREF(v); PyList_SET_ITEM(o, n, v); Py_DECREF(old); return 1; } } else { PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; if (likely(m && m->sq_ass_item)) { if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { Py_ssize_t l = m->sq_length(o); if (likely(l >= 0)) { i += l; } else { if (!PyErr_ExceptionMatches(PyExc_OverflowError)) return -1; PyErr_Clear(); } } return m->sq_ass_item(o, i, v); } } #else #if CYTHON_COMPILING_IN_PYPY if (is_list || (PySequence_Check(o) && !PyDict_Check(o))) { #else if (is_list || PySequence_Check(o)) { #endif return PySequence_SetItem(o, i, v); } #endif return __Pyx_SetItemInt_Generic(o, PyInt_FromSsize_t(i), v); } /* IterFinish */ static CYTHON_INLINE int __Pyx_IterFinish(void) { #if CYTHON_COMPILING_IN_CPYTHON PyThreadState *tstate = PyThreadState_GET(); PyObject* exc_type = tstate->curexc_type; if (unlikely(exc_type)) { if (likely(exc_type == PyExc_StopIteration) || PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration)) { PyObject *exc_value, *exc_tb; exc_value = tstate->curexc_value; exc_tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; Py_DECREF(exc_type); Py_XDECREF(exc_value); Py_XDECREF(exc_tb); return 0; } else { return -1; } } return 0; #else if (unlikely(PyErr_Occurred())) { if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) { PyErr_Clear(); return 0; } else { return -1; } } return 0; #endif } /* PyObjectCallMethO */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { PyObject *self, *result; PyCFunction cfunc; cfunc = PyCFunction_GET_FUNCTION(func); self = PyCFunction_GET_SELF(func); if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) return NULL; result = cfunc(self, arg); Py_LeaveRecursiveCall(); if (unlikely(!result) && unlikely(!PyErr_Occurred())) { PyErr_SetString( PyExc_SystemError, "NULL result without error in PyObject_Call"); } return result; } #endif /* PyObjectCallNoArg */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE PyObject* __Pyx_PyObject_CallNoArg(PyObject *func) { #ifdef __Pyx_CyFunction_USED if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) { #else if (likely(PyCFunction_Check(func))) { #endif if (likely(PyCFunction_GET_FLAGS(func) & METH_NOARGS)) { return __Pyx_PyObject_CallMethO(func, NULL); } } return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); } #endif /* PyObjectCallOneArg */ #if CYTHON_COMPILING_IN_CPYTHON static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { PyObject *result; PyObject *args = PyTuple_New(1); if (unlikely(!args)) return NULL; Py_INCREF(arg); PyTuple_SET_ITEM(args, 0, arg); result = __Pyx_PyObject_Call(func, args, NULL); Py_DECREF(args); return result; } static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { #ifdef __Pyx_CyFunction_USED if (likely(PyCFunction_Check(func) || PyObject_TypeCheck(func, __pyx_CyFunctionType))) { #else if (likely(PyCFunction_Check(func))) { #endif if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { return __Pyx_PyObject_CallMethO(func, arg); } } return __Pyx__PyObject_CallOneArg(func, arg); } #else static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { PyObject *result; PyObject *args = PyTuple_Pack(1, arg); if (unlikely(!args)) return NULL; result = __Pyx_PyObject_Call(func, args, NULL); Py_DECREF(args); return result; } #endif /* PyObjectCallMethod0 */ static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name) { PyObject *method, *result = NULL; method = __Pyx_PyObject_GetAttrStr(obj, method_name); if (unlikely(!method)) goto bad; #if CYTHON_COMPILING_IN_CPYTHON if (likely(PyMethod_Check(method))) { PyObject *self = PyMethod_GET_SELF(method); if (likely(self)) { PyObject *function = PyMethod_GET_FUNCTION(method); result = __Pyx_PyObject_CallOneArg(function, self); Py_DECREF(method); return result; } } #endif result = __Pyx_PyObject_CallNoArg(method); Py_DECREF(method); bad: return result; } /* RaiseNeedMoreValuesToUnpack */ static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { PyErr_Format(PyExc_ValueError, "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", index, (index == 1) ? "" : "s"); } /* RaiseTooManyValuesToUnpack */ static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { PyErr_Format(PyExc_ValueError, "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); } /* UnpackItemEndCheck */ static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) { if (unlikely(retval)) { Py_DECREF(retval); __Pyx_RaiseTooManyValuesError(expected); return -1; } else { return __Pyx_IterFinish(); } return 0; } /* RaiseNoneIterError */ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); } /* UnpackTupleError */ static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) { if (t == Py_None) { __Pyx_RaiseNoneNotIterableError(); } else if (PyTuple_GET_SIZE(t) < index) { __Pyx_RaiseNeedMoreValuesError(PyTuple_GET_SIZE(t)); } else { __Pyx_RaiseTooManyValuesError(index); } } /* UnpackTuple2 */ static CYTHON_INLINE int __Pyx_unpack_tuple2(PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2, int is_tuple, int has_known_size, int decref_tuple) { Py_ssize_t index; PyObject *value1 = NULL, *value2 = NULL, *iter = NULL; if (!is_tuple && unlikely(!PyTuple_Check(tuple))) { iternextfunc iternext; iter = PyObject_GetIter(tuple); if (unlikely(!iter)) goto bad; if (decref_tuple) { Py_DECREF(tuple); tuple = NULL; } iternext = Py_TYPE(iter)->tp_iternext; value1 = iternext(iter); if (unlikely(!value1)) { index = 0; goto unpacking_failed; } value2 = iternext(iter); if (unlikely(!value2)) { index = 1; goto unpacking_failed; } if (!has_known_size && unlikely(__Pyx_IternextUnpackEndCheck(iternext(iter), 2))) goto bad; Py_DECREF(iter); } else { if (!has_known_size && unlikely(PyTuple_GET_SIZE(tuple) != 2)) { __Pyx_UnpackTupleError(tuple, 2); goto bad; } #if CYTHON_COMPILING_IN_PYPY value1 = PySequence_ITEM(tuple, 0); if (unlikely(!value1)) goto bad; value2 = PySequence_ITEM(tuple, 1); if (unlikely(!value2)) goto bad; #else value1 = PyTuple_GET_ITEM(tuple, 0); value2 = PyTuple_GET_ITEM(tuple, 1); Py_INCREF(value1); Py_INCREF(value2); #endif if (decref_tuple) { Py_DECREF(tuple); } } *pvalue1 = value1; *pvalue2 = value2; return 0; unpacking_failed: if (!has_known_size && __Pyx_IterFinish() == 0) __Pyx_RaiseNeedMoreValuesError(index); bad: Py_XDECREF(iter); Py_XDECREF(value1); Py_XDECREF(value2); if (decref_tuple) { Py_XDECREF(tuple); } return -1; } /* dict_iter */ static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* iterable, int is_dict, PyObject* method_name, Py_ssize_t* p_orig_length, int* p_source_is_dict) { is_dict = is_dict || likely(PyDict_CheckExact(iterable)); *p_source_is_dict = is_dict; #if !CYTHON_COMPILING_IN_PYPY if (is_dict) { *p_orig_length = PyDict_Size(iterable); Py_INCREF(iterable); return iterable; } #endif *p_orig_length = 0; if (method_name) { PyObject* iter; iterable = __Pyx_PyObject_CallMethod0(iterable, method_name); if (!iterable) return NULL; #if !CYTHON_COMPILING_IN_PYPY if (PyTuple_CheckExact(iterable) || PyList_CheckExact(iterable)) return iterable; #endif iter = PyObject_GetIter(iterable); Py_DECREF(iterable); return iter; } return PyObject_GetIter(iterable); } static CYTHON_INLINE int __Pyx_dict_iter_next( PyObject* iter_obj, CYTHON_NCP_UNUSED Py_ssize_t orig_length, CYTHON_NCP_UNUSED Py_ssize_t* ppos, PyObject** pkey, PyObject** pvalue, PyObject** pitem, int source_is_dict) { PyObject* next_item; #if !CYTHON_COMPILING_IN_PYPY if (source_is_dict) { PyObject *key, *value; if (unlikely(orig_length != PyDict_Size(iter_obj))) { PyErr_SetString(PyExc_RuntimeError, "dictionary changed size during iteration"); return -1; } if (unlikely(!PyDict_Next(iter_obj, ppos, &key, &value))) { return 0; } if (pitem) { PyObject* tuple = PyTuple_New(2); if (unlikely(!tuple)) { return -1; } Py_INCREF(key); Py_INCREF(value); PyTuple_SET_ITEM(tuple, 0, key); PyTuple_SET_ITEM(tuple, 1, value); *pitem = tuple; } else { if (pkey) { Py_INCREF(key); *pkey = key; } if (pvalue) { Py_INCREF(value); *pvalue = value; } } return 1; } else if (PyTuple_CheckExact(iter_obj)) { Py_ssize_t pos = *ppos; if (unlikely(pos >= PyTuple_GET_SIZE(iter_obj))) return 0; *ppos = pos + 1; next_item = PyTuple_GET_ITEM(iter_obj, pos); Py_INCREF(next_item); } else if (PyList_CheckExact(iter_obj)) { Py_ssize_t pos = *ppos; if (unlikely(pos >= PyList_GET_SIZE(iter_obj))) return 0; *ppos = pos + 1; next_item = PyList_GET_ITEM(iter_obj, pos); Py_INCREF(next_item); } else #endif { next_item = PyIter_Next(iter_obj); if (unlikely(!next_item)) { return __Pyx_IterFinish(); } } if (pitem) { *pitem = next_item; } else if (pkey && pvalue) { if (__Pyx_unpack_tuple2(next_item, pkey, pvalue, source_is_dict, source_is_dict, 1)) return -1; } else if (pkey) { *pkey = next_item; } else { *pvalue = next_item; } return 1; } /* ArgTypeTest */ static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) { PyErr_Format(PyExc_TypeError, "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", name, type->tp_name, Py_TYPE(obj)->tp_name); } static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, const char *name, int exact) { if (unlikely(!type)) { PyErr_SetString(PyExc_SystemError, "Missing type object"); return 0; } if (none_allowed && obj == Py_None) return 1; else if (exact) { if (likely(Py_TYPE(obj) == type)) return 1; #if PY_MAJOR_VERSION == 2 else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; #endif } else { if (likely(PyObject_TypeCheck(obj, type))) return 1; } __Pyx_RaiseArgumentTypeInvalid(name, obj, type); return 0; } /* None */ static CYTHON_INLINE void __Pyx_RaiseClosureNameError(const char *varname) { PyErr_Format(PyExc_NameError, "free variable '%s' referenced before assignment in enclosing scope", varname); } /* BufferFormatCheck */ static CYTHON_INLINE int __Pyx_IsLittleEndian(void) { unsigned int n = 1; return *(unsigned char*)(&n) != 0; } static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, __Pyx_BufFmt_StackElem* stack, __Pyx_TypeInfo* type) { stack[0].field = &ctx->root; stack[0].parent_offset = 0; ctx->root.type = type; ctx->root.name = "buffer dtype"; ctx->root.offset = 0; ctx->head = stack; ctx->head->field = &ctx->root; ctx->fmt_offset = 0; ctx->head->parent_offset = 0; ctx->new_packmode = '@'; ctx->enc_packmode = '@'; ctx->new_count = 1; ctx->enc_count = 0; ctx->enc_type = 0; ctx->is_complex = 0; ctx->is_valid_array = 0; ctx->struct_alignment = 0; while (type->typegroup == 'S') { ++ctx->head; ctx->head->field = type->fields; ctx->head->parent_offset = 0; type = type->fields->type; } } static int __Pyx_BufFmt_ParseNumber(const char** ts) { int count; const char* t = *ts; if (*t < '0' || *t > '9') { return -1; } else { count = *t++ - '0'; while (*t >= '0' && *t < '9') { count *= 10; count += *t++ - '0'; } } *ts = t; return count; } static int __Pyx_BufFmt_ExpectNumber(const char **ts) { int number = __Pyx_BufFmt_ParseNumber(ts); if (number == -1) PyErr_Format(PyExc_ValueError,\ "Does not understand character buffer dtype format string ('%c')", **ts); return number; } static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { PyErr_Format(PyExc_ValueError, "Unexpected format string character: '%c'", ch); } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { case 'c': return "'char'"; case 'b': return "'signed char'"; case 'B': return "'unsigned char'"; case 'h': return "'short'"; case 'H': return "'unsigned short'"; case 'i': return "'int'"; case 'I': return "'unsigned int'"; case 'l': return "'long'"; case 'L': return "'unsigned long'"; case 'q': return "'long long'"; case 'Q': return "'unsigned long long'"; case 'f': return (is_complex ? "'complex float'" : "'float'"); case 'd': return (is_complex ? "'complex double'" : "'double'"); case 'g': return (is_complex ? "'complex long double'" : "'long double'"); case 'T': return "a struct"; case 'O': return "Python object"; case 'P': return "a pointer"; case 's': case 'p': return "a string"; case 0: return "end"; default: return "unparseable format string"; } } static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return 2; case 'i': case 'I': case 'l': case 'L': return 4; case 'q': case 'Q': return 8; case 'f': return (is_complex ? 8 : 4); case 'd': return (is_complex ? 16 : 8); case 'g': { PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); return 0; } case 'O': case 'P': return sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(float) * (is_complex ? 2 : 1); case 'd': return sizeof(double) * (is_complex ? 2 : 1); case 'g': return sizeof(long double) * (is_complex ? 2 : 1); case 'O': case 'P': return sizeof(void*); default: { __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } } typedef struct { char c; short x; } __Pyx_st_short; typedef struct { char c; int x; } __Pyx_st_int; typedef struct { char c; long x; } __Pyx_st_long; typedef struct { char c; float x; } __Pyx_st_float; typedef struct { char c; double x; } __Pyx_st_double; typedef struct { char c; long double x; } __Pyx_st_longdouble; typedef struct { char c; void *x; } __Pyx_st_void_p; #ifdef HAVE_LONG_LONG typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; #endif static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(__Pyx_st_float) - sizeof(float); case 'd': return sizeof(__Pyx_st_double) - sizeof(double); case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } /* These are for computing the padding at the end of the struct to align on the first member of the struct. This will probably the same as above, but we don't have any guarantees. */ typedef struct { short x; char c; } __Pyx_pad_short; typedef struct { int x; char c; } __Pyx_pad_int; typedef struct { long x; char c; } __Pyx_pad_long; typedef struct { float x; char c; } __Pyx_pad_float; typedef struct { double x; char c; } __Pyx_pad_double; typedef struct { long double x; char c; } __Pyx_pad_longdouble; typedef struct { void *x; char c; } __Pyx_pad_void_p; #ifdef HAVE_LONG_LONG typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; #endif static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { switch (ch) { case 'c': return 'H'; case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); case 'O': return 'O'; case 'P': return 'P'; default: { __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } } static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { if (ctx->head == NULL || ctx->head->field == &ctx->root) { const char* expected; const char* quote; if (ctx->head == NULL) { expected = "end"; quote = ""; } else { expected = ctx->head->field->type->name; quote = "'"; } PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch, expected %s%s%s but got %s", quote, expected, quote, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); } else { __Pyx_StructField* field = ctx->head->field; __Pyx_StructField* parent = (ctx->head - 1)->field; PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), parent->type->name, field->name); } } static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { char group; size_t size, offset, arraysize = 1; if (ctx->enc_type == 0) return 0; if (ctx->head->field->type->arraysize[0]) { int i, ndim = 0; if (ctx->enc_type == 's' || ctx->enc_type == 'p') { ctx->is_valid_array = ctx->head->field->type->ndim == 1; ndim = 1; if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { PyErr_Format(PyExc_ValueError, "Expected a dimension of size %zu, got %zu", ctx->head->field->type->arraysize[0], ctx->enc_count); return -1; } } if (!ctx->is_valid_array) { PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", ctx->head->field->type->ndim, ndim); return -1; } for (i = 0; i < ctx->head->field->type->ndim; i++) { arraysize *= ctx->head->field->type->arraysize[i]; } ctx->is_valid_array = 0; ctx->enc_count = 1; } group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); do { __Pyx_StructField* field = ctx->head->field; __Pyx_TypeInfo* type = field->type; if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); } else { size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); } if (ctx->enc_packmode == '@') { size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); size_t align_mod_offset; if (align_at == 0) return -1; align_mod_offset = ctx->fmt_offset % align_at; if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; if (ctx->struct_alignment == 0) ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, ctx->is_complex); } if (type->size != size || type->typegroup != group) { if (type->typegroup == 'C' && type->fields != NULL) { size_t parent_offset = ctx->head->parent_offset + field->offset; ++ctx->head; ctx->head->field = type->fields; ctx->head->parent_offset = parent_offset; continue; } if ((type->typegroup == 'H' || group == 'H') && type->size == size) { } else { __Pyx_BufFmt_RaiseExpected(ctx); return -1; } } offset = ctx->head->parent_offset + field->offset; if (ctx->fmt_offset != offset) { PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); return -1; } ctx->fmt_offset += size; if (arraysize) ctx->fmt_offset += (arraysize - 1) * size; --ctx->enc_count; while (1) { if (field == &ctx->root) { ctx->head = NULL; if (ctx->enc_count != 0) { __Pyx_BufFmt_RaiseExpected(ctx); return -1; } break; } ctx->head->field = ++field; if (field->type == NULL) { --ctx->head; field = ctx->head->field; continue; } else if (field->type->typegroup == 'S') { size_t parent_offset = ctx->head->parent_offset + field->offset; if (field->type->fields->type == NULL) continue; field = field->type->fields; ++ctx->head; ctx->head->field = field; ctx->head->parent_offset = parent_offset; break; } else { break; } } } while (ctx->enc_count); ctx->enc_type = 0; ctx->is_complex = 0; return 0; } static CYTHON_INLINE PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; int i = 0, number; int ndim = ctx->head->field->type->ndim; ; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, "Cannot handle repeated arrays in format string"); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; default: break; } number = __Pyx_BufFmt_ExpectNumber(&ts); if (number == -1) return NULL; if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) return PyErr_Format(PyExc_ValueError, "Expected a dimension of size %zu, got %d", ctx->head->field->type->arraysize[i], number); if (*ts != ',' && *ts != ')') return PyErr_Format(PyExc_ValueError, "Expected a comma in format string, got '%c'", *ts); if (*ts == ',') ts++; i++; } if (i != ndim) return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", ctx->head->field->type->ndim, i); if (!*ts) { PyErr_SetString(PyExc_ValueError, "Unexpected end of format string, expected ')'"); return NULL; } ctx->is_valid_array = 1; ctx->new_count = 1; *tsp = ++ts; return Py_None; } static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { int got_Z = 0; while (1) { switch(*ts) { case 0: if (ctx->enc_type != 0 && ctx->head == NULL) { __Pyx_BufFmt_RaiseExpected(ctx); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; if (ctx->head != NULL) { __Pyx_BufFmt_RaiseExpected(ctx); return NULL; } return ts; case ' ': case '\r': case '\n': ++ts; break; case '<': if (!__Pyx_IsLittleEndian()) { PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); return NULL; } ctx->new_packmode = '='; ++ts; break; case '>': case '!': if (__Pyx_IsLittleEndian()) { PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); return NULL; } ctx->new_packmode = '='; ++ts; break; case '=': case '@': case '^': ctx->new_packmode = *ts++; break; case 'T': { const char* ts_after_sub; size_t i, struct_count = ctx->new_count; size_t struct_alignment = ctx->struct_alignment; ctx->new_count = 1; ++ts; if (*ts != '{') { PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_type = 0; ctx->enc_count = 0; ctx->struct_alignment = 0; ++ts; ts_after_sub = ts; for (i = 0; i != struct_count; ++i) { ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); if (!ts_after_sub) return NULL; } ts = ts_after_sub; if (struct_alignment) ctx->struct_alignment = struct_alignment; } break; case '}': { size_t alignment = ctx->struct_alignment; ++ts; if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_type = 0; if (alignment && ctx->fmt_offset % alignment) { ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); } } return ts; case 'x': if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->fmt_offset += ctx->new_count; ctx->new_count = 1; ctx->enc_count = 0; ctx->enc_type = 0; ctx->enc_packmode = ctx->new_packmode; ++ts; break; case 'Z': got_Z = 1; ++ts; if (*ts != 'f' && *ts != 'd' && *ts != 'g') { __Pyx_BufFmt_RaiseUnexpectedChar('Z'); return NULL; } case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': if (ctx->enc_type == *ts && got_Z == ctx->is_complex && ctx->enc_packmode == ctx->new_packmode) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; ++ts; break; } case 's': if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_count = ctx->new_count; ctx->enc_packmode = ctx->new_packmode; ctx->enc_type = *ts; ctx->is_complex = got_Z; ++ts; ctx->new_count = 1; got_Z = 0; break; case ':': ++ts; while(*ts != ':') ++ts; ++ts; break; case '(': if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; break; default: { int number = __Pyx_BufFmt_ExpectNumber(&ts); if (number == -1) return NULL; ctx->new_count = (size_t)number; } } } } static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) { buf->buf = NULL; buf->obj = NULL; buf->strides = __Pyx_zeros; buf->shape = __Pyx_zeros; buf->suboffsets = __Pyx_minusones; } static CYTHON_INLINE int __Pyx_GetBufferAndValidate( Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack) { if (obj == Py_None || obj == NULL) { __Pyx_ZeroBuffer(buf); return 0; } buf->buf = NULL; if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail; if (buf->ndim != nd) { PyErr_Format(PyExc_ValueError, "Buffer has wrong number of dimensions (expected %d, got %d)", nd, buf->ndim); goto fail; } if (!cast) { __Pyx_BufFmt_Context ctx; __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } if ((unsigned)buf->itemsize != dtype->size) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); goto fail; } if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; return 0; fail:; __Pyx_ZeroBuffer(buf); return -1; } static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { if (info->buf == NULL) return; if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; __Pyx_ReleaseBuffer(info); } /* GetItemInt */ static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { PyObject *r; if (!j) return NULL; r = PyObject_GetItem(o, j); Py_DECREF(j); return r; } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o); if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) { PyObject *r = PyList_GET_ITEM(o, i); Py_INCREF(r); return r; } return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); #else return PySequence_GetItem(o, i); #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o); if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) { PyObject *r = PyTuple_GET_ITEM(o, i); Py_INCREF(r); return r; } return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); #else return PySequence_GetItem(o, i); #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (is_list || PyList_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) { PyObject *r = PyList_GET_ITEM(o, n); Py_INCREF(r); return r; } } else if (PyTuple_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) { PyObject *r = PyTuple_GET_ITEM(o, n); Py_INCREF(r); return r; } } else { PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; if (likely(m && m->sq_item)) { if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { Py_ssize_t l = m->sq_length(o); if (likely(l >= 0)) { i += l; } else { if (!PyErr_ExceptionMatches(PyExc_OverflowError)) return NULL; PyErr_Clear(); } } return m->sq_item(o, i); } } #else if (is_list || PySequence_Check(o)) { return PySequence_GetItem(o, i); } #endif return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); } /* ExtTypeTest */ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { if (unlikely(!type)) { PyErr_SetString(PyExc_SystemError, "Missing type object"); return 0; } if (likely(PyObject_TypeCheck(obj, type))) return 1; PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", Py_TYPE(obj)->tp_name, type->tp_name); return 0; } /* GetModuleGlobalName */ static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) { PyObject *result; #if CYTHON_COMPILING_IN_CPYTHON result = PyDict_GetItem(__pyx_d, name); if (likely(result)) { Py_INCREF(result); } else { #else result = PyObject_GetItem(__pyx_d, name); if (!result) { PyErr_Clear(); #endif result = __Pyx_GetBuiltinName(name); } return result; } /* BufferFallbackError */ static void __Pyx_RaiseBufferFallbackError(void) { PyErr_SetString(PyExc_ValueError, "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!"); } /* BytesEquals */ static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); #else if (s1 == s2) { return (equals == Py_EQ); } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { const char *ps1, *ps2; Py_ssize_t length = PyBytes_GET_SIZE(s1); if (length != PyBytes_GET_SIZE(s2)) return (equals == Py_NE); ps1 = PyBytes_AS_STRING(s1); ps2 = PyBytes_AS_STRING(s2); if (ps1[0] != ps2[0]) { return (equals == Py_NE); } else if (length == 1) { return (equals == Py_EQ); } else { int result = memcmp(ps1, ps2, (size_t)length); return (equals == Py_EQ) ? (result == 0) : (result != 0); } } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { return (equals == Py_NE); } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { return (equals == Py_NE); } else { int result; PyObject* py_result = PyObject_RichCompare(s1, s2, equals); if (!py_result) return -1; result = __Pyx_PyObject_IsTrue(py_result); Py_DECREF(py_result); return result; } #endif } /* UnicodeEquals */ static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); #else #if PY_MAJOR_VERSION < 3 PyObject* owned_ref = NULL; #endif int s1_is_unicode, s2_is_unicode; if (s1 == s2) { goto return_eq; } s1_is_unicode = PyUnicode_CheckExact(s1); s2_is_unicode = PyUnicode_CheckExact(s2); #if PY_MAJOR_VERSION < 3 if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { owned_ref = PyUnicode_FromObject(s2); if (unlikely(!owned_ref)) return -1; s2 = owned_ref; s2_is_unicode = 1; } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { owned_ref = PyUnicode_FromObject(s1); if (unlikely(!owned_ref)) return -1; s1 = owned_ref; s1_is_unicode = 1; } else if (((!s2_is_unicode) & (!s1_is_unicode))) { return __Pyx_PyBytes_Equals(s1, s2, equals); } #endif if (s1_is_unicode & s2_is_unicode) { Py_ssize_t length; int kind; void *data1, *data2; if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) return -1; length = __Pyx_PyUnicode_GET_LENGTH(s1); if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { goto return_ne; } kind = __Pyx_PyUnicode_KIND(s1); if (kind != __Pyx_PyUnicode_KIND(s2)) { goto return_ne; } data1 = __Pyx_PyUnicode_DATA(s1); data2 = __Pyx_PyUnicode_DATA(s2); if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { goto return_ne; } else if (length == 1) { goto return_eq; } else { int result = memcmp(data1, data2, (size_t)(length * kind)); #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_EQ) ? (result == 0) : (result != 0); } } else if ((s1 == Py_None) & s2_is_unicode) { goto return_ne; } else if ((s2 == Py_None) & s1_is_unicode) { goto return_ne; } else { int result; PyObject* py_result = PyObject_RichCompare(s1, s2, equals); if (!py_result) return -1; result = __Pyx_PyObject_IsTrue(py_result); Py_DECREF(py_result); return result; } return_eq: #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_EQ); return_ne: #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_NE); #endif } /* None */ static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) { Py_ssize_t q = a / b; Py_ssize_t r = a - q*b; q -= ((r != 0) & ((r ^ b) < 0)); return q; } /* GetAttr */ static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { #if CYTHON_COMPILING_IN_CPYTHON #if PY_MAJOR_VERSION >= 3 if (likely(PyUnicode_Check(n))) #else if (likely(PyString_Check(n))) #endif return __Pyx_PyObject_GetAttrStr(o, n); #endif return PyObject_GetAttr(o, n); } /* decode_c_string */ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( const char* cstring, Py_ssize_t start, Py_ssize_t stop, const char* encoding, const char* errors, PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { Py_ssize_t length; if (unlikely((start < 0) | (stop < 0))) { size_t slen = strlen(cstring); if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { PyErr_SetString(PyExc_OverflowError, "c-string too long to convert to Python"); return NULL; } length = (Py_ssize_t) slen; if (start < 0) { start += length; if (start < 0) start = 0; } if (stop < 0) stop += length; } length = stop - start; if (unlikely(length <= 0)) return PyUnicode_FromUnicode(NULL, 0); cstring += start; if (decode_func) { return decode_func(cstring, length, errors); } else { return PyUnicode_Decode(cstring, length, encoding, errors); } } /* SwapException */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = *type; tstate->exc_value = *value; tstate->exc_traceback = *tb; *type = tmp_type; *value = tmp_value; *tb = tmp_tb; } #else static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); PyErr_SetExcInfo(*type, *value, *tb); *type = tmp_type; *value = tmp_value; *tb = tmp_tb; } #endif /* PyIntBinop */ #if CYTHON_COMPILING_IN_CPYTHON static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) { #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(op1))) { const long b = intval; long x; long a = PyInt_AS_LONG(op1); x = (long)((unsigned long)a + b); if (likely((x^a) >= 0 || (x^b) >= 0)) return PyInt_FromLong(x); return PyLong_Type.tp_as_number->nb_add(op1, op2); } #endif #if CYTHON_USE_PYLONG_INTERNALS && PY_MAJOR_VERSION >= 3 if (likely(PyLong_CheckExact(op1))) { const long b = intval; long a, x; const PY_LONG_LONG llb = intval; PY_LONG_LONG lla, llx; const digit* digits = ((PyLongObject*)op1)->ob_digit; const Py_ssize_t size = Py_SIZE(op1); if (likely(__Pyx_sst_abs(size) <= 1)) { a = likely(size) ? digits[0] : 0; if (size == -1) a = -a; } else { switch (size) { case -2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case 2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case -3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case 3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case -4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case 4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } default: return PyLong_Type.tp_as_number->nb_add(op1, op2); } } x = a + b; return PyLong_FromLong(x); long_long: llx = lla + llb; return PyLong_FromLongLong(llx); } #endif if (PyFloat_CheckExact(op1)) { const long b = intval; double a = PyFloat_AS_DOUBLE(op1); double result; PyFPE_START_PROTECT("add", return NULL) result = ((double)a) + (double)b; PyFPE_END_PROTECT(result) return PyFloat_FromDouble(result); } return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); } #endif /* None */ static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); } /* None */ static CYTHON_INLINE long __Pyx_div_long(long a, long b) { long q = a / b; long r = a - q*b; q -= ((r != 0) & ((r ^ b) < 0)); return q; } /* WriteUnraisableException */ static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, int full_traceback, CYTHON_UNUSED int nogil) { PyObject *old_exc, *old_val, *old_tb; PyObject *ctx; __Pyx_PyThreadState_declare #ifdef WITH_THREAD PyGILState_STATE state; if (nogil) state = PyGILState_Ensure(); #ifdef _MSC_VER else state = (PyGILState_STATE)-1; #endif #endif __Pyx_PyThreadState_assign __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); if (full_traceback) { Py_XINCREF(old_exc); Py_XINCREF(old_val); Py_XINCREF(old_tb); __Pyx_ErrRestore(old_exc, old_val, old_tb); PyErr_PrintEx(1); } #if PY_MAJOR_VERSION < 3 ctx = PyString_FromString(name); #else ctx = PyUnicode_FromString(name); #endif __Pyx_ErrRestore(old_exc, old_val, old_tb); if (!ctx) { PyErr_WriteUnraisable(Py_None); } else { PyErr_WriteUnraisable(ctx); Py_DECREF(ctx); } #ifdef WITH_THREAD if (nogil) PyGILState_Release(state); #endif } /* SetVTable */ static int __Pyx_SetVtable(PyObject *dict, void *vtable) { #if PY_VERSION_HEX >= 0x02070000 PyObject *ob = PyCapsule_New(vtable, 0, 0); #else PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); #endif if (!ob) goto bad; if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) goto bad; Py_DECREF(ob); return 0; bad: Py_XDECREF(ob); return -1; } /* FetchCommonType */ static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type) { PyObject* fake_module; PyTypeObject* cached_type = NULL; fake_module = PyImport_AddModule((char*) "_cython_" CYTHON_ABI); if (!fake_module) return NULL; Py_INCREF(fake_module); cached_type = (PyTypeObject*) PyObject_GetAttrString(fake_module, type->tp_name); if (cached_type) { if (!PyType_Check((PyObject*)cached_type)) { PyErr_Format(PyExc_TypeError, "Shared Cython type %.200s is not a type object", type->tp_name); goto bad; } if (cached_type->tp_basicsize != type->tp_basicsize) { PyErr_Format(PyExc_TypeError, "Shared Cython type %.200s has the wrong size, try recompiling", type->tp_name); goto bad; } } else { if (!PyErr_ExceptionMatches(PyExc_AttributeError)) goto bad; PyErr_Clear(); if (PyType_Ready(type) < 0) goto bad; if (PyObject_SetAttrString(fake_module, type->tp_name, (PyObject*) type) < 0) goto bad; Py_INCREF(type); cached_type = type; } done: Py_DECREF(fake_module); return cached_type; bad: Py_XDECREF(cached_type); cached_type = NULL; goto done; } /* CythonFunction */ static PyObject * __Pyx_CyFunction_get_doc(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *closure) { if (unlikely(op->func_doc == NULL)) { if (op->func.m_ml->ml_doc) { #if PY_MAJOR_VERSION >= 3 op->func_doc = PyUnicode_FromString(op->func.m_ml->ml_doc); #else op->func_doc = PyString_FromString(op->func.m_ml->ml_doc); #endif if (unlikely(op->func_doc == NULL)) return NULL; } else { Py_INCREF(Py_None); return Py_None; } } Py_INCREF(op->func_doc); return op->func_doc; } static int __Pyx_CyFunction_set_doc(__pyx_CyFunctionObject *op, PyObject *value) { PyObject *tmp = op->func_doc; if (value == NULL) { value = Py_None; } Py_INCREF(value); op->func_doc = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_name(__pyx_CyFunctionObject *op) { if (unlikely(op->func_name == NULL)) { #if PY_MAJOR_VERSION >= 3 op->func_name = PyUnicode_InternFromString(op->func.m_ml->ml_name); #else op->func_name = PyString_InternFromString(op->func.m_ml->ml_name); #endif if (unlikely(op->func_name == NULL)) return NULL; } Py_INCREF(op->func_name); return op->func_name; } static int __Pyx_CyFunction_set_name(__pyx_CyFunctionObject *op, PyObject *value) { PyObject *tmp; #if PY_MAJOR_VERSION >= 3 if (unlikely(value == NULL || !PyUnicode_Check(value))) { #else if (unlikely(value == NULL || !PyString_Check(value))) { #endif PyErr_SetString(PyExc_TypeError, "__name__ must be set to a string object"); return -1; } tmp = op->func_name; Py_INCREF(value); op->func_name = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_qualname(__pyx_CyFunctionObject *op) { Py_INCREF(op->func_qualname); return op->func_qualname; } static int __Pyx_CyFunction_set_qualname(__pyx_CyFunctionObject *op, PyObject *value) { PyObject *tmp; #if PY_MAJOR_VERSION >= 3 if (unlikely(value == NULL || !PyUnicode_Check(value))) { #else if (unlikely(value == NULL || !PyString_Check(value))) { #endif PyErr_SetString(PyExc_TypeError, "__qualname__ must be set to a string object"); return -1; } tmp = op->func_qualname; Py_INCREF(value); op->func_qualname = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_self(__pyx_CyFunctionObject *m, CYTHON_UNUSED void *closure) { PyObject *self; self = m->func_closure; if (self == NULL) self = Py_None; Py_INCREF(self); return self; } static PyObject * __Pyx_CyFunction_get_dict(__pyx_CyFunctionObject *op) { if (unlikely(op->func_dict == NULL)) { op->func_dict = PyDict_New(); if (unlikely(op->func_dict == NULL)) return NULL; } Py_INCREF(op->func_dict); return op->func_dict; } static int __Pyx_CyFunction_set_dict(__pyx_CyFunctionObject *op, PyObject *value) { PyObject *tmp; if (unlikely(value == NULL)) { PyErr_SetString(PyExc_TypeError, "function's dictionary may not be deleted"); return -1; } if (unlikely(!PyDict_Check(value))) { PyErr_SetString(PyExc_TypeError, "setting function's dictionary to a non-dict"); return -1; } tmp = op->func_dict; Py_INCREF(value); op->func_dict = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_globals(__pyx_CyFunctionObject *op) { Py_INCREF(op->func_globals); return op->func_globals; } static PyObject * __Pyx_CyFunction_get_closure(CYTHON_UNUSED __pyx_CyFunctionObject *op) { Py_INCREF(Py_None); return Py_None; } static PyObject * __Pyx_CyFunction_get_code(__pyx_CyFunctionObject *op) { PyObject* result = (op->func_code) ? op->func_code : Py_None; Py_INCREF(result); return result; } static int __Pyx_CyFunction_init_defaults(__pyx_CyFunctionObject *op) { int result = 0; PyObject *res = op->defaults_getter((PyObject *) op); if (unlikely(!res)) return -1; #if CYTHON_COMPILING_IN_CPYTHON op->defaults_tuple = PyTuple_GET_ITEM(res, 0); Py_INCREF(op->defaults_tuple); op->defaults_kwdict = PyTuple_GET_ITEM(res, 1); Py_INCREF(op->defaults_kwdict); #else op->defaults_tuple = PySequence_ITEM(res, 0); if (unlikely(!op->defaults_tuple)) result = -1; else { op->defaults_kwdict = PySequence_ITEM(res, 1); if (unlikely(!op->defaults_kwdict)) result = -1; } #endif Py_DECREF(res); return result; } static int __Pyx_CyFunction_set_defaults(__pyx_CyFunctionObject *op, PyObject* value) { PyObject* tmp; if (!value) { value = Py_None; } else if (value != Py_None && !PyTuple_Check(value)) { PyErr_SetString(PyExc_TypeError, "__defaults__ must be set to a tuple object"); return -1; } Py_INCREF(value); tmp = op->defaults_tuple; op->defaults_tuple = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_defaults(__pyx_CyFunctionObject *op) { PyObject* result = op->defaults_tuple; if (unlikely(!result)) { if (op->defaults_getter) { if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL; result = op->defaults_tuple; } else { result = Py_None; } } Py_INCREF(result); return result; } static int __Pyx_CyFunction_set_kwdefaults(__pyx_CyFunctionObject *op, PyObject* value) { PyObject* tmp; if (!value) { value = Py_None; } else if (value != Py_None && !PyDict_Check(value)) { PyErr_SetString(PyExc_TypeError, "__kwdefaults__ must be set to a dict object"); return -1; } Py_INCREF(value); tmp = op->defaults_kwdict; op->defaults_kwdict = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_kwdefaults(__pyx_CyFunctionObject *op) { PyObject* result = op->defaults_kwdict; if (unlikely(!result)) { if (op->defaults_getter) { if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL; result = op->defaults_kwdict; } else { result = Py_None; } } Py_INCREF(result); return result; } static int __Pyx_CyFunction_set_annotations(__pyx_CyFunctionObject *op, PyObject* value) { PyObject* tmp; if (!value || value == Py_None) { value = NULL; } else if (!PyDict_Check(value)) { PyErr_SetString(PyExc_TypeError, "__annotations__ must be set to a dict object"); return -1; } Py_XINCREF(value); tmp = op->func_annotations; op->func_annotations = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_annotations(__pyx_CyFunctionObject *op) { PyObject* result = op->func_annotations; if (unlikely(!result)) { result = PyDict_New(); if (unlikely(!result)) return NULL; op->func_annotations = result; } Py_INCREF(result); return result; } static PyGetSetDef __pyx_CyFunction_getsets[] = { {(char *) "func_doc", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0}, {(char *) "__doc__", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0}, {(char *) "func_name", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0}, {(char *) "__name__", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0}, {(char *) "__qualname__", (getter)__Pyx_CyFunction_get_qualname, (setter)__Pyx_CyFunction_set_qualname, 0, 0}, {(char *) "__self__", (getter)__Pyx_CyFunction_get_self, 0, 0, 0}, {(char *) "func_dict", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0}, {(char *) "__dict__", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0}, {(char *) "func_globals", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0}, {(char *) "__globals__", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0}, {(char *) "func_closure", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0}, {(char *) "__closure__", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0}, {(char *) "func_code", (getter)__Pyx_CyFunction_get_code, 0, 0, 0}, {(char *) "__code__", (getter)__Pyx_CyFunction_get_code, 0, 0, 0}, {(char *) "func_defaults", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0}, {(char *) "__defaults__", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0}, {(char *) "__kwdefaults__", (getter)__Pyx_CyFunction_get_kwdefaults, (setter)__Pyx_CyFunction_set_kwdefaults, 0, 0}, {(char *) "__annotations__", (getter)__Pyx_CyFunction_get_annotations, (setter)__Pyx_CyFunction_set_annotations, 0, 0}, {0, 0, 0, 0, 0} }; static PyMemberDef __pyx_CyFunction_members[] = { {(char *) "__module__", T_OBJECT, offsetof(__pyx_CyFunctionObject, func.m_module), PY_WRITE_RESTRICTED, 0}, {0, 0, 0, 0, 0} }; static PyObject * __Pyx_CyFunction_reduce(__pyx_CyFunctionObject *m, CYTHON_UNUSED PyObject *args) { #if PY_MAJOR_VERSION >= 3 return PyUnicode_FromString(m->func.m_ml->ml_name); #else return PyString_FromString(m->func.m_ml->ml_name); #endif } static PyMethodDef __pyx_CyFunction_methods[] = { {"__reduce__", (PyCFunction)__Pyx_CyFunction_reduce, METH_VARARGS, 0}, {0, 0, 0, 0} }; #if PY_VERSION_HEX < 0x030500A0 #define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func_weakreflist) #else #define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func.m_weakreflist) #endif static PyObject *__Pyx_CyFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags, PyObject* qualname, PyObject *closure, PyObject *module, PyObject* globals, PyObject* code) { __pyx_CyFunctionObject *op = PyObject_GC_New(__pyx_CyFunctionObject, type); if (op == NULL) return NULL; op->flags = flags; __Pyx_CyFunction_weakreflist(op) = NULL; op->func.m_ml = ml; op->func.m_self = (PyObject *) op; Py_XINCREF(closure); op->func_closure = closure; Py_XINCREF(module); op->func.m_module = module; op->func_dict = NULL; op->func_name = NULL; Py_INCREF(qualname); op->func_qualname = qualname; op->func_doc = NULL; op->func_classobj = NULL; op->func_globals = globals; Py_INCREF(op->func_globals); Py_XINCREF(code); op->func_code = code; op->defaults_pyobjects = 0; op->defaults = NULL; op->defaults_tuple = NULL; op->defaults_kwdict = NULL; op->defaults_getter = NULL; op->func_annotations = NULL; PyObject_GC_Track(op); return (PyObject *) op; } static int __Pyx_CyFunction_clear(__pyx_CyFunctionObject *m) { Py_CLEAR(m->func_closure); Py_CLEAR(m->func.m_module); Py_CLEAR(m->func_dict); Py_CLEAR(m->func_name); Py_CLEAR(m->func_qualname); Py_CLEAR(m->func_doc); Py_CLEAR(m->func_globals); Py_CLEAR(m->func_code); Py_CLEAR(m->func_classobj); Py_CLEAR(m->defaults_tuple); Py_CLEAR(m->defaults_kwdict); Py_CLEAR(m->func_annotations); if (m->defaults) { PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m); int i; for (i = 0; i < m->defaults_pyobjects; i++) Py_XDECREF(pydefaults[i]); PyObject_Free(m->defaults); m->defaults = NULL; } return 0; } static void __Pyx_CyFunction_dealloc(__pyx_CyFunctionObject *m) { PyObject_GC_UnTrack(m); if (__Pyx_CyFunction_weakreflist(m) != NULL) PyObject_ClearWeakRefs((PyObject *) m); __Pyx_CyFunction_clear(m); PyObject_GC_Del(m); } static int __Pyx_CyFunction_traverse(__pyx_CyFunctionObject *m, visitproc visit, void *arg) { Py_VISIT(m->func_closure); Py_VISIT(m->func.m_module); Py_VISIT(m->func_dict); Py_VISIT(m->func_name); Py_VISIT(m->func_qualname); Py_VISIT(m->func_doc); Py_VISIT(m->func_globals); Py_VISIT(m->func_code); Py_VISIT(m->func_classobj); Py_VISIT(m->defaults_tuple); Py_VISIT(m->defaults_kwdict); if (m->defaults) { PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m); int i; for (i = 0; i < m->defaults_pyobjects; i++) Py_VISIT(pydefaults[i]); } return 0; } static PyObject *__Pyx_CyFunction_descr_get(PyObject *func, PyObject *obj, PyObject *type) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; if (m->flags & __Pyx_CYFUNCTION_STATICMETHOD) { Py_INCREF(func); return func; } if (m->flags & __Pyx_CYFUNCTION_CLASSMETHOD) { if (type == NULL) type = (PyObject *)(Py_TYPE(obj)); return __Pyx_PyMethod_New(func, type, (PyObject *)(Py_TYPE(type))); } if (obj == Py_None) obj = NULL; return __Pyx_PyMethod_New(func, obj, type); } static PyObject* __Pyx_CyFunction_repr(__pyx_CyFunctionObject *op) { #if PY_MAJOR_VERSION >= 3 return PyUnicode_FromFormat("", op->func_qualname, (void *)op); #else return PyString_FromFormat("", PyString_AsString(op->func_qualname), (void *)op); #endif } #if CYTHON_COMPILING_IN_PYPY static PyObject * __Pyx_CyFunction_Call(PyObject *func, PyObject *arg, PyObject *kw) { PyCFunctionObject* f = (PyCFunctionObject*)func; PyCFunction meth = f->m_ml->ml_meth; PyObject *self = f->m_self; Py_ssize_t size; switch (f->m_ml->ml_flags & (METH_VARARGS | METH_KEYWORDS | METH_NOARGS | METH_O)) { case METH_VARARGS: if (likely(kw == NULL || PyDict_Size(kw) == 0)) return (*meth)(self, arg); break; case METH_VARARGS | METH_KEYWORDS: return (*(PyCFunctionWithKeywords)meth)(self, arg, kw); case METH_NOARGS: if (likely(kw == NULL || PyDict_Size(kw) == 0)) { size = PyTuple_GET_SIZE(arg); if (likely(size == 0)) return (*meth)(self, NULL); PyErr_Format(PyExc_TypeError, "%.200s() takes no arguments (%" CYTHON_FORMAT_SSIZE_T "d given)", f->m_ml->ml_name, size); return NULL; } break; case METH_O: if (likely(kw == NULL || PyDict_Size(kw) == 0)) { size = PyTuple_GET_SIZE(arg); if (likely(size == 1)) { PyObject *result, *arg0 = PySequence_ITEM(arg, 0); if (unlikely(!arg0)) return NULL; result = (*meth)(self, arg0); Py_DECREF(arg0); return result; } PyErr_Format(PyExc_TypeError, "%.200s() takes exactly one argument (%" CYTHON_FORMAT_SSIZE_T "d given)", f->m_ml->ml_name, size); return NULL; } break; default: PyErr_SetString(PyExc_SystemError, "Bad call flags in " "__Pyx_CyFunction_Call. METH_OLDARGS is no " "longer supported!"); return NULL; } PyErr_Format(PyExc_TypeError, "%.200s() takes no keyword arguments", f->m_ml->ml_name); return NULL; } #else static PyObject * __Pyx_CyFunction_Call(PyObject *func, PyObject *arg, PyObject *kw) { return PyCFunction_Call(func, arg, kw); } #endif static PyTypeObject __pyx_CyFunctionType_type = { PyVarObject_HEAD_INIT(0, 0) "cython_function_or_method", sizeof(__pyx_CyFunctionObject), 0, (destructor) __Pyx_CyFunction_dealloc, 0, 0, 0, #if PY_MAJOR_VERSION < 3 0, #else 0, #endif (reprfunc) __Pyx_CyFunction_repr, 0, 0, 0, 0, __Pyx_CyFunction_Call, 0, 0, 0, 0, Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, 0, (traverseproc) __Pyx_CyFunction_traverse, (inquiry) __Pyx_CyFunction_clear, 0, #if PY_VERSION_HEX < 0x030500A0 offsetof(__pyx_CyFunctionObject, func_weakreflist), #else offsetof(PyCFunctionObject, m_weakreflist), #endif 0, 0, __pyx_CyFunction_methods, __pyx_CyFunction_members, __pyx_CyFunction_getsets, 0, 0, __Pyx_CyFunction_descr_get, 0, offsetof(__pyx_CyFunctionObject, func_dict), 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, #if PY_VERSION_HEX >= 0x030400a1 0, #endif }; static int __pyx_CyFunction_init(void) { #if !CYTHON_COMPILING_IN_PYPY __pyx_CyFunctionType_type.tp_call = PyCFunction_Call; #endif __pyx_CyFunctionType = __Pyx_FetchCommonType(&__pyx_CyFunctionType_type); if (__pyx_CyFunctionType == NULL) { return -1; } return 0; } static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *func, size_t size, int pyobjects) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; m->defaults = PyObject_Malloc(size); if (!m->defaults) return PyErr_NoMemory(); memset(m->defaults, 0, size); m->defaults_pyobjects = pyobjects; return m->defaults; } static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *func, PyObject *tuple) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; m->defaults_tuple = tuple; Py_INCREF(tuple); } static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *func, PyObject *dict) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; m->defaults_kwdict = dict; Py_INCREF(dict); } static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *func, PyObject *dict) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; m->func_annotations = dict; Py_INCREF(dict); } /* FusedFunction */ static PyObject * __pyx_FusedFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags, PyObject *qualname, PyObject *self, PyObject *module, PyObject *globals, PyObject *code) { __pyx_FusedFunctionObject *fusedfunc = (__pyx_FusedFunctionObject *) __Pyx_CyFunction_New(type, ml, flags, qualname, self, module, globals, code); if (!fusedfunc) return NULL; fusedfunc->__signatures__ = NULL; fusedfunc->type = NULL; fusedfunc->self = NULL; return (PyObject *) fusedfunc; } static void __pyx_FusedFunction_dealloc(__pyx_FusedFunctionObject *self) { __pyx_FusedFunction_clear(self); __pyx_FusedFunctionType->tp_free((PyObject *) self); } static int __pyx_FusedFunction_traverse(__pyx_FusedFunctionObject *self, visitproc visit, void *arg) { Py_VISIT(self->self); Py_VISIT(self->type); Py_VISIT(self->__signatures__); return __Pyx_CyFunction_traverse((__pyx_CyFunctionObject *) self, visit, arg); } static int __pyx_FusedFunction_clear(__pyx_FusedFunctionObject *self) { Py_CLEAR(self->self); Py_CLEAR(self->type); Py_CLEAR(self->__signatures__); return __Pyx_CyFunction_clear((__pyx_CyFunctionObject *) self); } static PyObject * __pyx_FusedFunction_descr_get(PyObject *self, PyObject *obj, PyObject *type) { __pyx_FusedFunctionObject *func, *meth; func = (__pyx_FusedFunctionObject *) self; if (func->self || func->func.flags & __Pyx_CYFUNCTION_STATICMETHOD) { Py_INCREF(self); return self; } if (obj == Py_None) obj = NULL; meth = (__pyx_FusedFunctionObject *) __pyx_FusedFunction_NewEx( ((PyCFunctionObject *) func)->m_ml, ((__pyx_CyFunctionObject *) func)->flags, ((__pyx_CyFunctionObject *) func)->func_qualname, ((__pyx_CyFunctionObject *) func)->func_closure, ((PyCFunctionObject *) func)->m_module, ((__pyx_CyFunctionObject *) func)->func_globals, ((__pyx_CyFunctionObject *) func)->func_code); if (!meth) return NULL; Py_XINCREF(func->func.func_classobj); meth->func.func_classobj = func->func.func_classobj; Py_XINCREF(func->__signatures__); meth->__signatures__ = func->__signatures__; Py_XINCREF(type); meth->type = type; Py_XINCREF(func->func.defaults_tuple); meth->func.defaults_tuple = func->func.defaults_tuple; if (func->func.flags & __Pyx_CYFUNCTION_CLASSMETHOD) obj = type; Py_XINCREF(obj); meth->self = obj; return (PyObject *) meth; } static PyObject * _obj_to_str(PyObject *obj) { if (PyType_Check(obj)) return PyObject_GetAttr(obj, __pyx_n_s_name_2); else return PyObject_Str(obj); } static PyObject * __pyx_FusedFunction_getitem(__pyx_FusedFunctionObject *self, PyObject *idx) { PyObject *signature = NULL; PyObject *unbound_result_func; PyObject *result_func = NULL; if (self->__signatures__ == NULL) { PyErr_SetString(PyExc_TypeError, "Function is not fused"); return NULL; } if (PyTuple_Check(idx)) { PyObject *list = PyList_New(0); Py_ssize_t n = PyTuple_GET_SIZE(idx); PyObject *string = NULL; PyObject *sep = NULL; int i; if (!list) return NULL; for (i = 0; i < n; i++) { #if CYTHON_COMPILING_IN_CPYTHON PyObject *item = PyTuple_GET_ITEM(idx, i); #else PyObject *item = PySequence_ITEM(idx, i); #endif string = _obj_to_str(item); #if !CYTHON_COMPILING_IN_CPYTHON Py_DECREF(item); #endif if (!string || PyList_Append(list, string) < 0) goto __pyx_err; Py_DECREF(string); } sep = PyUnicode_FromString("|"); if (sep) signature = PyUnicode_Join(sep, list); __pyx_err: ; Py_DECREF(list); Py_XDECREF(sep); } else { signature = _obj_to_str(idx); } if (!signature) return NULL; unbound_result_func = PyObject_GetItem(self->__signatures__, signature); if (unbound_result_func) { if (self->self || self->type) { __pyx_FusedFunctionObject *unbound = (__pyx_FusedFunctionObject *) unbound_result_func; Py_CLEAR(unbound->func.func_classobj); Py_XINCREF(self->func.func_classobj); unbound->func.func_classobj = self->func.func_classobj; result_func = __pyx_FusedFunction_descr_get(unbound_result_func, self->self, self->type); } else { result_func = unbound_result_func; Py_INCREF(result_func); } } Py_DECREF(signature); Py_XDECREF(unbound_result_func); return result_func; } static PyObject * __pyx_FusedFunction_callfunction(PyObject *func, PyObject *args, PyObject *kw) { __pyx_CyFunctionObject *cyfunc = (__pyx_CyFunctionObject *) func; PyObject *result; int static_specialized = (cyfunc->flags & __Pyx_CYFUNCTION_STATICMETHOD && !((__pyx_FusedFunctionObject *) func)->__signatures__); if (cyfunc->flags & __Pyx_CYFUNCTION_CCLASS && !static_specialized) { Py_ssize_t argc; PyObject *new_args; PyObject *self; PyObject *m_self; argc = PyTuple_GET_SIZE(args); new_args = PyTuple_GetSlice(args, 1, argc); if (!new_args) return NULL; self = PyTuple_GetItem(args, 0); if (!self) return NULL; m_self = cyfunc->func.m_self; cyfunc->func.m_self = self; result = __Pyx_CyFunction_Call(func, new_args, kw); cyfunc->func.m_self = m_self; Py_DECREF(new_args); } else { result = __Pyx_CyFunction_Call(func, args, kw); } return result; } static PyObject * __pyx_FusedFunction_call(PyObject *func, PyObject *args, PyObject *kw) { __pyx_FusedFunctionObject *binding_func = (__pyx_FusedFunctionObject *) func; Py_ssize_t argc = PyTuple_GET_SIZE(args); PyObject *new_args = NULL; __pyx_FusedFunctionObject *new_func = NULL; PyObject *result = NULL; PyObject *self = NULL; int is_staticmethod = binding_func->func.flags & __Pyx_CYFUNCTION_STATICMETHOD; int is_classmethod = binding_func->func.flags & __Pyx_CYFUNCTION_CLASSMETHOD; if (binding_func->self) { Py_ssize_t i; new_args = PyTuple_New(argc + 1); if (!new_args) return NULL; self = binding_func->self; #if !CYTHON_COMPILING_IN_CPYTHON Py_INCREF(self); #endif Py_INCREF(self); PyTuple_SET_ITEM(new_args, 0, self); for (i = 0; i < argc; i++) { #if CYTHON_COMPILING_IN_CPYTHON PyObject *item = PyTuple_GET_ITEM(args, i); Py_INCREF(item); #else PyObject *item = PySequence_ITEM(args, i); if (unlikely(!item)) goto bad; #endif PyTuple_SET_ITEM(new_args, i + 1, item); } args = new_args; } else if (binding_func->type) { if (argc < 1) { PyErr_SetString(PyExc_TypeError, "Need at least one argument, 0 given."); return NULL; } #if CYTHON_COMPILING_IN_CPYTHON self = PyTuple_GET_ITEM(args, 0); #else self = PySequence_ITEM(args, 0); if (unlikely(!self)) return NULL; #endif } if (self && !is_classmethod && !is_staticmethod) { int is_instance = PyObject_IsInstance(self, binding_func->type); if (unlikely(!is_instance)) { PyErr_Format(PyExc_TypeError, "First argument should be of type %.200s, got %.200s.", ((PyTypeObject *) binding_func->type)->tp_name, self->ob_type->tp_name); goto bad; } else if (unlikely(is_instance == -1)) { goto bad; } } #if !CYTHON_COMPILING_IN_CPYTHON Py_XDECREF(self); self = NULL; #endif if (binding_func->__signatures__) { PyObject *tup = PyTuple_Pack(4, binding_func->__signatures__, args, kw == NULL ? Py_None : kw, binding_func->func.defaults_tuple); if (!tup) goto bad; new_func = (__pyx_FusedFunctionObject *) __pyx_FusedFunction_callfunction(func, tup, NULL); Py_DECREF(tup); if (!new_func) goto bad; Py_XINCREF(binding_func->func.func_classobj); Py_CLEAR(new_func->func.func_classobj); new_func->func.func_classobj = binding_func->func.func_classobj; func = (PyObject *) new_func; } result = __pyx_FusedFunction_callfunction(func, args, kw); bad: #if !CYTHON_COMPILING_IN_CPYTHON Py_XDECREF(self); #endif Py_XDECREF(new_args); Py_XDECREF((PyObject *) new_func); return result; } static PyMemberDef __pyx_FusedFunction_members[] = { {(char *) "__signatures__", T_OBJECT, offsetof(__pyx_FusedFunctionObject, __signatures__), READONLY, 0}, {0, 0, 0, 0, 0}, }; static PyMappingMethods __pyx_FusedFunction_mapping_methods = { 0, (binaryfunc) __pyx_FusedFunction_getitem, 0, }; static PyTypeObject __pyx_FusedFunctionType_type = { PyVarObject_HEAD_INIT(0, 0) "fused_cython_function", sizeof(__pyx_FusedFunctionObject), 0, (destructor) __pyx_FusedFunction_dealloc, 0, 0, 0, #if PY_MAJOR_VERSION < 3 0, #else 0, #endif 0, 0, 0, &__pyx_FusedFunction_mapping_methods, 0, (ternaryfunc) __pyx_FusedFunction_call, 0, 0, 0, 0, Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC | Py_TPFLAGS_BASETYPE, 0, (traverseproc) __pyx_FusedFunction_traverse, (inquiry) __pyx_FusedFunction_clear, 0, 0, 0, 0, 0, __pyx_FusedFunction_members, __pyx_CyFunction_getsets, &__pyx_CyFunctionType_type, 0, __pyx_FusedFunction_descr_get, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, #if PY_VERSION_HEX >= 0x030400a1 0, #endif }; static int __pyx_FusedFunction_init(void) { __pyx_FusedFunctionType = __Pyx_FetchCommonType(&__pyx_FusedFunctionType_type); if (__pyx_FusedFunctionType == NULL) { return -1; } return 0; } /* CodeObjectCache */ static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { int start = 0, mid = 0, end = count - 1; if (end >= 0 && code_line > entries[end].code_line) { return count; } while (start < end) { mid = start + (end - start) / 2; if (code_line < entries[mid].code_line) { end = mid; } else if (code_line > entries[mid].code_line) { start = mid + 1; } else { return mid; } } if (code_line <= entries[mid].code_line) { return mid; } else { return mid + 1; } } static PyCodeObject *__pyx_find_code_object(int code_line) { PyCodeObject* code_object; int pos; if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { return NULL; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { return NULL; } code_object = __pyx_code_cache.entries[pos].code_object; Py_INCREF(code_object); return code_object; } static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { int pos, i; __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; if (unlikely(!code_line)) { return; } if (unlikely(!entries)) { entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); if (likely(entries)) { __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = 64; __pyx_code_cache.count = 1; entries[0].code_line = code_line; entries[0].code_object = code_object; Py_INCREF(code_object); } return; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { PyCodeObject* tmp = entries[pos].code_object; entries[pos].code_object = code_object; Py_DECREF(tmp); return; } if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = new_max; } for (i=__pyx_code_cache.count; i>pos; i--) { entries[i] = entries[i-1]; } entries[pos].code_line = code_line; entries[pos].code_object = code_object; __pyx_code_cache.count++; Py_INCREF(code_object); } /* AddTraceback */ #include "compile.h" #include "frameobject.h" #include "traceback.h" static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyObject *py_srcfile = 0; PyObject *py_funcname = 0; #if PY_MAJOR_VERSION < 3 py_srcfile = PyString_FromString(filename); #else py_srcfile = PyUnicode_FromString(filename); #endif if (!py_srcfile) goto bad; if (c_line) { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); #else py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); #endif } else { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromString(funcname); #else py_funcname = PyUnicode_FromString(funcname); #endif } if (!py_funcname) goto bad; py_code = __Pyx_PyCode_New( 0, 0, 0, 0, 0, __pyx_empty_bytes, /*PyObject *code,*/ __pyx_empty_tuple, /*PyObject *consts,*/ __pyx_empty_tuple, /*PyObject *names,*/ __pyx_empty_tuple, /*PyObject *varnames,*/ __pyx_empty_tuple, /*PyObject *freevars,*/ __pyx_empty_tuple, /*PyObject *cellvars,*/ py_srcfile, /*PyObject *filename,*/ py_funcname, /*PyObject *name,*/ py_line, __pyx_empty_bytes /*PyObject *lnotab*/ ); Py_DECREF(py_srcfile); Py_DECREF(py_funcname); return py_code; bad: Py_XDECREF(py_srcfile); Py_XDECREF(py_funcname); return NULL; } static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyFrameObject *py_frame = 0; py_code = __pyx_find_code_object(c_line ? c_line : py_line); if (!py_code) { py_code = __Pyx_CreateCodeObjectForTraceback( funcname, c_line, py_line, filename); if (!py_code) goto bad; __pyx_insert_code_object(c_line ? c_line : py_line, py_code); } py_frame = PyFrame_New( PyThreadState_GET(), /*PyThreadState *tstate,*/ py_code, /*PyCodeObject *code,*/ __pyx_d, /*PyObject *globals,*/ 0 /*PyObject *locals*/ ); if (!py_frame) goto bad; py_frame->f_lineno = py_line; PyTraceBack_Here(py_frame); bad: Py_XDECREF(py_code); Py_XDECREF(py_frame); } #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); return -1; } static void __Pyx_ReleaseBuffer(Py_buffer *view) { PyObject *obj = view->obj; if (!obj) return; if (PyObject_CheckBuffer(obj)) { PyBuffer_Release(view); return; } if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) { __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); return; } Py_DECREF(obj); view->obj = NULL; } #endif /* MemviewSliceIsContig */ static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) { int i, index, step, start; Py_ssize_t itemsize = mvs.memview->view.itemsize; if (order == 'F') { step = 1; start = 0; } else { step = -1; start = ndim - 1; } for (i = 0; i < ndim; i++) { index = start + step * i; if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) return 0; itemsize *= mvs.shape[index]; } return 1; } /* OverlappingSlices */ static void __pyx_get_array_memory_extents(__Pyx_memviewslice *slice, void **out_start, void **out_end, int ndim, size_t itemsize) { char *start, *end; int i; start = end = slice->data; for (i = 0; i < ndim; i++) { Py_ssize_t stride = slice->strides[i]; Py_ssize_t extent = slice->shape[i]; if (extent == 0) { *out_start = *out_end = start; return; } else { if (stride > 0) end += stride * (extent - 1); else start += stride * (extent - 1); } } *out_start = start; *out_end = end + itemsize; } static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, __Pyx_memviewslice *slice2, int ndim, size_t itemsize) { void *start1, *end1, *start2, *end2; __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); return (start1 < end2) && (start2 < end1); } /* Capsule */ static CYTHON_INLINE PyObject * __pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) { PyObject *cobj; #if PY_VERSION_HEX >= 0x02070000 cobj = PyCapsule_New(p, sig, NULL); #else cobj = PyCObject_FromVoidPtr(p, NULL); #endif return cobj; } /* TypeInfoCompare */ static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) { int i; if (!a || !b) return 0; if (a == b) return 1; if (a->size != b->size || a->typegroup != b->typegroup || a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { if (a->typegroup == 'H' || b->typegroup == 'H') { return a->size == b->size; } else { return 0; } } if (a->ndim) { for (i = 0; i < a->ndim; i++) if (a->arraysize[i] != b->arraysize[i]) return 0; } if (a->typegroup == 'S') { if (a->flags != b->flags) return 0; if (a->fields || b->fields) { if (!(a->fields && b->fields)) return 0; for (i = 0; a->fields[i].type && b->fields[i].type; i++) { __Pyx_StructField *field_a = a->fields + i; __Pyx_StructField *field_b = b->fields + i; if (field_a->offset != field_b->offset || !__pyx_typeinfo_cmp(field_a->type, field_b->type)) return 0; } return !a->fields[i].type && !b->fields[i].type; } } return 1; } /* MemviewSliceValidateAndInit */ static int __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) { if (buf->shape[dim] <= 1) return 1; if (buf->strides) { if (spec & __Pyx_MEMVIEW_CONTIG) { if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { if (buf->strides[dim] != sizeof(void *)) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly contiguous " "in dimension %d.", dim); goto fail; } } else if (buf->strides[dim] != buf->itemsize) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); goto fail; } } if (spec & __Pyx_MEMVIEW_FOLLOW) { Py_ssize_t stride = buf->strides[dim]; if (stride < 0) stride = -stride; if (stride < buf->itemsize) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); goto fail; } } } else { if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not contiguous in " "dimension %d", dim); goto fail; } else if (spec & (__Pyx_MEMVIEW_PTR)) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not indirect in " "dimension %d", dim); goto fail; } else if (buf->suboffsets) { PyErr_SetString(PyExc_ValueError, "Buffer exposes suboffsets but no strides"); goto fail; } } return 1; fail: return 0; } static int __pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) { if (spec & __Pyx_MEMVIEW_DIRECT) { if (buf->suboffsets && buf->suboffsets[dim] >= 0) { PyErr_Format(PyExc_ValueError, "Buffer not compatible with direct access " "in dimension %d.", dim); goto fail; } } if (spec & __Pyx_MEMVIEW_PTR) { if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly accessible " "in dimension %d.", dim); goto fail; } } return 1; fail: return 0; } static int __pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) { int i; if (c_or_f_flag & __Pyx_IS_F_CONTIG) { Py_ssize_t stride = 1; for (i = 0; i < ndim; i++) { if (stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1) { PyErr_SetString(PyExc_ValueError, "Buffer not fortran contiguous."); goto fail; } stride = stride * buf->shape[i]; } } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { Py_ssize_t stride = 1; for (i = ndim - 1; i >- 1; i--) { if (stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1) { PyErr_SetString(PyExc_ValueError, "Buffer not C contiguous."); goto fail; } stride = stride * buf->shape[i]; } } return 1; fail: return 0; } static int __Pyx_ValidateAndInit_memviewslice( int *axes_specs, int c_or_f_flag, int buf_flags, int ndim, __Pyx_TypeInfo *dtype, __Pyx_BufFmt_StackElem stack[], __Pyx_memviewslice *memviewslice, PyObject *original_obj) { struct __pyx_memoryview_obj *memview, *new_memview; __Pyx_RefNannyDeclarations Py_buffer *buf; int i, spec = 0, retval = -1; __Pyx_BufFmt_Context ctx; int from_memoryview = __pyx_memoryview_check(original_obj); __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) original_obj)->typeinfo)) { memview = (struct __pyx_memoryview_obj *) original_obj; new_memview = NULL; } else { memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( original_obj, buf_flags, 0, dtype); new_memview = memview; if (unlikely(!memview)) goto fail; } buf = &memview->view; if (buf->ndim != ndim) { PyErr_Format(PyExc_ValueError, "Buffer has wrong number of dimensions (expected %d, got %d)", ndim, buf->ndim); goto fail; } if (new_memview) { __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } if ((unsigned) buf->itemsize != dtype->size) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", dtype->name, dtype->size, (dtype->size > 1) ? "s" : ""); goto fail; } for (i = 0; i < ndim; i++) { spec = axes_specs[i]; if (!__pyx_check_strides(buf, i, ndim, spec)) goto fail; if (!__pyx_check_suboffsets(buf, i, ndim, spec)) goto fail; } if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag)) goto fail; if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, new_memview != NULL) == -1)) { goto fail; } retval = 0; goto no_fail; fail: Py_XDECREF(new_memview); retval = -1; no_fail: __Pyx_RefNannyFinishContext(); return retval; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5numpy_float32_t(PyObject *obj) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS, 2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float32_t, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5numpy_float64_t(PyObject *obj) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS, 2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(long), little, !is_unsigned); } } /* CIntFromPyVerify */ #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) #define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) #define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ {\ func_type value = func_value;\ if (sizeof(target_type) < sizeof(func_type)) {\ if (unlikely(value != (func_type) (target_type) value)) {\ func_type zero = 0;\ if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ return (target_type) -1;\ if (is_unsigned && unlikely(value < zero))\ goto raise_neg_overflow;\ else\ goto raise_overflow;\ }\ }\ return (target_type) value;\ } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_int(unsigned int value) { const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(unsigned int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(unsigned int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); } else if (sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(unsigned int) <= sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(unsigned int) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(unsigned int), little, !is_unsigned); } } /* BytesContains */ static CYTHON_INLINE int __Pyx_BytesContains(PyObject* bytes, char character) { const Py_ssize_t length = PyBytes_GET_SIZE(bytes); char* char_start = PyBytes_AS_STRING(bytes); char* pos; for (pos=char_start; pos < char_start+length; pos++) { if (character == pos[0]) return 1; } return 0; } /* None */ #if CYTHON_CCOMPLEX #ifdef __cplusplus static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { return ::std::complex< float >(x, y); } #else static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { return x + y*(__pyx_t_float_complex)_Complex_I; } #endif #else static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { __pyx_t_float_complex z; z.real = x; z.imag = y; return z; } #endif /* None */ #if CYTHON_CCOMPLEX #else static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) { return (a.real == b.real) && (a.imag == b.imag); } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real + b.real; z.imag = a.imag + b.imag; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real - b.real; z.imag = a.imag - b.imag; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real * b.real - a.imag * b.imag; z.imag = a.real * b.imag + a.imag * b.real; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; float denom = b.real * b.real + b.imag * b.imag; z.real = (a.real * b.real + a.imag * b.imag) / denom; z.imag = (a.imag * b.real - a.real * b.imag) / denom; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) { __pyx_t_float_complex z; z.real = -a.real; z.imag = -a.imag; return z; } static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) { return (a.real == 0) && (a.imag == 0); } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) { __pyx_t_float_complex z; z.real = a.real; z.imag = -a.imag; return z; } #if 1 static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex z) { #if !defined(HAVE_HYPOT) || defined(_MSC_VER) return sqrtf(z.real*z.real + z.imag*z.imag); #else return hypotf(z.real, z.imag); #endif } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; float r, lnr, theta, z_r, z_theta; if (b.imag == 0 && b.real == (int)b.real) { if (b.real < 0) { float denom = a.real * a.real + a.imag * a.imag; a.real = a.real / denom; a.imag = -a.imag / denom; b.real = -b.real; } switch ((int)b.real) { case 0: z.real = 1; z.imag = 0; return z; case 1: return a; case 2: z = __Pyx_c_prodf(a, a); return __Pyx_c_prodf(a, a); case 3: z = __Pyx_c_prodf(a, a); return __Pyx_c_prodf(z, a); case 4: z = __Pyx_c_prodf(a, a); return __Pyx_c_prodf(z, z); } } if (a.imag == 0) { if (a.real == 0) { return a; } r = a.real; theta = 0; } else { r = __Pyx_c_absf(a); theta = atan2f(a.imag, a.real); } lnr = logf(r); z_r = expf(lnr * b.real - theta * b.imag); z_theta = theta * b.real + lnr * b.imag; z.real = z_r * cosf(z_theta); z.imag = z_r * sinf(z_theta); return z; } #endif #endif /* None */ #if CYTHON_CCOMPLEX #ifdef __cplusplus static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { return ::std::complex< double >(x, y); } #else static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { return x + y*(__pyx_t_double_complex)_Complex_I; } #endif #else static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { __pyx_t_double_complex z; z.real = x; z.imag = y; return z; } #endif /* None */ #if CYTHON_CCOMPLEX #else static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) { return (a.real == b.real) && (a.imag == b.imag); } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real + b.real; z.imag = a.imag + b.imag; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real - b.real; z.imag = a.imag - b.imag; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real * b.real - a.imag * b.imag; z.imag = a.real * b.imag + a.imag * b.real; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; double denom = b.real * b.real + b.imag * b.imag; z.real = (a.real * b.real + a.imag * b.imag) / denom; z.imag = (a.imag * b.real - a.real * b.imag) / denom; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) { __pyx_t_double_complex z; z.real = -a.real; z.imag = -a.imag; return z; } static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) { return (a.real == 0) && (a.imag == 0); } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) { __pyx_t_double_complex z; z.real = a.real; z.imag = -a.imag; return z; } #if 1 static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex z) { #if !defined(HAVE_HYPOT) || defined(_MSC_VER) return sqrt(z.real*z.real + z.imag*z.imag); #else return hypot(z.real, z.imag); #endif } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; double r, lnr, theta, z_r, z_theta; if (b.imag == 0 && b.real == (int)b.real) { if (b.real < 0) { double denom = a.real * a.real + a.imag * a.imag; a.real = a.real / denom; a.imag = -a.imag / denom; b.real = -b.real; } switch ((int)b.real) { case 0: z.real = 1; z.imag = 0; return z; case 1: return a; case 2: z = __Pyx_c_prod(a, a); return __Pyx_c_prod(a, a); case 3: z = __Pyx_c_prod(a, a); return __Pyx_c_prod(z, a); case 4: z = __Pyx_c_prod(a, a); return __Pyx_c_prod(z, z); } } if (a.imag == 0) { if (a.real == 0) { return a; } r = a.real; theta = 0; } else { r = __Pyx_c_abs(a); theta = atan2(a.imag, a.real); } lnr = log(r); z_r = exp(lnr * b.real - theta * b.imag); z_theta = theta * b.real + lnr * b.imag; z.real = z_r * cos(z_theta); z.imag = z_r * sin(z_theta); return z; } #endif #endif /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(int) <= sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(int), little, !is_unsigned); } } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { const enum NPY_TYPES neg_one = (enum NPY_TYPES) -1, const_zero = (enum NPY_TYPES) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(enum NPY_TYPES) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(enum NPY_TYPES) <= sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(enum NPY_TYPES), little, !is_unsigned); } } /* MemviewSliceCopyTemplate */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, const char *mode, int ndim, size_t sizeof_dtype, int contig_flag, int dtype_is_object) { __Pyx_RefNannyDeclarations int i; __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; struct __pyx_memoryview_obj *from_memview = from_mvs->memview; Py_buffer *buf = &from_memview->view; PyObject *shape_tuple = NULL; PyObject *temp_int = NULL; struct __pyx_array_obj *array_obj = NULL; struct __pyx_memoryview_obj *memview_obj = NULL; __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); for (i = 0; i < ndim; i++) { if (from_mvs->suboffsets[i] >= 0) { PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " "indirect dimensions (axis %d)", i); goto fail; } } shape_tuple = PyTuple_New(ndim); if (unlikely(!shape_tuple)) { goto fail; } __Pyx_GOTREF(shape_tuple); for(i = 0; i < ndim; i++) { temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); if(unlikely(!temp_int)) { goto fail; } else { PyTuple_SET_ITEM(shape_tuple, i, temp_int); temp_int = NULL; } } array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); if (unlikely(!array_obj)) { goto fail; } __Pyx_GOTREF(array_obj); memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( (PyObject *) array_obj, contig_flag, dtype_is_object, from_mvs->memview->typeinfo); if (unlikely(!memview_obj)) goto fail; if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) goto fail; if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, dtype_is_object) < 0)) goto fail; goto no_fail; fail: __Pyx_XDECREF(new_mvs.memview); new_mvs.memview = NULL; new_mvs.data = NULL; no_fail: __Pyx_XDECREF(shape_tuple); __Pyx_XDECREF(temp_int); __Pyx_XDECREF(array_obj); __Pyx_RefNannyFinishContext(); return new_mvs; } /* MemviewSliceInit */ static int __Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, int ndim, __Pyx_memviewslice *memviewslice, int memview_is_new_reference) { __Pyx_RefNannyDeclarations int i, retval=-1; Py_buffer *buf = &memview->view; __Pyx_RefNannySetupContext("init_memviewslice", 0); if (!buf) { PyErr_SetString(PyExc_ValueError, "buf is NULL."); goto fail; } else if (memviewslice->memview || memviewslice->data) { PyErr_SetString(PyExc_ValueError, "memviewslice is already initialized!"); goto fail; } if (buf->strides) { for (i = 0; i < ndim; i++) { memviewslice->strides[i] = buf->strides[i]; } } else { Py_ssize_t stride = buf->itemsize; for (i = ndim - 1; i >= 0; i--) { memviewslice->strides[i] = stride; stride *= buf->shape[i]; } } for (i = 0; i < ndim; i++) { memviewslice->shape[i] = buf->shape[i]; if (buf->suboffsets) { memviewslice->suboffsets[i] = buf->suboffsets[i]; } else { memviewslice->suboffsets[i] = -1; } } memviewslice->memview = memview; memviewslice->data = (char *)buf->buf; if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { Py_INCREF(memview); } retval = 0; goto no_fail; fail: memviewslice->memview = 0; memviewslice->data = 0; retval = -1; no_fail: __Pyx_RefNannyFinishContext(); return retval; } static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) { va_list vargs; char msg[200]; #ifdef HAVE_STDARG_PROTOTYPES va_start(vargs, fmt); #else va_start(vargs); #endif vsnprintf(msg, 200, fmt, vargs); Py_FatalError(msg); va_end(vargs); } static CYTHON_INLINE int __pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, PyThread_type_lock lock) { int result; PyThread_acquire_lock(lock, 1); result = (*acquisition_count)++; PyThread_release_lock(lock); return result; } static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, PyThread_type_lock lock) { int result; PyThread_acquire_lock(lock, 1); result = (*acquisition_count)--; PyThread_release_lock(lock); return result; } static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int first_time; struct __pyx_memoryview_obj *memview = memslice->memview; if (!memview || (PyObject *) memview == Py_None) return; if (__pyx_get_slice_count(memview) < 0) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); first_time = __pyx_add_acquisition_count(memview) == 0; if (first_time) { if (have_gil) { Py_INCREF((PyObject *) memview); } else { PyGILState_STATE _gilstate = PyGILState_Ensure(); Py_INCREF((PyObject *) memview); PyGILState_Release(_gilstate); } } } static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int last_time; struct __pyx_memoryview_obj *memview = memslice->memview; if (!memview ) { return; } else if ((PyObject *) memview == Py_None) { memslice->memview = NULL; return; } if (__pyx_get_slice_count(memview) <= 0) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); last_time = __pyx_sub_acquisition_count(memview) == 1; memslice->data = NULL; if (last_time) { if (have_gil) { Py_CLEAR(memslice->memview); } else { PyGILState_STATE _gilstate = PyGILState_Ensure(); Py_CLEAR(memslice->memview); PyGILState_Release(_gilstate); } } else { memslice->memview = NULL; } } /* CIntFromPy */ static CYTHON_INLINE size_t __Pyx_PyInt_As_size_t(PyObject *x) { const size_t neg_one = (size_t) -1, const_zero = (size_t) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(size_t) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(size_t, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (size_t) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (size_t) 0; case 1: __PYX_VERIFY_RETURN_INT(size_t, digit, digits[0]) case 2: if (8 * sizeof(size_t) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) >= 2 * PyLong_SHIFT) { return (size_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } } break; case 3: if (8 * sizeof(size_t) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) >= 3 * PyLong_SHIFT) { return (size_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } } break; case 4: if (8 * sizeof(size_t) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) >= 4 * PyLong_SHIFT) { return (size_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (size_t) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(size_t) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(size_t, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(size_t) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(size_t, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (size_t) 0; case -1: __PYX_VERIFY_RETURN_INT(size_t, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(size_t, digit, +digits[0]) case -2: if (8 * sizeof(size_t) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { return (size_t) (((size_t)-1)*(((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); } } break; case 2: if (8 * sizeof(size_t) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { return (size_t) ((((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); } } break; case -3: if (8 * sizeof(size_t) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { return (size_t) (((size_t)-1)*(((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); } } break; case 3: if (8 * sizeof(size_t) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { return (size_t) ((((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); } } break; case -4: if (8 * sizeof(size_t) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) - 1 > 4 * PyLong_SHIFT) { return (size_t) (((size_t)-1)*(((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); } } break; case 4: if (8 * sizeof(size_t) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(size_t, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(size_t) - 1 > 4 * PyLong_SHIFT) { return (size_t) ((((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0]))); } } break; } #endif if (sizeof(size_t) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(size_t, long, PyLong_AsLong(x)) } else if (sizeof(size_t) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(size_t, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else size_t val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (size_t) -1; } } else { size_t val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (size_t) -1; val = __Pyx_PyInt_As_size_t(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to size_t"); return (size_t) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to size_t"); return (size_t) -1; } /* CIntFromPy */ static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *x) { const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(unsigned int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(unsigned int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (unsigned int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (unsigned int) 0; case 1: __PYX_VERIFY_RETURN_INT(unsigned int, digit, digits[0]) case 2: if (8 * sizeof(unsigned int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) >= 2 * PyLong_SHIFT) { return (unsigned int) (((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); } } break; case 3: if (8 * sizeof(unsigned int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) >= 3 * PyLong_SHIFT) { return (unsigned int) (((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); } } break; case 4: if (8 * sizeof(unsigned int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) >= 4 * PyLong_SHIFT) { return (unsigned int) (((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (unsigned int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(unsigned int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (unsigned int) 0; case -1: __PYX_VERIFY_RETURN_INT(unsigned int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(unsigned int, digit, +digits[0]) case -2: if (8 * sizeof(unsigned int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) { return (unsigned int) (((unsigned int)-1)*(((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case 2: if (8 * sizeof(unsigned int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) { return (unsigned int) ((((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case -3: if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) { return (unsigned int) (((unsigned int)-1)*(((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case 3: if (8 * sizeof(unsigned int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) { return (unsigned int) ((((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case -4: if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT) { return (unsigned int) (((unsigned int)-1)*(((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case 4: if (8 * sizeof(unsigned int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT) { return (unsigned int) ((((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; } #endif if (sizeof(unsigned int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(unsigned int, long, PyLong_AsLong(x)) } else if (sizeof(unsigned int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(unsigned int, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else unsigned int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (unsigned int) -1; } } else { unsigned int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (unsigned int) -1; val = __Pyx_PyInt_As_unsigned_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to unsigned int"); return (unsigned int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to unsigned int"); return (unsigned int) -1; } /* CIntFromPy */ static CYTHON_INLINE npy_int8 __Pyx_PyInt_As_npy_int8(PyObject *x) { const npy_int8 neg_one = (npy_int8) -1, const_zero = (npy_int8) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(npy_int8) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(npy_int8, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (npy_int8) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (npy_int8) 0; case 1: __PYX_VERIFY_RETURN_INT(npy_int8, digit, digits[0]) case 2: if (8 * sizeof(npy_int8) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) >= 2 * PyLong_SHIFT) { return (npy_int8) (((((npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0])); } } break; case 3: if (8 * sizeof(npy_int8) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) >= 3 * PyLong_SHIFT) { return (npy_int8) (((((((npy_int8)digits[2]) << PyLong_SHIFT) | (npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0])); } } break; case 4: if (8 * sizeof(npy_int8) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) >= 4 * PyLong_SHIFT) { return (npy_int8) (((((((((npy_int8)digits[3]) << PyLong_SHIFT) | (npy_int8)digits[2]) << PyLong_SHIFT) | (npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (npy_int8) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(npy_int8) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(npy_int8, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(npy_int8) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(npy_int8, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (npy_int8) 0; case -1: __PYX_VERIFY_RETURN_INT(npy_int8, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(npy_int8, digit, +digits[0]) case -2: if (8 * sizeof(npy_int8) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) - 1 > 2 * PyLong_SHIFT) { return (npy_int8) (((npy_int8)-1)*(((((npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0]))); } } break; case 2: if (8 * sizeof(npy_int8) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) - 1 > 2 * PyLong_SHIFT) { return (npy_int8) ((((((npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0]))); } } break; case -3: if (8 * sizeof(npy_int8) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) - 1 > 3 * PyLong_SHIFT) { return (npy_int8) (((npy_int8)-1)*(((((((npy_int8)digits[2]) << PyLong_SHIFT) | (npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0]))); } } break; case 3: if (8 * sizeof(npy_int8) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) - 1 > 3 * PyLong_SHIFT) { return (npy_int8) ((((((((npy_int8)digits[2]) << PyLong_SHIFT) | (npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0]))); } } break; case -4: if (8 * sizeof(npy_int8) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) - 1 > 4 * PyLong_SHIFT) { return (npy_int8) (((npy_int8)-1)*(((((((((npy_int8)digits[3]) << PyLong_SHIFT) | (npy_int8)digits[2]) << PyLong_SHIFT) | (npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0]))); } } break; case 4: if (8 * sizeof(npy_int8) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(npy_int8, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(npy_int8) - 1 > 4 * PyLong_SHIFT) { return (npy_int8) ((((((((((npy_int8)digits[3]) << PyLong_SHIFT) | (npy_int8)digits[2]) << PyLong_SHIFT) | (npy_int8)digits[1]) << PyLong_SHIFT) | (npy_int8)digits[0]))); } } break; } #endif if (sizeof(npy_int8) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(npy_int8, long, PyLong_AsLong(x)) } else if (sizeof(npy_int8) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(npy_int8, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else npy_int8 val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (npy_int8) -1; } } else { npy_int8 val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (npy_int8) -1; val = __Pyx_PyInt_As_npy_int8(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to npy_int8"); return (npy_int8) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to npy_int8"); return (npy_int8) -1; } /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) case -2: if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -3: if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -4: if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; } #endif if (sizeof(int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (int) -1; } } else { int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (int) -1; val = __Pyx_PyInt_As_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to int"); return (int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to int"); return (int) -1; } /* CIntFromPy */ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { const char neg_one = (char) -1, const_zero = (char) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(char) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (char) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (char) 0; case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) case 2: if (8 * sizeof(char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; case 3: if (8 * sizeof(char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; case 4: if (8 * sizeof(char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (char) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(char) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (char) 0; case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) case -2: if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 2: if (8 * sizeof(char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case -3: if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 3: if (8 * sizeof(char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case -4: if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 4: if (8 * sizeof(char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; } #endif if (sizeof(char) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else char val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (char) -1; } } else { char val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (char) -1; val = __Pyx_PyInt_As_char(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to char"); return (char) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to char"); return (char) -1; } /* CIntFromPy */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(long) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (long) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (long) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(long) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) case -2: if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -3: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -4: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; } #endif if (sizeof(long) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else long val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (long) -1; } } else { long val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (long) -1; val = __Pyx_PyInt_As_long(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to long"); return (long) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to long"); return (long) -1; } /* PyObjectCallMethod1 */ static PyObject* __Pyx_PyObject_CallMethod1(PyObject* obj, PyObject* method_name, PyObject* arg) { PyObject *method, *result = NULL; method = __Pyx_PyObject_GetAttrStr(obj, method_name); if (unlikely(!method)) goto bad; #if CYTHON_COMPILING_IN_CPYTHON if (likely(PyMethod_Check(method))) { PyObject *self = PyMethod_GET_SELF(method); if (likely(self)) { PyObject *args; PyObject *function = PyMethod_GET_FUNCTION(method); args = PyTuple_New(2); if (unlikely(!args)) goto bad; Py_INCREF(self); PyTuple_SET_ITEM(args, 0, self); Py_INCREF(arg); PyTuple_SET_ITEM(args, 1, arg); Py_INCREF(function); Py_DECREF(method); method = NULL; result = __Pyx_PyObject_Call(function, args, NULL); Py_DECREF(args); Py_DECREF(function); return result; } } #endif result = __Pyx_PyObject_CallOneArg(method, arg); bad: Py_XDECREF(method); return result; } /* CoroutineBase */ #include #include static PyObject *__Pyx_Coroutine_Send(PyObject *self, PyObject *value); static PyObject *__Pyx_Coroutine_Close(PyObject *self); static PyObject *__Pyx_Coroutine_Throw(PyObject *gen, PyObject *args); #define __Pyx_Coroutine_Undelegate(gen) Py_CLEAR((gen)->yieldfrom) #if 1 || PY_VERSION_HEX < 0x030300B0 static int __Pyx_PyGen_FetchStopIterationValue(PyObject **pvalue) { PyObject *et, *ev, *tb; PyObject *value = NULL; __Pyx_PyThreadState_declare __Pyx_PyThreadState_assign __Pyx_ErrFetch(&et, &ev, &tb); if (!et) { Py_XDECREF(tb); Py_XDECREF(ev); Py_INCREF(Py_None); *pvalue = Py_None; return 0; } if (likely(et == PyExc_StopIteration)) { #if PY_VERSION_HEX >= 0x030300A0 if (ev && Py_TYPE(ev) == (PyTypeObject*)PyExc_StopIteration) { value = ((PyStopIterationObject *)ev)->value; Py_INCREF(value); Py_DECREF(ev); Py_XDECREF(tb); Py_DECREF(et); *pvalue = value; return 0; } #endif if (!ev || !PyObject_TypeCheck(ev, (PyTypeObject*)PyExc_StopIteration)) { if (!ev) { Py_INCREF(Py_None); ev = Py_None; } else if (PyTuple_Check(ev)) { if (PyTuple_GET_SIZE(ev) >= 1) { PyObject *value; #if CYTHON_COMPILING_IN_CPYTHON value = PySequence_ITEM(ev, 0); #else value = PyTuple_GET_ITEM(ev, 0); Py_INCREF(value); #endif Py_DECREF(ev); ev = value; } else { Py_INCREF(Py_None); Py_DECREF(ev); ev = Py_None; } } Py_XDECREF(tb); Py_DECREF(et); *pvalue = ev; return 0; } } else if (!PyErr_GivenExceptionMatches(et, PyExc_StopIteration)) { __Pyx_ErrRestore(et, ev, tb); return -1; } PyErr_NormalizeException(&et, &ev, &tb); if (unlikely(!PyObject_TypeCheck(ev, (PyTypeObject*)PyExc_StopIteration))) { __Pyx_ErrRestore(et, ev, tb); return -1; } Py_XDECREF(tb); Py_DECREF(et); #if PY_VERSION_HEX >= 0x030300A0 value = ((PyStopIterationObject *)ev)->value; Py_INCREF(value); Py_DECREF(ev); #else { PyObject* args = __Pyx_PyObject_GetAttrStr(ev, __pyx_n_s_args); Py_DECREF(ev); if (likely(args)) { value = PySequence_GetItem(args, 0); Py_DECREF(args); } if (unlikely(!value)) { __Pyx_ErrRestore(NULL, NULL, NULL); Py_INCREF(Py_None); value = Py_None; } } #endif *pvalue = value; return 0; } #endif static CYTHON_INLINE void __Pyx_Coroutine_ExceptionClear(__pyx_CoroutineObject *self) { PyObject *exc_type = self->exc_type; PyObject *exc_value = self->exc_value; PyObject *exc_traceback = self->exc_traceback; self->exc_type = NULL; self->exc_value = NULL; self->exc_traceback = NULL; Py_XDECREF(exc_type); Py_XDECREF(exc_value); Py_XDECREF(exc_traceback); } static CYTHON_INLINE int __Pyx_Coroutine_CheckRunning(__pyx_CoroutineObject *gen) { if (unlikely(gen->is_running)) { PyErr_SetString(PyExc_ValueError, "generator already executing"); return 1; } return 0; } static CYTHON_INLINE PyObject *__Pyx_Coroutine_SendEx(__pyx_CoroutineObject *self, PyObject *value) { PyObject *retval; __Pyx_PyThreadState_declare assert(!self->is_running); if (unlikely(self->resume_label == 0)) { if (unlikely(value && value != Py_None)) { PyErr_SetString(PyExc_TypeError, "can't send non-None value to a " "just-started generator"); return NULL; } } if (unlikely(self->resume_label == -1)) { PyErr_SetNone(PyExc_StopIteration); return NULL; } __Pyx_PyThreadState_assign if (value) { #if CYTHON_COMPILING_IN_PYPY #else if (self->exc_traceback) { PyTracebackObject *tb = (PyTracebackObject *) self->exc_traceback; PyFrameObject *f = tb->tb_frame; Py_XINCREF(__pyx_tstate->frame); assert(f->f_back == NULL); f->f_back = __pyx_tstate->frame; } #endif __Pyx_ExceptionSwap(&self->exc_type, &self->exc_value, &self->exc_traceback); } else { __Pyx_Coroutine_ExceptionClear(self); } self->is_running = 1; retval = self->body((PyObject *) self, value); self->is_running = 0; if (retval) { __Pyx_ExceptionSwap(&self->exc_type, &self->exc_value, &self->exc_traceback); #if CYTHON_COMPILING_IN_PYPY #else if (self->exc_traceback) { PyTracebackObject *tb = (PyTracebackObject *) self->exc_traceback; PyFrameObject *f = tb->tb_frame; Py_CLEAR(f->f_back); } #endif } else { __Pyx_Coroutine_ExceptionClear(self); } return retval; } static CYTHON_INLINE PyObject *__Pyx_Coroutine_MethodReturn(PyObject *retval) { if (unlikely(!retval && !PyErr_Occurred())) { PyErr_SetNone(PyExc_StopIteration); } return retval; } static CYTHON_INLINE PyObject *__Pyx_Coroutine_FinishDelegation(__pyx_CoroutineObject *gen) { PyObject *ret; PyObject *val = NULL; __Pyx_Coroutine_Undelegate(gen); __Pyx_PyGen_FetchStopIterationValue(&val); ret = __Pyx_Coroutine_SendEx(gen, val); Py_XDECREF(val); return ret; } static PyObject *__Pyx_Coroutine_Send(PyObject *self, PyObject *value) { PyObject *retval; __pyx_CoroutineObject *gen = (__pyx_CoroutineObject*) self; PyObject *yf = gen->yieldfrom; if (unlikely(__Pyx_Coroutine_CheckRunning(gen))) return NULL; if (yf) { PyObject *ret; gen->is_running = 1; #ifdef __Pyx_Generator_USED if (__Pyx_Generator_CheckExact(yf)) { ret = __Pyx_Coroutine_Send(yf, value); } else #endif #ifdef __Pyx_Coroutine_USED if (__Pyx_Coroutine_CheckExact(yf)) { ret = __Pyx_Coroutine_Send(yf, value); } else #endif { if (value == Py_None) ret = Py_TYPE(yf)->tp_iternext(yf); else ret = __Pyx_PyObject_CallMethod1(yf, __pyx_n_s_send, value); } gen->is_running = 0; if (likely(ret)) { return ret; } retval = __Pyx_Coroutine_FinishDelegation(gen); } else { retval = __Pyx_Coroutine_SendEx(gen, value); } return __Pyx_Coroutine_MethodReturn(retval); } static int __Pyx_Coroutine_CloseIter(__pyx_CoroutineObject *gen, PyObject *yf) { PyObject *retval = NULL; int err = 0; #ifdef __Pyx_Generator_USED if (__Pyx_Generator_CheckExact(yf)) { retval = __Pyx_Coroutine_Close(yf); if (!retval) return -1; } else #endif #ifdef __Pyx_Coroutine_USED if (__Pyx_Coroutine_CheckExact(yf)) { retval = __Pyx_Coroutine_Close(yf); if (!retval) return -1; } else #endif { PyObject *meth; gen->is_running = 1; meth = __Pyx_PyObject_GetAttrStr(yf, __pyx_n_s_close); if (unlikely(!meth)) { if (!PyErr_ExceptionMatches(PyExc_AttributeError)) { PyErr_WriteUnraisable(yf); } PyErr_Clear(); } else { retval = PyObject_CallFunction(meth, NULL); Py_DECREF(meth); if (!retval) err = -1; } gen->is_running = 0; } Py_XDECREF(retval); return err; } static PyObject *__Pyx_Generator_Next(PyObject *self) { __pyx_CoroutineObject *gen = (__pyx_CoroutineObject*) self; PyObject *yf = gen->yieldfrom; if (unlikely(__Pyx_Coroutine_CheckRunning(gen))) return NULL; if (yf) { PyObject *ret; gen->is_running = 1; ret = Py_TYPE(yf)->tp_iternext(yf); gen->is_running = 0; if (likely(ret)) { return ret; } return __Pyx_Coroutine_FinishDelegation(gen); } return __Pyx_Coroutine_SendEx(gen, Py_None); } static PyObject *__Pyx_Coroutine_Close(PyObject *self) { __pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self; PyObject *retval, *raised_exception; PyObject *yf = gen->yieldfrom; int err = 0; if (unlikely(__Pyx_Coroutine_CheckRunning(gen))) return NULL; if (yf) { Py_INCREF(yf); err = __Pyx_Coroutine_CloseIter(gen, yf); __Pyx_Coroutine_Undelegate(gen); Py_DECREF(yf); } if (err == 0) PyErr_SetNone(PyExc_GeneratorExit); retval = __Pyx_Coroutine_SendEx(gen, NULL); if (retval) { Py_DECREF(retval); PyErr_SetString(PyExc_RuntimeError, "generator ignored GeneratorExit"); return NULL; } raised_exception = PyErr_Occurred(); if (!raised_exception || raised_exception == PyExc_StopIteration || raised_exception == PyExc_GeneratorExit || PyErr_GivenExceptionMatches(raised_exception, PyExc_GeneratorExit) || PyErr_GivenExceptionMatches(raised_exception, PyExc_StopIteration)) { if (raised_exception) PyErr_Clear(); Py_INCREF(Py_None); return Py_None; } return NULL; } static PyObject *__Pyx_Coroutine_Throw(PyObject *self, PyObject *args) { __pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self; PyObject *typ; PyObject *tb = NULL; PyObject *val = NULL; PyObject *yf = gen->yieldfrom; if (!PyArg_UnpackTuple(args, (char *)"throw", 1, 3, &typ, &val, &tb)) return NULL; if (unlikely(__Pyx_Coroutine_CheckRunning(gen))) return NULL; if (yf) { PyObject *ret; Py_INCREF(yf); if (PyErr_GivenExceptionMatches(typ, PyExc_GeneratorExit)) { int err = __Pyx_Coroutine_CloseIter(gen, yf); Py_DECREF(yf); __Pyx_Coroutine_Undelegate(gen); if (err < 0) return __Pyx_Coroutine_MethodReturn(__Pyx_Coroutine_SendEx(gen, NULL)); goto throw_here; } gen->is_running = 1; #ifdef __Pyx_Generator_USED if (__Pyx_Generator_CheckExact(yf)) { ret = __Pyx_Coroutine_Throw(yf, args); } else #endif #ifdef __Pyx_Coroutine_USED if (__Pyx_Coroutine_CheckExact(yf)) { ret = __Pyx_Coroutine_Throw(yf, args); } else #endif { PyObject *meth = __Pyx_PyObject_GetAttrStr(yf, __pyx_n_s_throw); if (unlikely(!meth)) { Py_DECREF(yf); if (!PyErr_ExceptionMatches(PyExc_AttributeError)) { gen->is_running = 0; return NULL; } PyErr_Clear(); __Pyx_Coroutine_Undelegate(gen); gen->is_running = 0; goto throw_here; } ret = PyObject_CallObject(meth, args); Py_DECREF(meth); } gen->is_running = 0; Py_DECREF(yf); if (!ret) { ret = __Pyx_Coroutine_FinishDelegation(gen); } return __Pyx_Coroutine_MethodReturn(ret); } throw_here: __Pyx_Raise(typ, val, tb, NULL); return __Pyx_Coroutine_MethodReturn(__Pyx_Coroutine_SendEx(gen, NULL)); } static int __Pyx_Coroutine_traverse(PyObject *self, visitproc visit, void *arg) { __pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self; Py_VISIT(gen->closure); Py_VISIT(gen->classobj); Py_VISIT(gen->yieldfrom); Py_VISIT(gen->exc_type); Py_VISIT(gen->exc_value); Py_VISIT(gen->exc_traceback); return 0; } static int __Pyx_Coroutine_clear(PyObject *self) { __pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self; Py_CLEAR(gen->closure); Py_CLEAR(gen->classobj); Py_CLEAR(gen->yieldfrom); Py_CLEAR(gen->exc_type); Py_CLEAR(gen->exc_value); Py_CLEAR(gen->exc_traceback); Py_CLEAR(gen->gi_name); Py_CLEAR(gen->gi_qualname); return 0; } static void __Pyx_Coroutine_dealloc(PyObject *self) { __pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self; PyObject_GC_UnTrack(gen); if (gen->gi_weakreflist != NULL) PyObject_ClearWeakRefs(self); if (gen->resume_label > 0) { PyObject_GC_Track(self); #if PY_VERSION_HEX >= 0x030400a1 if (PyObject_CallFinalizerFromDealloc(self)) #else Py_TYPE(gen)->tp_del(self); if (self->ob_refcnt > 0) #endif { return; } PyObject_GC_UnTrack(self); } __Pyx_Coroutine_clear(self); PyObject_GC_Del(gen); } static void __Pyx_Coroutine_del(PyObject *self) { PyObject *res; PyObject *error_type, *error_value, *error_traceback; __pyx_CoroutineObject *gen = (__pyx_CoroutineObject *) self; __Pyx_PyThreadState_declare if (gen->resume_label <= 0) return ; #if PY_VERSION_HEX < 0x030400a1 assert(self->ob_refcnt == 0); self->ob_refcnt = 1; #endif __Pyx_PyThreadState_assign __Pyx_ErrFetch(&error_type, &error_value, &error_traceback); res = __Pyx_Coroutine_Close(self); if (res == NULL) PyErr_WriteUnraisable(self); else Py_DECREF(res); __Pyx_ErrRestore(error_type, error_value, error_traceback); #if PY_VERSION_HEX < 0x030400a1 assert(self->ob_refcnt > 0); if (--self->ob_refcnt == 0) { return; } { Py_ssize_t refcnt = self->ob_refcnt; _Py_NewReference(self); self->ob_refcnt = refcnt; } #if CYTHON_COMPILING_IN_CPYTHON assert(PyType_IS_GC(self->ob_type) && _Py_AS_GC(self)->gc.gc_refs != _PyGC_REFS_UNTRACKED); _Py_DEC_REFTOTAL; #endif #ifdef COUNT_ALLOCS --Py_TYPE(self)->tp_frees; --Py_TYPE(self)->tp_allocs; #endif #endif } static PyObject * __Pyx_Coroutine_get_name(__pyx_CoroutineObject *self) { Py_INCREF(self->gi_name); return self->gi_name; } static int __Pyx_Coroutine_set_name(__pyx_CoroutineObject *self, PyObject *value) { PyObject *tmp; #if PY_MAJOR_VERSION >= 3 if (unlikely(value == NULL || !PyUnicode_Check(value))) { #else if (unlikely(value == NULL || !PyString_Check(value))) { #endif PyErr_SetString(PyExc_TypeError, "__name__ must be set to a string object"); return -1; } tmp = self->gi_name; Py_INCREF(value); self->gi_name = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_Coroutine_get_qualname(__pyx_CoroutineObject *self) { Py_INCREF(self->gi_qualname); return self->gi_qualname; } static int __Pyx_Coroutine_set_qualname(__pyx_CoroutineObject *self, PyObject *value) { PyObject *tmp; #if PY_MAJOR_VERSION >= 3 if (unlikely(value == NULL || !PyUnicode_Check(value))) { #else if (unlikely(value == NULL || !PyString_Check(value))) { #endif PyErr_SetString(PyExc_TypeError, "__qualname__ must be set to a string object"); return -1; } tmp = self->gi_qualname; Py_INCREF(value); self->gi_qualname = value; Py_XDECREF(tmp); return 0; } static __pyx_CoroutineObject *__Pyx__Coroutine_New(PyTypeObject* type, __pyx_coroutine_body_t body, PyObject *closure, PyObject *name, PyObject *qualname) { __pyx_CoroutineObject *gen = PyObject_GC_New(__pyx_CoroutineObject, type); if (gen == NULL) return NULL; gen->body = body; gen->closure = closure; Py_XINCREF(closure); gen->is_running = 0; gen->resume_label = 0; gen->classobj = NULL; gen->yieldfrom = NULL; gen->exc_type = NULL; gen->exc_value = NULL; gen->exc_traceback = NULL; gen->gi_weakreflist = NULL; Py_XINCREF(qualname); gen->gi_qualname = qualname; Py_XINCREF(name); gen->gi_name = name; PyObject_GC_Track(gen); return gen; } /* PatchModuleWithCoroutine */ static PyObject* __Pyx_Coroutine_patch_module(PyObject* module, const char* py_code) { #if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED) int result; PyObject *globals, *result_obj; globals = PyDict_New(); if (unlikely(!globals)) goto ignore; result = PyDict_SetItemString(globals, "_cython_coroutine_type", #ifdef __Pyx_Coroutine_USED (PyObject*)__pyx_CoroutineType); #else Py_None); #endif if (unlikely(result < 0)) goto ignore; result = PyDict_SetItemString(globals, "_cython_generator_type", #ifdef __Pyx_Generator_USED (PyObject*)__pyx_GeneratorType); #else Py_None); #endif if (unlikely(result < 0)) goto ignore; if (unlikely(PyDict_SetItemString(globals, "_module", module) < 0)) goto ignore; if (unlikely(PyDict_SetItemString(globals, "__builtins__", __pyx_b) < 0)) goto ignore; result_obj = PyRun_String(py_code, Py_file_input, globals, globals); if (unlikely(!result_obj)) goto ignore; Py_DECREF(result_obj); Py_DECREF(globals); return module; ignore: Py_XDECREF(globals); PyErr_WriteUnraisable(module); if (unlikely(PyErr_WarnEx(PyExc_RuntimeWarning, "Cython module failed to patch module with custom type", 1) < 0)) { Py_DECREF(module); module = NULL; } #else py_code++; #endif return module; } /* PatchGeneratorABC */ #if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED) static PyObject* __Pyx_patch_abc_module(PyObject *module); static PyObject* __Pyx_patch_abc_module(PyObject *module) { module = __Pyx_Coroutine_patch_module( module, "" "if _cython_generator_type is not None:\n" " try: Generator = _module.Generator\n" " except AttributeError: pass\n" " else: Generator.register(_cython_generator_type)\n" "if _cython_coroutine_type is not None:\n" " try: Coroutine = _module.Coroutine\n" " except AttributeError: pass\n" " else: Coroutine.register(_cython_coroutine_type)\n" ); return module; } #endif static int __Pyx_patch_abc(void) { #if defined(__Pyx_Generator_USED) || defined(__Pyx_Coroutine_USED) static int abc_patched = 0; if (!abc_patched) { PyObject *module; module = PyImport_ImportModule((PY_VERSION_HEX >= 0x03030000) ? "collections.abc" : "collections"); if (!module) { PyErr_WriteUnraisable(NULL); if (unlikely(PyErr_WarnEx(PyExc_RuntimeWarning, ((PY_VERSION_HEX >= 0x03030000) ? "Cython module failed to register with collections.abc module" : "Cython module failed to register with collections module"), 1) < 0)) { return -1; } } else { module = __Pyx_patch_abc_module(module); abc_patched = 1; if (unlikely(!module)) return -1; Py_DECREF(module); } module = PyImport_ImportModule("backports_abc"); if (module) { module = __Pyx_patch_abc_module(module); Py_XDECREF(module); } if (!module) { PyErr_Clear(); } } #else if (0) __Pyx_Coroutine_patch_module(NULL, NULL); #endif return 0; } /* Generator */ static PyMethodDef __pyx_Generator_methods[] = { {"send", (PyCFunction) __Pyx_Coroutine_Send, METH_O, (char*) PyDoc_STR("send(arg) -> send 'arg' into generator,\nreturn next yielded value or raise StopIteration.")}, {"throw", (PyCFunction) __Pyx_Coroutine_Throw, METH_VARARGS, (char*) PyDoc_STR("throw(typ[,val[,tb]]) -> raise exception in generator,\nreturn next yielded value or raise StopIteration.")}, {"close", (PyCFunction) __Pyx_Coroutine_Close, METH_NOARGS, (char*) PyDoc_STR("close() -> raise GeneratorExit inside generator.")}, {0, 0, 0, 0} }; static PyMemberDef __pyx_Generator_memberlist[] = { {(char *) "gi_running", T_BOOL, offsetof(__pyx_CoroutineObject, is_running), READONLY, NULL}, {(char*) "gi_yieldfrom", T_OBJECT, offsetof(__pyx_CoroutineObject, yieldfrom), READONLY, (char*) PyDoc_STR("object being iterated by 'yield from', or None")}, {0, 0, 0, 0, 0} }; static PyGetSetDef __pyx_Generator_getsets[] = { {(char *) "__name__", (getter)__Pyx_Coroutine_get_name, (setter)__Pyx_Coroutine_set_name, (char*) PyDoc_STR("name of the generator"), 0}, {(char *) "__qualname__", (getter)__Pyx_Coroutine_get_qualname, (setter)__Pyx_Coroutine_set_qualname, (char*) PyDoc_STR("qualified name of the generator"), 0}, {0, 0, 0, 0, 0} }; static PyTypeObject __pyx_GeneratorType_type = { PyVarObject_HEAD_INIT(0, 0) "generator", sizeof(__pyx_CoroutineObject), 0, (destructor) __Pyx_Coroutine_dealloc, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC | Py_TPFLAGS_HAVE_FINALIZE, 0, (traverseproc) __Pyx_Coroutine_traverse, 0, 0, offsetof(__pyx_CoroutineObject, gi_weakreflist), 0, (iternextfunc) __Pyx_Generator_Next, __pyx_Generator_methods, __pyx_Generator_memberlist, __pyx_Generator_getsets, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, #if PY_VERSION_HEX >= 0x030400a1 0, #else __Pyx_Coroutine_del, #endif 0, #if PY_VERSION_HEX >= 0x030400a1 __Pyx_Coroutine_del, #endif }; static int __pyx_Generator_init(void) { __pyx_GeneratorType_type.tp_getattro = PyObject_GenericGetAttr; __pyx_GeneratorType_type.tp_iter = PyObject_SelfIter; __pyx_GeneratorType = __Pyx_FetchCommonType(&__pyx_GeneratorType_type); if (unlikely(!__pyx_GeneratorType)) { return -1; } return 0; } /* CheckBinaryVersion */ static int __Pyx_check_binary_version(void) { char ctversion[4], rtversion[4]; PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { char message[200]; PyOS_snprintf(message, sizeof(message), "compiletime version %s of module '%.100s' " "does not match runtime version %s", ctversion, __Pyx_MODULE_NAME, rtversion); return PyErr_WarnEx(NULL, message, 1); } return 0; } /* ModuleImport */ #ifndef __PYX_HAVE_RT_ImportModule #define __PYX_HAVE_RT_ImportModule static PyObject *__Pyx_ImportModule(const char *name) { PyObject *py_name = 0; PyObject *py_module = 0; py_name = __Pyx_PyIdentifier_FromString(name); if (!py_name) goto bad; py_module = PyImport_Import(py_name); Py_DECREF(py_name); return py_module; bad: Py_XDECREF(py_name); return 0; } #endif /* TypeImport */ #ifndef __PYX_HAVE_RT_ImportType #define __PYX_HAVE_RT_ImportType static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict) { PyObject *py_module = 0; PyObject *result = 0; PyObject *py_name = 0; char warning[200]; Py_ssize_t basicsize; #ifdef Py_LIMITED_API PyObject *py_basicsize; #endif py_module = __Pyx_ImportModule(module_name); if (!py_module) goto bad; py_name = __Pyx_PyIdentifier_FromString(class_name); if (!py_name) goto bad; result = PyObject_GetAttr(py_module, py_name); Py_DECREF(py_name); py_name = 0; Py_DECREF(py_module); py_module = 0; if (!result) goto bad; if (!PyType_Check(result)) { PyErr_Format(PyExc_TypeError, "%.200s.%.200s is not a type object", module_name, class_name); goto bad; } #ifndef Py_LIMITED_API basicsize = ((PyTypeObject *)result)->tp_basicsize; #else py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); if (!py_basicsize) goto bad; basicsize = PyLong_AsSsize_t(py_basicsize); Py_DECREF(py_basicsize); py_basicsize = 0; if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) goto bad; #endif if (!strict && (size_t)basicsize > size) { PyOS_snprintf(warning, sizeof(warning), "%s.%s size changed, may indicate binary incompatibility. Expected %zd, got %zd", module_name, class_name, basicsize, size); if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; } else if ((size_t)basicsize != size) { PyErr_Format(PyExc_ValueError, "%.200s.%.200s has the wrong size, try recompiling. Expected %zd, got %zd", module_name, class_name, basicsize, size); goto bad; } return (PyTypeObject *)result; bad: Py_XDECREF(py_module); Py_XDECREF(result); return NULL; } #endif /* InitStrings */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 if (t->is_unicode) { *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); } else if (t->intern) { *t->p = PyString_InternFromString(t->s); } else { *t->p = PyString_FromStringAndSize(t->s, t->n - 1); } #else if (t->is_unicode | t->is_str) { if (t->intern) { *t->p = PyUnicode_InternFromString(t->s); } else if (t->encoding) { *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); } else { *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); } } else { *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); } #endif if (!*t->p) return -1; ++t; } return 0; } static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); } static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { Py_ssize_t ignore; return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { #if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && #endif PyUnicode_Check(o)) { #if PY_VERSION_HEX < 0x03030000 char* defenc_c; PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); if (!defenc) return NULL; defenc_c = PyBytes_AS_STRING(defenc); #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII { char* end = defenc_c + PyBytes_GET_SIZE(defenc); char* c; for (c = defenc_c; c < end; c++) { if ((unsigned char) (*c) >= 128) { PyUnicode_AsASCIIString(o); return NULL; } } } #endif *length = PyBytes_GET_SIZE(defenc); return defenc_c; #else if (__Pyx_PyUnicode_READY(o) == -1) return NULL; #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII if (PyUnicode_IS_ASCII(o)) { *length = PyUnicode_GET_LENGTH(o); return PyUnicode_AsUTF8(o); } else { PyUnicode_AsASCIIString(o); return NULL; } #else return PyUnicode_AsUTF8AndSize(o, length); #endif #endif } else #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); } else #endif { char* result; int r = PyBytes_AsStringAndSize(o, &result, length); if (unlikely(r < 0)) { return NULL; } else { return result; } } } static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { int is_true = x == Py_True; if (is_true | (x == Py_False) | (x == Py_None)) return is_true; else return PyObject_IsTrue(x); } static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { PyNumberMethods *m; const char *name = NULL; PyObject *res = NULL; #if PY_MAJOR_VERSION < 3 if (PyInt_Check(x) || PyLong_Check(x)) #else if (PyLong_Check(x)) #endif return __Pyx_NewRef(x); m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { name = "int"; res = PyNumber_Int(x); } else if (m && m->nb_long) { name = "long"; res = PyNumber_Long(x); } #else if (m && m->nb_int) { name = "int"; res = PyNumber_Long(x); } #endif if (res) { #if PY_MAJOR_VERSION < 3 if (!PyInt_Check(res) && !PyLong_Check(res)) { #else if (!PyLong_Check(res)) { #endif PyErr_Format(PyExc_TypeError, "__%.4s__ returned non-%.4s (type %.200s)", name, name, Py_TYPE(res)->tp_name); Py_DECREF(res); return NULL; } } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_TypeError, "an integer is required"); } return res; } static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(b))) { if (sizeof(Py_ssize_t) >= sizeof(long)) return PyInt_AS_LONG(b); else return PyInt_AsSsize_t(x); } #endif if (likely(PyLong_CheckExact(b))) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)b)->ob_digit; const Py_ssize_t size = Py_SIZE(b); if (likely(__Pyx_sst_abs(size) <= 1)) { ival = likely(size) ? digits[0] : 0; if (size == -1) ival = -ival; return ival; } else { switch (size) { case 2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; } } #endif return PyLong_AsSsize_t(b); } x = PyNumber_Index(b); if (!x) return -1; ival = PyInt_AsSsize_t(x); Py_DECREF(x); return ival; } static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { return PyInt_FromSize_t(ival); } #endif /* Py_PYTHON_H */ pyresample-1.2.9/pyresample/ewa/_fornav.pyx000066400000000000000000000367651302372600000210470ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2016 # Author(s): # David Hoese # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # You should have received a copy of the GNU General Public License # along with this program. If not, see . """Resampling swath data to uniform grid using an Elliptical Weighted Averaging (EWA) algorithm. """ __docformat__ = "restructuredtext en" import cython cimport cython import numpy cimport numpy cimport cpython from libc.stdlib cimport calloc, malloc, free cdef extern from "_fornav_templates.h": ctypedef float weight_type ctypedef float ewa_param_type ctypedef float accum_type cdef float EPSILON #ctypedef double weight_type #ctypedef double ewa_param_type #ctypedef double accum_type #cdef double EPSILON ctypedef struct ewa_parameters: ewa_param_type a ewa_param_type b ewa_param_type c ewa_param_type f ewa_param_type u_del ewa_param_type v_del ctypedef struct ewa_weight: int count weight_type min weight_type distance_max weight_type delta_max weight_type sum_min weight_type alpha weight_type qmax weight_type qfactor weight_type *wtab cdef int initialize_weight(size_t chan_count, unsigned int weight_count, weight_type weight_min, weight_type weight_distance_max, weight_type weight_delta_max, weight_type weight_sum_min, ewa_weight *ewaw) cdef void deinitialize_weight(ewa_weight *ewaw) cdef accum_type **initialize_grid_accums(size_t chan_count, size_t grid_cols, size_t grid_rows) cdef weight_type **initialize_grid_weights(size_t chan_count, size_t grid_cols, size_t grid_rows) cdef void deinitialize_grids(size_t chan_count, void **grids) cdef int compute_ewa_parameters[CR_TYPE](size_t swath_cols, size_t swath_rows, CR_TYPE *uimg, CR_TYPE *vimg, ewa_weight *ewaw, ewa_parameters *ewap) cdef int compute_ewa[CR_TYPE, IMAGE_TYPE](size_t chan_count, bint maximum_weight_mode, size_t swath_cols, size_t swath_rows, size_t grid_cols, size_t grid_rows, CR_TYPE *uimg, CR_TYPE *vimg, IMAGE_TYPE **images, IMAGE_TYPE img_fill, accum_type **grid_accums, weight_type **grid_weights, ewa_weight *ewaw, ewa_parameters *ewap) # For some reason cython can't deduce the type when using the template #cdef int write_grid_image[GRID_TYPE](GRID_TYPE *output_image, GRID_TYPE fill, size_t grid_cols, size_t grid_rows, # accum_type *grid_accum, weight_type *grid_weights, # int maximum_weight_mode, weight_type weight_sum_min) cdef unsigned int write_grid_image(numpy.float32_t *output_image, numpy.float32_t fill, size_t grid_cols, size_t grid_rows, accum_type *grid_accum, weight_type *grid_weights, int maximum_weight_mode, weight_type weight_sum_min) cdef unsigned int write_grid_image(numpy.float64_t *output_image, numpy.float64_t fill, size_t grid_cols, size_t grid_rows, accum_type *grid_accum, weight_type *grid_weights, int maximum_weight_mode, weight_type weight_sum_min) cdef unsigned int write_grid_image(numpy.int8_t *output_image, numpy.int8_t fill, size_t grid_cols, size_t grid_rows, accum_type *grid_accum, weight_type *grid_weights, int maximum_weight_mode, weight_type weight_sum_min) ctypedef fused cr_dtype: numpy.float32_t numpy.float64_t # FUTURE: Add other types, but for now these are the basics ctypedef fused image_dtype: numpy.float32_t numpy.float64_t numpy.int8_t ctypedef fused grid_dtype: numpy.float32_t numpy.float64_t numpy.int8_t @cython.boundscheck(False) @cython.wraparound(False) cdef int fornav(unsigned int *valid_list, size_t chan_count, size_t swath_cols, size_t swath_rows, size_t grid_cols, size_t grid_rows, cr_dtype *cols_pointer, cr_dtype *rows_pointer, image_dtype **input_arrays, grid_dtype **output_arrays, image_dtype input_fill, grid_dtype output_fill, size_t rows_per_scan, unsigned int weight_count, weight_type weight_min, weight_type weight_distance_max, weight_type weight_delta_max, weight_type weight_sum_min, bint maximum_weight_mode) except -1: cdef unsigned int row_idx cdef unsigned int idx cdef bint got_point = 0 cdef bint tmp_got_point cdef int func_result cdef cr_dtype *tmp_cols_pointer cdef cr_dtype *tmp_rows_pointer cdef image_dtype **input_images cdef ewa_weight ewaw cdef ewa_parameters *ewap # other defaults if weight_sum_min == -1.0: weight_sum_min = weight_min func_result = initialize_weight(chan_count, weight_count, weight_min, weight_distance_max, weight_delta_max, weight_sum_min, &ewaw) if func_result < 0: raise RuntimeError("Could not initialize weight structure for EWA resampling") # Allocate location for storing the sum of all of the pixels involved in each grid cell # XXX: Do these need to be initialized to a fill value? cdef accum_type **grid_accums = initialize_grid_accums(chan_count, grid_cols, grid_rows) if grid_accums is NULL: raise MemoryError() cdef weight_type **grid_weights = initialize_grid_weights(chan_count, grid_cols, grid_rows) if grid_weights is NULL: raise MemoryError() # Allocate memory for the parameters specific to each column ewap = malloc(swath_cols * sizeof(ewa_parameters)) if ewap is NULL: raise MemoryError() # Allocate pointers to the correct portion of the data arrays that we will use input_images = malloc(chan_count * sizeof(image_dtype *)) if input_images is NULL: raise MemoryError() # NOTE: Have to use old school pyrex for loop because cython only supports compile-time known steps for row_idx from 0 <= row_idx < swath_rows by rows_per_scan: tmp_cols_pointer = &cols_pointer[row_idx * swath_cols] tmp_rows_pointer = &rows_pointer[row_idx * swath_cols] # print "Current cols pointer: %d" % (tmp_cols_pointer,) # Assign the python/numpy array objects to a pointer location for the rest of the functions for idx in range(chan_count): input_images[idx] = &input_arrays[idx][row_idx * swath_cols] # print "Current input 0 pointer: %d" % (input_images[idx],) # Calculate EWA parameters for each column index func_result = compute_ewa_parameters(swath_cols, rows_per_scan, tmp_cols_pointer, tmp_rows_pointer, &ewaw, ewap) if func_result < 0: got_point = got_point or 0 # raise RuntimeError("Could compute EWA parameters for EWA resampling") continue # NOTE: In the C version this is where the image array data is loaded tmp_got_point = compute_ewa(chan_count, maximum_weight_mode, swath_cols, rows_per_scan, grid_cols, grid_rows, tmp_cols_pointer, tmp_rows_pointer, input_images, input_fill, grid_accums, grid_weights, &ewaw, ewap) got_point = got_point or tmp_got_point free(input_images) free(ewap) if not got_point: raise RuntimeError("EWA Resampling: No swath pixels found inside grid to be resampled") for idx in range(chan_count): valid_list[idx] = write_grid_image(output_arrays[idx], output_fill, grid_cols, grid_rows, grid_accums[idx], grid_weights[idx], maximum_weight_mode, weight_sum_min) # free(grid_accums) deinitialize_weight(&ewaw) deinitialize_grids(chan_count, grid_accums) deinitialize_grids(chan_count, grid_weights) return 0 @cython.boundscheck(False) @cython.wraparound(False) def fornav_wrapper(numpy.ndarray[cr_dtype, ndim=2, mode='c'] cols_array, numpy.ndarray[cr_dtype, ndim=2, mode='c'] rows_array, tuple input_arrays, tuple output_arrays, input_fill, output_fill, size_t rows_per_scan, unsigned int weight_count=10000, weight_type weight_min=0.01, weight_type weight_distance_max=1.0, weight_type weight_delta_max=10.0, weight_type weight_sum_min=-1.0, cpython.bool maximum_weight_mode=False): """Python wrapper around the C interface to fornav. The main difficulty is that the C code can operate on multiple input arrays, but the python->C cython interface doesn't automatically know the data type of the numpy arrays inside a tuple. This function casts the array pointers to the corresponding C type and then calls the templated cython and C++ functions. This algorithm works under the assumption that the data is observed one scan line at a time. However, good results can still be achieved for non-scan based data is provided if `rows_per_scan` is set to the number of rows in the entire swath. :param cols_array: numpy array of grid column coordinates for each input swath pixel :param rows_array: numpy array of grid row coordinates for each input swath pixel :param input_arrays: tuple of numpy arrays with the same geolocation and same dtype :param output_arrays: tuple of empty numpy arrays to be filled with gridded data (must be writeable) :param input_fill: fill value in input data arrays representing invalid/bad values :param output_fill: fill value written to output data arrays representing invalid/bad or out of swath values :param rows_per_scan: number of input swath rows making up one scan line or all of the rows in the swath :param weight_count: number of elements to create in the gaussian weight table. Default is 10000. Must be at least 2 :param weight_min: the minimum value to store in the last position of the weight table. Default is 0.01, which, with a `weight_distance_max` of 1.0 produces a weight of 0.01 at a grid cell distance of 1.0. Must be greater than 0. :param weight_distance_max: distance in grid cell units at which to apply a weight of `weight_min`. Default is 1.0. Must be greater than 0. :param weight_delta_max: maximum distance in grid cells in each grid dimension over which to distribute a single swath cell. Default is 10.0. :param weight_sum_min: minimum weight sum value. Cells whose weight sums are less than `weight_sum_min` are set to the grid fill value. Default is EPSILON. :param maximum_weight_mode: If -m is not present, a weighted average of all swath cells that map to a particular grid cell is used. If -m is present, the swath cell having the maximum weight of all swath cells that map to a particular grid cell is used. The -m option should be used for coded data, i.e. snow cover. :return: tuple of valid grid points written for each output array """ cdef size_t num_items = len(input_arrays) cdef size_t num_outputs = len(output_arrays) cdef size_t swath_cols = cols_array.shape[1] cdef size_t swath_rows = cols_array.shape[0] cdef size_t grid_cols = output_arrays[0].shape[1] cdef size_t grid_rows = output_arrays[0].shape[0] cdef unsigned int i if num_items != num_outputs: raise ValueError("Must have same number of inputs and outputs") if num_items <= 0: raise ValueError("No input arrays given") if rows_per_scan < 2 or swath_rows % rows_per_scan != 0: raise ValueError("EWA requires 2 or more rows_per_scan and must be a factor of the total number of input rows") cdef numpy.dtype in_type = input_arrays[0].dtype cdef numpy.dtype out_type = output_arrays[0].dtype if in_type != out_type: raise ValueError("Input and Output must be of the same type") if not all(input_array.dtype == in_type for input_array in input_arrays): raise ValueError("Input arrays must all be of the same data type") if not all(output_array.dtype == out_type for output_array in output_arrays): raise ValueError("Input arrays must all be of the same data type") cdef void **input_pointer = malloc(num_items * sizeof(void *)) if not input_pointer: raise MemoryError() cdef void **output_pointer = malloc(num_items * sizeof(void *)) if not output_pointer: raise MemoryError() cdef unsigned int *valid_arr = malloc(num_items * sizeof(unsigned int)) valid_list = [] cdef numpy.ndarray[numpy.float32_t, ndim=2] tmp_arr_f32 cdef numpy.ndarray[numpy.float64_t, ndim=2] tmp_arr_f64 cdef numpy.ndarray[numpy.int8_t, ndim=2] tmp_arr_i8 cdef cr_dtype *cols_pointer = &cols_array[0, 0] cdef cr_dtype *rows_pointer = &rows_array[0, 0] cdef int func_result if in_type == numpy.float32: for i in range(num_items): tmp_arr_f32 = input_arrays[i] input_pointer[i] = &tmp_arr_f32[0, 0] tmp_arr_f32 = output_arrays[i] output_pointer[i] = &tmp_arr_f32[0, 0] func_result = fornav(valid_arr, num_items, swath_cols, swath_rows, grid_cols, grid_rows, cols_pointer, rows_pointer, input_pointer, output_pointer, input_fill, output_fill, rows_per_scan, weight_count, weight_min, weight_distance_max, weight_delta_max, weight_sum_min, maximum_weight_mode) elif in_type == numpy.float64: for i in range(num_items): tmp_arr_f64 = input_arrays[i] input_pointer[i] = &tmp_arr_f64[0, 0] tmp_arr_f64 = output_arrays[i] output_pointer[i] = &tmp_arr_f64[0, 0] func_result = fornav(valid_arr, num_items, swath_cols, swath_rows, grid_cols, grid_rows, cols_pointer, rows_pointer, input_pointer, output_pointer, input_fill, output_fill, rows_per_scan, weight_count, weight_min, weight_distance_max, weight_delta_max, weight_sum_min, maximum_weight_mode) elif in_type == numpy.int8: for i in range(num_items): tmp_arr_i8 = input_arrays[i] input_pointer[i] = &tmp_arr_i8[0, 0] tmp_arr_i8 = output_arrays[i] output_pointer[i] = &tmp_arr_i8[0, 0] func_result = fornav(valid_arr, num_items, swath_cols, swath_rows, grid_cols, grid_rows, cols_pointer, rows_pointer, input_pointer, output_pointer, input_fill, output_fill, rows_per_scan, weight_count, weight_min, weight_distance_max, weight_delta_max, weight_sum_min, maximum_weight_mode) else: raise ValueError("Unknown input and output data type") for i in range(num_items): valid_list.append(valid_arr[i]) free(input_pointer) free(output_pointer) return valid_list pyresample-1.2.9/pyresample/ewa/_fornav_templates.cpp000066400000000000000000000336051302372600000230550ustar00rootroot00000000000000#include "Python.h" #include #include "math.h" #include "numpy/arrayobject.h" #include "numpy/npy_math.h" #include "_fornav_templates.h" template int __isnan(IMAGE_TYPE x) { // Return numpy's isnan for normal float arguments (see __isnan below for ints) return npy_isnan(x); } int __isnan(npy_int8 x) { // Sometimes input data may be integers, need to be able to handle those similarly return 0; } int initialize_weight(size_t chan_count, unsigned int weight_count, weight_type weight_min, weight_type weight_distance_max, weight_type weight_delta_max, weight_type weight_sum_min, ewa_weight *ewaw) { unsigned int idx; weight_type *wptr; ewaw->wtab = (weight_type *)calloc(weight_count, sizeof(weight_type)); if (!ewaw->wtab) { return -1; } ewaw->count = weight_count; ewaw->min = weight_min; ewaw->distance_max = weight_distance_max; ewaw->delta_max = weight_delta_max; ewaw->sum_min = weight_sum_min; if (weight_count < 2) { // must be at least 2 return -1; } if (weight_min <= 0.0) { // must be greater than 0 return -1; } if (weight_distance_max <= 0.0) { // must be greater than 0 return -1; } ewaw->qmax = ewaw->distance_max * ewaw->distance_max; ewaw->alpha = -log(ewaw->min) / ewaw->qmax; wptr = ewaw->wtab; for (idx=0; idx < weight_count; idx++) { wptr[idx] = exp(-ewaw->alpha * ewaw->qmax * idx / (ewaw->count - 1)); } ewaw->qfactor = ewaw->count / ewaw->qmax; return 0; } void deinitialize_weight(ewa_weight *ewaw) { if (ewaw->wtab) { free(ewaw->wtab); } } accum_type **initialize_grid_accums(size_t chan_count, size_t grid_cols, size_t grid_rows) { accum_type **grid_accums = (accum_type **)malloc(chan_count * sizeof(accum_type *)); unsigned int i; if (!grid_accums) { return NULL; } for (i=0; i < chan_count; i++) { grid_accums[i] = (accum_type *)calloc(grid_cols * grid_rows, sizeof(accum_type)); if (!grid_accums[i]) { return NULL; } } return grid_accums; } weight_type **initialize_grid_weights(size_t chan_count, size_t grid_cols, size_t grid_rows) { weight_type **grid_weights = (weight_type **)malloc(chan_count * sizeof(weight_type *)); unsigned int i; if (!grid_weights) { return NULL; } for (i=0; i int compute_ewa_parameters(size_t swath_cols, size_t swath_rows, CR_TYPE *uimg, CR_TYPE *vimg, ewa_weight *ewaw, ewa_parameters *ewap) { ewa_param_type ux; ewa_param_type uy; ewa_param_type vx; ewa_param_type vy; ewa_param_type f_scale; // For testing: original C version uses doubles here // double ux; // double uy; // double vx; // double vy; // double f_scale; ewa_param_type d; ewa_param_type qmax; ewa_param_type distance_max; ewa_param_type delta_max; unsigned int rowsm1; unsigned int colsm1; unsigned int rowsov2; unsigned int col; ewa_parameters *this_ewap; qmax = ewaw->qmax; distance_max = ewaw->distance_max; delta_max = ewaw->delta_max; rowsm1 = swath_rows - 1; colsm1 = swath_cols - 1; rowsov2 = swath_rows / 2; for (col = 1, this_ewap=ewap + 1; col < colsm1; col++, this_ewap++) { ux = ((uimg[col - 1 + rowsov2 * swath_cols + 2] - uimg[col - 1 + rowsov2 * swath_cols]) / 2.0) * distance_max; vx = ((vimg[col - 1 + rowsov2 * swath_cols + 2] - vimg[col - 1 + rowsov2 * swath_cols]) / 2.0) * distance_max; uy = ((uimg[col + rowsm1 * swath_cols] - uimg[col]) / rowsm1) * distance_max; vy = ((vimg[col + rowsm1 * swath_cols] - vimg[col]) / rowsm1) * distance_max; f_scale = ux * vy - uy * vx; f_scale = f_scale * f_scale; if (f_scale < EPSILON) { f_scale = EPSILON; } f_scale = qmax / f_scale; this_ewap->a = (vx * vx + vy * vy) * f_scale; this_ewap->b = -2.0 * (ux * vx + uy * vy) * f_scale; this_ewap->c = (ux * ux + uy * uy) * f_scale; d = 4.0 * this_ewap->a * this_ewap->c - this_ewap->b * this_ewap->b; if (d < EPSILON) { d = EPSILON; } d = ((4.0 * qmax) / d); this_ewap->f = qmax; this_ewap->u_del = sqrt(this_ewap->c * d); this_ewap->v_del = sqrt(this_ewap->a * d); if (this_ewap->u_del > delta_max) { this_ewap->u_del = delta_max; } if (this_ewap->v_del > delta_max) { this_ewap->v_del = delta_max; } } // Copy the parameters from the penultimate column to the last column (this_ewap should be at the final column) *this_ewap = *(this_ewap - 1); // Copy the parameters from the second column to the first column *ewap = *(ewap + 1); return 0; } template int compute_ewa(size_t chan_count, int maximum_weight_mode, size_t swath_cols, size_t swath_rows, size_t grid_cols, size_t grid_rows, CR_TYPE *uimg, CR_TYPE *vimg, IMAGE_TYPE **images, IMAGE_TYPE img_fill, accum_type **grid_accums, weight_type **grid_weights, ewa_weight *ewaw, ewa_parameters *ewap) { // This was originally copied from a cython C file for 32-bit float inputs (that explains some of the weird parens and other syntax int got_point; unsigned int row; unsigned int col; ewa_parameters *this_ewap; int iu1; int iu2; int iv1; int iv2; int iu; int iv; CR_TYPE u0; CR_TYPE v0; weight_type ddq; weight_type dq; weight_type q; weight_type u; weight_type v; weight_type a2up1; weight_type au2; weight_type bu; weight_type weight; // Test: This is how the original fornav did its calculations // double u0; // double v0; // double ddq; // double dq; // double q; // double u; // double v; // double a2up1; // double au2; // double bu; // double weight; // double qfactor; int iw; IMAGE_TYPE this_val; unsigned int swath_offset; unsigned int grid_offset; size_t chan; got_point = 0; for (row = 0, swath_offset=0; row < swath_rows; row+=1) { for (col = 0, this_ewap = ewap; col < swath_cols; col++, this_ewap++, swath_offset++) { u0 = uimg[swath_offset]; v0 = vimg[swath_offset]; if (u0 < 0.0 || v0 < 0.0 || __isnan(u0) || npy_isnan(v0)) { continue; } iu1 = ((int)(u0 - this_ewap->u_del)); iu2 = ((int)(u0 + this_ewap->u_del)); iv1 = ((int)(v0 - this_ewap->v_del)); iv2 = ((int)(v0 + this_ewap->v_del)); if (iu1 < 0) { iu1 = 0; } if (iu2 >= grid_cols) { iu2 = (grid_cols - 1); } if (iv1 < 0) { iv1 = 0; } if (iv2 >= grid_rows) { iv2 = (grid_rows - 1); } if (iu1 < grid_cols && iu2 >= 0 && iv1 < grid_rows && iv2 >= 0) { got_point = 1; ddq = 2.0 * this_ewap->a; u = (iu1 - u0); a2up1 = (this_ewap->a * ((2.0 * u) + 1.0)); bu = this_ewap->b * u; au2 = this_ewap->a * u * u; for (iv = iv1; iv <= iv2; iv++) { v = (iv - v0); dq = (a2up1 + (this_ewap->b * v)); q = ((((this_ewap->c * v) + bu) * v) + au2); for (iu = iu1; iu <= iu2; iu++) { if ((q >= 0.0) && (q < this_ewap->f)) { iw = ((int)(q * ewaw->qfactor)); if (iw >= ewaw->count) { iw = (ewaw->count - 1); } weight = (ewaw->wtab[iw]); grid_offset = ((iv * grid_cols) + iu); for (chan = 0; chan < chan_count; chan+=1) { this_val = ((images[chan])[swath_offset]); if (maximum_weight_mode) { if (weight > grid_weights[chan][grid_offset]) { ((grid_weights[chan])[grid_offset]) = weight; if ((this_val == img_fill) || (__isnan(this_val))) { ((grid_accums[chan])[grid_offset]) = (accum_type)NPY_NANF; } else { ((grid_accums[chan])[grid_offset]) = (accum_type)this_val; } } } else { if ((this_val != img_fill) && !(__isnan(this_val))) { ((grid_weights[chan])[grid_offset]) += weight; ((grid_accums[chan])[grid_offset]) += (accum_type)this_val * weight; } } } } q += dq; dq += ddq; } } } } } /* function exit code */ return got_point; } // Overloaded functions for specific types for `write_grid_image` //static void write_grid_pixel(npy_uint8 *output_image, accum_type chanf) { // if (chanf < 0.0) { // *output_image = 0; // } else if (chanf > 255.0) { // *output_image = 255; // } else { // *output_image = (npy_uint8)chanf; // } //} inline void write_grid_pixel(npy_int8 *output_image, accum_type chanf) { if (chanf < -128.0) { *output_image = -128; } else if (chanf > 127.0) { *output_image = 127; } else { *output_image = (npy_int8)chanf; } } //static void write_grid_pixel(npy_uint16 *output_image, accum_type chanf) { // if (chanf < 0.0) { // *output_image = 0; // } else if (chanf > 65535.0) { // *output_image = 65535; // } else { // *output_image = (npy_uint16)chanf; // } //} //static void write_grid_pixel(npy_int16 *output_image, accum_type chanf) { // if (chanf < -32768.0) { // *output_image = -32768; // } else if (chanf > 32767.0) { // *output_image = 32767; // } else { // *output_image = (npy_int16)chanf; // } //} //static void write_grid_pixel(npy_uint32 *output_image, accum_type chanf) { // if (chanf < 0.0) { // *output_image = 0; // } else if (chanf > 4294967295.0) { // *output_image = 4294967295; // } else { // *output_image = (npy_uint32)chanf; // } //} //static void write_grid_pixel(npy_int32 *output_image, accum_type chanf) { // if (chanf < -2147483648.0) { // *output_image = -2147483648; // } else if (chanf > 2147483647.0) { // *output_image = 2147483647; // } else { // *output_image = (npy_int32)chanf; // } //} inline void write_grid_pixel(npy_float32 *output_image, accum_type chanf) { *output_image = (npy_float32)chanf; } inline void write_grid_pixel(npy_float64 *output_image, accum_type chanf) { *output_image = (npy_float64)chanf; } // End of overload functions for `write_grid_image` template inline accum_type get_rounding(GRID_TYPE *output_image) { return 0.5; } template<> inline accum_type get_rounding(npy_float32 *output_image) { return 0.0; } template<> inline accum_type get_rounding(npy_float64 *output_image) { return 0.0; } template unsigned int write_grid_image(GRID_TYPE *output_image, GRID_TYPE fill, size_t grid_cols, size_t grid_rows, accum_type *grid_accum, weight_type *grid_weights, int maximum_weight_mode, weight_type weight_sum_min) { accum_type chanf; unsigned int i; unsigned int valid_count = 0; size_t grid_size = grid_cols * grid_rows; if (weight_sum_min <= 0.0) { weight_sum_min = EPSILON; } for (i=0; i < grid_size; i++, grid_accum++, grid_weights++, output_image++) { // Calculate the elliptical weighted average value for each cell (float -> not-float needs rounding) // The fill value for the weight and accumulation arrays is static at NaN if (*grid_weights < weight_sum_min || __isnan(*grid_accum)) { chanf = (accum_type)NPY_NANF; } else if (maximum_weight_mode) { // keep the current value chanf = *grid_accum; } else if (*grid_accum >= 0.0) { chanf = *grid_accum / *grid_weights + get_rounding(output_image); } else { chanf = *grid_accum / *grid_weights - get_rounding(output_image); } if (__isnan(chanf)) { *output_image = (GRID_TYPE)fill; } else { valid_count++; write_grid_pixel(output_image, chanf); } } return valid_count; } // Col/Row as 32-bit floats template int compute_ewa_parameters(size_t, size_t, npy_float32*, npy_float32*, ewa_weight*, ewa_parameters*); template int compute_ewa(size_t, int, size_t, size_t, size_t, size_t, npy_float32*, npy_float32*, npy_float32**, npy_float32, accum_type**, weight_type**, ewa_weight*, ewa_parameters*); template int compute_ewa(size_t, int, size_t, size_t, size_t, size_t, npy_float32*, npy_float32*, npy_float64**, npy_float64, accum_type**, weight_type**, ewa_weight*, ewa_parameters*); template int compute_ewa(size_t, int, size_t, size_t, size_t, size_t, npy_float32*, npy_float32*, npy_int8**, npy_int8, accum_type**, weight_type**, ewa_weight*, ewa_parameters*); // Col/Row as 64-bit floats template int compute_ewa_parameters(size_t, size_t, npy_float64*, npy_float64*, ewa_weight*, ewa_parameters*); template int compute_ewa(size_t, int, size_t, size_t, size_t, size_t, npy_float64*, npy_float64*, npy_float32**, npy_float32, accum_type**, weight_type**, ewa_weight*, ewa_parameters*); template int compute_ewa(size_t, int, size_t, size_t, size_t, size_t, npy_float64*, npy_float64*, npy_float64**, npy_float64, accum_type**, weight_type**, ewa_weight*, ewa_parameters*); template int compute_ewa(size_t, int, size_t, size_t, size_t, size_t, npy_float64*, npy_float64*, npy_int8**, npy_int8, accum_type**, weight_type**, ewa_weight*, ewa_parameters*); // Output Grid types template unsigned int write_grid_image(npy_float32*, npy_float32, size_t, size_t, accum_type*, weight_type*, int, weight_type); template unsigned int write_grid_image(npy_float64*, npy_float64, size_t, size_t, accum_type*, weight_type*, int, weight_type); template unsigned int write_grid_image(npy_int8*, npy_int8, size_t, size_t, accum_type*, weight_type*, int, weight_type); pyresample-1.2.9/pyresample/ewa/_fornav_templates.h000066400000000000000000000042431302372600000225160ustar00rootroot00000000000000#ifndef _FORNAV_TEMPLATES_H #define _FORNAV_TEMPLATES_H // The types used for all of the intermediate storage between input swath pixels and output grid pixels // Mainly here for testing, but should never be a non-floating type typedef float weight_type; typedef float ewa_param_type; typedef float accum_type; //typedef double weight_type; //typedef double ewa_param_type; //typedef double accum_type; //const weight_type EPSILON = 1e-8; #define EPSILON (1e-8) typedef struct { ewa_param_type a; ewa_param_type b; ewa_param_type c; ewa_param_type f; ewa_param_type u_del; ewa_param_type v_del; } ewa_parameters; typedef struct { int count; weight_type min; weight_type distance_max; weight_type delta_max; weight_type sum_min; weight_type alpha; weight_type qmax; weight_type qfactor; weight_type *wtab; } ewa_weight; int initialize_weight(size_t chan_count, unsigned int weight_count, weight_type weight_min, weight_type weight_distance_max, weight_type weight_delta_max, weight_type weight_sum_min, ewa_weight *ewaw); void deinitialize_weight(ewa_weight *ewaw); accum_type **initialize_grid_accums(size_t chan_count, size_t grid_cols, size_t grid_rows); weight_type **initialize_grid_weights(size_t chan_count, size_t grid_cols, size_t grid_rows); void deinitialize_grids(size_t chan_count, void **grids); template int compute_ewa_parameters(size_t swath_cols, size_t swath_rows, CR_TYPE *uimg, CR_TYPE *vimg, ewa_weight *ewaw, ewa_parameters *ewap); template extern int compute_ewa(size_t chan_count, int maximum_weight_mode, size_t swath_cols, size_t swath_rows, size_t grid_cols, size_t grid_rows, CR_TYPE *uimg, CR_TYPE *vimg, IMAGE_TYPE **images, IMAGE_TYPE img_fill, accum_type **grid_accums, weight_type **grid_weights, ewa_weight *ewaw, ewa_parameters *ewap); template unsigned int write_grid_image(GRID_TYPE *output_image, GRID_TYPE fill, size_t grid_cols, size_t grid_rows, accum_type *grid_accum, weight_type *grid_weights, int maximum_weight_mode, weight_type weight_sum_min); #endifpyresample-1.2.9/pyresample/ewa/_ll2cr.c000066400000000000000000040127151302372600000201650ustar00rootroot00000000000000/* Generated by Cython 0.24 */ /* BEGIN: Cython Metadata { "distutils": { "depends": [], "extra_compile_args": [ "-O3", "-Wno-unused-function" ] } } END: Cython Metadata */ #define PY_SSIZE_T_CLEAN #include "Python.h" #ifndef Py_PYTHON_H #error Python headers needed to compile C extensions, please install development version of Python. #elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03020000) #error Cython requires Python 2.6+ or Python 3.2+. #else #define CYTHON_ABI "0_24" #include #ifndef offsetof #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) #endif #if !defined(WIN32) && !defined(MS_WINDOWS) #ifndef __stdcall #define __stdcall #endif #ifndef __cdecl #define __cdecl #endif #ifndef __fastcall #define __fastcall #endif #endif #ifndef DL_IMPORT #define DL_IMPORT(t) t #endif #ifndef DL_EXPORT #define DL_EXPORT(t) t #endif #ifndef PY_LONG_LONG #define PY_LONG_LONG LONG_LONG #endif #ifndef Py_HUGE_VAL #define Py_HUGE_VAL HUGE_VAL #endif #ifdef PYPY_VERSION #define CYTHON_COMPILING_IN_PYPY 1 #define CYTHON_COMPILING_IN_CPYTHON 0 #else #define CYTHON_COMPILING_IN_PYPY 0 #define CYTHON_COMPILING_IN_CPYTHON 1 #endif #if !defined(CYTHON_USE_PYLONG_INTERNALS) && CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x02070000 #define CYTHON_USE_PYLONG_INTERNALS 1 #endif #if CYTHON_USE_PYLONG_INTERNALS #include "longintrepr.h" #undef SHIFT #undef BASE #undef MASK #endif #if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) #define Py_OptimizeFlag 0 #endif #define __PYX_BUILD_PY_SSIZE_T "n" #define CYTHON_FORMAT_SSIZE_T "z" #if PY_MAJOR_VERSION < 3 #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyClass_Type #else #define __Pyx_BUILTIN_MODULE_NAME "builtins" #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) #define __Pyx_DefaultClassType PyType_Type #endif #ifndef Py_TPFLAGS_CHECKTYPES #define Py_TPFLAGS_CHECKTYPES 0 #endif #ifndef Py_TPFLAGS_HAVE_INDEX #define Py_TPFLAGS_HAVE_INDEX 0 #endif #ifndef Py_TPFLAGS_HAVE_NEWBUFFER #define Py_TPFLAGS_HAVE_NEWBUFFER 0 #endif #ifndef Py_TPFLAGS_HAVE_FINALIZE #define Py_TPFLAGS_HAVE_FINALIZE 0 #endif #if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) #define CYTHON_PEP393_ENABLED 1 #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ 0 : _PyUnicode_Ready((PyObject *)(op))) #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? 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struct __Pyx_StructField_* fields; size_t size; size_t arraysize[8]; int ndim; char typegroup; char is_unsigned; int flags; } __Pyx_TypeInfo; typedef struct __Pyx_StructField_ { __Pyx_TypeInfo* type; const char* name; size_t offset; } __Pyx_StructField; typedef struct { __Pyx_StructField* field; size_t parent_offset; } __Pyx_BufFmt_StackElem; typedef struct { __Pyx_StructField root; __Pyx_BufFmt_StackElem* head; size_t fmt_offset; size_t new_count, enc_count; size_t struct_alignment; int is_complex; char enc_type; char new_packmode; char enc_packmode; char is_valid_array; } __Pyx_BufFmt_Context; /* MemviewSliceStruct.proto */ struct __pyx_memoryview_obj; typedef struct { struct __pyx_memoryview_obj *memview; char *data; Py_ssize_t shape[8]; Py_ssize_t strides[8]; Py_ssize_t suboffsets[8]; } __Pyx_memviewslice; /* Atomics.proto */ #include #ifndef CYTHON_ATOMICS #define CYTHON_ATOMICS 1 #endif #define __pyx_atomic_int_type int #if CYTHON_ATOMICS && __GNUC__ >= 4 && (__GNUC_MINOR__ > 1 ||\ (__GNUC_MINOR__ == 1 && __GNUC_PATCHLEVEL >= 2)) &&\ !defined(__i386__) #define __pyx_atomic_incr_aligned(value, lock) __sync_fetch_and_add(value, 1) #define __pyx_atomic_decr_aligned(value, lock) __sync_fetch_and_sub(value, 1) #ifdef __PYX_DEBUG_ATOMICS #warning "Using GNU atomics" #endif #elif CYTHON_ATOMICS && defined(_MSC_VER) && 0 #include #undef __pyx_atomic_int_type #define __pyx_atomic_int_type LONG #define __pyx_atomic_incr_aligned(value, lock) InterlockedIncrement(value) #define __pyx_atomic_decr_aligned(value, lock) InterlockedDecrement(value) #ifdef __PYX_DEBUG_ATOMICS #pragma message ("Using MSVC atomics") #endif #elif CYTHON_ATOMICS && (defined(__ICC) || defined(__INTEL_COMPILER)) && 0 #define __pyx_atomic_incr_aligned(value, lock) _InterlockedIncrement(value) #define __pyx_atomic_decr_aligned(value, lock) _InterlockedDecrement(value) #ifdef __PYX_DEBUG_ATOMICS #warning "Using Intel atomics" #endif #else #undef CYTHON_ATOMICS #define CYTHON_ATOMICS 0 #ifdef __PYX_DEBUG_ATOMICS #warning "Not using atomics" #endif #endif typedef volatile __pyx_atomic_int_type __pyx_atomic_int; #if CYTHON_ATOMICS #define __pyx_add_acquisition_count(memview)\ __pyx_atomic_incr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #define __pyx_sub_acquisition_count(memview)\ __pyx_atomic_decr_aligned(__pyx_get_slice_count_pointer(memview), memview->lock) #else #define __pyx_add_acquisition_count(memview)\ __pyx_add_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #define __pyx_sub_acquisition_count(memview)\ __pyx_sub_acquisition_count_locked(__pyx_get_slice_count_pointer(memview), memview->lock) #endif /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":725 * # in Cython to enable them only on the right systems. * * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t */ typedef npy_int8 __pyx_t_5numpy_int8_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":726 * * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t */ typedef npy_int16 __pyx_t_5numpy_int16_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":727 * ctypedef npy_int8 int8_t * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< * ctypedef npy_int64 int64_t * #ctypedef npy_int96 int96_t */ typedef npy_int32 __pyx_t_5numpy_int32_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":728 * ctypedef npy_int16 int16_t * ctypedef npy_int32 int32_t * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< * #ctypedef npy_int96 int96_t * #ctypedef npy_int128 int128_t */ typedef npy_int64 __pyx_t_5numpy_int64_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":732 * #ctypedef npy_int128 int128_t * * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t */ typedef npy_uint8 __pyx_t_5numpy_uint8_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":733 * * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t */ typedef npy_uint16 __pyx_t_5numpy_uint16_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":734 * ctypedef npy_uint8 uint8_t * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< * ctypedef npy_uint64 uint64_t * #ctypedef npy_uint96 uint96_t */ typedef npy_uint32 __pyx_t_5numpy_uint32_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":735 * ctypedef npy_uint16 uint16_t * ctypedef npy_uint32 uint32_t * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< * #ctypedef npy_uint96 uint96_t * #ctypedef npy_uint128 uint128_t */ typedef npy_uint64 __pyx_t_5numpy_uint64_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":739 * #ctypedef npy_uint128 uint128_t * * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< * ctypedef npy_float64 float64_t * #ctypedef npy_float80 float80_t */ typedef npy_float32 __pyx_t_5numpy_float32_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":740 * * ctypedef npy_float32 float32_t * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< * #ctypedef npy_float80 float80_t * #ctypedef npy_float128 float128_t */ typedef npy_float64 __pyx_t_5numpy_float64_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":749 * # The int types are mapped a bit surprising -- * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t # <<<<<<<<<<<<<< * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t */ typedef npy_long __pyx_t_5numpy_int_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":750 * # numpy.int corresponds to 'l' and numpy.long to 'q' * ctypedef npy_long int_t * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< * ctypedef npy_longlong longlong_t * */ typedef npy_longlong __pyx_t_5numpy_long_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":751 * ctypedef npy_long int_t * ctypedef npy_longlong long_t * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< * * ctypedef npy_ulong uint_t */ typedef npy_longlong __pyx_t_5numpy_longlong_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":753 * ctypedef npy_longlong longlong_t * * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t */ typedef npy_ulong __pyx_t_5numpy_uint_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":754 * * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< * ctypedef npy_ulonglong ulonglong_t * */ typedef npy_ulonglong __pyx_t_5numpy_ulong_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":755 * ctypedef npy_ulong uint_t * ctypedef npy_ulonglong ulong_t * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< * * ctypedef npy_intp intp_t */ typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":757 * ctypedef npy_ulonglong ulonglong_t * * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< * ctypedef npy_uintp uintp_t * */ typedef npy_intp __pyx_t_5numpy_intp_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":758 * * ctypedef npy_intp intp_t * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< * * ctypedef npy_double float_t */ typedef npy_uintp __pyx_t_5numpy_uintp_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":760 * ctypedef npy_uintp uintp_t * * ctypedef npy_double float_t # <<<<<<<<<<<<<< * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t */ typedef npy_double __pyx_t_5numpy_float_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":761 * * ctypedef npy_double float_t * ctypedef npy_double double_t # <<<<<<<<<<<<<< * ctypedef npy_longdouble longdouble_t * */ typedef npy_double __pyx_t_5numpy_double_t; /* "../../../../../opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/Cython/Includes/numpy/__init__.pxd":762 * ctypedef npy_double float_t * ctypedef npy_double double_t * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< * * ctypedef npy_cfloat cfloat_t */ typedef npy_longdouble __pyx_t_5numpy_longdouble_t; 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(long)__Pyx_PyUnicode_AsPy_UCS4(c) : __Pyx__PyObject_Ord(c)) #else #define __Pyx_PyObject_Ord(c) __Pyx__PyObject_Ord(c) #endif static long __Pyx__PyObject_Ord(PyObject* c); /* SetItemInt.proto */ #define __Pyx_SetItemInt(o, i, v, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_SetItemInt_Fast(o, (Py_ssize_t)i, v, is_list, wraparound, boundscheck) :\ (is_list ? 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static CYTHON_INLINE int __Pyx_dict_iter_next(PyObject* dict_or_iter, Py_ssize_t orig_length, Py_ssize_t* ppos, PyObject** pkey, PyObject** pvalue, PyObject** pitem, int is_dict); /* ListAppend.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE int __Pyx_PyList_Append(PyObject* list, PyObject* x) { PyListObject* L = (PyListObject*) list; Py_ssize_t len = Py_SIZE(list); if (likely(L->allocated > len) & likely(len > (L->allocated >> 1))) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); Py_SIZE(list) = len+1; return 0; } return PyList_Append(list, x); } #else #define __Pyx_PyList_Append(L,x) PyList_Append(L,x) #endif /* ArgTypeTest.proto */ static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, const char *name, int exact); /* BufferFormatCheck.proto */ static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, __Pyx_BufFmt_StackElem* stack, __Pyx_TypeInfo* type); // PROTO /* MemviewSliceInit.proto */ #define __Pyx_BUF_MAX_NDIMS %(BUF_MAX_NDIMS)d #define __Pyx_MEMVIEW_DIRECT 1 #define __Pyx_MEMVIEW_PTR 2 #define __Pyx_MEMVIEW_FULL 4 #define __Pyx_MEMVIEW_CONTIG 8 #define __Pyx_MEMVIEW_STRIDED 16 #define __Pyx_MEMVIEW_FOLLOW 32 #define __Pyx_IS_C_CONTIG 1 #define __Pyx_IS_F_CONTIG 2 static int __Pyx_init_memviewslice( struct __pyx_memoryview_obj *memview, int ndim, __Pyx_memviewslice *memviewslice, int memview_is_new_reference); static CYTHON_INLINE int __pyx_add_acquisition_count_locked( __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); static CYTHON_INLINE int __pyx_sub_acquisition_count_locked( __pyx_atomic_int *acquisition_count, PyThread_type_lock lock); #define __pyx_get_slice_count_pointer(memview) (memview->acquisition_count_aligned_p) #define __pyx_get_slice_count(memview) (*__pyx_get_slice_count_pointer(memview)) #define __PYX_INC_MEMVIEW(slice, have_gil) __Pyx_INC_MEMVIEW(slice, have_gil, __LINE__) #define __PYX_XDEC_MEMVIEW(slice, have_gil) __Pyx_XDEC_MEMVIEW(slice, have_gil, __LINE__) static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *, int, int); static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *, int, int); /* ExtTypeTest.proto */ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); /* IncludeStringH.proto */ #include /* BytesEquals.proto */ static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals); /* UnicodeEquals.proto */ static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals); /* StrEquals.proto */ #if PY_MAJOR_VERSION >= 3 #define __Pyx_PyString_Equals __Pyx_PyUnicode_Equals #else #define __Pyx_PyString_Equals __Pyx_PyBytes_Equals #endif /* None.proto */ static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t, Py_ssize_t); /* UnaryNegOverflows.proto */ #define UNARY_NEG_WOULD_OVERFLOW(x)\ (((x) < 0) & ((unsigned long)(x) == 0-(unsigned long)(x))) static CYTHON_UNUSED int __pyx_array_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *); /*proto*/ /* GetAttr.proto */ static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *, PyObject *); /* decode_c_string.proto */ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( const char* cstring, Py_ssize_t start, Py_ssize_t stop, const char* encoding, const char* errors, PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); /* SwapException.proto */ #if CYTHON_COMPILING_IN_CPYTHON #define __Pyx_ExceptionSwap(type, value, tb) __Pyx__ExceptionSwap(__pyx_tstate, type, value, tb) static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); #else static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb); #endif /* GetItemInt.proto */ #define __Pyx_GetItemInt(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_Fast(o, (Py_ssize_t)i, is_list, wraparound, boundscheck) :\ (is_list ? (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL) :\ __Pyx_GetItemInt_Generic(o, to_py_func(i)))) #define __Pyx_GetItemInt_List(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_List_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, "list index out of range"), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); #define __Pyx_GetItemInt_Tuple(o, i, type, is_signed, to_py_func, is_list, wraparound, boundscheck)\ (__Pyx_fits_Py_ssize_t(i, type, is_signed) ?\ __Pyx_GetItemInt_Tuple_Fast(o, (Py_ssize_t)i, wraparound, boundscheck) :\ (PyErr_SetString(PyExc_IndexError, "tuple index out of range"), (PyObject*)NULL)) static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, int wraparound, int boundscheck); static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j); static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, int wraparound, int boundscheck); static CYTHON_UNUSED int __pyx_memoryview_getbuffer(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/ /* ListCompAppend.proto */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE int __Pyx_ListComp_Append(PyObject* list, PyObject* x) { PyListObject* L = (PyListObject*) list; Py_ssize_t len = Py_SIZE(list); if (likely(L->allocated > len)) { Py_INCREF(x); PyList_SET_ITEM(list, len, x); Py_SIZE(list) = len+1; return 0; } return PyList_Append(list, x); } #else #define __Pyx_ListComp_Append(L,x) PyList_Append(L,x) #endif /* PyIntBinop.proto */ #if CYTHON_COMPILING_IN_CPYTHON static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, long intval, int inplace); #else #define __Pyx_PyInt_AddObjC(op1, op2, intval, inplace)\ (inplace ? 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/* FetchCommonType.proto */ static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type); /* CythonFunction.proto */ #define __Pyx_CyFunction_USED 1 #include #define __Pyx_CYFUNCTION_STATICMETHOD 0x01 #define __Pyx_CYFUNCTION_CLASSMETHOD 0x02 #define __Pyx_CYFUNCTION_CCLASS 0x04 #define __Pyx_CyFunction_GetClosure(f)\ (((__pyx_CyFunctionObject *) (f))->func_closure) #define __Pyx_CyFunction_GetClassObj(f)\ (((__pyx_CyFunctionObject *) (f))->func_classobj) #define __Pyx_CyFunction_Defaults(type, f)\ ((type *)(((__pyx_CyFunctionObject *) (f))->defaults)) #define __Pyx_CyFunction_SetDefaultsGetter(f, g)\ ((__pyx_CyFunctionObject *) (f))->defaults_getter = (g) typedef struct { PyCFunctionObject func; #if PY_VERSION_HEX < 0x030500A0 PyObject *func_weakreflist; #endif PyObject *func_dict; PyObject *func_name; PyObject *func_qualname; PyObject *func_doc; PyObject *func_globals; PyObject *func_code; PyObject *func_closure; PyObject *func_classobj; void *defaults; int defaults_pyobjects; int flags; 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static PyObject *__Pyx_Py3ClassCreate(PyObject *metaclass, PyObject *name, PyObject *bases, PyObject *dict, PyObject *mkw, int calculate_metaclass, int allow_py2_metaclass); /* FusedFunction.proto */ typedef struct { __pyx_CyFunctionObject func; PyObject *__signatures__; PyObject *type; PyObject *self; } __pyx_FusedFunctionObject; #define __pyx_FusedFunction_NewEx(ml, flags, qualname, self, module, globals, code)\ __pyx_FusedFunction_New(__pyx_FusedFunctionType, ml, flags, qualname, self, module, globals, code) static PyObject *__pyx_FusedFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags, PyObject *qualname, PyObject *self, PyObject *module, PyObject *globals, PyObject *code); static int __pyx_FusedFunction_clear(__pyx_FusedFunctionObject *self); static PyTypeObject *__pyx_FusedFunctionType = NULL; static int __pyx_FusedFunction_init(void); #define __Pyx_FusedFunction_USED /* CodeObjectCache.proto */ typedef struct { PyCodeObject* code_object; int code_line; } __Pyx_CodeObjectCacheEntry; struct __Pyx_CodeObjectCache { int count; int max_count; __Pyx_CodeObjectCacheEntry* entries; }; static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); static PyCodeObject *__pyx_find_code_object(int code_line); static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); /* AddTraceback.proto */ static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename); #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); static void __Pyx_ReleaseBuffer(Py_buffer *view); #else #define __Pyx_GetBuffer PyObject_GetBuffer #define __Pyx_ReleaseBuffer PyBuffer_Release #endif /* BufferStructDeclare.proto */ typedef struct { Py_ssize_t shape, strides, suboffsets; } __Pyx_Buf_DimInfo; typedef struct { size_t refcount; Py_buffer pybuffer; } __Pyx_Buffer; typedef struct { __Pyx_Buffer *rcbuffer; char *data; __Pyx_Buf_DimInfo diminfo[8]; } __Pyx_LocalBuf_ND; /* None.proto */ static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0}; static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1}; /* MemviewSliceIsContig.proto */ static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim); /* OverlappingSlices.proto */ static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, __Pyx_memviewslice *slice2, int ndim, size_t itemsize); /* Capsule.proto */ static CYTHON_INLINE PyObject *__pyx_capsule_create(void *p, const char *sig); /* TypeInfoCompare.proto */ static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b); /* MemviewSliceValidateAndInit.proto */ static int __Pyx_ValidateAndInit_memviewslice( int *axes_specs, int c_or_f_flag, int buf_flags, int ndim, __Pyx_TypeInfo *dtype, __Pyx_BufFmt_StackElem stack[], __Pyx_memviewslice *memviewslice, PyObject *original_obj); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5numpy_float64_t(PyObject *); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); /* BytesContains.proto */ static CYTHON_INLINE int __Pyx_BytesContains(PyObject* bytes, char character); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_int(unsigned int value); /* None.proto */ #if CYTHON_CCOMPLEX #ifdef __cplusplus #define __Pyx_CREAL(z) ((z).real()) #define __Pyx_CIMAG(z) ((z).imag()) #else #define __Pyx_CREAL(z) (__real__(z)) #define __Pyx_CIMAG(z) (__imag__(z)) #endif #else #define __Pyx_CREAL(z) ((z).real) #define __Pyx_CIMAG(z) ((z).imag) #endif #if defined(__cplusplus) && CYTHON_CCOMPLEX && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) #define __Pyx_SET_CREAL(z,x) ((z).real(x)) #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) #else #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) #endif /* None.proto */ static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float); /* None.proto */ #if CYTHON_CCOMPLEX #define __Pyx_c_eqf(a, b) ((a)==(b)) #define __Pyx_c_sumf(a, b) ((a)+(b)) #define __Pyx_c_difff(a, b) ((a)-(b)) #define __Pyx_c_prodf(a, b) ((a)*(b)) #define __Pyx_c_quotf(a, b) ((a)/(b)) #define __Pyx_c_negf(a) (-(a)) #ifdef __cplusplus #define __Pyx_c_is_zerof(z) ((z)==(float)0) #define __Pyx_c_conjf(z) (::std::conj(z)) #if 1 #define __Pyx_c_absf(z) (::std::abs(z)) #define __Pyx_c_powf(a, b) (::std::pow(a, b)) #endif #else #define __Pyx_c_is_zerof(z) ((z)==0) #define __Pyx_c_conjf(z) (conjf(z)) #if 1 #define __Pyx_c_absf(z) (cabsf(z)) #define __Pyx_c_powf(a, b) (cpowf(a, b)) #endif #endif #else static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex, __pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex); static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex); #if 1 static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex); static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex, __pyx_t_float_complex); #endif #endif /* None.proto */ static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double); /* None.proto */ #if CYTHON_CCOMPLEX #define __Pyx_c_eq(a, b) ((a)==(b)) #define __Pyx_c_sum(a, b) ((a)+(b)) #define __Pyx_c_diff(a, b) ((a)-(b)) #define __Pyx_c_prod(a, b) ((a)*(b)) #define __Pyx_c_quot(a, b) ((a)/(b)) #define __Pyx_c_neg(a) (-(a)) #ifdef __cplusplus #define __Pyx_c_is_zero(z) ((z)==(double)0) #define __Pyx_c_conj(z) (::std::conj(z)) #if 1 #define __Pyx_c_abs(z) (::std::abs(z)) #define __Pyx_c_pow(a, b) (::std::pow(a, b)) #endif #else #define __Pyx_c_is_zero(z) ((z)==0) #define __Pyx_c_conj(z) (conj(z)) #if 1 #define __Pyx_c_abs(z) (cabs(z)) #define __Pyx_c_pow(a, b) (cpow(a, b)) #endif #endif #else static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex, __pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex); static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex); #if 1 static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex); static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex, __pyx_t_double_complex); #endif #endif /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value); /* CIntToPy.proto */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value); /* MemviewSliceCopyTemplate.proto */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, const char *mode, int ndim, size_t sizeof_dtype, int contig_flag, int dtype_is_object); /* CIntFromPy.proto */ static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *); /* CIntFromPy.proto */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); /* ObjectToMemviewSlice.proto */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_5numpy_float64_t(PyObject *); /* CheckBinaryVersion.proto */ static int __Pyx_check_binary_version(void); /* PyIdentifierFromString.proto */ #if !defined(__Pyx_PyIdentifier_FromString) #if PY_MAJOR_VERSION < 3 #define __Pyx_PyIdentifier_FromString(s) PyString_FromString(s) #else #define __Pyx_PyIdentifier_FromString(s) PyUnicode_FromString(s) #endif #endif /* ModuleImport.proto */ static PyObject *__Pyx_ImportModule(const char *name); /* TypeImport.proto */ static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict); /* InitStrings.proto */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); static PyObject *__pyx_array_get_memview(struct __pyx_array_obj *__pyx_v_self); /* proto*/ static char *__pyx_memoryview_get_item_pointer(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto*/ static PyObject *__pyx_memoryview_is_slice(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj); /* proto*/ static PyObject *__pyx_memoryview_setitem_slice_assignment(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_dst, PyObject *__pyx_v_src); /* proto*/ static PyObject *__pyx_memoryview_setitem_slice_assign_scalar(struct __pyx_memoryview_obj *__pyx_v_self, struct __pyx_memoryview_obj *__pyx_v_dst, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryview_setitem_indexed(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryview_convert_item_to_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ static PyObject *__pyx_memoryview_assign_item_from_object(struct __pyx_memoryview_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ static PyObject *__pyx_memoryviewslice_convert_item_to_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp); /* proto*/ static PyObject *__pyx_memoryviewslice_assign_item_from_object(struct __pyx_memoryviewslice_obj *__pyx_v_self, char *__pyx_v_itemp, PyObject *__pyx_v_value); /* proto*/ /* Module declarations from 'cython.view' */ /* Module declarations from 'cython' */ /* Module declarations from 'cpython.version' */ /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.type' */ static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; /* Module declarations from 'libc.string' */ /* Module declarations from 'libc.stdio' */ /* Module declarations from 'cpython.object' */ /* Module declarations from 'cpython.ref' */ /* Module declarations from 'cpython.exc' */ /* Module declarations from 'cpython.module' */ /* Module declarations from 'cpython.mem' */ /* Module declarations from 'cpython.tuple' */ /* Module declarations from 'cpython.list' */ /* Module declarations from 'cpython.sequence' */ /* Module declarations from 'cpython.mapping' */ /* Module declarations from 'cpython.iterator' */ /* Module declarations from 'cpython.number' */ /* Module declarations from 'cpython.int' */ /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.bool' */ static PyTypeObject *__pyx_ptype_7cpython_4bool_bool = 0; /* Module declarations from 'cpython.long' */ /* Module declarations from 'cpython.float' */ /* Module declarations from '__builtin__' */ /* Module declarations from 'cpython.complex' */ static PyTypeObject *__pyx_ptype_7cpython_7complex_complex = 0; /* Module declarations from 'cpython.string' */ /* Module declarations from 'cpython.unicode' */ /* Module declarations from 'cpython.dict' */ /* Module declarations from 'cpython.instance' */ /* Module declarations from 'cpython.function' */ /* Module declarations from 'cpython.method' */ /* Module declarations from 'cpython.weakref' */ /* Module declarations from 'cpython.getargs' */ /* Module declarations from 'cpython.pythread' */ /* Module declarations from 'cpython.pystate' */ /* Module declarations from 'cpython.cobject' */ /* Module declarations from 'cpython.oldbuffer' */ /* Module declarations from 'cpython.set' */ /* Module declarations from 'cpython.buffer' */ /* Module declarations from 'cpython.bytes' */ /* Module declarations from 'cpython.pycapsule' */ /* Module declarations from 'cpython' */ /* Module declarations from 'libc.stdlib' */ /* Module declarations from 'numpy' */ /* Module declarations from 'numpy' */ static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/ /* Module declarations from 'pyresample.ewa._ll2cr' */ static PyTypeObject *__pyx_array_type = 0; static PyTypeObject *__pyx_MemviewEnum_type = 0; static PyTypeObject *__pyx_memoryview_type = 0; static PyTypeObject *__pyx_memoryviewslice_type = 0; static PyObject *generic = 0; static PyObject *strided = 0; static PyObject *indirect = 0; static PyObject *contiguous = 0; static PyObject *indirect_contiguous = 0; static int __pyx_memoryview_thread_locks_used; static PyThread_type_lock __pyx_memoryview_thread_locks[8]; static struct __pyx_array_obj *__pyx_array_new(PyObject *, Py_ssize_t, char *, char *, char *); /*proto*/ static void *__pyx_align_pointer(void *, size_t); /*proto*/ static PyObject *__pyx_memoryview_new(PyObject *, int, int, __Pyx_TypeInfo *); /*proto*/ static CYTHON_INLINE int __pyx_memoryview_check(PyObject *); /*proto*/ static PyObject *_unellipsify(PyObject *, int); /*proto*/ static PyObject *assert_direct_dimensions(Py_ssize_t *, int); /*proto*/ static struct __pyx_memoryview_obj *__pyx_memview_slice(struct __pyx_memoryview_obj *, PyObject *); /*proto*/ static int __pyx_memoryview_slice_memviewslice(__Pyx_memviewslice *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int *, Py_ssize_t, Py_ssize_t, Py_ssize_t, int, int, int, int); /*proto*/ static char *__pyx_pybuffer_index(Py_buffer *, char *, Py_ssize_t, Py_ssize_t); /*proto*/ static int __pyx_memslice_transpose(__Pyx_memviewslice *); /*proto*/ static PyObject *__pyx_memoryview_fromslice(__Pyx_memviewslice, int, PyObject *(*)(char *), int (*)(char *, PyObject *), int); /*proto*/ static __Pyx_memviewslice *__pyx_memoryview_get_slice_from_memoryview(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static void __pyx_memoryview_slice_copy(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static PyObject *__pyx_memoryview_copy_object(struct __pyx_memoryview_obj *); /*proto*/ static PyObject *__pyx_memoryview_copy_object_from_slice(struct __pyx_memoryview_obj *, __Pyx_memviewslice *); /*proto*/ static Py_ssize_t abs_py_ssize_t(Py_ssize_t); /*proto*/ static char __pyx_get_best_slice_order(__Pyx_memviewslice *, int); /*proto*/ static void _copy_strided_to_strided(char *, Py_ssize_t *, char *, Py_ssize_t *, Py_ssize_t *, Py_ssize_t *, int, size_t); /*proto*/ static void copy_strided_to_strided(__Pyx_memviewslice *, __Pyx_memviewslice *, int, size_t); /*proto*/ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *, int); /*proto*/ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *, Py_ssize_t *, Py_ssize_t, int, char); /*proto*/ static void *__pyx_memoryview_copy_data_to_temp(__Pyx_memviewslice *, __Pyx_memviewslice *, char, int); /*proto*/ static int __pyx_memoryview_err_extents(int, Py_ssize_t, Py_ssize_t); /*proto*/ static int __pyx_memoryview_err_dim(PyObject *, char *, int); /*proto*/ static int __pyx_memoryview_err(PyObject *, char *); /*proto*/ static int __pyx_memoryview_copy_contents(__Pyx_memviewslice, __Pyx_memviewslice, int, int, int); /*proto*/ static void __pyx_memoryview_broadcast_leading(__Pyx_memviewslice *, int, int); /*proto*/ static void __pyx_memoryview_refcount_copying(__Pyx_memviewslice *, int, int, int); /*proto*/ static void __pyx_memoryview_refcount_objects_in_slice_with_gil(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ static void __pyx_memoryview_refcount_objects_in_slice(char *, Py_ssize_t *, Py_ssize_t *, int, int); /*proto*/ static void __pyx_memoryview_slice_assign_scalar(__Pyx_memviewslice *, int, size_t, void *, int); /*proto*/ static void __pyx_memoryview__slice_assign_scalar(char *, Py_ssize_t *, Py_ssize_t *, int, size_t, void *); /*proto*/ static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t = { "float64_t", NULL, sizeof(__pyx_t_5numpy_float64_t), { 0 }, 0, 'R', 0, 0 }; #define __Pyx_MODULE_NAME "pyresample.ewa._ll2cr" int __pyx_module_is_main_pyresample__ewa___ll2cr = 0; /* Implementation of 'pyresample.ewa._ll2cr' */ static PyObject *__pyx_builtin_super; static PyObject *__pyx_builtin_ImportError; static PyObject *__pyx_builtin_AttributeError; static PyObject *__pyx_builtin_TypeError; static PyObject *__pyx_builtin_zip; static PyObject *__pyx_builtin_range; static PyObject *__pyx_builtin_ValueError; static PyObject *__pyx_builtin_RuntimeError; static PyObject *__pyx_builtin_MemoryError; static PyObject *__pyx_builtin_enumerate; static PyObject *__pyx_builtin_Ellipsis; static PyObject *__pyx_builtin_id; static PyObject *__pyx_builtin_IndexError; static const char __pyx_k_O[] = "O"; static const char __pyx_k_c[] = "c"; static const char __pyx_k_h[] = "h"; static const char __pyx_k_p[] = "p"; static const char __pyx_k_w[] = "w"; static const char __pyx_k__2[] = "()"; static const char __pyx_k__4[] = "|"; static const char __pyx_k_id[] = "id"; static const char __pyx_k_ox[] = "ox"; static const char __pyx_k_oy[] = "oy"; static const char __pyx_k_x0[] = "x0"; static const char __pyx_k_x1[] = "x1"; static const char __pyx_k_x2[] = "x2"; static const char __pyx_k_y0[] = "y0"; static const char __pyx_k_y1[] = "y1"; static const char __pyx_k_y2[] = "y2"; static const char __pyx_k_col[] = "col"; static const char __pyx_k_doc[] = "__doc__"; static const char __pyx_k_fwd[] = "_fwd"; static const char __pyx_k_get[] = "get"; static const char __pyx_k_inv[] = "_inv"; static const char __pyx_k_obj[] = "obj"; static const char __pyx_k_row[] = "row"; static const char __pyx_k_zip[] = "zip"; static const char __pyx_k_Proj[] = "Proj"; static const char __pyx_k_args[] = "args"; static const char __pyx_k_base[] = "base"; static const char __pyx_k_call[] = "__call__"; static const char __pyx_k_kind[] = "kind"; static const char __pyx_k_lat0[] = "lat0"; static const char __pyx_k_lat1[] = "lat1"; static const char __pyx_k_lats[] = "lats"; static const char __pyx_k_lon0[] = "lon0"; static const char __pyx_k_lon1[] = "lon1"; static const char __pyx_k_lons[] = "lons"; static const char __pyx_k_main[] = "__main__"; static const char __pyx_k_mode[] = "mode"; static const char __pyx_k_name[] = "name"; static const char __pyx_k_ndim[] = "ndim"; static const char __pyx_k_pack[] = "pack"; static const char __pyx_k_proj[] = "_proj"; static const char __pyx_k_self[] = "self"; static const char __pyx_k_size[] = "size"; static const char __pyx_k_step[] = "step"; static const char __pyx_k_stop[] = "stop"; static const char __pyx_k_test[] = "__test__"; static const char __pyx_k_xmax[] = "xmax"; static const char __pyx_k_xmin[] = "xmin"; static const char __pyx_k_ymax[] = "ymax"; static const char __pyx_k_ymin[] = "ymin"; static const char __pyx_k_ASCII[] = "ASCII"; static const char __pyx_k_class[] = "__class__"; static const char __pyx_k_dtype[] = "dtype"; static const char __pyx_k_error[] = "error"; static const char __pyx_k_flags[] = "flags"; static const char __pyx_k_numpy[] = "numpy"; static const char __pyx_k_range[] = "range"; static const char __pyx_k_shape[] = "shape"; static const char __pyx_k_split[] = "split"; static const char __pyx_k_start[] = "start"; static const char __pyx_k_strip[] = "strip"; static const char __pyx_k_super[] = "super"; static const char __pyx_k_width[] = "width"; static const char __pyx_k_x_tmp[] = "x_tmp"; static const char __pyx_k_y_tmp[] = "y_tmp"; static const char __pyx_k_MyProj[] = "MyProj"; static const char __pyx_k_encode[] = "encode"; static const char __pyx_k_format[] = "format"; static const char __pyx_k_height[] = "height"; static const char __pyx_k_import[] = "__import__"; static const char __pyx_k_kwargs[] = "kwargs"; static const char __pyx_k_module[] = "__module__"; static const char __pyx_k_name_2[] = "__name__"; static const char __pyx_k_pyproj[] = "pyproj"; static const char __pyx_k_struct[] = "struct"; static const char __pyx_k_unpack[] = "unpack"; static const char __pyx_k_fill_in[] = "fill_in"; static const char __pyx_k_fortran[] = "fortran"; static const char __pyx_k_inverse[] = "inverse"; static const char __pyx_k_lat_arr[] = "lat_arr"; static const char __pyx_k_lon_arr[] = "lon_arr"; static const char __pyx_k_memview[] = "memview"; static const char __pyx_k_ndarray[] = "ndarray"; static const char __pyx_k_prepare[] = "__prepare__"; static const char __pyx_k_radians[] = "radians"; static const char __pyx_k_Ellipsis[] = "Ellipsis"; static const char __pyx_k_cols_out[] = "cols_out"; static const char __pyx_k_defaults[] = "defaults"; static const char __pyx_k_errcheck[] = "errcheck"; static const char __pyx_k_itemsize[] = "itemsize"; static const char __pyx_k_num_cols[] = "num_cols"; static const char __pyx_k_num_rows[] = "num_rows"; static const char __pyx_k_origin_x[] = "origin_x"; static const char __pyx_k_origin_y[] = "origin_y"; static const char __pyx_k_qualname[] = "__qualname__"; static const char __pyx_k_rows_out[] = "rows_out"; static const char __pyx_k_TypeError[] = "TypeError"; static const char __pyx_k_docformat[] = "__docformat__"; static const char __pyx_k_enumerate[] = "enumerate"; static const char __pyx_k_float64_t[] = "float64_t"; static const char __pyx_k_metaclass[] = "__metaclass__"; static const char __pyx_k_IndexError[] = "IndexError"; static const char __pyx_k_ValueError[] = "ValueError"; static const char __pyx_k_cell_width[] = "cell_width"; static const char __pyx_k_is_latlong[] = "is_latlong"; static const char __pyx_k_pyx_vtable[] = "__pyx_vtable__"; static const char __pyx_k_signatures[] = "signatures"; static const char __pyx_k_ImportError[] = "ImportError"; static const char __pyx_k_MemoryError[] = "MemoryError"; static const char __pyx_k_cell_height[] = "cell_height"; static const char __pyx_k_proj_circum[] = "proj_circum"; static const char __pyx_k_RuntimeError[] = "RuntimeError"; static const char __pyx_k_ll2cr_static[] = "ll2cr_static"; static const char __pyx_k_MyProj___call[] = "MyProj.__call__"; static const char __pyx_k_ll2cr_dynamic[] = "ll2cr_dynamic"; static const char __pyx_k_pyx_getbuffer[] = "__pyx_getbuffer"; static const char __pyx_k_AttributeError[] = "AttributeError"; static const char __pyx_k_points_in_grid[] = "points_in_grid"; static const char __pyx_k_allocate_buffer[] = "allocate_buffer"; static const char __pyx_k_dtype_is_object[] = "dtype_is_object"; static const char __pyx_k_projected_tuple[] = "projected_tuple"; static const char __pyx_k_proj4_definition[] = "proj4_definition"; static const char __pyx_k_strided_and_direct[] = ""; static const char __pyx_k_restructuredtext_en[] = "restructuredtext en"; static const char __pyx_k_strided_and_indirect[] = ""; static const char __pyx_k_contiguous_and_direct[] = ""; static const char __pyx_k_pyresample_ewa__ll2cr[] = "pyresample.ewa._ll2cr"; static const char __pyx_k_MemoryView_of_r_object[] = ""; static const char __pyx_k_MemoryView_of_r_at_0x_x[] = ""; static const char __pyx_k_contiguous_and_indirect[] = ""; static const char __pyx_k_Cannot_index_with_type_s[] = "Cannot index with type '%s'"; static const char __pyx_k_projection_circumference[] = "projection_circumference"; static const char __pyx_k_Invalid_shape_in_axis_d_d[] = "Invalid shape in axis %d: %d."; static const char __pyx_k_No_matching_signature_found[] = "No matching signature found"; static const char __pyx_k_itemsize_0_for_cython_array[] = "itemsize <= 0 for cython.array"; static const char __pyx_k_ndarray_is_not_C_contiguous[] = "ndarray is not C contiguous"; static const char __pyx_k_Expected_at_least_d_arguments[] = "Expected at least %d arguments"; static const char __pyx_k_unable_to_allocate_array_data[] = "unable to allocate array data."; static const char __pyx_k_strided_and_direct_or_indirect[] = ""; static const char __pyx_k_Users_davidh_repos_git_pyresamp[] = "/Users/davidh/repos/git/pyresample/pyresample/ewa/_ll2cr.pyx"; static const char __pyx_k_unknown_dtype_code_in_numpy_pxd[] = "unknown dtype code in numpy.pxd (%d)"; static const char __pyx_k_Buffer_view_does_not_expose_stri[] = "Buffer view does not expose strides"; static const char __pyx_k_Can_only_create_a_buffer_that_is[] = "Can only create a buffer that is contiguous in memory."; static const char __pyx_k_Custom_class_to_make_ll2cr_proje[] = "Custom class to make ll2cr projection work faster without compiling against the PROJ.4 library itself.\n\n THIS SHOULD NOT BE USED OUTSIDE OF LL2CR! It makes assumptions and has requirements that may not make sense outside\n of the ll2cr modules.\n "; static const char __pyx_k_Empty_shape_tuple_for_cython_arr[] = "Empty shape tuple for cython.array"; static const char __pyx_k_Format_string_allocated_too_shor[] = "Format string allocated too short, see comment in numpy.pxd"; static const char __pyx_k_Function_call_with_ambiguous_arg[] = "Function call with ambiguous argument types"; static const char __pyx_k_Indirect_dimensions_not_supporte[] = "Indirect dimensions not supported"; static const char __pyx_k_Invalid_mode_expected_c_or_fortr[] = "Invalid mode, expected 'c' or 'fortran', got %s"; static const char __pyx_k_Map_longitude_latitude_points_to[] = "Map longitude/latitude points to column/rows of a grid.\n"; static const char __pyx_k_Non_native_byte_order_not_suppor[] = "Non-native byte order not supported"; static const char __pyx_k_Out_of_bounds_on_buffer_access_a[] = "Out of bounds on buffer access (axis %d)"; static const char __pyx_k_Unable_to_convert_item_to_object[] = "Unable to convert item to object"; static const char __pyx_k_got_differing_extents_in_dimensi[] = "got differing extents in dimension %d (got %d and %d)"; static const char __pyx_k_ndarray_is_not_Fortran_contiguou[] = "ndarray is not Fortran contiguous"; static const char __pyx_k_unable_to_allocate_shape_and_str[] = "unable to allocate shape and strides."; static const char __pyx_k_Format_string_allocated_too_shor_2[] = "Format string allocated too short."; static PyObject *__pyx_n_s_ASCII; static PyObject *__pyx_n_s_AttributeError; static PyObject *__pyx_kp_s_Buffer_view_does_not_expose_stri; static PyObject *__pyx_kp_s_Can_only_create_a_buffer_that_is; static PyObject *__pyx_kp_s_Cannot_index_with_type_s; static PyObject *__pyx_kp_s_Custom_class_to_make_ll2cr_proje; static PyObject *__pyx_n_s_Ellipsis; static PyObject *__pyx_kp_s_Empty_shape_tuple_for_cython_arr; static PyObject *__pyx_kp_s_Expected_at_least_d_arguments; static PyObject *__pyx_kp_u_Format_string_allocated_too_shor; static PyObject *__pyx_kp_u_Format_string_allocated_too_shor_2; static PyObject *__pyx_kp_s_Function_call_with_ambiguous_arg; static PyObject *__pyx_n_s_ImportError; static PyObject *__pyx_n_s_IndexError; static PyObject *__pyx_kp_s_Indirect_dimensions_not_supporte; static PyObject *__pyx_kp_s_Invalid_mode_expected_c_or_fortr; static PyObject *__pyx_kp_s_Invalid_shape_in_axis_d_d; static PyObject *__pyx_n_s_MemoryError; static PyObject *__pyx_kp_s_MemoryView_of_r_at_0x_x; static PyObject *__pyx_kp_s_MemoryView_of_r_object; static PyObject *__pyx_n_s_MyProj; static PyObject *__pyx_n_s_MyProj___call; static PyObject *__pyx_kp_s_No_matching_signature_found; static PyObject *__pyx_kp_u_Non_native_byte_order_not_suppor; static PyObject *__pyx_n_b_O; static PyObject *__pyx_kp_s_Out_of_bounds_on_buffer_access_a; static PyObject *__pyx_n_s_Proj; static PyObject *__pyx_n_s_RuntimeError; static PyObject *__pyx_n_s_TypeError; static PyObject *__pyx_kp_s_Unable_to_convert_item_to_object; static PyObject *__pyx_kp_s_Users_davidh_repos_git_pyresamp; static PyObject *__pyx_n_s_ValueError; static PyObject *__pyx_kp_s__2; static PyObject *__pyx_kp_s__4; static PyObject *__pyx_n_s_allocate_buffer; static PyObject *__pyx_n_s_args; static PyObject *__pyx_n_s_base; static PyObject *__pyx_n_s_c; static PyObject *__pyx_n_u_c; static PyObject *__pyx_n_s_call; static PyObject *__pyx_n_s_cell_height; static PyObject *__pyx_n_s_cell_width; static PyObject *__pyx_n_s_class; static PyObject *__pyx_n_s_col; static PyObject *__pyx_n_s_cols_out; static PyObject *__pyx_kp_s_contiguous_and_direct; static PyObject *__pyx_kp_s_contiguous_and_indirect; static PyObject *__pyx_n_s_defaults; static PyObject *__pyx_n_s_doc; static PyObject *__pyx_n_s_docformat; static PyObject *__pyx_n_s_dtype; static PyObject *__pyx_n_s_dtype_is_object; static PyObject *__pyx_n_s_encode; static PyObject *__pyx_n_s_enumerate; static PyObject *__pyx_n_s_errcheck; static PyObject *__pyx_n_s_error; static PyObject *__pyx_n_s_fill_in; static PyObject *__pyx_n_s_flags; static PyObject *__pyx_n_s_float64_t; static PyObject *__pyx_n_s_format; static PyObject *__pyx_n_s_fortran; static PyObject *__pyx_n_u_fortran; static PyObject *__pyx_n_s_fwd; static PyObject *__pyx_n_s_get; static PyObject *__pyx_kp_s_got_differing_extents_in_dimensi; static PyObject *__pyx_n_s_h; static PyObject *__pyx_n_s_height; static PyObject *__pyx_n_s_id; static PyObject *__pyx_n_s_import; static PyObject *__pyx_n_s_inv; static PyObject *__pyx_n_s_inverse; static PyObject *__pyx_n_s_is_latlong; static PyObject *__pyx_n_s_itemsize; static PyObject *__pyx_kp_s_itemsize_0_for_cython_array; static PyObject *__pyx_n_s_kind; static PyObject *__pyx_n_s_kwargs; static PyObject *__pyx_n_s_lat0; static PyObject *__pyx_n_s_lat1; static PyObject *__pyx_n_s_lat_arr; static PyObject *__pyx_n_s_lats; static PyObject *__pyx_n_s_ll2cr_dynamic; static PyObject *__pyx_n_s_ll2cr_static; static PyObject *__pyx_n_s_lon0; static PyObject *__pyx_n_s_lon1; static PyObject *__pyx_n_s_lon_arr; static PyObject *__pyx_n_s_lons; static PyObject *__pyx_n_s_main; static PyObject *__pyx_n_s_memview; static PyObject *__pyx_n_s_metaclass; static PyObject *__pyx_n_s_mode; static PyObject *__pyx_n_s_module; static PyObject *__pyx_n_s_name; static PyObject *__pyx_n_s_name_2; static PyObject *__pyx_n_s_ndarray; static PyObject *__pyx_kp_u_ndarray_is_not_C_contiguous; static PyObject *__pyx_kp_u_ndarray_is_not_Fortran_contiguou; static PyObject *__pyx_n_s_ndim; static PyObject *__pyx_n_s_num_cols; static PyObject *__pyx_n_s_num_rows; static PyObject *__pyx_n_s_numpy; static PyObject *__pyx_n_s_obj; static PyObject *__pyx_n_s_origin_x; static PyObject *__pyx_n_s_origin_y; static PyObject *__pyx_n_s_ox; static PyObject *__pyx_n_s_oy; static PyObject *__pyx_n_s_p; static PyObject *__pyx_n_s_pack; static PyObject *__pyx_n_s_points_in_grid; static PyObject *__pyx_n_s_prepare; static PyObject *__pyx_n_s_proj; static PyObject *__pyx_n_s_proj4_definition; static PyObject *__pyx_n_s_proj_circum; static PyObject *__pyx_n_s_projected_tuple; static PyObject *__pyx_n_s_projection_circumference; static PyObject *__pyx_n_s_pyproj; static PyObject *__pyx_n_s_pyresample_ewa__ll2cr; static PyObject *__pyx_n_s_pyx_getbuffer; static PyObject *__pyx_n_s_pyx_vtable; static PyObject *__pyx_n_s_qualname; static PyObject *__pyx_n_s_radians; static PyObject *__pyx_n_s_range; static PyObject *__pyx_kp_s_restructuredtext_en; static PyObject *__pyx_n_s_row; static PyObject *__pyx_n_s_rows_out; static PyObject *__pyx_n_s_self; static PyObject *__pyx_n_s_shape; static PyObject *__pyx_n_s_signatures; static PyObject *__pyx_n_s_size; static PyObject *__pyx_n_s_split; static PyObject *__pyx_n_s_start; static PyObject *__pyx_n_s_step; static PyObject *__pyx_n_s_stop; static PyObject *__pyx_kp_s_strided_and_direct; static PyObject *__pyx_kp_s_strided_and_direct_or_indirect; static PyObject *__pyx_kp_s_strided_and_indirect; static PyObject *__pyx_n_s_strip; static PyObject *__pyx_n_s_struct; static PyObject *__pyx_n_s_super; static PyObject *__pyx_n_s_test; static PyObject *__pyx_kp_s_unable_to_allocate_array_data; static PyObject *__pyx_kp_s_unable_to_allocate_shape_and_str; static PyObject *__pyx_kp_u_unknown_dtype_code_in_numpy_pxd; static PyObject *__pyx_n_s_unpack; static PyObject *__pyx_n_s_w; static PyObject *__pyx_n_s_width; static PyObject *__pyx_n_s_x0; static PyObject *__pyx_n_s_x1; static PyObject *__pyx_n_s_x2; static PyObject *__pyx_n_s_x_tmp; static PyObject *__pyx_n_s_xmax; static PyObject *__pyx_n_s_xmin; static PyObject *__pyx_n_s_y0; static PyObject *__pyx_n_s_y1; static PyObject *__pyx_n_s_y2; static PyObject *__pyx_n_s_y_tmp; static PyObject *__pyx_n_s_ymax; static PyObject *__pyx_n_s_ymin; static PyObject *__pyx_n_s_zip; static PyObject *__pyx_pf_10pyresample_3ewa_6_ll2cr_6MyProj___call__(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_self, PyObject *__pyx_v_lons, PyObject *__pyx_v_lats, PyObject *__pyx_v_kwargs); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_6_ll2cr_projection_circumference(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_p); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_6_ll2cr_2ll2cr_dynamic(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_signatures, PyObject *__pyx_v_args, PyObject *__pyx_v_kwargs, CYTHON_UNUSED PyObject *__pyx_v_defaults); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_6_ll2cr_16__defaults__(CYTHON_UNUSED PyObject *__pyx_self); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_6_ll2cr_6ll2cr_dynamic(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_lon_arr, PyArrayObject *__pyx_v_lat_arr, __pyx_t_5numpy_float64_t __pyx_v_fill_in, PyObject *__pyx_v_proj4_definition, double __pyx_v_cell_width, double __pyx_v_cell_height, PyObject *__pyx_v_width, PyObject *__pyx_v_height, PyObject *__pyx_v_origin_x, PyObject *__pyx_v_origin_y); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_6_ll2cr_4ll2cr_static(CYTHON_UNUSED PyObject *__pyx_self, PyObject *__pyx_v_signatures, PyObject *__pyx_v_args, PyObject *__pyx_v_kwargs, CYTHON_UNUSED PyObject *__pyx_v_defaults); /* proto */ static PyObject *__pyx_pf_10pyresample_3ewa_6_ll2cr_10ll2cr_static(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_lon_arr, PyArrayObject *__pyx_v_lat_arr, __pyx_t_5numpy_float64_t __pyx_v_fill_in, PyObject *__pyx_v_proj4_definition, double __pyx_v_cell_width, double __pyx_v_cell_height, unsigned int __pyx_v_width, unsigned int __pyx_v_height, double __pyx_v_origin_x, double __pyx_v_origin_y); /* proto */ static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array___cinit__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_shape, Py_ssize_t __pyx_v_itemsize, PyObject *__pyx_v_format, PyObject *__pyx_v_mode, int __pyx_v_allocate_buffer); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_2__getbuffer__(struct __pyx_array_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static void __pyx_array___pyx_pf_15View_dot_MemoryView_5array_4__dealloc__(struct __pyx_array_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_5array_7memview___get__(struct __pyx_array_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_6__getattr__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_attr); /* proto */ static PyObject *__pyx_array___pyx_pf_15View_dot_MemoryView_5array_8__getitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item); /* proto */ static int __pyx_array___pyx_pf_15View_dot_MemoryView_5array_10__setitem__(struct __pyx_array_obj *__pyx_v_self, PyObject *__pyx_v_item, PyObject *__pyx_v_value); /* proto */ static int __pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum___init__(struct __pyx_MemviewEnum_obj *__pyx_v_self, PyObject *__pyx_v_name); /* proto */ static PyObject *__pyx_MemviewEnum___pyx_pf_15View_dot_MemoryView_4Enum_2__repr__(struct __pyx_MemviewEnum_obj *__pyx_v_self); /* proto */ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview___cinit__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_obj, int __pyx_v_flags, int __pyx_v_dtype_is_object); /* proto */ static void __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_2__dealloc__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_4__getitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index); /* proto */ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_6__setitem__(struct __pyx_memoryview_obj *__pyx_v_self, PyObject *__pyx_v_index, PyObject *__pyx_v_value); /* proto */ static int __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_8__getbuffer__(struct __pyx_memoryview_obj *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_1T___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4base___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_5shape___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_7strides___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_10suboffsets___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4ndim___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_8itemsize___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_6nbytes___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_10memoryview_4size___get__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static Py_ssize_t __pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_10__len__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_12__repr__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_14__str__(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_16is_c_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_18is_f_contig(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_20copy(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_memoryview___pyx_pf_15View_dot_MemoryView_10memoryview_22copy_fortran(struct __pyx_memoryview_obj *__pyx_v_self); /* proto */ static void __pyx_memoryviewslice___pyx_pf_15View_dot_MemoryView_16_memoryviewslice___dealloc__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_pf_15View_dot_MemoryView_16_memoryviewslice_4base___get__(struct __pyx_memoryviewslice_obj *__pyx_v_self); /* proto */ static PyObject *__pyx_tp_new_array(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_Enum(PyTypeObject *t, PyObject *a, PyObject *k); /*proto*/ static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k); 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if (!__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L8_bool_binop_done; } __pyx_t_25 = (npy_isnan(__pyx_v_xmin) != 0); __pyx_t_24 = __pyx_t_25; __pyx_L8_bool_binop_done:; if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":160 * continue * elif x_tmp < xmin or npy_isnan(xmin): * xmin = x_tmp # <<<<<<<<<<<<<< * elif x_tmp > xmax or npy_isnan(xmax) or xmax == 1e30: * # Note: technically 2 valid points are required to get here if there are a lot of NaNs */ __pyx_v_xmin = __pyx_v_x_tmp; /* "pyresample/ewa/_ll2cr.pyx":159 * # we technically don't ever check for the fill value, but if fill values are valid lon/lats then WTF * continue * elif x_tmp < xmin or npy_isnan(xmin): # <<<<<<<<<<<<<< * xmin = x_tmp * elif x_tmp > xmax or npy_isnan(xmax) or xmax == 1e30: */ goto __pyx_L7; } /* "pyresample/ewa/_ll2cr.pyx":161 * elif x_tmp < xmin or npy_isnan(xmin): * xmin = x_tmp * elif x_tmp > xmax or npy_isnan(xmax) or xmax == 1e30: # <<<<<<<<<<<<<< * # Note: technically 2 valid points are required to get here if there are a lot of NaNs * xmax = x_tmp */ __pyx_t_25 = ((__pyx_v_x_tmp > __pyx_v_xmax) != 0); if (!__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L10_bool_binop_done; } __pyx_t_25 = (npy_isnan(__pyx_v_xmax) != 0); if (!__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L10_bool_binop_done; } __pyx_t_25 = ((__pyx_v_xmax == 1e30) != 0); __pyx_t_24 = __pyx_t_25; __pyx_L10_bool_binop_done:; if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":163 * elif x_tmp > xmax or npy_isnan(xmax) or xmax == 1e30: * # Note: technically 2 valid points are required to get here if there are a lot of NaNs * xmax = x_tmp # <<<<<<<<<<<<<< * * if y_tmp < ymin or npy_isnan(ymin): */ __pyx_v_xmax = __pyx_v_x_tmp; /* "pyresample/ewa/_ll2cr.pyx":161 * elif x_tmp < xmin or npy_isnan(xmin): * xmin = x_tmp * elif x_tmp > xmax or npy_isnan(xmax) or xmax == 1e30: # <<<<<<<<<<<<<< * # Note: technically 2 valid points are required to get here if there are a lot of NaNs * xmax = x_tmp */ } __pyx_L7:; /* "pyresample/ewa/_ll2cr.pyx":165 * xmax = x_tmp * * if y_tmp < ymin or npy_isnan(ymin): # <<<<<<<<<<<<<< * ymin = y_tmp * elif y_tmp > ymax or npy_isnan(ymax) or ymax == 1e30: */ __pyx_t_25 = ((__pyx_v_y_tmp < __pyx_v_ymin) != 0); if (!__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L14_bool_binop_done; } __pyx_t_25 = (npy_isnan(__pyx_v_ymin) != 0); __pyx_t_24 = __pyx_t_25; __pyx_L14_bool_binop_done:; if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":166 * * if y_tmp < ymin or npy_isnan(ymin): * ymin = y_tmp # <<<<<<<<<<<<<< * elif y_tmp > ymax or npy_isnan(ymax) or ymax == 1e30: * # Note: technically 2 valid points are required to get here if there are a lot of NaNs */ __pyx_v_ymin = __pyx_v_y_tmp; /* "pyresample/ewa/_ll2cr.pyx":165 * xmax = x_tmp * * if y_tmp < ymin or npy_isnan(ymin): # <<<<<<<<<<<<<< * ymin = y_tmp * elif y_tmp > ymax or npy_isnan(ymax) or ymax == 1e30: */ goto __pyx_L13; } /* "pyresample/ewa/_ll2cr.pyx":167 * if y_tmp < ymin or npy_isnan(ymin): * ymin = y_tmp * elif y_tmp > ymax or npy_isnan(ymax) or ymax == 1e30: # <<<<<<<<<<<<<< * # Note: technically 2 valid points are required to get here if there are a lot of NaNs * ymax = y_tmp */ __pyx_t_25 = ((__pyx_v_y_tmp > __pyx_v_ymax) != 0); if (!__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L16_bool_binop_done; } __pyx_t_25 = (npy_isnan(__pyx_v_ymax) != 0); if (!__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L16_bool_binop_done; } __pyx_t_25 = ((__pyx_v_ymax == 1e30) != 0); __pyx_t_24 = __pyx_t_25; __pyx_L16_bool_binop_done:; if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":169 * elif y_tmp > ymax or npy_isnan(ymax) or ymax == 1e30: * # Note: technically 2 valid points are required to get here if there are a lot of NaNs * ymax = y_tmp # <<<<<<<<<<<<<< * * # Check if we cross the antimeridian */ __pyx_v_ymax = __pyx_v_y_tmp; /* "pyresample/ewa/_ll2cr.pyx":167 * if y_tmp < ymin or npy_isnan(ymin): * ymin = y_tmp * elif y_tmp > ymax or npy_isnan(ymax) or ymax == 1e30: # <<<<<<<<<<<<<< * # Note: technically 2 valid points are required to get here if there are a lot of NaNs * ymax = y_tmp */ } __pyx_L13:; __pyx_L5_continue:; } } /* "pyresample/ewa/_ll2cr.pyx":172 * * # Check if we cross the antimeridian * if proj_circum != 0 and xmax - xmin >= proj_circum * .75: # <<<<<<<<<<<<<< * # xmax will increase, but we need to reset xmin so that it gets properly detected * if xmin < 0: */ __pyx_t_25 = ((__pyx_v_proj_circum != 0.0) != 0); if (__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L20_bool_binop_done; } __pyx_t_25 = (((__pyx_v_xmax - __pyx_v_xmin) >= (__pyx_v_proj_circum * .75)) != 0); __pyx_t_24 = __pyx_t_25; __pyx_L20_bool_binop_done:; if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":174 * if proj_circum != 0 and xmax - xmin >= proj_circum * .75: * # xmax will increase, but we need to reset xmin so that it gets properly detected * if xmin < 0: # <<<<<<<<<<<<<< * xmin = xmax * for row in range(num_rows): */ __pyx_t_24 = ((__pyx_v_xmin < 0.0) != 0); if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":175 * # xmax will increase, but we need to reset xmin so that it gets properly detected * if xmin < 0: * xmin = xmax # <<<<<<<<<<<<<< * for row in range(num_rows): * for col in range(num_cols): */ __pyx_v_xmin = __pyx_v_xmax; /* "pyresample/ewa/_ll2cr.pyx":174 * if proj_circum != 0 and xmax - xmin >= proj_circum * .75: * # xmax will increase, but we need to reset xmin so that it gets properly detected * if xmin < 0: # <<<<<<<<<<<<<< * xmin = xmax * for row in range(num_rows): */ } /* "pyresample/ewa/_ll2cr.pyx":176 * if xmin < 0: * xmin = xmax * for row in range(num_rows): # <<<<<<<<<<<<<< * for col in range(num_cols): * x_tmp = cols_out[row, col] */ __pyx_t_16 = __pyx_v_num_rows; for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_16; __pyx_t_17+=1) { __pyx_v_row = __pyx_t_17; /* "pyresample/ewa/_ll2cr.pyx":177 * xmin = xmax * for row in range(num_rows): * for col in range(num_cols): # <<<<<<<<<<<<<< * x_tmp = cols_out[row, col] * if x_tmp < 0: */ __pyx_t_18 = __pyx_v_num_cols; for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) { __pyx_v_col = __pyx_t_19; /* "pyresample/ewa/_ll2cr.pyx":178 * for row in range(num_rows): * for col in range(num_cols): * x_tmp = cols_out[row, col] # <<<<<<<<<<<<<< * if x_tmp < 0: * x_tmp += proj_circum */ __pyx_t_26 = __pyx_v_row; __pyx_t_27 = __pyx_v_col; __pyx_v_x_tmp = (*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ ((char *) (((__pyx_t_5numpy_float64_t *) ( /* dim=0 */ (__pyx_v_cols_out.data + __pyx_t_26 * __pyx_v_cols_out.strides[0]) )) + __pyx_t_27)) ))); /* "pyresample/ewa/_ll2cr.pyx":179 * for col in range(num_cols): * x_tmp = cols_out[row, col] * if x_tmp < 0: # <<<<<<<<<<<<<< * x_tmp += proj_circum * cols_out[row, col] = x_tmp */ __pyx_t_24 = ((__pyx_v_x_tmp < 0.0) != 0); if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":180 * x_tmp = cols_out[row, col] * if x_tmp < 0: * x_tmp += proj_circum # <<<<<<<<<<<<<< * cols_out[row, col] = x_tmp * # xmax won't increase unless we've added the circumference */ __pyx_v_x_tmp = (__pyx_v_x_tmp + __pyx_v_proj_circum); /* "pyresample/ewa/_ll2cr.pyx":181 * if x_tmp < 0: * x_tmp += proj_circum * cols_out[row, col] = x_tmp # <<<<<<<<<<<<<< * # xmax won't increase unless we've added the circumference * if x_tmp > xmax: */ __pyx_t_28 = __pyx_v_row; __pyx_t_29 = __pyx_v_col; *((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ ((char *) (((__pyx_t_5numpy_float64_t *) ( /* dim=0 */ (__pyx_v_cols_out.data + __pyx_t_28 * __pyx_v_cols_out.strides[0]) )) + __pyx_t_29)) )) = __pyx_v_x_tmp; /* "pyresample/ewa/_ll2cr.pyx":183 * cols_out[row, col] = x_tmp * # xmax won't increase unless we've added the circumference * if x_tmp > xmax: # <<<<<<<<<<<<<< * xmax = x_tmp * elif x_tmp >= 1e30: */ __pyx_t_24 = ((__pyx_v_x_tmp > __pyx_v_xmax) != 0); if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":184 * # xmax won't increase unless we've added the circumference * if x_tmp > xmax: * xmax = x_tmp # <<<<<<<<<<<<<< * elif x_tmp >= 1e30: * continue */ __pyx_v_xmax = __pyx_v_x_tmp; /* "pyresample/ewa/_ll2cr.pyx":183 * cols_out[row, col] = x_tmp * # xmax won't increase unless we've added the circumference * if x_tmp > xmax: # <<<<<<<<<<<<<< * xmax = x_tmp * elif x_tmp >= 1e30: */ } /* "pyresample/ewa/_ll2cr.pyx":179 * for col in range(num_cols): * x_tmp = cols_out[row, col] * if x_tmp < 0: # <<<<<<<<<<<<<< * x_tmp += proj_circum * cols_out[row, col] = x_tmp */ goto __pyx_L27; } /* "pyresample/ewa/_ll2cr.pyx":185 * if x_tmp > xmax: * xmax = x_tmp * elif x_tmp >= 1e30: # <<<<<<<<<<<<<< * continue * elif x_tmp < xmin: */ __pyx_t_24 = ((__pyx_v_x_tmp >= 1e30) != 0); if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":186 * xmax = x_tmp * elif x_tmp >= 1e30: * continue # <<<<<<<<<<<<<< * elif x_tmp < xmin: * # xmin could change with any of the remaining entries */ goto __pyx_L25_continue; /* "pyresample/ewa/_ll2cr.pyx":185 * if x_tmp > xmax: * xmax = x_tmp * elif x_tmp >= 1e30: # <<<<<<<<<<<<<< * continue * elif x_tmp < xmin: */ } /* "pyresample/ewa/_ll2cr.pyx":187 * elif x_tmp >= 1e30: * continue * elif x_tmp < xmin: # <<<<<<<<<<<<<< * # xmin could change with any of the remaining entries * xmin = x_tmp */ __pyx_t_24 = ((__pyx_v_x_tmp < __pyx_v_xmin) != 0); if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":189 * elif x_tmp < xmin: * # xmin could change with any of the remaining entries * xmin = x_tmp # <<<<<<<<<<<<<< * * if origin_x is None: */ __pyx_v_xmin = __pyx_v_x_tmp; /* "pyresample/ewa/_ll2cr.pyx":187 * elif x_tmp >= 1e30: * continue * elif x_tmp < xmin: # <<<<<<<<<<<<<< * # xmin could change with any of the remaining entries * xmin = x_tmp */ } __pyx_L27:; __pyx_L25_continue:; } } /* "pyresample/ewa/_ll2cr.pyx":172 * * # Check if we cross the antimeridian * if proj_circum != 0 and xmax - xmin >= proj_circum * .75: # <<<<<<<<<<<<<< * # xmax will increase, but we need to reset xmin so that it gets properly detected * if xmin < 0: */ } /* "pyresample/ewa/_ll2cr.pyx":191 * xmin = x_tmp * * if origin_x is None: # <<<<<<<<<<<<<< * # upper-left corner * ox = xmin */ __pyx_t_24 = (__pyx_v_origin_x == Py_None); __pyx_t_25 = (__pyx_t_24 != 0); if (__pyx_t_25) { /* "pyresample/ewa/_ll2cr.pyx":193 * if origin_x is None: * # upper-left corner * ox = xmin # <<<<<<<<<<<<<< * oy = ymax * else: */ __pyx_v_ox = __pyx_v_xmin; /* "pyresample/ewa/_ll2cr.pyx":194 * # upper-left corner * ox = xmin * oy = ymax # <<<<<<<<<<<<<< * else: * ox = origin_x */ __pyx_v_oy = __pyx_v_ymax; /* "pyresample/ewa/_ll2cr.pyx":191 * xmin = x_tmp * * if origin_x is None: # <<<<<<<<<<<<<< * # upper-left corner * ox = xmin */ goto __pyx_L29; } /* "pyresample/ewa/_ll2cr.pyx":196 * oy = ymax * else: * ox = origin_x # <<<<<<<<<<<<<< * oy = origin_y * */ /*else*/ { __pyx_t_7 = __pyx_PyFloat_AsDouble(__pyx_v_origin_x); if (unlikely((__pyx_t_7 == (double)-1) && PyErr_Occurred())) __PYX_ERR(0, 196, __pyx_L1_error) __pyx_v_ox = __pyx_t_7; /* "pyresample/ewa/_ll2cr.pyx":197 * else: * ox = origin_x * oy = origin_y # <<<<<<<<<<<<<< * * if width is None: */ __pyx_t_7 = __pyx_PyFloat_AsDouble(__pyx_v_origin_y); if (unlikely((__pyx_t_7 == (double)-1) && PyErr_Occurred())) __PYX_ERR(0, 197, __pyx_L1_error) __pyx_v_oy = __pyx_t_7; } __pyx_L29:; /* "pyresample/ewa/_ll2cr.pyx":199 * oy = origin_y * * if width is None: # <<<<<<<<<<<<<< * w = int(abs((xmax - ox) / cell_width)) * h = int(abs((oy - ymin) / cell_height)) */ __pyx_t_25 = (__pyx_v_width == Py_None); __pyx_t_24 = (__pyx_t_25 != 0); if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":200 * * if width is None: * w = int(abs((xmax - ox) / cell_width)) # <<<<<<<<<<<<<< * h = int(abs((oy - ymin) / cell_height)) * else: */ __pyx_v_w = ((unsigned int)fabs(((__pyx_v_xmax - __pyx_v_ox) / __pyx_v_cell_width))); /* "pyresample/ewa/_ll2cr.pyx":201 * if width is None: * w = int(abs((xmax - ox) / cell_width)) * h = int(abs((oy - ymin) / cell_height)) # <<<<<<<<<<<<<< * else: * w = width */ __pyx_v_h = ((unsigned int)fabs(((__pyx_v_oy - __pyx_v_ymin) / __pyx_v_cell_height))); /* "pyresample/ewa/_ll2cr.pyx":199 * oy = origin_y * * if width is None: # <<<<<<<<<<<<<< * w = int(abs((xmax - ox) / cell_width)) * h = int(abs((oy - ymin) / cell_height)) */ goto __pyx_L30; } /* "pyresample/ewa/_ll2cr.pyx":203 * h = int(abs((oy - ymin) / cell_height)) * else: * w = width # <<<<<<<<<<<<<< * h = height * */ /*else*/ { __pyx_t_16 = __Pyx_PyInt_As_unsigned_int(__pyx_v_width); if (unlikely((__pyx_t_16 == (unsigned int)-1) && PyErr_Occurred())) __PYX_ERR(0, 203, __pyx_L1_error) __pyx_v_w = __pyx_t_16; /* "pyresample/ewa/_ll2cr.pyx":204 * else: * w = width * h = height # <<<<<<<<<<<<<< * * for row in range(num_rows): */ __pyx_t_16 = __Pyx_PyInt_As_unsigned_int(__pyx_v_height); if (unlikely((__pyx_t_16 == (unsigned int)-1) && PyErr_Occurred())) __PYX_ERR(0, 204, __pyx_L1_error) __pyx_v_h = __pyx_t_16; } __pyx_L30:; /* "pyresample/ewa/_ll2cr.pyx":206 * h = height * * for row in range(num_rows): # <<<<<<<<<<<<<< * for col in range(num_cols): * x_tmp = cols_out[row, col] */ __pyx_t_16 = __pyx_v_num_rows; for (__pyx_t_17 = 0; __pyx_t_17 < __pyx_t_16; __pyx_t_17+=1) { __pyx_v_row = __pyx_t_17; /* "pyresample/ewa/_ll2cr.pyx":207 * * for row in range(num_rows): * for col in range(num_cols): # <<<<<<<<<<<<<< * x_tmp = cols_out[row, col] * y_tmp = rows_out[row, col] */ __pyx_t_18 = __pyx_v_num_cols; for (__pyx_t_19 = 0; __pyx_t_19 < __pyx_t_18; __pyx_t_19+=1) { __pyx_v_col = __pyx_t_19; /* "pyresample/ewa/_ll2cr.pyx":208 * for row in range(num_rows): * for col in range(num_cols): * x_tmp = cols_out[row, col] # <<<<<<<<<<<<<< * y_tmp = rows_out[row, col] * if x_tmp >= 1e30: */ __pyx_t_30 = __pyx_v_row; __pyx_t_31 = __pyx_v_col; __pyx_v_x_tmp = (*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ ((char *) (((__pyx_t_5numpy_float64_t *) ( /* dim=0 */ (__pyx_v_cols_out.data + __pyx_t_30 * __pyx_v_cols_out.strides[0]) )) + __pyx_t_31)) ))); /* "pyresample/ewa/_ll2cr.pyx":209 * for col in range(num_cols): * x_tmp = cols_out[row, col] * y_tmp = rows_out[row, col] # <<<<<<<<<<<<<< * if x_tmp >= 1e30: * cols_out[row, col] = fill_in */ __pyx_t_32 = __pyx_v_row; __pyx_t_33 = __pyx_v_col; __pyx_v_y_tmp = (*((__pyx_t_5numpy_float64_t *) ( /* dim=1 */ ((char *) (((__pyx_t_5numpy_float64_t *) ( /* dim=0 */ (__pyx_v_rows_out.data + __pyx_t_32 * __pyx_v_rows_out.strides[0]) )) + __pyx_t_33)) ))); /* "pyresample/ewa/_ll2cr.pyx":210 * x_tmp = cols_out[row, col] * y_tmp = rows_out[row, col] * if x_tmp >= 1e30: # <<<<<<<<<<<<<< * cols_out[row, col] = fill_in * rows_out[row, col] = fill_in */ __pyx_t_24 = ((__pyx_v_x_tmp >= 1e30) != 0); if (__pyx_t_24) { /* "pyresample/ewa/_ll2cr.pyx":211 * y_tmp = rows_out[row, col] * if x_tmp >= 1e30: * cols_out[row, col] = fill_in # <<<<<<<<<<<<<< * rows_out[row, col] = fill_in * continue */ __pyx_t_34 = __pyx_v_row; 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/* "pyresample/ewa/_ll2cr.pyx":216 * * x_tmp = (x_tmp - ox) / cell_width * y_tmp = (y_tmp - oy) / cell_height # <<<<<<<<<<<<<< * if x_tmp >= -1 and x_tmp <= w + 1 and y_tmp >= -1 and y_tmp <= h + 1: * points_in_grid += 1 */ __pyx_v_y_tmp = ((__pyx_v_y_tmp - __pyx_v_oy) / __pyx_v_cell_height); /* "pyresample/ewa/_ll2cr.pyx":217 * x_tmp = (x_tmp - ox) / cell_width * y_tmp = (y_tmp - oy) / cell_height * if x_tmp >= -1 and x_tmp <= w + 1 and y_tmp >= -1 and y_tmp <= h + 1: # <<<<<<<<<<<<<< * points_in_grid += 1 * cols_out[row, col] = x_tmp */ __pyx_t_25 = ((__pyx_v_x_tmp >= -1.0) != 0); if (__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L37_bool_binop_done; } __pyx_t_25 = ((__pyx_v_x_tmp <= (__pyx_v_w + 1)) != 0); if (__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L37_bool_binop_done; } __pyx_t_25 = ((__pyx_v_y_tmp >= -1.0) != 0); if (__pyx_t_25) { } else { __pyx_t_24 = __pyx_t_25; goto __pyx_L37_bool_binop_done; } __pyx_t_25 = ((__pyx_v_y_tmp <= (__pyx_v_h + 1)) != 0); 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to_object_func, to_dtype_func, * memview.dtype_is_object) # <<<<<<<<<<<<<< * * */ __pyx_t_5 = __pyx_memoryview_fromslice((__pyx_v_memviewslice[0]), __pyx_v_memview->view.ndim, __pyx_v_to_object_func, __pyx_v_to_dtype_func, __pyx_v_memview->dtype_is_object); if (unlikely(!__pyx_t_5)) __PYX_ERR(2, 1084, __pyx_L1_error) __Pyx_GOTREF(__pyx_t_5); __pyx_r = __pyx_t_5; __pyx_t_5 = 0; goto __pyx_L0; /* "View.MemoryView":1070 * * @cname('__pyx_memoryview_copy_object_from_slice') * cdef memoryview_copy_from_slice(memoryview memview, __Pyx_memviewslice *memviewslice): # <<<<<<<<<<<<<< * """ * Create a new memoryview object from a given memoryview object and slice. */ /* function exit code */ __pyx_L1_error:; __Pyx_XDECREF(__pyx_t_5); __Pyx_AddTraceback("View.MemoryView.memoryview_copy_from_slice", __pyx_clineno, __pyx_lineno, __pyx_filename); __pyx_r = 0; __pyx_L0:; __Pyx_XGIVEREF(__pyx_r); __Pyx_RefNannyFinishContext(); return __pyx_r; } /* "View.MemoryView":1092 * * * cdef Py_ssize_t 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return -arg */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1099 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< * """ * Figure out the best memory access order for a given slice. */ static char __pyx_get_best_slice_order(__Pyx_memviewslice *__pyx_v_mslice, int __pyx_v_ndim) { int __pyx_v_i; Py_ssize_t __pyx_v_c_stride; Py_ssize_t __pyx_v_f_stride; char __pyx_r; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; /* "View.MemoryView":1104 * """ * cdef int i * cdef Py_ssize_t c_stride = 0 # <<<<<<<<<<<<<< * cdef Py_ssize_t f_stride = 0 * */ __pyx_v_c_stride = 0; /* "View.MemoryView":1105 * cdef int i * cdef Py_ssize_t c_stride = 0 * cdef Py_ssize_t f_stride = 0 # <<<<<<<<<<<<<< * * for i in range(ndim - 1, -1, -1): */ __pyx_v_f_stride = 0; /* "View.MemoryView":1107 * cdef Py_ssize_t f_stride = 0 * * for i in range(ndim - 1, -1, -1): # <<<<<<<<<<<<<< * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] */ for (__pyx_t_1 = (__pyx_v_ndim - 1); __pyx_t_1 > -1L; __pyx_t_1-=1) { __pyx_v_i = __pyx_t_1; /* "View.MemoryView":1108 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * c_stride = mslice.strides[i] * break */ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { /* "View.MemoryView":1109 * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] # <<<<<<<<<<<<<< * break * */ __pyx_v_c_stride = (__pyx_v_mslice->strides[__pyx_v_i]); /* "View.MemoryView":1110 * if mslice.shape[i] > 1: * c_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< * * for i in range(ndim): */ goto __pyx_L4_break; /* "View.MemoryView":1108 * * for i in range(ndim - 1, -1, -1): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * c_stride = mslice.strides[i] * break */ } } __pyx_L4_break:; /* "View.MemoryView":1112 * break * * for i in range(ndim): # <<<<<<<<<<<<<< * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] */ __pyx_t_1 = __pyx_v_ndim; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_1; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* "View.MemoryView":1113 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * f_stride = mslice.strides[i] * break */ __pyx_t_2 = (((__pyx_v_mslice->shape[__pyx_v_i]) > 1) != 0); if (__pyx_t_2) { /* "View.MemoryView":1114 * for i in range(ndim): * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] # <<<<<<<<<<<<<< * break * */ __pyx_v_f_stride = (__pyx_v_mslice->strides[__pyx_v_i]); /* "View.MemoryView":1115 * if mslice.shape[i] > 1: * f_stride = mslice.strides[i] * break # <<<<<<<<<<<<<< * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): */ goto __pyx_L7_break; /* "View.MemoryView":1113 * * for i in range(ndim): * if mslice.shape[i] > 1: # <<<<<<<<<<<<<< * f_stride = mslice.strides[i] * break */ } } __pyx_L7_break:; /* "View.MemoryView":1117 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< * return 'C' * else: */ __pyx_t_2 = ((abs_py_ssize_t(__pyx_v_c_stride) <= abs_py_ssize_t(__pyx_v_f_stride)) != 0); if (__pyx_t_2) { /* "View.MemoryView":1118 * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): * return 'C' # <<<<<<<<<<<<<< * else: * return 'F' */ __pyx_r = 'C'; goto __pyx_L0; /* "View.MemoryView":1117 * break * * if abs_py_ssize_t(c_stride) <= abs_py_ssize_t(f_stride): # <<<<<<<<<<<<<< * return 'C' * else: */ } /* "View.MemoryView":1120 * return 'C' * else: * return 'F' # <<<<<<<<<<<<<< * * @cython.cdivision(True) */ /*else*/ { __pyx_r = 'F'; goto __pyx_L0; } /* "View.MemoryView":1099 * * @cname('__pyx_get_best_slice_order') * cdef char get_best_order(__Pyx_memviewslice *mslice, int ndim) nogil: # <<<<<<<<<<<<<< * """ * Figure out the best memory access order for a given slice. */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1123 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< * char *dst_data, Py_ssize_t *dst_strides, * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, */ static void _copy_strided_to_strided(char *__pyx_v_src_data, Py_ssize_t *__pyx_v_src_strides, char *__pyx_v_dst_data, Py_ssize_t *__pyx_v_dst_strides, Py_ssize_t *__pyx_v_src_shape, Py_ssize_t *__pyx_v_dst_shape, int __pyx_v_ndim, size_t __pyx_v_itemsize) { CYTHON_UNUSED Py_ssize_t __pyx_v_i; CYTHON_UNUSED Py_ssize_t __pyx_v_src_extent; Py_ssize_t __pyx_v_dst_extent; Py_ssize_t __pyx_v_src_stride; Py_ssize_t __pyx_v_dst_stride; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; Py_ssize_t __pyx_t_4; Py_ssize_t __pyx_t_5; /* "View.MemoryView":1130 * * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] */ __pyx_v_src_extent = (__pyx_v_src_shape[0]); /* "View.MemoryView":1131 * cdef Py_ssize_t i * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] */ __pyx_v_dst_extent = (__pyx_v_dst_shape[0]); /* "View.MemoryView":1132 * cdef Py_ssize_t src_extent = src_shape[0] * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] # <<<<<<<<<<<<<< * cdef Py_ssize_t dst_stride = dst_strides[0] * */ __pyx_v_src_stride = (__pyx_v_src_strides[0]); /* "View.MemoryView":1133 * cdef Py_ssize_t dst_extent = dst_shape[0] * cdef Py_ssize_t src_stride = src_strides[0] * cdef Py_ssize_t dst_stride = dst_strides[0] # <<<<<<<<<<<<<< * * if ndim == 1: */ __pyx_v_dst_stride = (__pyx_v_dst_strides[0]); /* "View.MemoryView":1135 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): */ __pyx_t_1 = ((__pyx_v_ndim == 1) != 0); if (__pyx_t_1) { /* "View.MemoryView":1136 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ __pyx_t_2 = ((__pyx_v_src_stride > 0) != 0); if (__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } __pyx_t_2 = ((__pyx_v_dst_stride > 0) != 0); if (__pyx_t_2) { } else { __pyx_t_1 = __pyx_t_2; goto __pyx_L5_bool_binop_done; } /* "View.MemoryView":1137 * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): # <<<<<<<<<<<<<< * memcpy(dst_data, src_data, itemsize * dst_extent) * else: */ __pyx_t_2 = (((size_t)__pyx_v_src_stride) == __pyx_v_itemsize); if (__pyx_t_2) { __pyx_t_2 = (__pyx_v_itemsize == ((size_t)__pyx_v_dst_stride)); } __pyx_t_3 = (__pyx_t_2 != 0); __pyx_t_1 = __pyx_t_3; __pyx_L5_bool_binop_done:; /* "View.MemoryView":1136 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ if (__pyx_t_1) { /* "View.MemoryView":1138 * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) # <<<<<<<<<<<<<< * else: * for i in range(dst_extent): */ memcpy(__pyx_v_dst_data, __pyx_v_src_data, (__pyx_v_itemsize * __pyx_v_dst_extent)); /* "View.MemoryView":1136 * * if ndim == 1: * if (src_stride > 0 and dst_stride > 0 and # <<<<<<<<<<<<<< * src_stride == itemsize == dst_stride): * memcpy(dst_data, src_data, itemsize * dst_extent) */ goto __pyx_L4; } /* "View.MemoryView":1140 * memcpy(dst_data, src_data, itemsize * dst_extent) * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< * memcpy(dst_data, src_data, itemsize) * src_data += src_stride */ /*else*/ { __pyx_t_4 = __pyx_v_dst_extent; for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; /* "View.MemoryView":1141 * else: * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) # <<<<<<<<<<<<<< * src_data += src_stride * dst_data += dst_stride */ memcpy(__pyx_v_dst_data, __pyx_v_src_data, __pyx_v_itemsize); /* "View.MemoryView":1142 * for i in range(dst_extent): * memcpy(dst_data, src_data, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< * dst_data += dst_stride * else: */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); /* "View.MemoryView":1143 * memcpy(dst_data, src_data, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< * else: * for i in range(dst_extent): */ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); } } __pyx_L4:; /* "View.MemoryView":1135 * cdef Py_ssize_t dst_stride = dst_strides[0] * * if ndim == 1: # <<<<<<<<<<<<<< * if (src_stride > 0 and dst_stride > 0 and * src_stride == itemsize == dst_stride): */ goto __pyx_L3; } /* "View.MemoryView":1145 * dst_data += dst_stride * else: * for i in range(dst_extent): # <<<<<<<<<<<<<< * _copy_strided_to_strided(src_data, src_strides + 1, * dst_data, dst_strides + 1, */ /*else*/ { __pyx_t_4 = __pyx_v_dst_extent; for (__pyx_t_5 = 0; __pyx_t_5 < __pyx_t_4; __pyx_t_5+=1) { __pyx_v_i = __pyx_t_5; /* "View.MemoryView":1146 * else: * for i in range(dst_extent): * _copy_strided_to_strided(src_data, src_strides + 1, # <<<<<<<<<<<<<< * dst_data, dst_strides + 1, * src_shape + 1, dst_shape + 1, */ _copy_strided_to_strided(__pyx_v_src_data, (__pyx_v_src_strides + 1), __pyx_v_dst_data, (__pyx_v_dst_strides + 1), (__pyx_v_src_shape + 1), (__pyx_v_dst_shape + 1), (__pyx_v_ndim - 1), __pyx_v_itemsize); /* "View.MemoryView":1150 * src_shape + 1, dst_shape + 1, * ndim - 1, itemsize) * src_data += src_stride # <<<<<<<<<<<<<< * dst_data += dst_stride * */ __pyx_v_src_data = (__pyx_v_src_data + __pyx_v_src_stride); /* "View.MemoryView":1151 * ndim - 1, itemsize) * src_data += src_stride * dst_data += dst_stride # <<<<<<<<<<<<<< * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, */ __pyx_v_dst_data = (__pyx_v_dst_data + __pyx_v_dst_stride); } } __pyx_L3:; /* "View.MemoryView":1123 * * @cython.cdivision(True) * cdef void _copy_strided_to_strided(char *src_data, Py_ssize_t *src_strides, # <<<<<<<<<<<<<< * char *dst_data, Py_ssize_t *dst_strides, * Py_ssize_t *src_shape, Py_ssize_t *dst_shape, */ /* function exit code */ } /* "View.MemoryView":1153 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: */ static void copy_strided_to_strided(__Pyx_memviewslice *__pyx_v_src, __Pyx_memviewslice *__pyx_v_dst, int __pyx_v_ndim, size_t __pyx_v_itemsize) { /* "View.MemoryView":1156 * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: * _copy_strided_to_strided(src.data, src.strides, dst.data, dst.strides, # <<<<<<<<<<<<<< * src.shape, dst.shape, ndim, itemsize) * */ _copy_strided_to_strided(__pyx_v_src->data, __pyx_v_src->strides, __pyx_v_dst->data, __pyx_v_dst->strides, __pyx_v_src->shape, __pyx_v_dst->shape, __pyx_v_ndim, __pyx_v_itemsize); /* "View.MemoryView":1153 * dst_data += dst_stride * * cdef void copy_strided_to_strided(__Pyx_memviewslice *src, # <<<<<<<<<<<<<< * __Pyx_memviewslice *dst, * int ndim, size_t itemsize) nogil: */ /* function exit code */ } /* "View.MemoryView":1160 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< * "Return the size of the memory occupied by the slice in number of bytes" * cdef int i */ static Py_ssize_t __pyx_memoryview_slice_get_size(__Pyx_memviewslice *__pyx_v_src, int __pyx_v_ndim) { int __pyx_v_i; Py_ssize_t __pyx_v_size; Py_ssize_t __pyx_r; Py_ssize_t __pyx_t_1; int __pyx_t_2; int __pyx_t_3; /* "View.MemoryView":1163 * "Return the size of the memory occupied by the slice in number of bytes" * cdef int i * cdef Py_ssize_t size = src.memview.view.itemsize # <<<<<<<<<<<<<< * * for i in range(ndim): */ __pyx_t_1 = __pyx_v_src->memview->view.itemsize; __pyx_v_size = __pyx_t_1; /* "View.MemoryView":1165 * cdef Py_ssize_t size = src.memview.view.itemsize * * for i in range(ndim): # <<<<<<<<<<<<<< * size *= src.shape[i] * */ __pyx_t_2 = __pyx_v_ndim; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_i = __pyx_t_3; /* "View.MemoryView":1166 * * for i in range(ndim): * size *= src.shape[i] # <<<<<<<<<<<<<< * * return size */ __pyx_v_size = (__pyx_v_size * (__pyx_v_src->shape[__pyx_v_i])); } /* "View.MemoryView":1168 * size *= src.shape[i] * * return size # <<<<<<<<<<<<<< * * @cname('__pyx_fill_contig_strides_array') */ __pyx_r = __pyx_v_size; goto __pyx_L0; /* "View.MemoryView":1160 * * @cname('__pyx_memoryview_slice_get_size') * cdef Py_ssize_t slice_get_size(__Pyx_memviewslice *src, int ndim) nogil: # <<<<<<<<<<<<<< * "Return the size of the memory occupied by the slice in number of bytes" * cdef int i */ /* function exit code */ __pyx_L0:; return __pyx_r; } /* "View.MemoryView":1171 * * @cname('__pyx_fill_contig_strides_array') * cdef Py_ssize_t fill_contig_strides_array( # <<<<<<<<<<<<<< * Py_ssize_t *shape, Py_ssize_t *strides, Py_ssize_t stride, * int ndim, char order) nogil: */ static Py_ssize_t __pyx_fill_contig_strides_array(Py_ssize_t *__pyx_v_shape, Py_ssize_t *__pyx_v_strides, Py_ssize_t __pyx_v_stride, int __pyx_v_ndim, char __pyx_v_order) { int __pyx_v_idx; Py_ssize_t __pyx_r; int __pyx_t_1; int __pyx_t_2; int __pyx_t_3; /* "View.MemoryView":1180 * cdef int idx * * if order == 'F': # <<<<<<<<<<<<<< * for idx in range(ndim): * strides[idx] = stride */ __pyx_t_1 = ((__pyx_v_order == 'F') != 0); if (__pyx_t_1) { /* "View.MemoryView":1181 * * if order == 'F': * for idx in range(ndim): # <<<<<<<<<<<<<< * strides[idx] = stride * stride = stride * shape[idx] */ __pyx_t_2 = __pyx_v_ndim; for (__pyx_t_3 = 0; __pyx_t_3 < __pyx_t_2; __pyx_t_3+=1) { __pyx_v_idx = __pyx_t_3; /* "View.MemoryView":1182 * if order == 'F': * for idx 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'C', ndim) * elif slice_is_contig(src, 'F', ndim): */ goto __pyx_L12; } /* "View.MemoryView":1299 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'F', ndim) * */ __pyx_t_2 = (__pyx_memviewslice_is_contig(__pyx_v_src, 'F', __pyx_v_ndim) != 0); if (__pyx_t_2) { /* "View.MemoryView":1300 * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): * direct_copy = slice_is_contig(dst, 'F', ndim) # <<<<<<<<<<<<<< * * if direct_copy: */ __pyx_v_direct_copy = __pyx_memviewslice_is_contig(__pyx_v_dst, 'F', __pyx_v_ndim); /* "View.MemoryView":1299 * if slice_is_contig(src, 'C', ndim): * direct_copy = slice_is_contig(dst, 'C', ndim) * elif slice_is_contig(src, 'F', ndim): # <<<<<<<<<<<<<< * direct_copy = slice_is_contig(dst, 'F', ndim) * */ } __pyx_L12:; /* "View.MemoryView":1302 * direct_copy = slice_is_contig(dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< * * refcount_copying(&dst, dtype_is_object, ndim, False) */ __pyx_t_2 = (__pyx_v_direct_copy != 0); if (__pyx_t_2) { /* "View.MemoryView":1304 * if direct_copy: * * refcount_copying(&dst, dtype_is_object, ndim, False) # <<<<<<<<<<<<<< * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); /* "View.MemoryView":1305 * * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) # <<<<<<<<<<<<<< * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) */ memcpy(__pyx_v_dst.data, __pyx_v_src.data, __pyx_memoryview_slice_get_size((&__pyx_v_src), __pyx_v_ndim)); /* "View.MemoryView":1306 * refcount_copying(&dst, dtype_is_object, ndim, False) * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< * free(tmpdata) * return 0 */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); /* "View.MemoryView":1307 * memcpy(dst.data, src.data, slice_get_size(&src, ndim)) * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) # <<<<<<<<<<<<<< * return 0 * */ free(__pyx_v_tmpdata); /* "View.MemoryView":1308 * refcount_copying(&dst, dtype_is_object, ndim, True) * free(tmpdata) * return 0 # <<<<<<<<<<<<<< * * if order == 'F' == get_best_order(&dst, ndim): */ __pyx_r = 0; goto __pyx_L0; /* "View.MemoryView":1302 * direct_copy = slice_is_contig(dst, 'F', ndim) * * if direct_copy: # <<<<<<<<<<<<<< * * refcount_copying(&dst, dtype_is_object, ndim, False) */ } /* "View.MemoryView":1294 * src = tmp * * if not broadcasting: # <<<<<<<<<<<<<< * * */ } /* "View.MemoryView":1310 * return 0 * * if order == 'F' == get_best_order(&dst, ndim): # <<<<<<<<<<<<<< * * */ __pyx_t_2 = (__pyx_v_order == 'F'); if (__pyx_t_2) { __pyx_t_2 = ('F' 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__pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 0); /* "View.MemoryView":1317 * * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) # <<<<<<<<<<<<<< * refcount_copying(&dst, dtype_is_object, ndim, True) * */ copy_strided_to_strided((&__pyx_v_src), (&__pyx_v_dst), __pyx_v_ndim, __pyx_v_itemsize); /* "View.MemoryView":1318 * refcount_copying(&dst, dtype_is_object, ndim, False) * copy_strided_to_strided(&src, &dst, ndim, itemsize) * refcount_copying(&dst, dtype_is_object, ndim, True) # <<<<<<<<<<<<<< * * free(tmpdata) */ __pyx_memoryview_refcount_copying((&__pyx_v_dst), __pyx_v_dtype_is_object, __pyx_v_ndim, 1); /* "View.MemoryView":1320 * refcount_copying(&dst, dtype_is_object, ndim, True) * * free(tmpdata) # <<<<<<<<<<<<<< * return 0 * */ free(__pyx_v_tmpdata); /* "View.MemoryView":1321 * * free(tmpdata) * return 0 # <<<<<<<<<<<<<< * * @cname('__pyx_memoryview_broadcast_leading') */ __pyx_r 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__pyx_vtable_memoryview; static PyObject *__pyx_tp_new_memoryview(PyTypeObject *t, PyObject *a, PyObject *k) { struct __pyx_memoryview_obj *p; PyObject *o; if (likely((t->tp_flags & Py_TPFLAGS_IS_ABSTRACT) == 0)) { o = (*t->tp_alloc)(t, 0); } else { o = (PyObject *) PyBaseObject_Type.tp_new(t, __pyx_empty_tuple, 0); } if (unlikely(!o)) return 0; p = ((struct __pyx_memoryview_obj *)o); p->__pyx_vtab = __pyx_vtabptr_memoryview; p->obj = Py_None; Py_INCREF(Py_None); p->_size = Py_None; Py_INCREF(Py_None); p->_array_interface = Py_None; Py_INCREF(Py_None); p->view.obj = NULL; if (unlikely(__pyx_memoryview___cinit__(o, a, k) < 0)) { Py_DECREF(o); o = 0; } return o; } static void __pyx_tp_dealloc_memoryview(PyObject *o) { struct __pyx_memoryview_obj *p = (struct __pyx_memoryview_obj *)o; #if PY_VERSION_HEX >= 0x030400a1 if (unlikely(Py_TYPE(o)->tp_finalize) && !_PyGC_FINALIZED(o)) { if (PyObject_CallFinalizerFromDealloc(o)) return; } #endif PyObject_GC_UnTrack(o); { PyObject *etype, *eval, 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} } return __Pyx_PyObject_Call(func, __pyx_empty_tuple, NULL); } #endif /* dict_getitem_default */ static PyObject* __Pyx_PyDict_GetItemDefault(PyObject* d, PyObject* key, PyObject* default_value) { PyObject* value; #if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY value = PyDict_GetItemWithError(d, key); if (unlikely(!value)) { if (unlikely(PyErr_Occurred())) return NULL; value = default_value; } Py_INCREF(value); #else if (PyString_CheckExact(key) || PyUnicode_CheckExact(key) || PyInt_CheckExact(key)) { value = PyDict_GetItem(d, key); if (unlikely(!value)) { value = default_value; } Py_INCREF(value); } else { if (default_value == Py_None) default_value = NULL; value = PyObject_CallMethodObjArgs( d, __pyx_n_s_get, key, default_value, NULL); } #endif return value; } /* GetModuleGlobalName */ static CYTHON_INLINE PyObject *__Pyx_GetModuleGlobalName(PyObject *name) { PyObject *result; #if CYTHON_COMPILING_IN_CPYTHON result = PyDict_GetItem(__pyx_d, name); if (likely(result)) { Py_INCREF(result); } else { #else result = PyObject_GetItem(__pyx_d, name); if (!result) { PyErr_Clear(); #endif result = __Pyx_GetBuiltinName(name); } return result; } /* RaiseTooManyValuesToUnpack */ static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) { PyErr_Format(PyExc_ValueError, "too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected); } /* RaiseNeedMoreValuesToUnpack */ static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) { PyErr_Format(PyExc_ValueError, "need more than %" CYTHON_FORMAT_SSIZE_T "d value%.1s to unpack", index, (index == 1) ? "" : "s"); } /* IterFinish */ static CYTHON_INLINE int __Pyx_IterFinish(void) { #if CYTHON_COMPILING_IN_CPYTHON PyThreadState *tstate = PyThreadState_GET(); PyObject* exc_type = tstate->curexc_type; if (unlikely(exc_type)) { if (likely(exc_type == PyExc_StopIteration) || PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration)) { PyObject *exc_value, *exc_tb; exc_value = tstate->curexc_value; exc_tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; Py_DECREF(exc_type); Py_XDECREF(exc_value); Py_XDECREF(exc_tb); return 0; } else { return -1; } } return 0; #else if (unlikely(PyErr_Occurred())) { if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) { PyErr_Clear(); return 0; } else { return -1; } } return 0; #endif } /* UnpackItemEndCheck */ static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) { if (unlikely(retval)) { Py_DECREF(retval); __Pyx_RaiseTooManyValuesError(expected); return -1; } else { return __Pyx_IterFinish(); } return 0; } /* PyFloatBinop */ #if CYTHON_COMPILING_IN_CPYTHON static PyObject* __Pyx_PyFloat_AddObjC(PyObject *op1, PyObject *op2, double floatval, CYTHON_UNUSED int inplace) { const double b = floatval; double a, result; if (likely(PyFloat_CheckExact(op1))) { a = PyFloat_AS_DOUBLE(op1); } else #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(op1))) { a = (double) PyInt_AS_LONG(op1); } else #endif if (likely(PyLong_CheckExact(op1))) { #if CYTHON_USE_PYLONG_INTERNALS && PY_MAJOR_VERSION >= 3 const digit* digits = ((PyLongObject*)op1)->ob_digit; const Py_ssize_t size = Py_SIZE(op1); switch (size) { case 0: a = 0.0; break; case -1: a = -(double) digits[0]; break; case 1: a = (double) digits[0]; break; case -2: case 2: if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (1 * PyLong_SHIFT < 53))) { a = (double) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); if ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53) || (a < (double) (1L<<53))) { if (size == -2) a = -a; break; } } case -3: case 3: if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (2 * PyLong_SHIFT < 53))) { a = (double) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); if ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53) || (a < (double) (1L<<53))) { if (size == -3) a = -a; break; } } case -4: case 4: if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT && ((8 * sizeof(unsigned long) < 53) || (3 * PyLong_SHIFT < 53))) { a = (double) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); if ((8 * sizeof(unsigned long) < 53) || (4 * PyLong_SHIFT < 53) || (a < (double) (1L<<53))) { if (size == -4) a = -a; break; } } default: #else { #endif a = PyLong_AsDouble(op1); if (unlikely(a == -1.0 && PyErr_Occurred())) return NULL; } } else { return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); } PyFPE_START_PROTECT("add", return NULL) result = a + b; PyFPE_END_PROTECT(result) return PyFloat_FromDouble(result); } #endif /* Import */ static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { PyObject *empty_list = 0; PyObject *module = 0; PyObject *global_dict = 0; PyObject *empty_dict = 0; PyObject *list; #if PY_VERSION_HEX < 0x03030000 PyObject *py_import; py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); if (!py_import) goto bad; #endif if (from_list) list = from_list; else { empty_list = PyList_New(0); if (!empty_list) goto bad; list = empty_list; } global_dict = PyModule_GetDict(__pyx_m); if (!global_dict) goto bad; empty_dict = PyDict_New(); if (!empty_dict) goto bad; { #if PY_MAJOR_VERSION >= 3 if (level == -1) { if (strchr(__Pyx_MODULE_NAME, '.')) { #if PY_VERSION_HEX < 0x03030000 PyObject *py_level = PyInt_FromLong(1); if (!py_level) goto bad; module = PyObject_CallFunctionObjArgs(py_import, name, global_dict, empty_dict, list, py_level, NULL); Py_DECREF(py_level); #else module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, 1); #endif if (!module) { if (!PyErr_ExceptionMatches(PyExc_ImportError)) goto bad; PyErr_Clear(); } } level = 0; } #endif if (!module) { #if PY_VERSION_HEX < 0x03030000 PyObject *py_level = PyInt_FromLong(level); if (!py_level) goto bad; module = PyObject_CallFunctionObjArgs(py_import, name, global_dict, empty_dict, list, py_level, NULL); Py_DECREF(py_level); #else module = PyImport_ImportModuleLevelObject( name, global_dict, empty_dict, list, level); #endif } } bad: #if PY_VERSION_HEX < 0x03030000 Py_XDECREF(py_import); #endif Py_XDECREF(empty_list); Py_XDECREF(empty_dict); return module; } /* SaveResetException */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { *type = tstate->exc_type; *value = tstate->exc_value; *tb = tstate->exc_traceback; Py_XINCREF(*type); Py_XINCREF(*value); Py_XINCREF(*tb); } static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = type; tstate->exc_value = value; tstate->exc_traceback = tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); } #endif /* PyErrExceptionMatches */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err) { PyObject *exc_type = tstate->curexc_type; if (exc_type == err) return 1; if (unlikely(!exc_type)) return 0; return PyErr_GivenExceptionMatches(exc_type, err); } #endif /* GetException */ #if CYTHON_COMPILING_IN_CPYTHON static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { #else static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) { #endif PyObject *local_type, *local_value, *local_tb; #if CYTHON_COMPILING_IN_CPYTHON PyObject *tmp_type, *tmp_value, *tmp_tb; local_type = tstate->curexc_type; local_value = tstate->curexc_value; local_tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; #else PyErr_Fetch(&local_type, &local_value, &local_tb); #endif PyErr_NormalizeException(&local_type, &local_value, &local_tb); #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(tstate->curexc_type)) #else if (unlikely(PyErr_Occurred())) #endif goto bad; #if PY_MAJOR_VERSION >= 3 if (local_tb) { if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) goto bad; } #endif Py_XINCREF(local_tb); Py_XINCREF(local_type); Py_XINCREF(local_value); *type = local_type; *value = local_value; *tb = local_tb; #if CYTHON_COMPILING_IN_CPYTHON tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = local_type; tstate->exc_value = local_value; tstate->exc_traceback = local_tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); #else PyErr_SetExcInfo(local_type, local_value, local_tb); #endif return 0; bad: *type = 0; *value = 0; *tb = 0; Py_XDECREF(local_type); Py_XDECREF(local_value); Py_XDECREF(local_tb); return -1; } /* PyErrFetchRestore */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->curexc_type; tmp_value = tstate->curexc_value; tmp_tb = tstate->curexc_traceback; tstate->curexc_type = type; tstate->curexc_value = value; tstate->curexc_traceback = tb; Py_XDECREF(tmp_type); Py_XDECREF(tmp_value); Py_XDECREF(tmp_tb); } static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { *type = tstate->curexc_type; *value = tstate->curexc_value; *tb = tstate->curexc_traceback; tstate->curexc_type = 0; tstate->curexc_value = 0; tstate->curexc_traceback = 0; } #endif /* RaiseException */ #if PY_MAJOR_VERSION < 3 static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, CYTHON_UNUSED PyObject *cause) { __Pyx_PyThreadState_declare Py_XINCREF(type); if (!value || value == Py_None) value = NULL; else Py_INCREF(value); if (!tb || tb == Py_None) tb = NULL; else { Py_INCREF(tb); if (!PyTraceBack_Check(tb)) { PyErr_SetString(PyExc_TypeError, "raise: arg 3 must be a traceback or None"); goto raise_error; } } if (PyType_Check(type)) { #if CYTHON_COMPILING_IN_PYPY if (!value) { Py_INCREF(Py_None); value = Py_None; } #endif PyErr_NormalizeException(&type, &value, &tb); } else { if (value) { PyErr_SetString(PyExc_TypeError, "instance exception may not have a separate value"); goto raise_error; } value = type; type = (PyObject*) Py_TYPE(type); Py_INCREF(type); if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { PyErr_SetString(PyExc_TypeError, "raise: exception class must be a subclass of BaseException"); goto raise_error; } } __Pyx_PyThreadState_assign __Pyx_ErrRestore(type, value, tb); return; raise_error: Py_XDECREF(value); Py_XDECREF(type); Py_XDECREF(tb); return; } #else static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { PyObject* owned_instance = NULL; if (tb == Py_None) { tb = 0; } else if (tb && !PyTraceBack_Check(tb)) { PyErr_SetString(PyExc_TypeError, "raise: arg 3 must be a traceback or None"); goto bad; } if (value == Py_None) value = 0; if (PyExceptionInstance_Check(type)) { if (value) { PyErr_SetString(PyExc_TypeError, "instance exception may not have a separate value"); goto bad; } value = type; type = (PyObject*) Py_TYPE(value); } else if (PyExceptionClass_Check(type)) { PyObject *instance_class = NULL; if (value && PyExceptionInstance_Check(value)) { instance_class = (PyObject*) Py_TYPE(value); if (instance_class != type) { int is_subclass = PyObject_IsSubclass(instance_class, type); if (!is_subclass) { instance_class = NULL; } else if (unlikely(is_subclass == -1)) { goto bad; } else { type = instance_class; } } } if (!instance_class) { PyObject *args; if (!value) args = PyTuple_New(0); else if (PyTuple_Check(value)) { Py_INCREF(value); args = value; } else args = PyTuple_Pack(1, value); if (!args) goto bad; owned_instance = PyObject_Call(type, args, NULL); Py_DECREF(args); if (!owned_instance) goto bad; value = owned_instance; if (!PyExceptionInstance_Check(value)) { PyErr_Format(PyExc_TypeError, "calling %R should have returned an instance of " "BaseException, not %R", type, Py_TYPE(value)); goto bad; } } } else { PyErr_SetString(PyExc_TypeError, "raise: exception class must be a subclass of BaseException"); goto bad; } #if PY_VERSION_HEX >= 0x03030000 if (cause) { #else if (cause && cause != Py_None) { #endif PyObject *fixed_cause; if (cause == Py_None) { fixed_cause = NULL; } else if (PyExceptionClass_Check(cause)) { fixed_cause = PyObject_CallObject(cause, NULL); if (fixed_cause == NULL) goto bad; } else if (PyExceptionInstance_Check(cause)) { fixed_cause = cause; Py_INCREF(fixed_cause); } else { PyErr_SetString(PyExc_TypeError, "exception causes must derive from " "BaseException"); goto bad; } PyException_SetCause(value, fixed_cause); } PyErr_SetObject(type, value); if (tb) { #if CYTHON_COMPILING_IN_PYPY PyObject *tmp_type, *tmp_value, *tmp_tb; PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); Py_INCREF(tb); PyErr_Restore(tmp_type, tmp_value, tb); Py_XDECREF(tmp_tb); #else PyThreadState *tstate = PyThreadState_GET(); PyObject* tmp_tb = tstate->curexc_traceback; if (tb != tmp_tb) { Py_INCREF(tb); tstate->curexc_traceback = tb; Py_XDECREF(tmp_tb); } #endif } bad: Py_XDECREF(owned_instance); return; } #endif /* UnicodeAsUCS4 */ static CYTHON_INLINE Py_UCS4 __Pyx_PyUnicode_AsPy_UCS4(PyObject* x) { Py_ssize_t length; #if CYTHON_PEP393_ENABLED length = PyUnicode_GET_LENGTH(x); if (likely(length == 1)) { return PyUnicode_READ_CHAR(x, 0); } #else length = PyUnicode_GET_SIZE(x); if (likely(length == 1)) { return PyUnicode_AS_UNICODE(x)[0]; } #if Py_UNICODE_SIZE == 2 else if (PyUnicode_GET_SIZE(x) == 2) { Py_UCS4 high_val = PyUnicode_AS_UNICODE(x)[0]; if (high_val >= 0xD800 && high_val <= 0xDBFF) { Py_UCS4 low_val = PyUnicode_AS_UNICODE(x)[1]; if (low_val >= 0xDC00 && low_val <= 0xDFFF) { return 0x10000 + (((high_val & ((1<<10)-1)) << 10) | (low_val & ((1<<10)-1))); } } } #endif #endif PyErr_Format(PyExc_ValueError, "only single character unicode strings can be converted to Py_UCS4, " "got length %" CYTHON_FORMAT_SSIZE_T "d", length); return (Py_UCS4)-1; } /* object_ord */ static long __Pyx__PyObject_Ord(PyObject* c) { Py_ssize_t size; if (PyBytes_Check(c)) { size = PyBytes_GET_SIZE(c); if (likely(size == 1)) { return (unsigned char) PyBytes_AS_STRING(c)[0]; } #if PY_MAJOR_VERSION < 3 } else if (PyUnicode_Check(c)) { return (long)__Pyx_PyUnicode_AsPy_UCS4(c); #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) } else if (PyByteArray_Check(c)) { size = PyByteArray_GET_SIZE(c); if (likely(size == 1)) { return (unsigned char) PyByteArray_AS_STRING(c)[0]; } #endif } else { PyErr_Format(PyExc_TypeError, "ord() expected string of length 1, but %.200s found", c->ob_type->tp_name); return (long)(Py_UCS4)-1; } PyErr_Format(PyExc_TypeError, "ord() expected a character, but string of length %zd found", size); return (long)(Py_UCS4)-1; } /* SetItemInt */ static CYTHON_INLINE int __Pyx_SetItemInt_Generic(PyObject *o, PyObject *j, PyObject *v) { int r; if (!j) return -1; r = PyObject_SetItem(o, j, v); Py_DECREF(j); return r; } static CYTHON_INLINE int __Pyx_SetItemInt_Fast(PyObject *o, Py_ssize_t i, PyObject *v, int is_list, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (is_list || PyList_CheckExact(o)) { Py_ssize_t n = (!wraparound) ? i : ((likely(i >= 0)) ? i : i + PyList_GET_SIZE(o)); if ((!boundscheck) || likely((n >= 0) & (n < PyList_GET_SIZE(o)))) { PyObject* old = PyList_GET_ITEM(o, n); Py_INCREF(v); PyList_SET_ITEM(o, n, v); Py_DECREF(old); return 1; } } else { PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; if (likely(m && m->sq_ass_item)) { if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { Py_ssize_t l = m->sq_length(o); if (likely(l >= 0)) { i += l; } else { if (!PyErr_ExceptionMatches(PyExc_OverflowError)) return -1; PyErr_Clear(); } } return m->sq_ass_item(o, i, v); } } #else #if CYTHON_COMPILING_IN_PYPY if (is_list || (PySequence_Check(o) && !PyDict_Check(o))) { #else if (is_list || PySequence_Check(o)) { #endif return PySequence_SetItem(o, i, v); } #endif return __Pyx_SetItemInt_Generic(o, PyInt_FromSsize_t(i), v); } /* PyObjectCallMethod0 */ static PyObject* __Pyx_PyObject_CallMethod0(PyObject* obj, PyObject* method_name) { PyObject *method, *result = NULL; method = __Pyx_PyObject_GetAttrStr(obj, method_name); if (unlikely(!method)) goto bad; #if CYTHON_COMPILING_IN_CPYTHON if (likely(PyMethod_Check(method))) { PyObject *self = PyMethod_GET_SELF(method); if (likely(self)) { PyObject *function = PyMethod_GET_FUNCTION(method); result = __Pyx_PyObject_CallOneArg(function, self); Py_DECREF(method); return result; } } #endif result = __Pyx_PyObject_CallNoArg(method); Py_DECREF(method); bad: return result; } /* RaiseNoneIterError */ static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) { PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable"); } /* UnpackTupleError */ static void __Pyx_UnpackTupleError(PyObject *t, Py_ssize_t index) { if (t == Py_None) { __Pyx_RaiseNoneNotIterableError(); } else if (PyTuple_GET_SIZE(t) < index) { __Pyx_RaiseNeedMoreValuesError(PyTuple_GET_SIZE(t)); } else { __Pyx_RaiseTooManyValuesError(index); } } /* UnpackTuple2 */ static CYTHON_INLINE int __Pyx_unpack_tuple2(PyObject* tuple, PyObject** pvalue1, PyObject** pvalue2, int is_tuple, int has_known_size, int decref_tuple) { Py_ssize_t index; PyObject *value1 = NULL, *value2 = NULL, *iter = NULL; if (!is_tuple && unlikely(!PyTuple_Check(tuple))) { iternextfunc iternext; iter = PyObject_GetIter(tuple); if (unlikely(!iter)) goto bad; if (decref_tuple) { Py_DECREF(tuple); tuple = NULL; } iternext = Py_TYPE(iter)->tp_iternext; value1 = iternext(iter); if (unlikely(!value1)) { index = 0; goto unpacking_failed; } value2 = iternext(iter); if (unlikely(!value2)) { index = 1; goto unpacking_failed; } if (!has_known_size && unlikely(__Pyx_IternextUnpackEndCheck(iternext(iter), 2))) goto bad; Py_DECREF(iter); } else { if (!has_known_size && unlikely(PyTuple_GET_SIZE(tuple) != 2)) { __Pyx_UnpackTupleError(tuple, 2); goto bad; } #if CYTHON_COMPILING_IN_PYPY value1 = PySequence_ITEM(tuple, 0); if (unlikely(!value1)) goto bad; value2 = PySequence_ITEM(tuple, 1); if (unlikely(!value2)) goto bad; #else value1 = PyTuple_GET_ITEM(tuple, 0); value2 = PyTuple_GET_ITEM(tuple, 1); Py_INCREF(value1); Py_INCREF(value2); #endif if (decref_tuple) { Py_DECREF(tuple); } } *pvalue1 = value1; *pvalue2 = value2; return 0; unpacking_failed: if (!has_known_size && __Pyx_IterFinish() == 0) __Pyx_RaiseNeedMoreValuesError(index); bad: Py_XDECREF(iter); Py_XDECREF(value1); Py_XDECREF(value2); if (decref_tuple) { Py_XDECREF(tuple); } return -1; } /* dict_iter */ static CYTHON_INLINE PyObject* __Pyx_dict_iterator(PyObject* iterable, int is_dict, PyObject* method_name, Py_ssize_t* p_orig_length, int* p_source_is_dict) { is_dict = is_dict || likely(PyDict_CheckExact(iterable)); *p_source_is_dict = is_dict; #if !CYTHON_COMPILING_IN_PYPY if (is_dict) { *p_orig_length = PyDict_Size(iterable); Py_INCREF(iterable); return iterable; } #endif *p_orig_length = 0; if (method_name) { PyObject* iter; iterable = __Pyx_PyObject_CallMethod0(iterable, method_name); if (!iterable) return NULL; #if !CYTHON_COMPILING_IN_PYPY if (PyTuple_CheckExact(iterable) || PyList_CheckExact(iterable)) return iterable; #endif iter = PyObject_GetIter(iterable); Py_DECREF(iterable); return iter; } return PyObject_GetIter(iterable); } static CYTHON_INLINE int __Pyx_dict_iter_next( PyObject* iter_obj, CYTHON_NCP_UNUSED Py_ssize_t orig_length, CYTHON_NCP_UNUSED Py_ssize_t* ppos, PyObject** pkey, PyObject** pvalue, PyObject** pitem, int source_is_dict) { PyObject* next_item; #if !CYTHON_COMPILING_IN_PYPY if (source_is_dict) { PyObject *key, *value; if (unlikely(orig_length != PyDict_Size(iter_obj))) { PyErr_SetString(PyExc_RuntimeError, "dictionary changed size during iteration"); return -1; } if (unlikely(!PyDict_Next(iter_obj, ppos, &key, &value))) { return 0; } if (pitem) { PyObject* tuple = PyTuple_New(2); if (unlikely(!tuple)) { return -1; } Py_INCREF(key); Py_INCREF(value); PyTuple_SET_ITEM(tuple, 0, key); PyTuple_SET_ITEM(tuple, 1, value); *pitem = tuple; } else { if (pkey) { Py_INCREF(key); *pkey = key; } if (pvalue) { Py_INCREF(value); *pvalue = value; } } return 1; } else if (PyTuple_CheckExact(iter_obj)) { Py_ssize_t pos = *ppos; if (unlikely(pos >= PyTuple_GET_SIZE(iter_obj))) return 0; *ppos = pos + 1; next_item = PyTuple_GET_ITEM(iter_obj, pos); Py_INCREF(next_item); } else if (PyList_CheckExact(iter_obj)) { Py_ssize_t pos = *ppos; if (unlikely(pos >= PyList_GET_SIZE(iter_obj))) return 0; *ppos = pos + 1; next_item = PyList_GET_ITEM(iter_obj, pos); Py_INCREF(next_item); } else #endif { next_item = PyIter_Next(iter_obj); if (unlikely(!next_item)) { return __Pyx_IterFinish(); } } if (pitem) { *pitem = next_item; } else if (pkey && pvalue) { if (__Pyx_unpack_tuple2(next_item, pkey, pvalue, source_is_dict, source_is_dict, 1)) return -1; } else if (pkey) { *pkey = next_item; } else { *pvalue = next_item; } return 1; } /* ArgTypeTest */ static void __Pyx_RaiseArgumentTypeInvalid(const char* name, PyObject *obj, PyTypeObject *type) { PyErr_Format(PyExc_TypeError, "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", name, type->tp_name, Py_TYPE(obj)->tp_name); } static CYTHON_INLINE int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed, const char *name, int exact) { if (unlikely(!type)) { PyErr_SetString(PyExc_SystemError, "Missing type object"); return 0; } if (none_allowed && obj == Py_None) return 1; else if (exact) { if (likely(Py_TYPE(obj) == type)) return 1; #if PY_MAJOR_VERSION == 2 else if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; #endif } else { if (likely(PyObject_TypeCheck(obj, type))) return 1; } __Pyx_RaiseArgumentTypeInvalid(name, obj, type); return 0; } /* BufferFormatCheck */ static CYTHON_INLINE int __Pyx_IsLittleEndian(void) { unsigned int n = 1; return *(unsigned char*)(&n) != 0; } static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, __Pyx_BufFmt_StackElem* stack, __Pyx_TypeInfo* type) { stack[0].field = &ctx->root; stack[0].parent_offset = 0; ctx->root.type = type; ctx->root.name = "buffer dtype"; ctx->root.offset = 0; ctx->head = stack; ctx->head->field = &ctx->root; ctx->fmt_offset = 0; ctx->head->parent_offset = 0; ctx->new_packmode = '@'; ctx->enc_packmode = '@'; ctx->new_count = 1; ctx->enc_count = 0; ctx->enc_type = 0; ctx->is_complex = 0; ctx->is_valid_array = 0; ctx->struct_alignment = 0; while (type->typegroup == 'S') { ++ctx->head; ctx->head->field = type->fields; ctx->head->parent_offset = 0; type = type->fields->type; } } static int __Pyx_BufFmt_ParseNumber(const char** ts) { int count; const char* t = *ts; if (*t < '0' || *t > '9') { return -1; } else { count = *t++ - '0'; while (*t >= '0' && *t < '9') { count *= 10; count += *t++ - '0'; } } *ts = t; return count; } static int __Pyx_BufFmt_ExpectNumber(const char **ts) { int number = __Pyx_BufFmt_ParseNumber(ts); if (number == -1) PyErr_Format(PyExc_ValueError,\ "Does not understand character buffer dtype format string ('%c')", **ts); return number; } static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { PyErr_Format(PyExc_ValueError, "Unexpected format string character: '%c'", ch); } static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { switch (ch) { case 'c': return "'char'"; case 'b': return "'signed char'"; case 'B': return "'unsigned char'"; case 'h': return "'short'"; case 'H': return "'unsigned short'"; case 'i': return "'int'"; case 'I': return "'unsigned int'"; case 'l': return "'long'"; case 'L': return "'unsigned long'"; case 'q': return "'long long'"; case 'Q': return "'unsigned long long'"; case 'f': return (is_complex ? "'complex float'" : "'float'"); case 'd': return (is_complex ? "'complex double'" : "'double'"); case 'g': return (is_complex ? "'complex long double'" : "'long double'"); case 'T': return "a struct"; case 'O': return "Python object"; case 'P': return "a pointer"; case 's': case 'p': return "a string"; case 0: return "end"; default: return "unparseable format string"; } } static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return 2; case 'i': case 'I': case 'l': case 'L': return 4; case 'q': case 'Q': return 8; case 'f': return (is_complex ? 8 : 4); case 'd': return (is_complex ? 16 : 8); case 'g': { PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); return 0; } case 'O': case 'P': return sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { switch (ch) { case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(short); case 'i': case 'I': return sizeof(int); case 'l': case 'L': return sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(float) * (is_complex ? 2 : 1); case 'd': return sizeof(double) * (is_complex ? 2 : 1); case 'g': return sizeof(long double) * (is_complex ? 2 : 1); case 'O': case 'P': return sizeof(void*); default: { __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } } typedef struct { char c; short x; } __Pyx_st_short; typedef struct { char c; int x; } __Pyx_st_int; typedef struct { char c; long x; } __Pyx_st_long; typedef struct { char c; float x; } __Pyx_st_float; typedef struct { char c; double x; } __Pyx_st_double; typedef struct { char c; long double x; } __Pyx_st_longdouble; typedef struct { char c; void *x; } __Pyx_st_void_p; #ifdef HAVE_LONG_LONG typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; #endif static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(__Pyx_st_float) - sizeof(float); case 'd': return sizeof(__Pyx_st_double) - sizeof(double); case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } /* These are for computing the padding at the end of the struct to align on the first member of the struct. This will probably the same as above, but we don't have any guarantees. */ typedef struct { short x; char c; } __Pyx_pad_short; typedef struct { int x; char c; } __Pyx_pad_int; typedef struct { long x; char c; } __Pyx_pad_long; typedef struct { float x; char c; } __Pyx_pad_float; typedef struct { double x; char c; } __Pyx_pad_double; typedef struct { long double x; char c; } __Pyx_pad_longdouble; typedef struct { void *x; char c; } __Pyx_pad_void_p; #ifdef HAVE_LONG_LONG typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; #endif static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { switch (ch) { case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); #ifdef HAVE_LONG_LONG case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); #endif case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); default: __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { switch (ch) { case 'c': return 'H'; case 'b': case 'h': case 'i': case 'l': case 'q': case 's': case 'p': return 'I'; case 'B': case 'H': case 'I': case 'L': case 'Q': return 'U'; case 'f': case 'd': case 'g': return (is_complex ? 'C' : 'R'); case 'O': return 'O'; case 'P': return 'P'; default: { __Pyx_BufFmt_RaiseUnexpectedChar(ch); return 0; } } } static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { if (ctx->head == NULL || ctx->head->field == &ctx->root) { const char* expected; const char* quote; if (ctx->head == NULL) { expected = "end"; quote = ""; } else { expected = ctx->head->field->type->name; quote = "'"; } PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch, expected %s%s%s but got %s", quote, expected, quote, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); } else { __Pyx_StructField* field = ctx->head->field; __Pyx_StructField* parent = (ctx->head - 1)->field; PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), parent->type->name, field->name); } } static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { char group; size_t size, offset, arraysize = 1; if (ctx->enc_type == 0) return 0; if (ctx->head->field->type->arraysize[0]) { int i, ndim = 0; if (ctx->enc_type == 's' || ctx->enc_type == 'p') { ctx->is_valid_array = ctx->head->field->type->ndim == 1; ndim = 1; if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { PyErr_Format(PyExc_ValueError, "Expected a dimension of size %zu, got %zu", ctx->head->field->type->arraysize[0], ctx->enc_count); return -1; } } if (!ctx->is_valid_array) { PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", ctx->head->field->type->ndim, ndim); return -1; } for (i = 0; i < ctx->head->field->type->ndim; i++) { arraysize *= ctx->head->field->type->arraysize[i]; } ctx->is_valid_array = 0; ctx->enc_count = 1; } group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); do { __Pyx_StructField* field = ctx->head->field; __Pyx_TypeInfo* type = field->type; if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); } else { size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); } if (ctx->enc_packmode == '@') { size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); size_t align_mod_offset; if (align_at == 0) return -1; align_mod_offset = ctx->fmt_offset % align_at; if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; if (ctx->struct_alignment == 0) ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, ctx->is_complex); } if (type->size != size || type->typegroup != group) { if (type->typegroup == 'C' && type->fields != NULL) { size_t parent_offset = ctx->head->parent_offset + field->offset; ++ctx->head; ctx->head->field = type->fields; ctx->head->parent_offset = parent_offset; continue; } if ((type->typegroup == 'H' || group == 'H') && type->size == size) { } else { __Pyx_BufFmt_RaiseExpected(ctx); return -1; } } offset = ctx->head->parent_offset + field->offset; if (ctx->fmt_offset != offset) { PyErr_Format(PyExc_ValueError, "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); return -1; } ctx->fmt_offset += size; if (arraysize) ctx->fmt_offset += (arraysize - 1) * size; --ctx->enc_count; while (1) { if (field == &ctx->root) { ctx->head = NULL; if (ctx->enc_count != 0) { __Pyx_BufFmt_RaiseExpected(ctx); return -1; } break; } ctx->head->field = ++field; if (field->type == NULL) { --ctx->head; field = ctx->head->field; continue; } else if (field->type->typegroup == 'S') { size_t parent_offset = ctx->head->parent_offset + field->offset; if (field->type->fields->type == NULL) continue; field = field->type->fields; ++ctx->head; ctx->head->field = field; ctx->head->parent_offset = parent_offset; break; } else { break; } } } while (ctx->enc_count); ctx->enc_type = 0; ctx->is_complex = 0; return 0; } static CYTHON_INLINE PyObject * __pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) { const char *ts = *tsp; int i = 0, number; int ndim = ctx->head->field->type->ndim; ; ++ts; if (ctx->new_count != 1) { PyErr_SetString(PyExc_ValueError, "Cannot handle repeated arrays in format string"); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; while (*ts && *ts != ')') { switch (*ts) { case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; default: break; } number = __Pyx_BufFmt_ExpectNumber(&ts); if (number == -1) return NULL; if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) return PyErr_Format(PyExc_ValueError, "Expected a dimension of size %zu, got %d", ctx->head->field->type->arraysize[i], number); if (*ts != ',' && *ts != ')') return PyErr_Format(PyExc_ValueError, "Expected a comma in format string, got '%c'", *ts); if (*ts == ',') ts++; i++; } if (i != ndim) return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", ctx->head->field->type->ndim, i); if (!*ts) { PyErr_SetString(PyExc_ValueError, "Unexpected end of format string, expected ')'"); return NULL; } ctx->is_valid_array = 1; ctx->new_count = 1; *tsp = ++ts; return Py_None; } static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { int got_Z = 0; while (1) { switch(*ts) { case 0: if (ctx->enc_type != 0 && ctx->head == NULL) { __Pyx_BufFmt_RaiseExpected(ctx); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; if (ctx->head != NULL) { __Pyx_BufFmt_RaiseExpected(ctx); return NULL; } return ts; case ' ': case '\r': case '\n': ++ts; break; case '<': if (!__Pyx_IsLittleEndian()) { PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); return NULL; } ctx->new_packmode = '='; ++ts; break; case '>': case '!': if (__Pyx_IsLittleEndian()) { PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); return NULL; } ctx->new_packmode = '='; ++ts; break; case '=': case '@': case '^': ctx->new_packmode = *ts++; break; case 'T': { const char* ts_after_sub; size_t i, struct_count = ctx->new_count; size_t struct_alignment = ctx->struct_alignment; ctx->new_count = 1; ++ts; if (*ts != '{') { PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); return NULL; } if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_type = 0; ctx->enc_count = 0; ctx->struct_alignment = 0; ++ts; ts_after_sub = ts; for (i = 0; i != struct_count; ++i) { ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); if (!ts_after_sub) return NULL; } ts = ts_after_sub; if (struct_alignment) ctx->struct_alignment = struct_alignment; } break; case '}': { size_t alignment = ctx->struct_alignment; ++ts; if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_type = 0; if (alignment && ctx->fmt_offset % alignment) { ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); } } return ts; case 'x': if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->fmt_offset += ctx->new_count; ctx->new_count = 1; ctx->enc_count = 0; ctx->enc_type = 0; ctx->enc_packmode = ctx->new_packmode; ++ts; break; case 'Z': got_Z = 1; ++ts; if (*ts != 'f' && *ts != 'd' && *ts != 'g') { __Pyx_BufFmt_RaiseUnexpectedChar('Z'); return NULL; } case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': case 'l': case 'L': case 'q': case 'Q': case 'f': case 'd': case 'g': case 'O': case 'p': if (ctx->enc_type == *ts && got_Z == ctx->is_complex && ctx->enc_packmode == ctx->new_packmode) { ctx->enc_count += ctx->new_count; ctx->new_count = 1; got_Z = 0; ++ts; break; } case 's': if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; ctx->enc_count = ctx->new_count; ctx->enc_packmode = ctx->new_packmode; ctx->enc_type = *ts; ctx->is_complex = got_Z; ++ts; ctx->new_count = 1; got_Z = 0; break; case ':': ++ts; while(*ts != ':') ++ts; ++ts; break; case '(': if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; break; default: { int number = __Pyx_BufFmt_ExpectNumber(&ts); if (number == -1) return NULL; ctx->new_count = (size_t)number; } } } } static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) { buf->buf = NULL; buf->obj = NULL; buf->strides = __Pyx_zeros; buf->shape = __Pyx_zeros; buf->suboffsets = __Pyx_minusones; } static CYTHON_INLINE int __Pyx_GetBufferAndValidate( Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack) { if (obj == Py_None || obj == NULL) { __Pyx_ZeroBuffer(buf); return 0; } buf->buf = NULL; if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail; if (buf->ndim != nd) { PyErr_Format(PyExc_ValueError, "Buffer has wrong number of dimensions (expected %d, got %d)", nd, buf->ndim); goto fail; } if (!cast) { __Pyx_BufFmt_Context ctx; __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } if ((unsigned)buf->itemsize != dtype->size) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); goto fail; } if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; return 0; fail:; __Pyx_ZeroBuffer(buf); return -1; } static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { if (info->buf == NULL) return; if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; __Pyx_ReleaseBuffer(info); } /* MemviewSliceInit */ static int __Pyx_init_memviewslice(struct __pyx_memoryview_obj *memview, int ndim, __Pyx_memviewslice *memviewslice, int memview_is_new_reference) { __Pyx_RefNannyDeclarations int i, retval=-1; Py_buffer *buf = &memview->view; __Pyx_RefNannySetupContext("init_memviewslice", 0); if (!buf) { PyErr_SetString(PyExc_ValueError, "buf is NULL."); goto fail; } else if (memviewslice->memview || memviewslice->data) { PyErr_SetString(PyExc_ValueError, "memviewslice is already initialized!"); goto fail; } if (buf->strides) { for (i = 0; i < ndim; i++) { memviewslice->strides[i] = buf->strides[i]; } } else { Py_ssize_t stride = buf->itemsize; for (i = ndim - 1; i >= 0; i--) { memviewslice->strides[i] = stride; stride *= buf->shape[i]; } } for (i = 0; i < ndim; i++) { memviewslice->shape[i] = buf->shape[i]; if (buf->suboffsets) { memviewslice->suboffsets[i] = buf->suboffsets[i]; } else { memviewslice->suboffsets[i] = -1; } } memviewslice->memview = memview; memviewslice->data = (char *)buf->buf; if (__pyx_add_acquisition_count(memview) == 0 && !memview_is_new_reference) { Py_INCREF(memview); } retval = 0; goto no_fail; fail: memviewslice->memview = 0; memviewslice->data = 0; retval = -1; no_fail: __Pyx_RefNannyFinishContext(); return retval; } static CYTHON_INLINE void __pyx_fatalerror(const char *fmt, ...) { va_list vargs; char msg[200]; #ifdef HAVE_STDARG_PROTOTYPES va_start(vargs, fmt); #else va_start(vargs); #endif vsnprintf(msg, 200, fmt, vargs); Py_FatalError(msg); va_end(vargs); } static CYTHON_INLINE int __pyx_add_acquisition_count_locked(__pyx_atomic_int *acquisition_count, PyThread_type_lock lock) { int result; PyThread_acquire_lock(lock, 1); result = (*acquisition_count)++; PyThread_release_lock(lock); return result; } static CYTHON_INLINE int __pyx_sub_acquisition_count_locked(__pyx_atomic_int *acquisition_count, PyThread_type_lock lock) { int result; PyThread_acquire_lock(lock, 1); result = (*acquisition_count)--; PyThread_release_lock(lock); return result; } static CYTHON_INLINE void __Pyx_INC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int first_time; struct __pyx_memoryview_obj *memview = memslice->memview; if (!memview || (PyObject *) memview == Py_None) return; if (__pyx_get_slice_count(memview) < 0) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); first_time = __pyx_add_acquisition_count(memview) == 0; if (first_time) { if (have_gil) { Py_INCREF((PyObject *) memview); } else { PyGILState_STATE _gilstate = PyGILState_Ensure(); Py_INCREF((PyObject *) memview); PyGILState_Release(_gilstate); } } } static CYTHON_INLINE void __Pyx_XDEC_MEMVIEW(__Pyx_memviewslice *memslice, int have_gil, int lineno) { int last_time; struct __pyx_memoryview_obj *memview = memslice->memview; if (!memview ) { return; } else if ((PyObject *) memview == Py_None) { memslice->memview = NULL; return; } if (__pyx_get_slice_count(memview) <= 0) __pyx_fatalerror("Acquisition count is %d (line %d)", __pyx_get_slice_count(memview), lineno); last_time = __pyx_sub_acquisition_count(memview) == 1; memslice->data = NULL; if (last_time) { if (have_gil) { Py_CLEAR(memslice->memview); } else { PyGILState_STATE _gilstate = PyGILState_Ensure(); Py_CLEAR(memslice->memview); PyGILState_Release(_gilstate); } } else { memslice->memview = NULL; } } /* ExtTypeTest */ static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { if (unlikely(!type)) { PyErr_SetString(PyExc_SystemError, "Missing type object"); return 0; } if (likely(PyObject_TypeCheck(obj, type))) return 1; PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", Py_TYPE(obj)->tp_name, type->tp_name); return 0; } /* BytesEquals */ static CYTHON_INLINE int __Pyx_PyBytes_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); #else if (s1 == s2) { return (equals == Py_EQ); } else if (PyBytes_CheckExact(s1) & PyBytes_CheckExact(s2)) { const char *ps1, *ps2; Py_ssize_t length = PyBytes_GET_SIZE(s1); if (length != PyBytes_GET_SIZE(s2)) return (equals == Py_NE); ps1 = PyBytes_AS_STRING(s1); ps2 = PyBytes_AS_STRING(s2); if (ps1[0] != ps2[0]) { return (equals == Py_NE); } else if (length == 1) { return (equals == Py_EQ); } else { int result = memcmp(ps1, ps2, (size_t)length); return (equals == Py_EQ) ? (result == 0) : (result != 0); } } else if ((s1 == Py_None) & PyBytes_CheckExact(s2)) { return (equals == Py_NE); } else if ((s2 == Py_None) & PyBytes_CheckExact(s1)) { return (equals == Py_NE); } else { int result; PyObject* py_result = PyObject_RichCompare(s1, s2, equals); if (!py_result) return -1; result = __Pyx_PyObject_IsTrue(py_result); Py_DECREF(py_result); return result; } #endif } /* UnicodeEquals */ static CYTHON_INLINE int __Pyx_PyUnicode_Equals(PyObject* s1, PyObject* s2, int equals) { #if CYTHON_COMPILING_IN_PYPY return PyObject_RichCompareBool(s1, s2, equals); #else #if PY_MAJOR_VERSION < 3 PyObject* owned_ref = NULL; #endif int s1_is_unicode, s2_is_unicode; if (s1 == s2) { goto return_eq; } s1_is_unicode = PyUnicode_CheckExact(s1); s2_is_unicode = PyUnicode_CheckExact(s2); #if PY_MAJOR_VERSION < 3 if ((s1_is_unicode & (!s2_is_unicode)) && PyString_CheckExact(s2)) { owned_ref = PyUnicode_FromObject(s2); if (unlikely(!owned_ref)) return -1; s2 = owned_ref; s2_is_unicode = 1; } else if ((s2_is_unicode & (!s1_is_unicode)) && PyString_CheckExact(s1)) { owned_ref = PyUnicode_FromObject(s1); if (unlikely(!owned_ref)) return -1; s1 = owned_ref; s1_is_unicode = 1; } else if (((!s2_is_unicode) & (!s1_is_unicode))) { return __Pyx_PyBytes_Equals(s1, s2, equals); } #endif if (s1_is_unicode & s2_is_unicode) { Py_ssize_t length; int kind; void *data1, *data2; if (unlikely(__Pyx_PyUnicode_READY(s1) < 0) || unlikely(__Pyx_PyUnicode_READY(s2) < 0)) return -1; length = __Pyx_PyUnicode_GET_LENGTH(s1); if (length != __Pyx_PyUnicode_GET_LENGTH(s2)) { goto return_ne; } kind = __Pyx_PyUnicode_KIND(s1); if (kind != __Pyx_PyUnicode_KIND(s2)) { goto return_ne; } data1 = __Pyx_PyUnicode_DATA(s1); data2 = __Pyx_PyUnicode_DATA(s2); if (__Pyx_PyUnicode_READ(kind, data1, 0) != __Pyx_PyUnicode_READ(kind, data2, 0)) { goto return_ne; } else if (length == 1) { goto return_eq; } else { int result = memcmp(data1, data2, (size_t)(length * kind)); #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_EQ) ? (result == 0) : (result != 0); } } else if ((s1 == Py_None) & s2_is_unicode) { goto return_ne; } else if ((s2 == Py_None) & s1_is_unicode) { goto return_ne; } else { int result; PyObject* py_result = PyObject_RichCompare(s1, s2, equals); if (!py_result) return -1; result = __Pyx_PyObject_IsTrue(py_result); Py_DECREF(py_result); return result; } return_eq: #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_EQ); return_ne: #if PY_MAJOR_VERSION < 3 Py_XDECREF(owned_ref); #endif return (equals == Py_NE); #endif } /* None */ static CYTHON_INLINE Py_ssize_t __Pyx_div_Py_ssize_t(Py_ssize_t a, Py_ssize_t b) { Py_ssize_t q = a / b; Py_ssize_t r = a - q*b; q -= ((r != 0) & ((r ^ b) < 0)); return q; } /* GetAttr */ static CYTHON_INLINE PyObject *__Pyx_GetAttr(PyObject *o, PyObject *n) { #if CYTHON_COMPILING_IN_CPYTHON #if PY_MAJOR_VERSION >= 3 if (likely(PyUnicode_Check(n))) #else if (likely(PyString_Check(n))) #endif return __Pyx_PyObject_GetAttrStr(o, n); #endif return PyObject_GetAttr(o, n); } /* decode_c_string */ static CYTHON_INLINE PyObject* __Pyx_decode_c_string( const char* cstring, Py_ssize_t start, Py_ssize_t stop, const char* encoding, const char* errors, PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { Py_ssize_t length; if (unlikely((start < 0) | (stop < 0))) { size_t slen = strlen(cstring); if (unlikely(slen > (size_t) PY_SSIZE_T_MAX)) { PyErr_SetString(PyExc_OverflowError, "c-string too long to convert to Python"); return NULL; } length = (Py_ssize_t) slen; if (start < 0) { start += length; if (start < 0) start = 0; } if (stop < 0) stop += length; } length = stop - start; if (unlikely(length <= 0)) return PyUnicode_FromUnicode(NULL, 0); cstring += start; if (decode_func) { return decode_func(cstring, length, errors); } else { return PyUnicode_Decode(cstring, length, encoding, errors); } } /* SwapException */ #if CYTHON_COMPILING_IN_CPYTHON static CYTHON_INLINE void __Pyx__ExceptionSwap(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; tmp_type = tstate->exc_type; tmp_value = tstate->exc_value; tmp_tb = tstate->exc_traceback; tstate->exc_type = *type; tstate->exc_value = *value; tstate->exc_traceback = *tb; *type = tmp_type; *value = tmp_value; *tb = tmp_tb; } #else static CYTHON_INLINE void __Pyx_ExceptionSwap(PyObject **type, PyObject **value, PyObject **tb) { PyObject *tmp_type, *tmp_value, *tmp_tb; PyErr_GetExcInfo(&tmp_type, &tmp_value, &tmp_tb); PyErr_SetExcInfo(*type, *value, *tb); *type = tmp_type; *value = tmp_value; *tb = tmp_tb; } #endif /* GetItemInt */ static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) { PyObject *r; if (!j) return NULL; r = PyObject_GetItem(o, j); Py_DECREF(j); return r; } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (wraparound & unlikely(i < 0)) i += PyList_GET_SIZE(o); if ((!boundscheck) || likely((0 <= i) & (i < PyList_GET_SIZE(o)))) { PyObject *r = PyList_GET_ITEM(o, i); Py_INCREF(r); return r; } return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); #else return PySequence_GetItem(o, i); #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (wraparound & unlikely(i < 0)) i += PyTuple_GET_SIZE(o); if ((!boundscheck) || likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) { PyObject *r = PyTuple_GET_ITEM(o, i); Py_INCREF(r); return r; } return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); #else return PySequence_GetItem(o, i); #endif } static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i, int is_list, CYTHON_NCP_UNUSED int wraparound, CYTHON_NCP_UNUSED int boundscheck) { #if CYTHON_COMPILING_IN_CPYTHON if (is_list || PyList_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyList_GET_SIZE(o); if ((!boundscheck) || (likely((n >= 0) & (n < PyList_GET_SIZE(o))))) { PyObject *r = PyList_GET_ITEM(o, n); Py_INCREF(r); return r; } } else if (PyTuple_CheckExact(o)) { Py_ssize_t n = ((!wraparound) | likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o); if ((!boundscheck) || likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) { PyObject *r = PyTuple_GET_ITEM(o, n); Py_INCREF(r); return r; } } else { PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence; if (likely(m && m->sq_item)) { if (wraparound && unlikely(i < 0) && likely(m->sq_length)) { Py_ssize_t l = m->sq_length(o); if (likely(l >= 0)) { i += l; } else { if (!PyErr_ExceptionMatches(PyExc_OverflowError)) return NULL; PyErr_Clear(); } } return m->sq_item(o, i); } } #else if (is_list || PySequence_Check(o)) { return PySequence_GetItem(o, i); } #endif return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i)); } /* PyIntBinop */ #if CYTHON_COMPILING_IN_CPYTHON static PyObject* __Pyx_PyInt_AddObjC(PyObject *op1, PyObject *op2, CYTHON_UNUSED long intval, CYTHON_UNUSED int inplace) { #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(op1))) { const long b = intval; long x; long a = PyInt_AS_LONG(op1); x = (long)((unsigned long)a + b); if (likely((x^a) >= 0 || (x^b) >= 0)) return PyInt_FromLong(x); return PyLong_Type.tp_as_number->nb_add(op1, op2); } #endif #if CYTHON_USE_PYLONG_INTERNALS && PY_MAJOR_VERSION >= 3 if (likely(PyLong_CheckExact(op1))) { const long b = intval; long a, x; const PY_LONG_LONG llb = intval; PY_LONG_LONG lla, llx; const digit* digits = ((PyLongObject*)op1)->ob_digit; const Py_ssize_t size = Py_SIZE(op1); if (likely(__Pyx_sst_abs(size) <= 1)) { a = likely(size) ? digits[0] : 0; if (size == -1) a = -a; } else { switch (size) { case -2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case 2: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { a = (long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 2 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case -3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case 3: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { a = (long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 3 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case -4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = -(PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } case 4: if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { a = (long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0])); break; } else if (8 * sizeof(PY_LONG_LONG) - 1 > 4 * PyLong_SHIFT) { lla = (PY_LONG_LONG) (((((((((unsigned PY_LONG_LONG)digits[3]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[2]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[1]) << PyLong_SHIFT) | (unsigned PY_LONG_LONG)digits[0])); goto long_long; } default: return PyLong_Type.tp_as_number->nb_add(op1, op2); } } x = a + b; return PyLong_FromLong(x); long_long: llx = lla + llb; return PyLong_FromLongLong(llx); } #endif if (PyFloat_CheckExact(op1)) { const long b = intval; double a = PyFloat_AS_DOUBLE(op1); double result; PyFPE_START_PROTECT("add", return NULL) result = ((double)a) + (double)b; PyFPE_END_PROTECT(result) return PyFloat_FromDouble(result); } return (inplace ? PyNumber_InPlaceAdd : PyNumber_Add)(op1, op2); } #endif /* None */ static CYTHON_INLINE void __Pyx_RaiseUnboundLocalError(const char *varname) { PyErr_Format(PyExc_UnboundLocalError, "local variable '%s' referenced before assignment", varname); } /* None */ static CYTHON_INLINE long __Pyx_div_long(long a, long b) { long q = a / b; long r = a - q*b; q -= ((r != 0) & ((r ^ b) < 0)); return q; } /* WriteUnraisableException */ static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno, CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename, int full_traceback, CYTHON_UNUSED int nogil) { PyObject *old_exc, *old_val, *old_tb; PyObject *ctx; __Pyx_PyThreadState_declare #ifdef WITH_THREAD PyGILState_STATE state; if (nogil) state = PyGILState_Ensure(); #ifdef _MSC_VER else state = (PyGILState_STATE)-1; #endif #endif __Pyx_PyThreadState_assign __Pyx_ErrFetch(&old_exc, &old_val, &old_tb); if (full_traceback) { Py_XINCREF(old_exc); Py_XINCREF(old_val); Py_XINCREF(old_tb); __Pyx_ErrRestore(old_exc, old_val, old_tb); PyErr_PrintEx(1); } #if PY_MAJOR_VERSION < 3 ctx = PyString_FromString(name); #else ctx = PyUnicode_FromString(name); #endif __Pyx_ErrRestore(old_exc, old_val, old_tb); if (!ctx) { PyErr_WriteUnraisable(Py_None); } else { PyErr_WriteUnraisable(ctx); Py_DECREF(ctx); } #ifdef WITH_THREAD if (nogil) PyGILState_Release(state); #endif } /* SetVTable */ static int __Pyx_SetVtable(PyObject *dict, void *vtable) { #if PY_VERSION_HEX >= 0x02070000 PyObject *ob = PyCapsule_New(vtable, 0, 0); #else PyObject *ob = PyCObject_FromVoidPtr(vtable, 0); #endif if (!ob) goto bad; if (PyDict_SetItem(dict, __pyx_n_s_pyx_vtable, ob) < 0) goto bad; Py_DECREF(ob); return 0; bad: Py_XDECREF(ob); return -1; } /* ImportFrom */ static PyObject* __Pyx_ImportFrom(PyObject* module, PyObject* name) { PyObject* value = __Pyx_PyObject_GetAttrStr(module, name); if (unlikely(!value) && PyErr_ExceptionMatches(PyExc_AttributeError)) { PyErr_Format(PyExc_ImportError, #if PY_MAJOR_VERSION < 3 "cannot import name %.230s", PyString_AS_STRING(name)); #else "cannot import name %S", name); #endif } return value; } /* CalculateMetaclass */ static PyObject *__Pyx_CalculateMetaclass(PyTypeObject *metaclass, PyObject *bases) { Py_ssize_t i, nbases = PyTuple_GET_SIZE(bases); for (i=0; i < nbases; i++) { PyTypeObject *tmptype; PyObject *tmp = PyTuple_GET_ITEM(bases, i); tmptype = Py_TYPE(tmp); #if PY_MAJOR_VERSION < 3 if (tmptype == &PyClass_Type) continue; #endif if (!metaclass) { metaclass = tmptype; continue; } if (PyType_IsSubtype(metaclass, tmptype)) continue; if (PyType_IsSubtype(tmptype, metaclass)) { metaclass = tmptype; continue; } PyErr_SetString(PyExc_TypeError, "metaclass conflict: " "the metaclass of a derived class " "must be a (non-strict) subclass " "of the metaclasses of all its bases"); return NULL; } if (!metaclass) { #if PY_MAJOR_VERSION < 3 metaclass = &PyClass_Type; #else metaclass = &PyType_Type; #endif } Py_INCREF((PyObject*) metaclass); return (PyObject*) metaclass; } /* FetchCommonType */ static PyTypeObject* __Pyx_FetchCommonType(PyTypeObject* type) { PyObject* fake_module; PyTypeObject* cached_type = NULL; fake_module = PyImport_AddModule((char*) "_cython_" CYTHON_ABI); if (!fake_module) return NULL; Py_INCREF(fake_module); cached_type = (PyTypeObject*) PyObject_GetAttrString(fake_module, type->tp_name); if (cached_type) { if (!PyType_Check((PyObject*)cached_type)) { PyErr_Format(PyExc_TypeError, "Shared Cython type %.200s is not a type object", type->tp_name); goto bad; } if (cached_type->tp_basicsize != type->tp_basicsize) { PyErr_Format(PyExc_TypeError, "Shared Cython type %.200s has the wrong size, try recompiling", type->tp_name); goto bad; } } else { if (!PyErr_ExceptionMatches(PyExc_AttributeError)) goto bad; PyErr_Clear(); if (PyType_Ready(type) < 0) goto bad; if (PyObject_SetAttrString(fake_module, type->tp_name, (PyObject*) type) < 0) goto bad; Py_INCREF(type); cached_type = type; } done: Py_DECREF(fake_module); return cached_type; bad: Py_XDECREF(cached_type); cached_type = NULL; goto done; } /* CythonFunction */ static PyObject * __Pyx_CyFunction_get_doc(__pyx_CyFunctionObject *op, CYTHON_UNUSED void *closure) { if (unlikely(op->func_doc == NULL)) { if (op->func.m_ml->ml_doc) { #if PY_MAJOR_VERSION >= 3 op->func_doc = PyUnicode_FromString(op->func.m_ml->ml_doc); #else op->func_doc = PyString_FromString(op->func.m_ml->ml_doc); #endif if (unlikely(op->func_doc == NULL)) return NULL; } else { Py_INCREF(Py_None); return Py_None; } } Py_INCREF(op->func_doc); return op->func_doc; } static int __Pyx_CyFunction_set_doc(__pyx_CyFunctionObject *op, PyObject *value) { PyObject *tmp = op->func_doc; if (value == NULL) { value = Py_None; } Py_INCREF(value); op->func_doc = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_name(__pyx_CyFunctionObject *op) { if (unlikely(op->func_name == NULL)) { #if PY_MAJOR_VERSION >= 3 op->func_name = PyUnicode_InternFromString(op->func.m_ml->ml_name); #else op->func_name = PyString_InternFromString(op->func.m_ml->ml_name); #endif if (unlikely(op->func_name == NULL)) return NULL; } Py_INCREF(op->func_name); return op->func_name; } static int __Pyx_CyFunction_set_name(__pyx_CyFunctionObject *op, PyObject *value) { PyObject *tmp; #if PY_MAJOR_VERSION >= 3 if (unlikely(value == NULL || !PyUnicode_Check(value))) { #else if (unlikely(value == NULL || !PyString_Check(value))) { #endif PyErr_SetString(PyExc_TypeError, "__name__ must be set to a string object"); return -1; } tmp = op->func_name; Py_INCREF(value); op->func_name = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_qualname(__pyx_CyFunctionObject *op) { Py_INCREF(op->func_qualname); return op->func_qualname; } static int __Pyx_CyFunction_set_qualname(__pyx_CyFunctionObject *op, PyObject *value) { PyObject *tmp; #if PY_MAJOR_VERSION >= 3 if (unlikely(value == NULL || !PyUnicode_Check(value))) { #else if (unlikely(value == NULL || !PyString_Check(value))) { #endif PyErr_SetString(PyExc_TypeError, "__qualname__ must be set to a string object"); return -1; } tmp = op->func_qualname; Py_INCREF(value); op->func_qualname = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_self(__pyx_CyFunctionObject *m, CYTHON_UNUSED void *closure) { PyObject *self; self = m->func_closure; if (self == NULL) self = Py_None; Py_INCREF(self); return self; } static PyObject * __Pyx_CyFunction_get_dict(__pyx_CyFunctionObject *op) { if (unlikely(op->func_dict == NULL)) { op->func_dict = PyDict_New(); if (unlikely(op->func_dict == NULL)) return NULL; } Py_INCREF(op->func_dict); return op->func_dict; } static int __Pyx_CyFunction_set_dict(__pyx_CyFunctionObject *op, PyObject *value) { PyObject *tmp; if (unlikely(value == NULL)) { PyErr_SetString(PyExc_TypeError, "function's dictionary may not be deleted"); return -1; } if (unlikely(!PyDict_Check(value))) { PyErr_SetString(PyExc_TypeError, "setting function's dictionary to a non-dict"); return -1; } tmp = op->func_dict; Py_INCREF(value); op->func_dict = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_globals(__pyx_CyFunctionObject *op) { Py_INCREF(op->func_globals); return op->func_globals; } static PyObject * __Pyx_CyFunction_get_closure(CYTHON_UNUSED __pyx_CyFunctionObject *op) { Py_INCREF(Py_None); return Py_None; } static PyObject * __Pyx_CyFunction_get_code(__pyx_CyFunctionObject *op) { PyObject* result = (op->func_code) ? op->func_code : Py_None; Py_INCREF(result); return result; } static int __Pyx_CyFunction_init_defaults(__pyx_CyFunctionObject *op) { int result = 0; PyObject *res = op->defaults_getter((PyObject *) op); if (unlikely(!res)) return -1; #if CYTHON_COMPILING_IN_CPYTHON op->defaults_tuple = PyTuple_GET_ITEM(res, 0); Py_INCREF(op->defaults_tuple); op->defaults_kwdict = PyTuple_GET_ITEM(res, 1); Py_INCREF(op->defaults_kwdict); #else op->defaults_tuple = PySequence_ITEM(res, 0); if (unlikely(!op->defaults_tuple)) result = -1; else { op->defaults_kwdict = PySequence_ITEM(res, 1); if (unlikely(!op->defaults_kwdict)) result = -1; } #endif Py_DECREF(res); return result; } static int __Pyx_CyFunction_set_defaults(__pyx_CyFunctionObject *op, PyObject* value) { PyObject* tmp; if (!value) { value = Py_None; } else if (value != Py_None && !PyTuple_Check(value)) { PyErr_SetString(PyExc_TypeError, "__defaults__ must be set to a tuple object"); return -1; } Py_INCREF(value); tmp = op->defaults_tuple; op->defaults_tuple = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_defaults(__pyx_CyFunctionObject *op) { PyObject* result = op->defaults_tuple; if (unlikely(!result)) { if (op->defaults_getter) { if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL; result = op->defaults_tuple; } else { result = Py_None; } } Py_INCREF(result); return result; } static int __Pyx_CyFunction_set_kwdefaults(__pyx_CyFunctionObject *op, PyObject* value) { PyObject* tmp; if (!value) { value = Py_None; } else if (value != Py_None && !PyDict_Check(value)) { PyErr_SetString(PyExc_TypeError, "__kwdefaults__ must be set to a dict object"); return -1; } Py_INCREF(value); tmp = op->defaults_kwdict; op->defaults_kwdict = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_kwdefaults(__pyx_CyFunctionObject *op) { PyObject* result = op->defaults_kwdict; if (unlikely(!result)) { if (op->defaults_getter) { if (__Pyx_CyFunction_init_defaults(op) < 0) return NULL; result = op->defaults_kwdict; } else { result = Py_None; } } Py_INCREF(result); return result; } static int __Pyx_CyFunction_set_annotations(__pyx_CyFunctionObject *op, PyObject* value) { PyObject* tmp; if (!value || value == Py_None) { value = NULL; } else if (!PyDict_Check(value)) { PyErr_SetString(PyExc_TypeError, "__annotations__ must be set to a dict object"); return -1; } Py_XINCREF(value); tmp = op->func_annotations; op->func_annotations = value; Py_XDECREF(tmp); return 0; } static PyObject * __Pyx_CyFunction_get_annotations(__pyx_CyFunctionObject *op) { PyObject* result = op->func_annotations; if (unlikely(!result)) { result = PyDict_New(); if (unlikely(!result)) return NULL; op->func_annotations = result; } Py_INCREF(result); return result; } static PyGetSetDef __pyx_CyFunction_getsets[] = { {(char *) "func_doc", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0}, {(char *) "__doc__", (getter)__Pyx_CyFunction_get_doc, (setter)__Pyx_CyFunction_set_doc, 0, 0}, {(char *) "func_name", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0}, {(char *) "__name__", (getter)__Pyx_CyFunction_get_name, (setter)__Pyx_CyFunction_set_name, 0, 0}, {(char *) "__qualname__", (getter)__Pyx_CyFunction_get_qualname, (setter)__Pyx_CyFunction_set_qualname, 0, 0}, {(char *) "__self__", (getter)__Pyx_CyFunction_get_self, 0, 0, 0}, {(char *) "func_dict", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0}, {(char *) "__dict__", (getter)__Pyx_CyFunction_get_dict, (setter)__Pyx_CyFunction_set_dict, 0, 0}, {(char *) "func_globals", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0}, {(char *) "__globals__", (getter)__Pyx_CyFunction_get_globals, 0, 0, 0}, {(char *) "func_closure", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0}, {(char *) "__closure__", (getter)__Pyx_CyFunction_get_closure, 0, 0, 0}, {(char *) "func_code", (getter)__Pyx_CyFunction_get_code, 0, 0, 0}, {(char *) "__code__", (getter)__Pyx_CyFunction_get_code, 0, 0, 0}, {(char *) "func_defaults", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0}, {(char *) "__defaults__", (getter)__Pyx_CyFunction_get_defaults, (setter)__Pyx_CyFunction_set_defaults, 0, 0}, {(char *) "__kwdefaults__", (getter)__Pyx_CyFunction_get_kwdefaults, (setter)__Pyx_CyFunction_set_kwdefaults, 0, 0}, {(char *) "__annotations__", (getter)__Pyx_CyFunction_get_annotations, (setter)__Pyx_CyFunction_set_annotations, 0, 0}, {0, 0, 0, 0, 0} }; static PyMemberDef __pyx_CyFunction_members[] = { {(char *) "__module__", T_OBJECT, offsetof(__pyx_CyFunctionObject, func.m_module), PY_WRITE_RESTRICTED, 0}, {0, 0, 0, 0, 0} }; static PyObject * __Pyx_CyFunction_reduce(__pyx_CyFunctionObject *m, CYTHON_UNUSED PyObject *args) { #if PY_MAJOR_VERSION >= 3 return PyUnicode_FromString(m->func.m_ml->ml_name); #else return PyString_FromString(m->func.m_ml->ml_name); #endif } static PyMethodDef __pyx_CyFunction_methods[] = { {"__reduce__", (PyCFunction)__Pyx_CyFunction_reduce, METH_VARARGS, 0}, {0, 0, 0, 0} }; #if PY_VERSION_HEX < 0x030500A0 #define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func_weakreflist) #else #define __Pyx_CyFunction_weakreflist(cyfunc) ((cyfunc)->func.m_weakreflist) #endif static PyObject *__Pyx_CyFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags, PyObject* qualname, PyObject *closure, PyObject *module, PyObject* globals, PyObject* code) { __pyx_CyFunctionObject *op = PyObject_GC_New(__pyx_CyFunctionObject, type); if (op == NULL) return NULL; op->flags = flags; __Pyx_CyFunction_weakreflist(op) = NULL; op->func.m_ml = ml; op->func.m_self = (PyObject *) op; Py_XINCREF(closure); op->func_closure = closure; Py_XINCREF(module); op->func.m_module = module; op->func_dict = NULL; op->func_name = NULL; Py_INCREF(qualname); op->func_qualname = qualname; op->func_doc = NULL; op->func_classobj = NULL; op->func_globals = globals; Py_INCREF(op->func_globals); Py_XINCREF(code); op->func_code = code; op->defaults_pyobjects = 0; op->defaults = NULL; op->defaults_tuple = NULL; op->defaults_kwdict = NULL; op->defaults_getter = NULL; op->func_annotations = NULL; PyObject_GC_Track(op); return (PyObject *) op; } static int __Pyx_CyFunction_clear(__pyx_CyFunctionObject *m) { Py_CLEAR(m->func_closure); Py_CLEAR(m->func.m_module); Py_CLEAR(m->func_dict); Py_CLEAR(m->func_name); Py_CLEAR(m->func_qualname); Py_CLEAR(m->func_doc); Py_CLEAR(m->func_globals); Py_CLEAR(m->func_code); Py_CLEAR(m->func_classobj); Py_CLEAR(m->defaults_tuple); Py_CLEAR(m->defaults_kwdict); Py_CLEAR(m->func_annotations); if (m->defaults) { PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m); int i; for (i = 0; i < m->defaults_pyobjects; i++) Py_XDECREF(pydefaults[i]); PyObject_Free(m->defaults); m->defaults = NULL; } return 0; } static void __Pyx_CyFunction_dealloc(__pyx_CyFunctionObject *m) { PyObject_GC_UnTrack(m); if (__Pyx_CyFunction_weakreflist(m) != NULL) PyObject_ClearWeakRefs((PyObject *) m); __Pyx_CyFunction_clear(m); PyObject_GC_Del(m); } static int __Pyx_CyFunction_traverse(__pyx_CyFunctionObject *m, visitproc visit, void *arg) { Py_VISIT(m->func_closure); Py_VISIT(m->func.m_module); Py_VISIT(m->func_dict); Py_VISIT(m->func_name); Py_VISIT(m->func_qualname); Py_VISIT(m->func_doc); Py_VISIT(m->func_globals); Py_VISIT(m->func_code); Py_VISIT(m->func_classobj); Py_VISIT(m->defaults_tuple); Py_VISIT(m->defaults_kwdict); if (m->defaults) { PyObject **pydefaults = __Pyx_CyFunction_Defaults(PyObject *, m); int i; for (i = 0; i < m->defaults_pyobjects; i++) Py_VISIT(pydefaults[i]); } return 0; } static PyObject *__Pyx_CyFunction_descr_get(PyObject *func, PyObject *obj, PyObject *type) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; if (m->flags & __Pyx_CYFUNCTION_STATICMETHOD) { Py_INCREF(func); return func; } if (m->flags & __Pyx_CYFUNCTION_CLASSMETHOD) { if (type == NULL) type = (PyObject *)(Py_TYPE(obj)); return __Pyx_PyMethod_New(func, type, (PyObject *)(Py_TYPE(type))); } if (obj == Py_None) obj = NULL; return __Pyx_PyMethod_New(func, obj, type); } static PyObject* __Pyx_CyFunction_repr(__pyx_CyFunctionObject *op) { #if PY_MAJOR_VERSION >= 3 return PyUnicode_FromFormat("", op->func_qualname, (void *)op); #else return PyString_FromFormat("", PyString_AsString(op->func_qualname), (void *)op); #endif } #if CYTHON_COMPILING_IN_PYPY static PyObject * __Pyx_CyFunction_Call(PyObject *func, PyObject *arg, PyObject *kw) { PyCFunctionObject* f = (PyCFunctionObject*)func; PyCFunction meth = f->m_ml->ml_meth; PyObject *self = f->m_self; Py_ssize_t size; switch (f->m_ml->ml_flags & (METH_VARARGS | METH_KEYWORDS | METH_NOARGS | METH_O)) { case METH_VARARGS: if (likely(kw == NULL || PyDict_Size(kw) == 0)) return (*meth)(self, arg); break; case METH_VARARGS | METH_KEYWORDS: return (*(PyCFunctionWithKeywords)meth)(self, arg, kw); case METH_NOARGS: if (likely(kw == NULL || PyDict_Size(kw) == 0)) { size = PyTuple_GET_SIZE(arg); if (likely(size == 0)) return (*meth)(self, NULL); PyErr_Format(PyExc_TypeError, "%.200s() takes no arguments (%" CYTHON_FORMAT_SSIZE_T "d given)", f->m_ml->ml_name, size); return NULL; } break; case METH_O: if (likely(kw == NULL || PyDict_Size(kw) == 0)) { size = PyTuple_GET_SIZE(arg); if (likely(size == 1)) { PyObject *result, *arg0 = PySequence_ITEM(arg, 0); if (unlikely(!arg0)) return NULL; result = (*meth)(self, arg0); Py_DECREF(arg0); return result; } PyErr_Format(PyExc_TypeError, "%.200s() takes exactly one argument (%" CYTHON_FORMAT_SSIZE_T "d given)", f->m_ml->ml_name, size); return NULL; } break; default: PyErr_SetString(PyExc_SystemError, "Bad call flags in " "__Pyx_CyFunction_Call. METH_OLDARGS is no " "longer supported!"); return NULL; } PyErr_Format(PyExc_TypeError, "%.200s() takes no keyword arguments", f->m_ml->ml_name); return NULL; } #else static PyObject * __Pyx_CyFunction_Call(PyObject *func, PyObject *arg, PyObject *kw) { return PyCFunction_Call(func, arg, kw); } #endif static PyTypeObject __pyx_CyFunctionType_type = { PyVarObject_HEAD_INIT(0, 0) "cython_function_or_method", sizeof(__pyx_CyFunctionObject), 0, (destructor) __Pyx_CyFunction_dealloc, 0, 0, 0, #if PY_MAJOR_VERSION < 3 0, #else 0, #endif (reprfunc) __Pyx_CyFunction_repr, 0, 0, 0, 0, __Pyx_CyFunction_Call, 0, 0, 0, 0, Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, 0, (traverseproc) __Pyx_CyFunction_traverse, (inquiry) __Pyx_CyFunction_clear, 0, #if PY_VERSION_HEX < 0x030500A0 offsetof(__pyx_CyFunctionObject, func_weakreflist), #else offsetof(PyCFunctionObject, m_weakreflist), #endif 0, 0, __pyx_CyFunction_methods, __pyx_CyFunction_members, __pyx_CyFunction_getsets, 0, 0, __Pyx_CyFunction_descr_get, 0, offsetof(__pyx_CyFunctionObject, func_dict), 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, #if PY_VERSION_HEX >= 0x030400a1 0, #endif }; static int __pyx_CyFunction_init(void) { #if !CYTHON_COMPILING_IN_PYPY __pyx_CyFunctionType_type.tp_call = PyCFunction_Call; #endif __pyx_CyFunctionType = __Pyx_FetchCommonType(&__pyx_CyFunctionType_type); if (__pyx_CyFunctionType == NULL) { return -1; } return 0; } static CYTHON_INLINE void *__Pyx_CyFunction_InitDefaults(PyObject *func, size_t size, int pyobjects) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; m->defaults = PyObject_Malloc(size); if (!m->defaults) return PyErr_NoMemory(); memset(m->defaults, 0, size); m->defaults_pyobjects = pyobjects; return m->defaults; } static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsTuple(PyObject *func, PyObject *tuple) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; m->defaults_tuple = tuple; Py_INCREF(tuple); } static CYTHON_INLINE void __Pyx_CyFunction_SetDefaultsKwDict(PyObject *func, PyObject *dict) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; m->defaults_kwdict = dict; Py_INCREF(dict); } static CYTHON_INLINE void __Pyx_CyFunction_SetAnnotationsDict(PyObject *func, PyObject *dict) { __pyx_CyFunctionObject *m = (__pyx_CyFunctionObject *) func; m->func_annotations = dict; Py_INCREF(dict); } /* Py3ClassCreate */ static PyObject *__Pyx_Py3MetaclassPrepare(PyObject *metaclass, PyObject *bases, PyObject *name, PyObject *qualname, PyObject *mkw, PyObject *modname, PyObject *doc) { PyObject *ns; if (metaclass) { PyObject *prep = __Pyx_PyObject_GetAttrStr(metaclass, __pyx_n_s_prepare); if (prep) { PyObject *pargs = PyTuple_Pack(2, name, bases); if (unlikely(!pargs)) { Py_DECREF(prep); return NULL; } ns = PyObject_Call(prep, pargs, mkw); Py_DECREF(prep); Py_DECREF(pargs); } else { if (unlikely(!PyErr_ExceptionMatches(PyExc_AttributeError))) return NULL; PyErr_Clear(); ns = PyDict_New(); } } else { ns = PyDict_New(); } if (unlikely(!ns)) return NULL; if (unlikely(PyObject_SetItem(ns, __pyx_n_s_module, modname) < 0)) goto bad; if (unlikely(PyObject_SetItem(ns, __pyx_n_s_qualname, qualname) < 0)) goto bad; if (unlikely(doc && PyObject_SetItem(ns, __pyx_n_s_doc, doc) < 0)) goto bad; return ns; bad: Py_DECREF(ns); return NULL; } static PyObject *__Pyx_Py3ClassCreate(PyObject *metaclass, PyObject *name, PyObject *bases, PyObject *dict, PyObject *mkw, int calculate_metaclass, int allow_py2_metaclass) { PyObject *result, *margs; PyObject *owned_metaclass = NULL; if (allow_py2_metaclass) { owned_metaclass = PyObject_GetItem(dict, __pyx_n_s_metaclass); if (owned_metaclass) { metaclass = owned_metaclass; } else if (likely(PyErr_ExceptionMatches(PyExc_KeyError))) { PyErr_Clear(); } else { return NULL; } } if (calculate_metaclass && (!metaclass || PyType_Check(metaclass))) { metaclass = __Pyx_CalculateMetaclass((PyTypeObject*) metaclass, bases); Py_XDECREF(owned_metaclass); if (unlikely(!metaclass)) return NULL; owned_metaclass = metaclass; } margs = PyTuple_Pack(3, name, bases, dict); if (unlikely(!margs)) { result = NULL; } else { result = PyObject_Call(metaclass, margs, mkw); Py_DECREF(margs); } Py_XDECREF(owned_metaclass); return result; } /* FusedFunction */ static PyObject * __pyx_FusedFunction_New(PyTypeObject *type, PyMethodDef *ml, int flags, PyObject *qualname, PyObject *self, PyObject *module, PyObject *globals, PyObject *code) { __pyx_FusedFunctionObject *fusedfunc = (__pyx_FusedFunctionObject *) __Pyx_CyFunction_New(type, ml, flags, qualname, self, module, globals, code); if (!fusedfunc) return NULL; fusedfunc->__signatures__ = NULL; fusedfunc->type = NULL; fusedfunc->self = NULL; return (PyObject *) fusedfunc; } static void __pyx_FusedFunction_dealloc(__pyx_FusedFunctionObject *self) { __pyx_FusedFunction_clear(self); __pyx_FusedFunctionType->tp_free((PyObject *) self); } static int __pyx_FusedFunction_traverse(__pyx_FusedFunctionObject *self, visitproc visit, void *arg) { Py_VISIT(self->self); Py_VISIT(self->type); Py_VISIT(self->__signatures__); return __Pyx_CyFunction_traverse((__pyx_CyFunctionObject *) self, visit, arg); } static int __pyx_FusedFunction_clear(__pyx_FusedFunctionObject *self) { Py_CLEAR(self->self); Py_CLEAR(self->type); Py_CLEAR(self->__signatures__); return __Pyx_CyFunction_clear((__pyx_CyFunctionObject *) self); } static PyObject * __pyx_FusedFunction_descr_get(PyObject *self, PyObject *obj, PyObject *type) { __pyx_FusedFunctionObject *func, *meth; func = (__pyx_FusedFunctionObject *) self; if (func->self || func->func.flags & __Pyx_CYFUNCTION_STATICMETHOD) { Py_INCREF(self); return self; } if (obj == Py_None) obj = NULL; meth = (__pyx_FusedFunctionObject *) __pyx_FusedFunction_NewEx( ((PyCFunctionObject *) func)->m_ml, ((__pyx_CyFunctionObject *) func)->flags, ((__pyx_CyFunctionObject *) func)->func_qualname, ((__pyx_CyFunctionObject *) func)->func_closure, ((PyCFunctionObject *) func)->m_module, ((__pyx_CyFunctionObject *) func)->func_globals, ((__pyx_CyFunctionObject *) func)->func_code); if (!meth) return NULL; Py_XINCREF(func->func.func_classobj); meth->func.func_classobj = func->func.func_classobj; Py_XINCREF(func->__signatures__); meth->__signatures__ = func->__signatures__; Py_XINCREF(type); meth->type = type; Py_XINCREF(func->func.defaults_tuple); meth->func.defaults_tuple = func->func.defaults_tuple; if (func->func.flags & __Pyx_CYFUNCTION_CLASSMETHOD) obj = type; Py_XINCREF(obj); meth->self = obj; return (PyObject *) meth; } static PyObject * _obj_to_str(PyObject *obj) { if (PyType_Check(obj)) return PyObject_GetAttr(obj, __pyx_n_s_name_2); else return PyObject_Str(obj); } static PyObject * __pyx_FusedFunction_getitem(__pyx_FusedFunctionObject *self, PyObject *idx) { PyObject *signature = NULL; PyObject *unbound_result_func; PyObject *result_func = NULL; if (self->__signatures__ == NULL) { PyErr_SetString(PyExc_TypeError, "Function is not fused"); return NULL; } if (PyTuple_Check(idx)) { PyObject *list = PyList_New(0); Py_ssize_t n = PyTuple_GET_SIZE(idx); PyObject *string = NULL; PyObject *sep = NULL; int i; if (!list) return NULL; for (i = 0; i < n; i++) { #if CYTHON_COMPILING_IN_CPYTHON PyObject *item = PyTuple_GET_ITEM(idx, i); #else PyObject *item = PySequence_ITEM(idx, i); #endif string = _obj_to_str(item); #if !CYTHON_COMPILING_IN_CPYTHON Py_DECREF(item); #endif if (!string || PyList_Append(list, string) < 0) goto __pyx_err; Py_DECREF(string); } sep = PyUnicode_FromString("|"); if (sep) signature = PyUnicode_Join(sep, list); __pyx_err: ; Py_DECREF(list); Py_XDECREF(sep); } else { signature = _obj_to_str(idx); } if (!signature) return NULL; unbound_result_func = PyObject_GetItem(self->__signatures__, signature); if (unbound_result_func) { if (self->self || self->type) { __pyx_FusedFunctionObject *unbound = (__pyx_FusedFunctionObject *) unbound_result_func; Py_CLEAR(unbound->func.func_classobj); Py_XINCREF(self->func.func_classobj); unbound->func.func_classobj = self->func.func_classobj; result_func = __pyx_FusedFunction_descr_get(unbound_result_func, self->self, self->type); } else { result_func = unbound_result_func; Py_INCREF(result_func); } } Py_DECREF(signature); Py_XDECREF(unbound_result_func); return result_func; } static PyObject * __pyx_FusedFunction_callfunction(PyObject *func, PyObject *args, PyObject *kw) { __pyx_CyFunctionObject *cyfunc = (__pyx_CyFunctionObject *) func; PyObject *result; int static_specialized = (cyfunc->flags & __Pyx_CYFUNCTION_STATICMETHOD && !((__pyx_FusedFunctionObject *) func)->__signatures__); if (cyfunc->flags & __Pyx_CYFUNCTION_CCLASS && !static_specialized) { Py_ssize_t argc; PyObject *new_args; PyObject *self; PyObject *m_self; argc = PyTuple_GET_SIZE(args); new_args = PyTuple_GetSlice(args, 1, argc); if (!new_args) return NULL; self = PyTuple_GetItem(args, 0); if (!self) return NULL; m_self = cyfunc->func.m_self; cyfunc->func.m_self = self; result = __Pyx_CyFunction_Call(func, new_args, kw); cyfunc->func.m_self = m_self; Py_DECREF(new_args); } else { result = __Pyx_CyFunction_Call(func, args, kw); } return result; } static PyObject * __pyx_FusedFunction_call(PyObject *func, PyObject *args, PyObject *kw) { __pyx_FusedFunctionObject *binding_func = (__pyx_FusedFunctionObject *) func; Py_ssize_t argc = PyTuple_GET_SIZE(args); PyObject *new_args = NULL; __pyx_FusedFunctionObject *new_func = NULL; PyObject *result = NULL; PyObject *self = NULL; int is_staticmethod = binding_func->func.flags & __Pyx_CYFUNCTION_STATICMETHOD; int is_classmethod = binding_func->func.flags & __Pyx_CYFUNCTION_CLASSMETHOD; if (binding_func->self) { Py_ssize_t i; new_args = PyTuple_New(argc + 1); if (!new_args) return NULL; self = binding_func->self; #if !CYTHON_COMPILING_IN_CPYTHON Py_INCREF(self); #endif Py_INCREF(self); PyTuple_SET_ITEM(new_args, 0, self); for (i = 0; i < argc; i++) { #if CYTHON_COMPILING_IN_CPYTHON PyObject *item = PyTuple_GET_ITEM(args, i); Py_INCREF(item); #else PyObject *item = PySequence_ITEM(args, i); if (unlikely(!item)) goto bad; #endif PyTuple_SET_ITEM(new_args, i + 1, item); } args = new_args; } else if (binding_func->type) { if (argc < 1) { PyErr_SetString(PyExc_TypeError, "Need at least one argument, 0 given."); return NULL; } #if CYTHON_COMPILING_IN_CPYTHON self = PyTuple_GET_ITEM(args, 0); #else self = PySequence_ITEM(args, 0); if (unlikely(!self)) return NULL; #endif } if (self && !is_classmethod && !is_staticmethod) { int is_instance = PyObject_IsInstance(self, binding_func->type); if (unlikely(!is_instance)) { PyErr_Format(PyExc_TypeError, "First argument should be of type %.200s, got %.200s.", ((PyTypeObject *) binding_func->type)->tp_name, self->ob_type->tp_name); goto bad; } else if (unlikely(is_instance == -1)) { goto bad; } } #if !CYTHON_COMPILING_IN_CPYTHON Py_XDECREF(self); self = NULL; #endif if (binding_func->__signatures__) { PyObject *tup = PyTuple_Pack(4, binding_func->__signatures__, args, kw == NULL ? Py_None : kw, binding_func->func.defaults_tuple); if (!tup) goto bad; new_func = (__pyx_FusedFunctionObject *) __pyx_FusedFunction_callfunction(func, tup, NULL); Py_DECREF(tup); if (!new_func) goto bad; Py_XINCREF(binding_func->func.func_classobj); Py_CLEAR(new_func->func.func_classobj); new_func->func.func_classobj = binding_func->func.func_classobj; func = (PyObject *) new_func; } result = __pyx_FusedFunction_callfunction(func, args, kw); bad: #if !CYTHON_COMPILING_IN_CPYTHON Py_XDECREF(self); #endif Py_XDECREF(new_args); Py_XDECREF((PyObject *) new_func); return result; } static PyMemberDef __pyx_FusedFunction_members[] = { {(char *) "__signatures__", T_OBJECT, offsetof(__pyx_FusedFunctionObject, __signatures__), READONLY, 0}, {0, 0, 0, 0, 0}, }; static PyMappingMethods __pyx_FusedFunction_mapping_methods = { 0, (binaryfunc) __pyx_FusedFunction_getitem, 0, }; static PyTypeObject __pyx_FusedFunctionType_type = { PyVarObject_HEAD_INIT(0, 0) "fused_cython_function", sizeof(__pyx_FusedFunctionObject), 0, (destructor) __pyx_FusedFunction_dealloc, 0, 0, 0, #if PY_MAJOR_VERSION < 3 0, #else 0, #endif 0, 0, 0, &__pyx_FusedFunction_mapping_methods, 0, (ternaryfunc) __pyx_FusedFunction_call, 0, 0, 0, 0, Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC | Py_TPFLAGS_BASETYPE, 0, (traverseproc) __pyx_FusedFunction_traverse, (inquiry) __pyx_FusedFunction_clear, 0, 0, 0, 0, 0, __pyx_FusedFunction_members, __pyx_CyFunction_getsets, &__pyx_CyFunctionType_type, 0, __pyx_FusedFunction_descr_get, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, #if PY_VERSION_HEX >= 0x030400a1 0, #endif }; static int __pyx_FusedFunction_init(void) { __pyx_FusedFunctionType = __Pyx_FetchCommonType(&__pyx_FusedFunctionType_type); if (__pyx_FusedFunctionType == NULL) { return -1; } return 0; } /* CodeObjectCache */ static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { int start = 0, mid = 0, end = count - 1; if (end >= 0 && code_line > entries[end].code_line) { return count; } while (start < end) { mid = start + (end - start) / 2; if (code_line < entries[mid].code_line) { end = mid; } else if (code_line > entries[mid].code_line) { start = mid + 1; } else { return mid; } } if (code_line <= entries[mid].code_line) { return mid; } else { return mid + 1; } } static PyCodeObject *__pyx_find_code_object(int code_line) { PyCodeObject* code_object; int pos; if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { return NULL; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { return NULL; } code_object = __pyx_code_cache.entries[pos].code_object; Py_INCREF(code_object); return code_object; } static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { int pos, i; __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; if (unlikely(!code_line)) { return; } if (unlikely(!entries)) { entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); if (likely(entries)) { __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = 64; __pyx_code_cache.count = 1; entries[0].code_line = code_line; entries[0].code_object = code_object; Py_INCREF(code_object); } return; } pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { PyCodeObject* tmp = entries[pos].code_object; entries[pos].code_object = code_object; Py_DECREF(tmp); return; } if (__pyx_code_cache.count == __pyx_code_cache.max_count) { int new_max = __pyx_code_cache.max_count + 64; entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( __pyx_code_cache.entries, (size_t)new_max*sizeof(__Pyx_CodeObjectCacheEntry)); if (unlikely(!entries)) { return; } __pyx_code_cache.entries = entries; __pyx_code_cache.max_count = new_max; } for (i=__pyx_code_cache.count; i>pos; i--) { entries[i] = entries[i-1]; } entries[pos].code_line = code_line; entries[pos].code_object = code_object; __pyx_code_cache.count++; Py_INCREF(code_object); } /* AddTraceback */ #include "compile.h" #include "frameobject.h" #include "traceback.h" static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyObject *py_srcfile = 0; PyObject *py_funcname = 0; #if PY_MAJOR_VERSION < 3 py_srcfile = PyString_FromString(filename); #else py_srcfile = PyUnicode_FromString(filename); #endif if (!py_srcfile) goto bad; if (c_line) { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); #else py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); #endif } else { #if PY_MAJOR_VERSION < 3 py_funcname = PyString_FromString(funcname); #else py_funcname = PyUnicode_FromString(funcname); #endif } if (!py_funcname) goto bad; py_code = __Pyx_PyCode_New( 0, 0, 0, 0, 0, __pyx_empty_bytes, /*PyObject *code,*/ __pyx_empty_tuple, /*PyObject *consts,*/ __pyx_empty_tuple, /*PyObject *names,*/ __pyx_empty_tuple, /*PyObject *varnames,*/ __pyx_empty_tuple, /*PyObject *freevars,*/ __pyx_empty_tuple, /*PyObject *cellvars,*/ py_srcfile, /*PyObject *filename,*/ py_funcname, /*PyObject *name,*/ py_line, __pyx_empty_bytes /*PyObject *lnotab*/ ); Py_DECREF(py_srcfile); Py_DECREF(py_funcname); return py_code; bad: Py_XDECREF(py_srcfile); Py_XDECREF(py_funcname); return NULL; } static void __Pyx_AddTraceback(const char *funcname, int c_line, int py_line, const char *filename) { PyCodeObject *py_code = 0; PyFrameObject *py_frame = 0; py_code = __pyx_find_code_object(c_line ? c_line : py_line); if (!py_code) { py_code = __Pyx_CreateCodeObjectForTraceback( funcname, c_line, py_line, filename); if (!py_code) goto bad; __pyx_insert_code_object(c_line ? c_line : py_line, py_code); } py_frame = PyFrame_New( PyThreadState_GET(), /*PyThreadState *tstate,*/ py_code, /*PyCodeObject *code,*/ __pyx_d, /*PyObject *globals,*/ 0 /*PyObject *locals*/ ); if (!py_frame) goto bad; py_frame->f_lineno = py_line; PyTraceBack_Here(py_frame); bad: Py_XDECREF(py_code); Py_XDECREF(py_frame); } #if PY_MAJOR_VERSION < 3 static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_array_type)) return __pyx_array_getbuffer(obj, view, flags); if (PyObject_TypeCheck(obj, __pyx_memoryview_type)) return __pyx_memoryview_getbuffer(obj, view, flags); PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); return -1; } static void __Pyx_ReleaseBuffer(Py_buffer *view) { PyObject *obj = view->obj; if (!obj) return; if (PyObject_CheckBuffer(obj)) { PyBuffer_Release(view); return; } if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) { __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); return; } Py_DECREF(obj); view->obj = NULL; } #endif /* MemviewSliceIsContig */ static int __pyx_memviewslice_is_contig(const __Pyx_memviewslice mvs, char order, int ndim) { int i, index, step, start; Py_ssize_t itemsize = mvs.memview->view.itemsize; if (order == 'F') { step = 1; start = 0; } else { step = -1; start = ndim - 1; } for (i = 0; i < ndim; i++) { index = start + step * i; if (mvs.suboffsets[index] >= 0 || mvs.strides[index] != itemsize) return 0; itemsize *= mvs.shape[index]; } return 1; } /* OverlappingSlices */ static void __pyx_get_array_memory_extents(__Pyx_memviewslice *slice, void **out_start, void **out_end, int ndim, size_t itemsize) { char *start, *end; int i; start = end = slice->data; for (i = 0; i < ndim; i++) { Py_ssize_t stride = slice->strides[i]; Py_ssize_t extent = slice->shape[i]; if (extent == 0) { *out_start = *out_end = start; return; } else { if (stride > 0) end += stride * (extent - 1); else start += stride * (extent - 1); } } *out_start = start; *out_end = end + itemsize; } static int __pyx_slices_overlap(__Pyx_memviewslice *slice1, __Pyx_memviewslice *slice2, int ndim, size_t itemsize) { void *start1, *end1, *start2, *end2; __pyx_get_array_memory_extents(slice1, &start1, &end1, ndim, itemsize); __pyx_get_array_memory_extents(slice2, &start2, &end2, ndim, itemsize); return (start1 < end2) && (start2 < end1); } /* Capsule */ static CYTHON_INLINE PyObject * __pyx_capsule_create(void *p, CYTHON_UNUSED const char *sig) { PyObject *cobj; #if PY_VERSION_HEX >= 0x02070000 cobj = PyCapsule_New(p, sig, NULL); #else cobj = PyCObject_FromVoidPtr(p, NULL); #endif return cobj; } /* TypeInfoCompare */ static int __pyx_typeinfo_cmp(__Pyx_TypeInfo *a, __Pyx_TypeInfo *b) { int i; if (!a || !b) return 0; if (a == b) return 1; if (a->size != b->size || a->typegroup != b->typegroup || a->is_unsigned != b->is_unsigned || a->ndim != b->ndim) { if (a->typegroup == 'H' || b->typegroup == 'H') { return a->size == b->size; } else { return 0; } } if (a->ndim) { for (i = 0; i < a->ndim; i++) if (a->arraysize[i] != b->arraysize[i]) return 0; } if (a->typegroup == 'S') { if (a->flags != b->flags) return 0; if (a->fields || b->fields) { if (!(a->fields && b->fields)) return 0; for (i = 0; a->fields[i].type && b->fields[i].type; i++) { __Pyx_StructField *field_a = a->fields + i; __Pyx_StructField *field_b = b->fields + i; if (field_a->offset != field_b->offset || !__pyx_typeinfo_cmp(field_a->type, field_b->type)) return 0; } return !a->fields[i].type && !b->fields[i].type; } } return 1; } /* MemviewSliceValidateAndInit */ static int __pyx_check_strides(Py_buffer *buf, int dim, int ndim, int spec) { if (buf->shape[dim] <= 1) return 1; if (buf->strides) { if (spec & __Pyx_MEMVIEW_CONTIG) { if (spec & (__Pyx_MEMVIEW_PTR|__Pyx_MEMVIEW_FULL)) { if (buf->strides[dim] != sizeof(void *)) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly contiguous " "in dimension %d.", dim); goto fail; } } else if (buf->strides[dim] != buf->itemsize) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); goto fail; } } if (spec & __Pyx_MEMVIEW_FOLLOW) { Py_ssize_t stride = buf->strides[dim]; if (stride < 0) stride = -stride; if (stride < buf->itemsize) { PyErr_SetString(PyExc_ValueError, "Buffer and memoryview are not contiguous " "in the same dimension."); goto fail; } } } else { if (spec & __Pyx_MEMVIEW_CONTIG && dim != ndim - 1) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not contiguous in " "dimension %d", dim); goto fail; } else if (spec & (__Pyx_MEMVIEW_PTR)) { PyErr_Format(PyExc_ValueError, "C-contiguous buffer is not indirect in " "dimension %d", dim); goto fail; } else if (buf->suboffsets) { PyErr_SetString(PyExc_ValueError, "Buffer exposes suboffsets but no strides"); goto fail; } } return 1; fail: return 0; } static int __pyx_check_suboffsets(Py_buffer *buf, int dim, CYTHON_UNUSED int ndim, int spec) { if (spec & __Pyx_MEMVIEW_DIRECT) { if (buf->suboffsets && buf->suboffsets[dim] >= 0) { PyErr_Format(PyExc_ValueError, "Buffer not compatible with direct access " "in dimension %d.", dim); goto fail; } } if (spec & __Pyx_MEMVIEW_PTR) { if (!buf->suboffsets || (buf->suboffsets && buf->suboffsets[dim] < 0)) { PyErr_Format(PyExc_ValueError, "Buffer is not indirectly accessible " "in dimension %d.", dim); goto fail; } } return 1; fail: return 0; } static int __pyx_verify_contig(Py_buffer *buf, int ndim, int c_or_f_flag) { int i; if (c_or_f_flag & __Pyx_IS_F_CONTIG) { Py_ssize_t stride = 1; for (i = 0; i < ndim; i++) { if (stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1) { PyErr_SetString(PyExc_ValueError, "Buffer not fortran contiguous."); goto fail; } stride = stride * buf->shape[i]; } } else if (c_or_f_flag & __Pyx_IS_C_CONTIG) { Py_ssize_t stride = 1; for (i = ndim - 1; i >- 1; i--) { if (stride * buf->itemsize != buf->strides[i] && buf->shape[i] > 1) { PyErr_SetString(PyExc_ValueError, "Buffer not C contiguous."); goto fail; } stride = stride * buf->shape[i]; } } return 1; fail: return 0; } static int __Pyx_ValidateAndInit_memviewslice( int *axes_specs, int c_or_f_flag, int buf_flags, int ndim, __Pyx_TypeInfo *dtype, __Pyx_BufFmt_StackElem stack[], __Pyx_memviewslice *memviewslice, PyObject *original_obj) { struct __pyx_memoryview_obj *memview, *new_memview; __Pyx_RefNannyDeclarations Py_buffer *buf; int i, spec = 0, retval = -1; __Pyx_BufFmt_Context ctx; int from_memoryview = __pyx_memoryview_check(original_obj); __Pyx_RefNannySetupContext("ValidateAndInit_memviewslice", 0); if (from_memoryview && __pyx_typeinfo_cmp(dtype, ((struct __pyx_memoryview_obj *) original_obj)->typeinfo)) { memview = (struct __pyx_memoryview_obj *) original_obj; new_memview = NULL; } else { memview = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( original_obj, buf_flags, 0, dtype); new_memview = memview; if (unlikely(!memview)) goto fail; } buf = &memview->view; if (buf->ndim != ndim) { PyErr_Format(PyExc_ValueError, "Buffer has wrong number of dimensions (expected %d, got %d)", ndim, buf->ndim); goto fail; } if (new_memview) { __Pyx_BufFmt_Init(&ctx, stack, dtype); if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; } if ((unsigned) buf->itemsize != dtype->size) { PyErr_Format(PyExc_ValueError, "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "u byte%s) " "does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "u byte%s)", buf->itemsize, (buf->itemsize > 1) ? "s" : "", dtype->name, dtype->size, (dtype->size > 1) ? "s" : ""); goto fail; } for (i = 0; i < ndim; i++) { spec = axes_specs[i]; if (!__pyx_check_strides(buf, i, ndim, spec)) goto fail; if (!__pyx_check_suboffsets(buf, i, ndim, spec)) goto fail; } if (buf->strides && !__pyx_verify_contig(buf, ndim, c_or_f_flag)) goto fail; if (unlikely(__Pyx_init_memviewslice(memview, ndim, memviewslice, new_memview != NULL) == -1)) { goto fail; } retval = 0; goto no_fail; fail: Py_XDECREF(new_memview); retval = -1; no_fail: __Pyx_RefNannyFinishContext(); return retval; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_dsds_nn___pyx_t_5numpy_float64_t(PyObject *obj) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_STRIDED) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, 0, PyBUF_RECORDS, 2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* CIntFromPyVerify */ #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) #define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) #define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ {\ func_type value = func_value;\ if (sizeof(target_type) < sizeof(func_type)) {\ if (unlikely(value != (func_type) (target_type) value)) {\ func_type zero = 0;\ if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ return (target_type) -1;\ if (is_unsigned && unlikely(value < zero))\ goto raise_neg_overflow;\ else\ goto raise_overflow;\ }\ }\ return (target_type) value;\ } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(long) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(long) <= sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(long), little, !is_unsigned); } } /* BytesContains */ static CYTHON_INLINE int __Pyx_BytesContains(PyObject* bytes, char character) { const Py_ssize_t length = PyBytes_GET_SIZE(bytes); char* char_start = PyBytes_AS_STRING(bytes); char* pos; for (pos=char_start; pos < char_start+length; pos++) { if (character == pos[0]) return 1; } return 0; } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_unsigned_int(unsigned int value) { const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(unsigned int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(unsigned int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); } else if (sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(unsigned int) <= sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(unsigned int) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(unsigned int), little, !is_unsigned); } } /* None */ #if CYTHON_CCOMPLEX #ifdef __cplusplus static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { return ::std::complex< float >(x, y); } #else static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { return x + y*(__pyx_t_float_complex)_Complex_I; } #endif #else static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { __pyx_t_float_complex z; z.real = x; z.imag = y; return z; } #endif /* None */ #if CYTHON_CCOMPLEX #else static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) { return (a.real == b.real) && (a.imag == b.imag); } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real + b.real; z.imag = a.imag + b.imag; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real - b.real; z.imag = a.imag - b.imag; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; z.real = a.real * b.real - a.imag * b.imag; z.imag = a.real * b.imag + a.imag * b.real; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; float denom = b.real * b.real + b.imag * b.imag; z.real = (a.real * b.real + a.imag * b.imag) / denom; z.imag = (a.imag * b.real - a.real * b.imag) / denom; return z; } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) { __pyx_t_float_complex z; z.real = -a.real; z.imag = -a.imag; return z; } static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) { return (a.real == 0) && (a.imag == 0); } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) { __pyx_t_float_complex z; z.real = a.real; z.imag = -a.imag; return z; } #if 1 static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex z) { #if !defined(HAVE_HYPOT) || defined(_MSC_VER) return sqrtf(z.real*z.real + z.imag*z.imag); #else return hypotf(z.real, z.imag); #endif } static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex a, __pyx_t_float_complex b) { __pyx_t_float_complex z; float r, lnr, theta, z_r, z_theta; if (b.imag == 0 && b.real == (int)b.real) { if (b.real < 0) { float denom = a.real * a.real + a.imag * a.imag; a.real = a.real / denom; a.imag = -a.imag / denom; b.real = -b.real; } switch ((int)b.real) { case 0: z.real = 1; z.imag = 0; return z; case 1: return a; case 2: z = __Pyx_c_prodf(a, a); return __Pyx_c_prodf(a, a); case 3: z = __Pyx_c_prodf(a, a); return __Pyx_c_prodf(z, a); case 4: z = __Pyx_c_prodf(a, a); return __Pyx_c_prodf(z, z); } } if (a.imag == 0) { if (a.real == 0) { return a; } r = a.real; theta = 0; } else { r = __Pyx_c_absf(a); theta = atan2f(a.imag, a.real); } lnr = logf(r); z_r = expf(lnr * b.real - theta * b.imag); z_theta = theta * b.real + lnr * b.imag; z.real = z_r * cosf(z_theta); z.imag = z_r * sinf(z_theta); return z; } #endif #endif /* None */ #if CYTHON_CCOMPLEX #ifdef __cplusplus static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { return ::std::complex< double >(x, y); } #else static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { return x + y*(__pyx_t_double_complex)_Complex_I; } #endif #else static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { __pyx_t_double_complex z; z.real = x; z.imag = y; return z; } #endif /* None */ #if CYTHON_CCOMPLEX #else static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) { return (a.real == b.real) && (a.imag == b.imag); } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real + b.real; z.imag = a.imag + b.imag; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real - b.real; z.imag = a.imag - b.imag; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; z.real = a.real * b.real - a.imag * b.imag; z.imag = a.real * b.imag + a.imag * b.real; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; double denom = b.real * b.real + b.imag * b.imag; z.real = (a.real * b.real + a.imag * b.imag) / denom; z.imag = (a.imag * b.real - a.real * b.imag) / denom; return z; } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) { __pyx_t_double_complex z; z.real = -a.real; z.imag = -a.imag; return z; } static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) { return (a.real == 0) && (a.imag == 0); } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) { __pyx_t_double_complex z; z.real = a.real; z.imag = -a.imag; return z; } #if 1 static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex z) { #if !defined(HAVE_HYPOT) || defined(_MSC_VER) return sqrt(z.real*z.real + z.imag*z.imag); #else return hypot(z.real, z.imag); #endif } static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex a, __pyx_t_double_complex b) { __pyx_t_double_complex z; double r, lnr, theta, z_r, z_theta; if (b.imag == 0 && b.real == (int)b.real) { if (b.real < 0) { double denom = a.real * a.real + a.imag * a.imag; a.real = a.real / denom; a.imag = -a.imag / denom; b.real = -b.real; } switch ((int)b.real) { case 0: z.real = 1; z.imag = 0; return z; case 1: return a; case 2: z = __Pyx_c_prod(a, a); return __Pyx_c_prod(a, a); case 3: z = __Pyx_c_prod(a, a); return __Pyx_c_prod(z, a); case 4: z = __Pyx_c_prod(a, a); return __Pyx_c_prod(z, z); } } if (a.imag == 0) { if (a.real == 0) { return a; } r = a.real; theta = 0; } else { r = __Pyx_c_abs(a); theta = atan2(a.imag, a.real); } lnr = log(r); z_r = exp(lnr * b.real - theta * b.imag); z_theta = theta * b.real + lnr * b.imag; z.real = z_r * cos(z_theta); z.imag = z_r * sin(z_theta); return z; } #endif #endif /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_int(int value) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(int) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(int) <= sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(int), little, !is_unsigned); } } /* CIntToPy */ static CYTHON_INLINE PyObject* __Pyx_PyInt_From_enum__NPY_TYPES(enum NPY_TYPES value) { const enum NPY_TYPES neg_one = (enum NPY_TYPES) -1, const_zero = (enum NPY_TYPES) 0; const int is_unsigned = neg_one > const_zero; if (is_unsigned) { if (sizeof(enum NPY_TYPES) < sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned long)) { return PyLong_FromUnsignedLong((unsigned long) value); } else if (sizeof(enum NPY_TYPES) <= sizeof(unsigned PY_LONG_LONG)) { return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); } } else { if (sizeof(enum NPY_TYPES) <= sizeof(long)) { return PyInt_FromLong((long) value); } else if (sizeof(enum NPY_TYPES) <= sizeof(PY_LONG_LONG)) { return PyLong_FromLongLong((PY_LONG_LONG) value); } } { int one = 1; int little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&value; return _PyLong_FromByteArray(bytes, sizeof(enum NPY_TYPES), little, !is_unsigned); } } /* MemviewSliceCopyTemplate */ static __Pyx_memviewslice __pyx_memoryview_copy_new_contig(const __Pyx_memviewslice *from_mvs, const char *mode, int ndim, size_t sizeof_dtype, int contig_flag, int dtype_is_object) { __Pyx_RefNannyDeclarations int i; __Pyx_memviewslice new_mvs = { 0, 0, { 0 }, { 0 }, { 0 } }; struct __pyx_memoryview_obj *from_memview = from_mvs->memview; Py_buffer *buf = &from_memview->view; PyObject *shape_tuple = NULL; PyObject *temp_int = NULL; struct __pyx_array_obj *array_obj = NULL; struct __pyx_memoryview_obj *memview_obj = NULL; __Pyx_RefNannySetupContext("__pyx_memoryview_copy_new_contig", 0); for (i = 0; i < ndim; i++) { if (from_mvs->suboffsets[i] >= 0) { PyErr_Format(PyExc_ValueError, "Cannot copy memoryview slice with " "indirect dimensions (axis %d)", i); goto fail; } } shape_tuple = PyTuple_New(ndim); if (unlikely(!shape_tuple)) { goto fail; } __Pyx_GOTREF(shape_tuple); for(i = 0; i < ndim; i++) { temp_int = PyInt_FromSsize_t(from_mvs->shape[i]); if(unlikely(!temp_int)) { goto fail; } else { PyTuple_SET_ITEM(shape_tuple, i, temp_int); temp_int = NULL; } } array_obj = __pyx_array_new(shape_tuple, sizeof_dtype, buf->format, (char *) mode, NULL); if (unlikely(!array_obj)) { goto fail; } __Pyx_GOTREF(array_obj); memview_obj = (struct __pyx_memoryview_obj *) __pyx_memoryview_new( (PyObject *) array_obj, contig_flag, dtype_is_object, from_mvs->memview->typeinfo); if (unlikely(!memview_obj)) goto fail; if (unlikely(__Pyx_init_memviewslice(memview_obj, ndim, &new_mvs, 1) < 0)) goto fail; if (unlikely(__pyx_memoryview_copy_contents(*from_mvs, new_mvs, ndim, ndim, dtype_is_object) < 0)) goto fail; goto no_fail; fail: __Pyx_XDECREF(new_mvs.memview); new_mvs.memview = NULL; new_mvs.data = NULL; no_fail: __Pyx_XDECREF(shape_tuple); __Pyx_XDECREF(temp_int); __Pyx_XDECREF(array_obj); __Pyx_RefNannyFinishContext(); return new_mvs; } /* CIntFromPy */ static CYTHON_INLINE unsigned int __Pyx_PyInt_As_unsigned_int(PyObject *x) { const unsigned int neg_one = (unsigned int) -1, const_zero = (unsigned int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(unsigned int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(unsigned int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (unsigned int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (unsigned int) 0; case 1: __PYX_VERIFY_RETURN_INT(unsigned int, digit, digits[0]) case 2: if (8 * sizeof(unsigned int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) >= 2 * PyLong_SHIFT) { return (unsigned int) (((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); } } break; case 3: if (8 * sizeof(unsigned int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) >= 3 * PyLong_SHIFT) { return (unsigned int) (((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); } } break; case 4: if (8 * sizeof(unsigned int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) >= 4 * PyLong_SHIFT) { return (unsigned int) (((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (unsigned int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(unsigned int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(unsigned int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(unsigned int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (unsigned int) 0; case -1: __PYX_VERIFY_RETURN_INT(unsigned int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(unsigned int, digit, +digits[0]) case -2: if (8 * sizeof(unsigned int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) { return (unsigned int) (((unsigned int)-1)*(((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case 2: if (8 * sizeof(unsigned int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) { return (unsigned int) ((((((unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case -3: if (8 * sizeof(unsigned int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) { return (unsigned int) (((unsigned int)-1)*(((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case 3: if (8 * sizeof(unsigned int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) { return (unsigned int) ((((((((unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case -4: if (8 * sizeof(unsigned int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT) { return (unsigned int) (((unsigned int)-1)*(((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; case 4: if (8 * sizeof(unsigned int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(unsigned int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(unsigned int) - 1 > 4 * PyLong_SHIFT) { return (unsigned int) ((((((((((unsigned int)digits[3]) << PyLong_SHIFT) | (unsigned int)digits[2]) << PyLong_SHIFT) | (unsigned int)digits[1]) << PyLong_SHIFT) | (unsigned int)digits[0]))); } } break; } #endif if (sizeof(unsigned int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(unsigned int, long, PyLong_AsLong(x)) } else if (sizeof(unsigned int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(unsigned int, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else unsigned int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (unsigned int) -1; } } else { unsigned int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (unsigned int) -1; val = __Pyx_PyInt_As_unsigned_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to unsigned int"); return (unsigned int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to unsigned int"); return (unsigned int) -1; } /* CIntFromPy */ static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { const int neg_one = (int) -1, const_zero = (int) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(int) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (int) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (int) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(int) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (int) 0; case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) case -2: if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 2: if (8 * sizeof(int) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -3: if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 3: if (8 * sizeof(int) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case -4: if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; case 4: if (8 * sizeof(int) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); } } break; } #endif if (sizeof(int) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else int val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (int) -1; } } else { int val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (int) -1; val = __Pyx_PyInt_As_int(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to int"); return (int) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to int"); return (int) -1; } /* CIntFromPy */ static CYTHON_INLINE char __Pyx_PyInt_As_char(PyObject *x) { const char neg_one = (char) -1, const_zero = (char) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(char) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(char, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (char) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (char) 0; case 1: __PYX_VERIFY_RETURN_INT(char, digit, digits[0]) case 2: if (8 * sizeof(char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 2 * PyLong_SHIFT) { return (char) (((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; case 3: if (8 * sizeof(char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 3 * PyLong_SHIFT) { return (char) (((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; case 4: if (8 * sizeof(char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) >= 4 * PyLong_SHIFT) { return (char) (((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (char) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(char) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(char, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(char) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(char, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (char) 0; case -1: __PYX_VERIFY_RETURN_INT(char, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(char, digit, +digits[0]) case -2: if (8 * sizeof(char) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { return (char) (((char)-1)*(((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 2: if (8 * sizeof(char) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { return (char) ((((((char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case -3: if (8 * sizeof(char) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { return (char) (((char)-1)*(((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 3: if (8 * sizeof(char) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { return (char) ((((((((char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case -4: if (8 * sizeof(char) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { return (char) (((char)-1)*(((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; case 4: if (8 * sizeof(char) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(char, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(char) - 1 > 4 * PyLong_SHIFT) { return (char) ((((((((((char)digits[3]) << PyLong_SHIFT) | (char)digits[2]) << PyLong_SHIFT) | (char)digits[1]) << PyLong_SHIFT) | (char)digits[0]))); } } break; } #endif if (sizeof(char) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(char, long, PyLong_AsLong(x)) } else if (sizeof(char) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(char, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else char val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (char) -1; } } else { char val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (char) -1; val = __Pyx_PyInt_As_char(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to char"); return (char) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to char"); return (char) -1; } /* CIntFromPy */ static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { const long neg_one = (long) -1, const_zero = (long) 0; const int is_unsigned = neg_one > const_zero; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_Check(x))) { if (sizeof(long) < sizeof(long)) { __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) } else { long val = PyInt_AS_LONG(x); if (is_unsigned && unlikely(val < 0)) { goto raise_neg_overflow; } return (long) val; } } else #endif if (likely(PyLong_Check(x))) { if (is_unsigned) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); } } break; } #endif #if CYTHON_COMPILING_IN_CPYTHON if (unlikely(Py_SIZE(x) < 0)) { goto raise_neg_overflow; } #else { int result = PyObject_RichCompareBool(x, Py_False, Py_LT); if (unlikely(result < 0)) return (long) -1; if (unlikely(result == 1)) goto raise_neg_overflow; } #endif if (sizeof(long) <= sizeof(unsigned long)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) } } else { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)x)->ob_digit; switch (Py_SIZE(x)) { case 0: return (long) 0; case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) case -2: if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 2: if (8 * sizeof(long) > 1 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -3: if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 3: if (8 * sizeof(long) > 2 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case -4: if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; case 4: if (8 * sizeof(long) > 3 * PyLong_SHIFT) { if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); } } break; } #endif if (sizeof(long) <= sizeof(long)) { __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) } } { #if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) PyErr_SetString(PyExc_RuntimeError, "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); #else long val; PyObject *v = __Pyx_PyNumber_IntOrLong(x); #if PY_MAJOR_VERSION < 3 if (likely(v) && !PyLong_Check(v)) { PyObject *tmp = v; v = PyNumber_Long(tmp); Py_DECREF(tmp); } #endif if (likely(v)) { int one = 1; int is_little = (int)*(unsigned char *)&one; unsigned char *bytes = (unsigned char *)&val; int ret = _PyLong_AsByteArray((PyLongObject *)v, bytes, sizeof(val), is_little, !is_unsigned); Py_DECREF(v); if (likely(!ret)) return val; } #endif return (long) -1; } } else { long val; PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); if (!tmp) return (long) -1; val = __Pyx_PyInt_As_long(tmp); Py_DECREF(tmp); return val; } raise_overflow: PyErr_SetString(PyExc_OverflowError, "value too large to convert to long"); return (long) -1; raise_neg_overflow: PyErr_SetString(PyExc_OverflowError, "can't convert negative value to long"); return (long) -1; } /* ObjectToMemviewSlice */ static CYTHON_INLINE __Pyx_memviewslice __Pyx_PyObject_to_MemoryviewSlice_d_dc_nn___pyx_t_5numpy_float64_t(PyObject *obj) { __Pyx_memviewslice result = { 0, 0, { 0 }, { 0 }, { 0 } }; __Pyx_BufFmt_StackElem stack[1]; int axes_specs[] = { (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_FOLLOW), (__Pyx_MEMVIEW_DIRECT | __Pyx_MEMVIEW_CONTIG) }; int retcode; if (obj == Py_None) { result.memview = (struct __pyx_memoryview_obj *) Py_None; return result; } retcode = __Pyx_ValidateAndInit_memviewslice(axes_specs, __Pyx_IS_C_CONTIG, (PyBUF_C_CONTIGUOUS | PyBUF_FORMAT | PyBUF_WRITABLE), 2, &__Pyx_TypeInfo_nn___pyx_t_5numpy_float64_t, stack, &result, obj); if (unlikely(retcode == -1)) goto __pyx_fail; return result; __pyx_fail: result.memview = NULL; result.data = NULL; return result; } /* CheckBinaryVersion */ static int __Pyx_check_binary_version(void) { char ctversion[4], rtversion[4]; PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION); PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion()); if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) { char message[200]; PyOS_snprintf(message, sizeof(message), "compiletime version %s of module '%.100s' " "does not match runtime version %s", ctversion, __Pyx_MODULE_NAME, rtversion); return PyErr_WarnEx(NULL, message, 1); } return 0; } /* ModuleImport */ #ifndef __PYX_HAVE_RT_ImportModule #define __PYX_HAVE_RT_ImportModule static PyObject *__Pyx_ImportModule(const char *name) { PyObject *py_name = 0; PyObject *py_module = 0; py_name = __Pyx_PyIdentifier_FromString(name); if (!py_name) goto bad; py_module = PyImport_Import(py_name); Py_DECREF(py_name); return py_module; bad: Py_XDECREF(py_name); return 0; } #endif /* TypeImport */ #ifndef __PYX_HAVE_RT_ImportType #define __PYX_HAVE_RT_ImportType static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict) { PyObject *py_module = 0; PyObject *result = 0; PyObject *py_name = 0; char warning[200]; Py_ssize_t basicsize; #ifdef Py_LIMITED_API PyObject *py_basicsize; #endif py_module = __Pyx_ImportModule(module_name); if (!py_module) goto bad; py_name = __Pyx_PyIdentifier_FromString(class_name); if (!py_name) goto bad; result = PyObject_GetAttr(py_module, py_name); Py_DECREF(py_name); py_name = 0; Py_DECREF(py_module); py_module = 0; if (!result) goto bad; if (!PyType_Check(result)) { PyErr_Format(PyExc_TypeError, "%.200s.%.200s is not a type object", module_name, class_name); goto bad; } #ifndef Py_LIMITED_API basicsize = ((PyTypeObject *)result)->tp_basicsize; #else py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); if (!py_basicsize) goto bad; basicsize = PyLong_AsSsize_t(py_basicsize); Py_DECREF(py_basicsize); py_basicsize = 0; if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) goto bad; #endif if (!strict && (size_t)basicsize > size) { PyOS_snprintf(warning, sizeof(warning), "%s.%s size changed, may indicate binary incompatibility. Expected %zd, got %zd", module_name, class_name, basicsize, size); if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; } else if ((size_t)basicsize != size) { PyErr_Format(PyExc_ValueError, "%.200s.%.200s has the wrong size, try recompiling. Expected %zd, got %zd", module_name, class_name, basicsize, size); goto bad; } return (PyTypeObject *)result; bad: Py_XDECREF(py_module); Py_XDECREF(result); return NULL; } #endif /* InitStrings */ static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { while (t->p) { #if PY_MAJOR_VERSION < 3 if (t->is_unicode) { *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); } else if (t->intern) { *t->p = PyString_InternFromString(t->s); } else { *t->p = PyString_FromStringAndSize(t->s, t->n - 1); } #else if (t->is_unicode | t->is_str) { if (t->intern) { *t->p = PyUnicode_InternFromString(t->s); } else if (t->encoding) { *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); } else { *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); } } else { *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); } #endif if (!*t->p) return -1; ++t; } return 0; } static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); } static CYTHON_INLINE char* __Pyx_PyObject_AsString(PyObject* o) { Py_ssize_t ignore; return __Pyx_PyObject_AsStringAndSize(o, &ignore); } static CYTHON_INLINE char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { #if CYTHON_COMPILING_IN_CPYTHON && (__PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT) if ( #if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII __Pyx_sys_getdefaultencoding_not_ascii && #endif PyUnicode_Check(o)) { #if PY_VERSION_HEX < 0x03030000 char* defenc_c; PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); if (!defenc) return NULL; defenc_c = PyBytes_AS_STRING(defenc); #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII { char* end = defenc_c + PyBytes_GET_SIZE(defenc); char* c; for (c = defenc_c; c < end; c++) { if ((unsigned char) (*c) >= 128) { PyUnicode_AsASCIIString(o); return NULL; } } } #endif *length = PyBytes_GET_SIZE(defenc); return defenc_c; #else if (__Pyx_PyUnicode_READY(o) == -1) return NULL; #if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII if (PyUnicode_IS_ASCII(o)) { *length = PyUnicode_GET_LENGTH(o); return PyUnicode_AsUTF8(o); } else { PyUnicode_AsASCIIString(o); return NULL; } #else return PyUnicode_AsUTF8AndSize(o, length); #endif #endif } else #endif #if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) if (PyByteArray_Check(o)) { *length = PyByteArray_GET_SIZE(o); return PyByteArray_AS_STRING(o); } else #endif { char* result; int r = PyBytes_AsStringAndSize(o, &result, length); if (unlikely(r < 0)) { return NULL; } else { return result; } } } static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { int is_true = x == Py_True; if (is_true | (x == Py_False) | (x == Py_None)) return is_true; else return PyObject_IsTrue(x); } static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { PyNumberMethods *m; const char *name = NULL; PyObject *res = NULL; #if PY_MAJOR_VERSION < 3 if (PyInt_Check(x) || PyLong_Check(x)) #else if (PyLong_Check(x)) #endif return __Pyx_NewRef(x); m = Py_TYPE(x)->tp_as_number; #if PY_MAJOR_VERSION < 3 if (m && m->nb_int) { name = "int"; res = PyNumber_Int(x); } else if (m && m->nb_long) { name = "long"; res = PyNumber_Long(x); } #else if (m && m->nb_int) { name = "int"; res = PyNumber_Long(x); } #endif if (res) { #if PY_MAJOR_VERSION < 3 if (!PyInt_Check(res) && !PyLong_Check(res)) { #else if (!PyLong_Check(res)) { #endif PyErr_Format(PyExc_TypeError, "__%.4s__ returned non-%.4s (type %.200s)", name, name, Py_TYPE(res)->tp_name); Py_DECREF(res); return NULL; } } else if (!PyErr_Occurred()) { PyErr_SetString(PyExc_TypeError, "an integer is required"); } return res; } static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { Py_ssize_t ival; PyObject *x; #if PY_MAJOR_VERSION < 3 if (likely(PyInt_CheckExact(b))) { if (sizeof(Py_ssize_t) >= sizeof(long)) return PyInt_AS_LONG(b); else return PyInt_AsSsize_t(x); } #endif if (likely(PyLong_CheckExact(b))) { #if CYTHON_USE_PYLONG_INTERNALS const digit* digits = ((PyLongObject*)b)->ob_digit; const Py_ssize_t size = Py_SIZE(b); if (likely(__Pyx_sst_abs(size) <= 1)) { ival = likely(size) ? digits[0] : 0; if (size == -1) ival = -ival; return ival; } else { switch (size) { case 2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -2: if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -3: if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case 4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; case -4: if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); } break; } } #endif return PyLong_AsSsize_t(b); } x = PyNumber_Index(b); if (!x) return -1; ival = PyInt_AsSsize_t(x); Py_DECREF(x); return ival; } static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { return PyInt_FromSize_t(ival); } #endif /* Py_PYTHON_H */ pyresample-1.2.9/pyresample/ewa/_ll2cr.pyx000066400000000000000000000273601302372600000205610ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2016 # Author(s): # David Hoese # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # You should have received a copy of the GNU General Public License # along with this program. If not, see . """Map longitude/latitude points to column/rows of a grid. """ __docformat__ = "restructuredtext en" from pyproj import _proj, Proj import numpy cimport cython from cpython cimport bool cimport numpy # column and rows can only be doubles for now until the PROJ.4 is linked directly so float->double casting can be done # inside the loop ctypedef fused cr_dtype: # numpy.float32_t numpy.float64_t cdef extern from "numpy/npy_math.h": bint npy_isnan(double x) class MyProj(Proj): """Custom class to make ll2cr projection work faster without compiling against the PROJ.4 library itself. THIS SHOULD NOT BE USED OUTSIDE OF LL2CR! It makes assumptions and has requirements that may not make sense outside of the ll2cr modules. """ def __call__(self, lons, lats, **kwargs): if self.is_latlong(): return lons, lats elif isinstance(lons, numpy.ndarray): # Because we are doing this we know that we are getting a double array inverse = kwargs.get('inverse', False) radians = kwargs.get('radians', False) errcheck = kwargs.get('errcheck', False) # call proj4 functions. inx and iny modified in place. if inverse: _proj.Proj._inv(self, lons, lats, radians=radians, errcheck=errcheck) else: _proj.Proj._fwd(self, lons, lats, radians=radians, errcheck=errcheck) # if inputs were lists, tuples or floats, convert back. return lons, lats else: return super(MyProj, self).__call__(lons, lats, **kwargs) def projection_circumference(p): """Return the projection circumference if the projection is cylindrical. None is returned otherwise. Projections that are not cylindrical and centered on the globes axis can not easily have data cross the antimeridian of the projection. """ lon0, lat0 = p(0, 0, inverse=True) lon1 = lon0 + 180.0 lat1 = lat0 + 5.0 x0, y0 = p(lon0, lat0) # should result in zero or near zero x1, y1 = p(lon1, lat0) x2, y2 = p(lon1, lat1) if y0 != y1 or x1 != x2: return 0.0 return abs(x1 - x0) * 2 @cython.boundscheck(False) @cython.wraparound(False) @cython.cdivision(True) def ll2cr_dynamic(numpy.ndarray[cr_dtype, ndim=2] lon_arr, numpy.ndarray[cr_dtype, ndim=2] lat_arr, cr_dtype fill_in, str proj4_definition, double cell_width, double cell_height, width=None, height=None, origin_x=None, origin_y=None): """Project longitude and latitude points to column rows in the specified grid in place This function is meant to operate on dynamic grids and is theoretically slower than the `ll2cr_static` function. Dynamic grids are those that have one or more set of parameters unspecified like the number of pixels in the grid (width, height) or the origin coordinates of the grid (origin_x, origin_y). This function will analyze the provided lon/lat data and determine what the missing parameters must be so all input swath data falls in the resulting grid. :param lon_arr: Numpy array of longitude floats :param lat_arr: Numpy array of latitude floats :param grid_info: dictionary of grid information (see below) :param fill_in: Fill value for input longitude and latitude arrays and used for output :param proj4_definition: PROJ.4 string projection definition :param cell_width: Pixel resolution in the X direction in projection space :param cell_height: Pixel resolution in the Y direction in projection space :param width: (optional) Number of pixels in the X direction in the final output grid :param height: (optional) Number of pixels in the Y direction in the final output grid :param origin_x: (optional) Grid X coordinate for the upper-left pixel of the output grid :param origin_y: (optional) Grid Y coordinate for the upper-left pixel of the output grid :returns: tuple(points_in_grid, cols_out, rows_out, origin_x, origin_y, width, height) Steps taken in this function: 1. Convert (lon, lat) points to (X, Y) points in the projection space 2. If grid is missing some parameters (dynamic grid), then fill them in 3. Convert (X, Y) points to (column, row) points in the grid space Note longitude and latitude arrays are limited to 64-bit floats because of limitations in pyproj. """ # pure python stuff for now p = MyProj(proj4_definition) # Pyproj currently makes a copy so we don't have to do anything special here cdef tuple projected_tuple = p(lon_arr, lat_arr) cdef cr_dtype [:, ::1] rows_out = projected_tuple[1] cdef cr_dtype [:, ::1] cols_out = projected_tuple[0] cdef double proj_circum = projection_circumference(p) cdef unsigned int w cdef unsigned int h cdef double ox cdef double oy # indexes cdef unsigned int row cdef unsigned int col # index bounds cdef unsigned int num_rows = lon_arr.shape[0] cdef unsigned int num_cols = lon_arr.shape[1] cdef cr_dtype xmin = cols_out[0, 0] cdef cr_dtype xmax = cols_out[0, 0] cdef cr_dtype ymin = rows_out[0, 0] cdef cr_dtype ymax = rows_out[0, 0] cdef cr_dtype x_tmp cdef cr_dtype y_tmp cdef unsigned int points_in_grid = 0 for row in range(num_rows): for col in range(num_cols): x_tmp = cols_out[row, col] y_tmp = rows_out[row, col] if x_tmp >= 1e30: # pyproj library should have set both x and y to the fill value # we technically don't ever check for the fill value, but if fill values are valid lon/lats then WTF continue elif x_tmp < xmin or npy_isnan(xmin): xmin = x_tmp elif x_tmp > xmax or npy_isnan(xmax) or xmax == 1e30: # Note: technically 2 valid points are required to get here if there are a lot of NaNs xmax = x_tmp if y_tmp < ymin or npy_isnan(ymin): ymin = y_tmp elif y_tmp > ymax or npy_isnan(ymax) or ymax == 1e30: # Note: technically 2 valid points are required to get here if there are a lot of NaNs ymax = y_tmp # Check if we cross the antimeridian if proj_circum != 0 and xmax - xmin >= proj_circum * .75: # xmax will increase, but we need to reset xmin so that it gets properly detected if xmin < 0: xmin = xmax for row in range(num_rows): for col in range(num_cols): x_tmp = cols_out[row, col] if x_tmp < 0: x_tmp += proj_circum cols_out[row, col] = x_tmp # xmax won't increase unless we've added the circumference if x_tmp > xmax: xmax = x_tmp elif x_tmp >= 1e30: continue elif x_tmp < xmin: # xmin could change with any of the remaining entries xmin = x_tmp if origin_x is None: # upper-left corner ox = xmin oy = ymax else: ox = origin_x oy = origin_y if width is None: w = int(abs((xmax - ox) / cell_width)) h = int(abs((oy - ymin) / cell_height)) else: w = width h = height for row in range(num_rows): for col in range(num_cols): x_tmp = cols_out[row, col] y_tmp = rows_out[row, col] if x_tmp >= 1e30: cols_out[row, col] = fill_in rows_out[row, col] = fill_in continue x_tmp = (x_tmp - ox) / cell_width y_tmp = (y_tmp - oy) / cell_height if x_tmp >= -1 and x_tmp <= w + 1 and y_tmp >= -1 and y_tmp <= h + 1: points_in_grid += 1 cols_out[row, col] = x_tmp rows_out[row, col] = y_tmp # return points_in_grid, x_arr, y_arr return points_in_grid, lon_arr, lat_arr, ox, oy, w, h @cython.boundscheck(False) @cython.wraparound(False) @cython.cdivision(True) def ll2cr_static(numpy.ndarray[cr_dtype, ndim=2] lon_arr, numpy.ndarray[cr_dtype, ndim=2] lat_arr, cr_dtype fill_in, str proj4_definition, double cell_width, double cell_height, unsigned int width, unsigned int height, double origin_x, double origin_y): """Project longitude and latitude points to column rows in the specified grid in place :param lon_arr: Numpy array of longitude floats :param lat_arr: Numpy array of latitude floats :param fill_in: Fill value for input longitude and latitude arrays and used for output :param cell_width: Pixel resolution in the X direction in projection space :param cell_height: Pixel resolution in the Y direction in projection space :param width: Number of pixels in the X direction in the final output grid :param height: Number of pixels in the Y direction in the final output grid :param origin_x: Grid X coordinate for the upper-left pixel of the output grid :param origin_y: Grid Y coordinate for the upper-left pixel of the output grid :returns: tuple(points_in_grid, cols_out, rows_out) Steps taken in this function: 1. Convert (lon, lat) points to (X, Y) points in the projection space 2. Convert (X, Y) points to (column, row) points in the grid space Note longitude and latitude arrays are limited to 64-bit floats because of limitations in pyproj. """ # pure python stuff for now p = MyProj(proj4_definition) # Pyproj currently makes a copy so we don't have to do anything special here cdef tuple projected_tuple = p(lon_arr, lat_arr) cdef cr_dtype [:, ::1] rows_out = projected_tuple[1] cdef cr_dtype [:, ::1] cols_out = projected_tuple[0] cdef double proj_circum = projection_circumference(p) # indexes cdef unsigned int row cdef unsigned int col # index bounds cdef unsigned int num_rows = lon_arr.shape[0] cdef unsigned int num_cols = lon_arr.shape[1] cdef cr_dtype x_tmp cdef cr_dtype y_tmp cdef unsigned int points_in_grid = 0 for row in range(num_rows): for col in range(num_cols): x_tmp = cols_out[row, col] y_tmp = rows_out[row, col] if x_tmp >= 1e30: cols_out[row, col] = fill_in rows_out[row, col] = fill_in continue elif proj_circum != 0 and abs(x_tmp - origin_x) >= (0.75 * proj_circum): # if x is more than 75% around the projection space, it is probably crossing the anti-meridian x_tmp += proj_circum x_tmp = (x_tmp - origin_x) / cell_width y_tmp = (y_tmp - origin_y) / cell_height if x_tmp >= -1 and x_tmp <= width + 1 and y_tmp >= -1 and y_tmp <= height + 1: points_in_grid += 1 cols_out[row, col] = x_tmp rows_out[row, col] = y_tmp # return points_in_grid, x_arr, y_arr return points_in_grid pyresample-1.2.9/pyresample/geo_filter.py000066400000000000000000000052771302372600000205620ustar00rootroot00000000000000import numpy as np from . import _spatial_mp from . import geometry class GridFilter(object): """Geographic filter from a grid :Parameters: grid_ll_x : float Projection x coordinate of lower left corner of lower left pixel grid_ll_y : float Projection y coordinate of lower left corner of lower left pixel grid_ur_x : float Projection x coordinate of upper right corner of upper right pixel grid_ur_y : float Projection y coordinate of upper right corner of upper right pixel proj4_string : string mask : numpy array Mask as boolean numpy array """ def __init__(self, area_def, filter, nprocs=1): self.area_def = area_def self._filter = filter.astype(np.bool) self.nprocs = nprocs def get_valid_index(self, geometry_def): """Calculates valid_index array based on lons and lats :Parameters: lons : numpy array lats : numpy array :Returns: Boolean numpy array of same shape as lons and lats """ lons = geometry_def.lons[:] lats = geometry_def.lats[:] # Get projection coords if self.nprocs > 1: proj = _spatial_mp.Proj_MP(**self.area_def.proj_dict) else: proj = _spatial_mp.Proj(**self.area_def.proj_dict) x_coord, y_coord = proj(lons, lats, nprocs=self.nprocs) # Find array indices of coordinates target_x = ((x_coord / self.area_def.pixel_size_x) + self.area_def.pixel_offset_x).astype(np.int32) target_y = (self.area_def.pixel_offset_y - (y_coord / self.area_def.pixel_size_y)).astype(np.int32) # Create mask for pixels outside array (invalid pixels) target_x_valid = (target_x >= 0) & (target_x < self.area_def.x_size) target_y_valid = (target_y >= 0) & (target_y < self.area_def.y_size) # Set index of invalid pixels to 0 target_x[np.invert(target_x_valid)] = 0 target_y[np.invert(target_y_valid)] = 0 # Find mask filter = self._filter[target_y, target_x] # Remove invalid pixels filter = (filter & target_x_valid & target_y_valid).astype(np.bool) return filter def filter(self, geometry_def, data): lons = geometry_def.lons[:] lats = geometry_def.lats[:] valid_index = self.get_valid_index(geometry_def) lons_f = lons[valid_index] lats_f = lats[valid_index] data_f = data[valid_index] geometry_def_f = \ geometry.CoordinateDefinition(lons_f, lats_f, nprocs=geometry_def.nprocs) return geometry_def_f, data_f pyresample-1.2.9/pyresample/geometry.py000066400000000000000000001066261302372600000202760ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010-2016 # # Authors: # Esben S. Nielsen # Thomas Lavergne # Adam Dybbroe # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """Classes for geometry operations""" import warnings import numpy as np from pyresample import _spatial_mp, utils class DimensionError(Exception): pass class Boundary(object): """Container for geometry boundary. Labelling starts in upper left corner and proceeds clockwise""" def __init__(self, side1, side2, side3, side4): self.side1 = side1 self.side2 = side2 self.side3 = side3 self.side4 = side4 class BaseDefinition(object): """Base class for geometry definitions""" def __init__(self, lons=None, lats=None, nprocs=1): if type(lons) != type(lats): raise TypeError('lons and lats must be of same type') elif lons is not None: if lons.shape != lats.shape: raise ValueError('lons and lats must have same shape') self.nprocs = nprocs # check the latitutes if lats is not None and ((lats.min() < -90. or lats.max() > +90.)): # throw exception raise ValueError( 'Some latitudes are outside the [-90.;+90] validity range') else: self.lats = lats # check the longitudes if lons is not None and ((lons.min() < -180. or lons.max() >= +180.)): # issue warning warnings.warn('All geometry objects expect longitudes in the [-180:+180[ range. ' + 'We will now automatically wrap your longitudes into [-180:+180[, and continue. ' + 'To avoid this warning next time, use routine utils.wrap_longitudes().') # wrap longitudes to [-180;+180[ self.lons = utils.wrap_longitudes(lons) else: self.lons = lons self.ndim = None self.cartesian_coords = None def __eq__(self, other): """Test for approximate equality""" if other.lons is None or other.lats is None: other_lons, other_lats = other.get_lonlats() else: other_lons = other.lons other_lats = other.lats if self.lons is None or self.lats is None: self_lons, self_lats = self.get_lonlats() else: self_lons = self.lons self_lats = self.lats try: return (np.allclose(self_lons, other_lons, atol=1e-6, rtol=5e-9) and np.allclose(self_lats, other_lats, atol=1e-6, rtol=5e-9)) except (AttributeError, ValueError): return False def __ne__(self, other): """Test for approximate equality""" return not self.__eq__(other) def get_area_extent_for_subset(self, row_LR, col_LR, row_UL, col_UL): """Retrieves area_extent for a subdomain rows are counted from upper left to lower left columns are counted from upper left to upper right :Parameters: row_LR : int row of the lower right pixel col_LR : int col of the lower right pixel row_UL : int row of the upper left pixel col_UL : int col of the upper left pixel :Returns: area_extent : list Area extent as a list (LL_x, LL_y, UR_x, UR_y) of the subset :Author: Ulrich Hamann """ (a, b) = self.get_proj_coords(data_slice=(row_LR, col_LR)) a = a - 0.5 * self.pixel_size_x b = b - 0.5 * self.pixel_size_y (c, d) = self.get_proj_coords(data_slice=(row_UL, col_UL)) c = c + 0.5 * self.pixel_size_x d = d + 0.5 * self.pixel_size_y return (a, b, c, d) def get_lonlat(self, row, col): """Retrieve lon and lat of single pixel Parameters ---------- row : int col : int Returns ------- (lon, lat) : tuple of floats """ if self.ndim != 2: raise DimensionError(('operation undefined ' 'for %sD geometry ') % self.ndim) elif self.lons is None or self.lats is None: raise ValueError('lon/lat values are not defined') return self.lons[row, col], self.lats[row, col] def get_lonlats(self, data_slice=None, **kwargs): """Base method for lon lat retrieval with slicing""" if self.lons is None or self.lats is None: raise ValueError('lon/lat values are not defined') elif data_slice is None: return self.lons, self.lats else: return self.lons[data_slice], self.lats[data_slice] def get_boundary_lonlats(self): """Returns Boundary objects""" side1 = self.get_lonlats(data_slice=(0, slice(None))) side2 = self.get_lonlats(data_slice=(slice(None), -1)) side3 = self.get_lonlats(data_slice=(-1, slice(None))) side4 = self.get_lonlats(data_slice=(slice(None), 0)) return Boundary(side1[0], side2[0], side3[0][::-1], side4[0][::-1]), Boundary(side1[1], side2[1], side3[1][::-1], side4[1][::-1]) def get_cartesian_coords(self, nprocs=None, data_slice=None, cache=False): """Retrieve cartesian coordinates of geometry definition Parameters ---------- nprocs : int, optional Number of processor cores to be used. Defaults to the nprocs set when instantiating object data_slice : slice object, optional Calculate only cartesian coordnates for the defined slice cache : bool, optional Store result the result. Requires data_slice to be None Returns ------- cartesian_coords : numpy array """ if self.cartesian_coords is None: # Coordinates are not cached if nprocs is None: nprocs = self.nprocs if data_slice is None: # Use full slice data_slice = slice(None) lons, lats = self.get_lonlats(nprocs=nprocs, data_slice=data_slice) if nprocs > 1: cartesian = _spatial_mp.Cartesian_MP(nprocs) else: cartesian = _spatial_mp.Cartesian() cartesian_coords = cartesian.transform_lonlats(np.ravel(lons), np.ravel(lats)) if isinstance(lons, np.ndarray) and lons.ndim > 1: # Reshape to correct shape cartesian_coords = cartesian_coords.reshape(lons.shape[0], lons.shape[1], 3) if cache and data_slice is None: self.cartesian_coords = cartesian_coords else: # Coordinates are cached if data_slice is None: cartesian_coords = self.cartesian_coords else: cartesian_coords = self.cartesian_coords[data_slice] return cartesian_coords @property def corners(self): """Returns the corners of the current area. """ from pyresample.spherical_geometry import Coordinate return [Coordinate(*self.get_lonlat(0, 0)), Coordinate(*self.get_lonlat(0, -1)), Coordinate(*self.get_lonlat(-1, -1)), Coordinate(*self.get_lonlat(-1, 0))] def __contains__(self, point): """Is a point inside the 4 corners of the current area? This uses great circle arcs as area boundaries. """ from pyresample.spherical_geometry import point_inside, Coordinate corners = self.corners if isinstance(point, tuple): return point_inside(Coordinate(*point), corners) else: return point_inside(point, corners) def overlaps(self, other): """Tests if the current area overlaps the *other* area. This is based solely on the corners of areas, assuming the boundaries to be great circles. Parameters ---------- other : object Instance of subclass of BaseDefinition Returns ------- overlaps : bool """ from pyresample.spherical_geometry import Arc self_corners = self.corners other_corners = other.corners for i in self_corners: if i in other: return True for i in other_corners: if i in self: return True self_arc1 = Arc(self_corners[0], self_corners[1]) self_arc2 = Arc(self_corners[1], self_corners[2]) self_arc3 = Arc(self_corners[2], self_corners[3]) self_arc4 = Arc(self_corners[3], self_corners[0]) other_arc1 = Arc(other_corners[0], other_corners[1]) other_arc2 = Arc(other_corners[1], other_corners[2]) other_arc3 = Arc(other_corners[2], other_corners[3]) other_arc4 = Arc(other_corners[3], other_corners[0]) for i in (self_arc1, self_arc2, self_arc3, self_arc4): for j in (other_arc1, other_arc2, other_arc3, other_arc4): if i.intersects(j): return True return False def get_area(self): """Get the area of the convex area defined by the corners of the current area. """ from pyresample.spherical_geometry import get_polygon_area return get_polygon_area(self.corners) def intersection(self, other): """Returns the corners of the intersection polygon of the current area with *other*. Parameters ---------- other : object Instance of subclass of BaseDefinition Returns ------- (corner1, corner2, corner3, corner4) : tuple of points """ from pyresample.spherical_geometry import intersection_polygon return intersection_polygon(self.corners, other.corners) def overlap_rate(self, other): """Get how much the current area overlaps an *other* area. Parameters ---------- other : object Instance of subclass of BaseDefinition Returns ------- overlap_rate : float """ from pyresample.spherical_geometry import get_polygon_area other_area = other.get_area() inter_area = get_polygon_area(self.intersection(other)) return inter_area / other_area class CoordinateDefinition(BaseDefinition): """Base class for geometry definitions defined by lons and lats only""" def __init__(self, lons, lats, nprocs=1): super(CoordinateDefinition, self).__init__(lons, lats, nprocs) if lons.shape == lats.shape and lons.dtype == lats.dtype: self.shape = lons.shape self.size = lons.size self.ndim = lons.ndim self.dtype = lons.dtype else: raise ValueError(('%s must be created with either ' 'lon/lats of the same shape with same dtype') % self.__class__.__name__) def concatenate(self, other): if self.ndim != other.ndim: raise DimensionError(('Unable to concatenate %sD and %sD ' 'geometries') % (self.ndim, other.ndim)) klass = _get_highest_level_class(self, other) lons = np.concatenate((self.lons, other.lons)) lats = np.concatenate((self.lats, other.lats)) nprocs = min(self.nprocs, other.nprocs) return klass(lons, lats, nprocs=nprocs) def append(self, other): if self.ndim != other.ndim: raise DimensionError(('Unable to append %sD and %sD ' 'geometries') % (self.ndim, other.ndim)) self.lons = np.concatenate((self.lons, other.lons)) self.lats = np.concatenate((self.lats, other.lats)) self.shape = self.lons.shape self.size = self.lons.size def __str__(self): # Rely on numpy's object printing return ('Shape: %s\nLons: %s\nLats: %s') % (str(self.shape), str(self.lons), str(self.lats)) class GridDefinition(CoordinateDefinition): """Grid defined by lons and lats Parameters ---------- lons : numpy array lats : numpy array nprocs : int, optional Number of processor cores to be used for calculations. Attributes ---------- shape : tuple Grid shape as (rows, cols) size : int Number of elements in grid lons : object Grid lons lats : object Grid lats cartesian_coords : object Grid cartesian coordinates """ def __init__(self, lons, lats, nprocs=1): super(GridDefinition, self).__init__(lons, lats, nprocs) if lons.shape != lats.shape: raise ValueError('lon and lat grid must have same shape') elif lons.ndim != 2: raise ValueError('2 dimensional lon lat grid expected') class SwathDefinition(CoordinateDefinition): """Swath defined by lons and lats Parameters ---------- lons : numpy array lats : numpy array nprocs : int, optional Number of processor cores to be used for calculations. Attributes ---------- shape : tuple Swath shape size : int Number of elements in swath ndims : int Swath dimensions lons : object Swath lons lats : object Swath lats cartesian_coords : object Swath cartesian coordinates """ def __init__(self, lons, lats, nprocs=1): super(SwathDefinition, self).__init__(lons, lats, nprocs) if lons.shape != lats.shape: raise ValueError('lon and lat arrays must have same shape') elif lons.ndim > 2: raise ValueError('Only 1 and 2 dimensional swaths are allowed') class AreaDefinition(BaseDefinition): """Holds definition of an area. Parameters ---------- area_id : str ID of area name : str Name of area proj_id : str ID of projection proj_dict : dict Dictionary with Proj.4 parameters x_size : int x dimension in number of pixels y_size : int y dimension in number of pixels area_extent : list Area extent as a list (LL_x, LL_y, UR_x, UR_y) nprocs : int, optional Number of processor cores to be used lons : numpy array, optional Grid lons lats : numpy array, optional Grid lats Attributes ---------- area_id : str ID of area name : str Name of area proj_id : str ID of projection proj_dict : dict Dictionary with Proj.4 parameters x_size : int x dimension in number of pixels y_size : int y dimension in number of pixels shape : tuple Corresponding array shape as (rows, cols) size : int Number of points in grid area_extent : tuple Area extent as a tuple (LL_x, LL_y, UR_x, UR_y) area_extent_ll : tuple Area extent in lons lats as a tuple (LL_lon, LL_lat, UR_lon, UR_lat) pixel_size_x : float Pixel width in projection units pixel_size_y : float Pixel height in projection units pixel_upper_left : list Coordinates (x, y) of center of upper left pixel in projection units pixel_offset_x : float x offset between projection center and upper left corner of upper left pixel in units of pixels. pixel_offset_y : float y offset between projection center and upper left corner of upper left pixel in units of pixels.. proj4_string : str Projection defined as Proj.4 string lons : object Grid lons lats : object Grid lats cartesian_coords : object Grid cartesian coordinates projection_x_coords : object Grid projection x coordinate projection_y_coords : object Grid projection y coordinate """ def __init__(self, area_id, name, proj_id, proj_dict, x_size, y_size, area_extent, nprocs=1, lons=None, lats=None, dtype=np.float64): if not isinstance(proj_dict, dict): raise TypeError('Wrong type for proj_dict: %s. Expected dict.' % type(proj_dict)) super(AreaDefinition, self).__init__(lons, lats, nprocs) self.area_id = area_id self.name = name self.proj_id = proj_id self.x_size = x_size self.y_size = y_size self.shape = (y_size, x_size) if lons is not None: if lons.shape != self.shape: raise ValueError('Shape of lon lat grid must match ' 'area definition') self.size = y_size * x_size self.ndim = 2 self.pixel_size_x = (area_extent[2] - area_extent[0]) / float(x_size) self.pixel_size_y = (area_extent[3] - area_extent[1]) / float(y_size) self.proj_dict = proj_dict self.area_extent = tuple(area_extent) # Calculate area_extent in lon lat proj = _spatial_mp.Proj(**proj_dict) corner_lons, corner_lats = proj((area_extent[0], area_extent[2]), (area_extent[1], area_extent[3]), inverse=True) self.area_extent_ll = (corner_lons[0], corner_lats[0], corner_lons[1], corner_lats[1]) # Calculate projection coordinates of center of upper left pixel self.pixel_upper_left = \ (float(area_extent[0]) + float(self.pixel_size_x) / 2, float(area_extent[3]) - float(self.pixel_size_y) / 2) # Pixel_offset defines the distance to projection center from origen (UL) # of image in units of pixels. self.pixel_offset_x = -self.area_extent[0] / self.pixel_size_x self.pixel_offset_y = self.area_extent[3] / self.pixel_size_y self.projection_x_coords = None self.projection_y_coords = None self.dtype = dtype def __str__(self): # We need a sorted dictionary for a unique hash of str(self) proj_dict = self.proj_dict proj_str = ('{' + ', '.join(["'%s': '%s'" % (str(k), str(proj_dict[k])) for k in sorted(proj_dict.keys())]) + '}') return ('Area ID: %s\nName: %s\nProjection ID: %s\n' 'Projection: %s\nNumber of columns: %s\nNumber of rows: %s\n' 'Area extent: %s') % (self.area_id, self.name, self.proj_id, proj_str, self.x_size, self.y_size, self.area_extent) def create_areas_def(self): proj_dict = self.proj_dict proj_str = ','.join(["%s=%s" % (str(k), str(proj_dict[k])) for k in sorted(proj_dict.keys())]) fmt = "REGION: {name} {{\n" fmt += "\tNAME:\t{name}\n" fmt += "\tPCS_ID:\t{area_id}\n" fmt += "\tPCS_DEF:\t{proj_str}\n" fmt += "\tXSIZE:\t{x_size}\n" fmt += "\tYSIZE:\t{y_size}\n" fmt += "\tAREA_EXTENT: {area_extent}\n}};\n" area_def_str = fmt.format(name=self.name, area_id=self.area_id, proj_str=proj_str, x_size=self.x_size, y_size=self.y_size, area_extent=self.area_extent) return area_def_str __repr__ = __str__ def __eq__(self, other): """Test for equality""" try: return ((self.proj_dict == other.proj_dict) and (self.shape == other.shape) and (np.allclose(self.area_extent, other.area_extent))) except AttributeError: return super(AreaDefinition, self).__eq__(other) def __ne__(self, other): """Test for equality""" return not self.__eq__(other) def colrow2lonlat(self, cols, rows): """ Return longitudes and latitudes for the given image columns and rows. Both scalars and arrays are supported. To be used with scarse data points instead of slices (see get_lonlats). """ p = _spatial_mp.Proj(self.proj4_string) x = self.proj_x_coords y = self.proj_y_coords return p(y[y.size - cols], x[x.size - rows], inverse=True) def lonlat2colrow(self, lons, lats): """ Return image columns and rows for the given longitudes and latitudes. Both scalars and arrays are supported. Same as get_xy_from_lonlat, renamed for convenience. """ return self.get_xy_from_lonlat(lons, lats) def get_xy_from_lonlat(self, lon, lat): """Retrieve closest x and y coordinates (column, row indices) for the specified geolocation (lon,lat) if inside area. If lon,lat is a point a ValueError is raised if the return point is outside the area domain. If lon,lat is a tuple of sequences of longitudes and latitudes, a tuple of masked arrays are returned. :Input: lon : point or sequence (list or array) of longitudes lat : point or sequence (list or array) of latitudes :Returns: (x, y) : tuple of integer points/arrays """ if isinstance(lon, list): lon = np.array(lon) if isinstance(lat, list): lat = np.array(lat) if ((isinstance(lon, np.ndarray) and not isinstance(lat, np.ndarray)) or (not isinstance(lon, np.ndarray) and isinstance(lat, np.ndarray))): raise ValueError("Both lon and lat needs to be of " + "the same type and have the same dimensions!") if isinstance(lon, np.ndarray) and isinstance(lat, np.ndarray): if lon.shape != lat.shape: raise ValueError("lon and lat is not of the same shape!") pobj = _spatial_mp.Proj(self.proj4_string) upl_x = self.area_extent[0] upl_y = self.area_extent[3] xscale = abs(self.area_extent[2] - self.area_extent[0]) / float(self.x_size) yscale = abs(self.area_extent[1] - self.area_extent[3]) / float(self.y_size) xm_, ym_ = pobj(lon, lat) x__ = (xm_ - upl_x) / xscale y__ = (upl_y - ym_) / yscale if isinstance(x__, np.ndarray) and isinstance(y__, np.ndarray): mask = (((x__ < 0) | (x__ > self.x_size)) | ((y__ < 0) | (y__ > self.y_size))) return (np.ma.masked_array(x__.astype('int'), mask=mask, fill_value=-1), np.ma.masked_array(y__.astype('int'), mask=mask, fill_value=-1)) else: if ((x__ < 0 or x__ > self.x_size) or (y__ < 0 or y__ > self.y_size)): raise ValueError('Point outside area:( %f %f)' % (x__, y__)) return int(x__), int(y__) def get_xy_from_proj_coords(self, xm_, ym_): """Retrieve closest x and y coordinates (column, row indices) for a location specified with projection coordinates (xm_,ym_) in meters. A ValueError is raised, if the return point is outside the area domain. If xm_,ym_ is a tuple of sequences of projection coordinates, a tuple of masked arrays are returned. :Input: xm_ : point or sequence (list or array) of x-coordinates in m (map projection) ym_ : point or sequence (list or array) of y-coordinates in m (map projection) :Returns: (x, y) : tuple of integer points/arrays """ if isinstance(xm_, list): xm_ = np.array(xm_) if isinstance(ym_, list): ym_ = np.array(ym_) if ((isinstance(xm_, np.ndarray) and not isinstance(ym_, np.ndarray)) or (not isinstance(xm_, np.ndarray) and isinstance(ym_, np.ndarray))): raise ValueError("Both projection coordinates xm_ and ym_ needs to be of " + "the same type and have the same dimensions!") if isinstance(xm_, np.ndarray) and isinstance(ym_, np.ndarray): if xm_.shape != ym_.shape: raise ValueError( "projection coordinates xm_ and ym_ is not of the same shape!") upl_x = self.area_extent[0] upl_y = self.area_extent[3] xscale = abs(self.area_extent[2] - self.area_extent[0]) / float(self.x_size) yscale = abs(self.area_extent[1] - self.area_extent[3]) / float(self.y_size) x__ = (xm_ - upl_x) / xscale y__ = (upl_y - ym_) / yscale if isinstance(x__, np.ndarray) and isinstance(y__, np.ndarray): mask = (((x__ < 0) | (x__ > self.x_size)) | ((y__ < 0) | (y__ > self.y_size))) return (np.ma.masked_array(x__.astype('int'), mask=mask, fill_value=-1), np.ma.masked_array(y__.astype('int'), mask=mask, fill_value=-1)) else: if ((x__ < 0 or x__ > self.x_size) or (y__ < 0 or y__ > self.y_size)): raise ValueError('Point outside area:( %f %f)' % (x__, y__)) return int(x__), int(y__) def get_lonlat(self, row, col): """Retrieves lon and lat values of single point in area grid Parameters ---------- row : int col : int Returns ------- (lon, lat) : tuple of floats """ return self.get_lonlats(nprocs=None, data_slice=(row, col)) def get_proj_coords(self, data_slice=None, cache=False, dtype=None): """Get projection coordinates of grid Parameters ---------- data_slice : slice object, optional Calculate only coordinates for specified slice cache : bool, optional Store result the result. Requires data_slice to be None Returns ------- (target_x, target_y) : tuple of numpy arrays Grids of area x- and y-coordinates in projection units """ def get_val(val, sub_val, max): # Get value with substitution and wrapping if val is None: return sub_val else: if val < 0: # Wrap index return max + val else: return val if self.projection_x_coords is not None and self.projection_y_coords is not None: # Projection coords are cached if data_slice is None: return self.projection_x_coords, self.projection_y_coords else: return self.projection_x_coords[data_slice], self.projection_y_coords[data_slice] is_single_value = False is_1d_select = False if dtype is None: dtype = self.dtype # create coordinates of local area as ndarrays if data_slice is None or data_slice == slice(None): # Full slice rows = self.y_size cols = self.x_size row_start = 0 col_start = 0 else: if isinstance(data_slice, slice): # Row slice row_start = get_val(data_slice.start, 0, self.y_size) col_start = 0 rows = get_val( data_slice.stop, self.y_size, self.y_size) - row_start cols = self.x_size elif isinstance(data_slice[0], slice) and isinstance(data_slice[1], slice): # Block slice row_start = get_val(data_slice[0].start, 0, self.y_size) col_start = get_val(data_slice[1].start, 0, self.x_size) rows = get_val( data_slice[0].stop, self.y_size, self.y_size) - row_start cols = get_val( data_slice[1].stop, self.x_size, self.x_size) - col_start elif isinstance(data_slice[0], slice): # Select from col is_1d_select = True row_start = get_val(data_slice[0].start, 0, self.y_size) col_start = get_val(data_slice[1], 0, self.x_size) rows = get_val( data_slice[0].stop, self.y_size, self.y_size) - row_start cols = 1 elif isinstance(data_slice[1], slice): # Select from row is_1d_select = True row_start = get_val(data_slice[0], 0, self.y_size) col_start = get_val(data_slice[1].start, 0, self.x_size) rows = 1 cols = get_val( data_slice[1].stop, self.x_size, self.x_size) - col_start else: # Single element select is_single_value = True row_start = get_val(data_slice[0], 0, self.y_size) col_start = get_val(data_slice[1], 0, self.x_size) rows = 1 cols = 1 # Calculate coordinates target_x = np.fromfunction(lambda i, j: (j + col_start) * self.pixel_size_x + self.pixel_upper_left[0], (rows, cols), dtype=dtype) target_y = np.fromfunction(lambda i, j: self.pixel_upper_left[1] - (i + row_start) * self.pixel_size_y, (rows, cols), dtype=dtype) if is_single_value: # Return single values target_x = float(target_x) target_y = float(target_y) elif is_1d_select: # Reshape to 1D array target_x = target_x.reshape((target_x.size,)) target_y = target_y.reshape((target_y.size,)) if cache and data_slice is None: # Cache the result if requested self.projection_x_coords = target_x self.projection_y_coords = target_y return target_x, target_y @property def proj_x_coords(self): return self.get_proj_coords(data_slice=(0, slice(None)))[0] @property def proj_y_coords(self): return self.get_proj_coords(data_slice=(slice(None), 0))[1] @property def outer_boundary_corners(self): """Returns the lon,lat of the outer edges of the corner points """ from pyresample.spherical_geometry import Coordinate proj = _spatial_mp.Proj(**self.proj_dict) corner_lons, corner_lats = proj((self.area_extent[0], self.area_extent[2], self.area_extent[2], self.area_extent[0]), (self.area_extent[3], self.area_extent[3], self.area_extent[1], self.area_extent[1]), inverse=True) return [Coordinate(corner_lons[0], corner_lats[0]), Coordinate(corner_lons[1], corner_lats[1]), Coordinate(corner_lons[2], corner_lats[2]), Coordinate(corner_lons[3], corner_lats[3])] def get_lonlats(self, nprocs=None, data_slice=None, cache=False, dtype=None): """Returns lon and lat arrays of area. Parameters ---------- nprocs : int, optional Number of processor cores to be used. Defaults to the nprocs set when instantiating object data_slice : slice object, optional Calculate only coordinates for specified slice cache : bool, optional Store result the result. Requires data_slice to be None Returns ------- (lons, lats) : tuple of numpy arrays Grids of area lons and and lats """ if dtype is None: dtype = self.dtype if self.lons is None or self.lats is None: #Data is not cached if nprocs is None: nprocs = self.nprocs # Proj.4 definition of target area projection if nprocs > 1: target_proj = _spatial_mp.Proj_MP(**self.proj_dict) else: target_proj = _spatial_mp.Proj(**self.proj_dict) # Get coordinates of local area as ndarrays target_x, target_y = self.get_proj_coords( data_slice=data_slice, dtype=dtype) # Get corresponding longitude and latitude values lons, lats = target_proj(target_x, target_y, inverse=True, nprocs=nprocs) lons = np.asanyarray(lons, dtype=dtype) lats = np.asanyarray(lats, dtype=dtype) if cache and data_slice is None: # Cache the result if requested self.lons = lons self.lats = lats # Free memory del(target_x) del(target_y) else: #Data is cached if data_slice is None: # Full slice lons = self.lons lats = self.lats else: lons = self.lons[data_slice] lats = self.lats[data_slice] return lons, lats @property def proj4_string(self): """Returns projection definition as Proj.4 string""" items = self.proj_dict.items() return '+' + ' +'.join([t[0] + '=' + str(t[1]) for t in items]) def _get_slice(segments, shape): """Generator for segmenting a 1D or 2D array""" if not (1 <= len(shape) <= 2): raise ValueError('Cannot segment array of shape: %s' % str(shape)) else: size = shape[0] slice_length = int(np.ceil(float(size) / segments)) start_idx = 0 end_idx = slice_length while start_idx < size: if len(shape) == 1: yield slice(start_idx, end_idx) else: yield (slice(start_idx, end_idx), slice(None)) start_idx = end_idx end_idx = min(start_idx + slice_length, size) def _flatten_cartesian_coords(cartesian_coords): """Flatten array to (n, 3) shape""" shape = cartesian_coords.shape if len(shape) > 2: cartesian_coords = cartesian_coords.reshape(shape[0] * shape[1], 3) return cartesian_coords def _get_highest_level_class(obj1, obj2): if (not issubclass(obj1.__class__, obj2.__class__) or not issubclass(obj2.__class__, obj1.__class__)): raise TypeError('No common superclass for %s and %s' % (obj1.__class__, obj2.__class__)) if obj1.__class__ == obj2.__class__: klass = obj1.__class__ elif issubclass(obj1.__class__, obj2.__class__): klass = obj2.__class__ else: klass = obj1.__class__ return klass pyresample-1.2.9/pyresample/grid.py000066400000000000000000000205131302372600000173560ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2014, 2015 Esben S. Nielsen # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or #(at your option) any later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """Resample image from one projection to another using nearest neighbour method in cartesian projection coordinate systems""" from __future__ import absolute_import import numpy as np from pyresample import geometry, _spatial_mp try: range = xrange except NameError: pass def get_image_from_linesample(row_indices, col_indices, source_image, fill_value=0): """Samples from image based on index arrays. Parameters ---------- row_indices : numpy array Row indices. Dimensions must match col_indices col_indices : numpy array Col indices. Dimensions must match row_indices source_image : numpy array Source image fill_value : int or None, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked Returns ------- image_data : numpy array Resampled image """ # mask out non valid row and col indices row_mask = (row_indices >= 0) * (row_indices < source_image.shape[0]) col_mask = (col_indices >= 0) * (col_indices < source_image.shape[1]) valid_rows = row_indices * row_mask valid_cols = col_indices * col_mask # free memory del(row_indices) del(col_indices) # get valid part of image target_image = source_image[valid_rows, valid_cols] # free memory del(valid_rows) del(valid_cols) # create mask for valid data points valid_data = row_mask * col_mask if valid_data.ndim != target_image.ndim: for i in range(target_image.ndim - valid_data.ndim): valid_data = np.expand_dims(valid_data, axis=valid_data.ndim) # free memory del(row_mask) del(col_mask) # fill the non valid part of the image if fill_value is not None: target_filled = (target_image * valid_data + (1 - valid_data) * fill_value) else: if np.ma.is_masked(target_image): mask = ((1 - valid_data) | target_image.mask) else: mask = (1 - valid_data) target_filled = np.ma.array(target_image, mask=mask) return target_filled.astype(target_image.dtype) def get_linesample(lons, lats, source_area_def, nprocs=1): """Returns index row and col arrays for resampling Parameters ---------- lons : numpy array Lons. Dimensions must match lats lats : numpy array Lats. Dimensions must match lons source_area_def : object Source definition as AreaDefinition object nprocs : int, optional Number of processor cores to be used Returns ------- (row_indices, col_indices) : tuple of numpy arrays Arrays for resampling area by array indexing """ # Proj.4 definition of source area projection if nprocs > 1: source_proj = _spatial_mp.Proj_MP(**source_area_def.proj_dict) else: source_proj = _spatial_mp.Proj(**source_area_def.proj_dict) # get cartesian projection values from longitude and latitude source_x, source_y = source_proj(lons, lats, nprocs=nprocs) # Find corresponding pixels (element by element conversion of ndarrays) source_pixel_x = (source_area_def.pixel_offset_x + source_x / source_area_def.pixel_size_x).astype(np.int32) source_pixel_y = (source_area_def.pixel_offset_y - source_y / source_area_def.pixel_size_y).astype(np.int32) return source_pixel_y, source_pixel_x def get_image_from_lonlats(lons, lats, source_area_def, source_image_data, fill_value=0, nprocs=1): """Samples from image based on lon lat arrays using nearest neighbour method in cartesian projection coordinate systems. Parameters ---------- lons : numpy array Lons. Dimensions must match lats lats : numpy array Lats. Dimensions must match lons source_area_def : object Source definition as AreaDefinition object source_image_data : numpy array Source image data fill_value : int or None, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked nprocs : int, optional Number of processor cores to be used Returns ------- image_data : numpy array Resampled image data """ source_pixel_y, source_pixel_x = get_linesample(lons, lats, source_area_def, nprocs=nprocs) # Return target image return get_image_from_linesample(source_pixel_y, source_pixel_x, source_image_data, fill_value) def get_resampled_image(target_area_def, source_area_def, source_image_data, fill_value=0, nprocs=1, segments=None): """Resamples image using nearest neighbour method in cartesian projection coordinate systems. Parameters ---------- target_area_def : object Target definition as AreaDefinition object source_area_def : object Source definition as AreaDefinition object source_image_data : numpy array Source image data fill_value : {int, None} optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked nprocs : int, optional Number of processor cores to be used segments : {int, None} optional Number of segments to use when resampling. If set to None an estimate will be calculated. Returns ------- image_data : numpy array Resampled image data """ if not isinstance(target_area_def, geometry.AreaDefinition): raise TypeError('target_area_def must be of type AreaDefinition') if not isinstance(source_area_def, geometry.AreaDefinition): raise TypeError('source_area_def must be of type AreaDefinition') if not isinstance(source_image_data, (np.ndarray, np.ma.core.MaskedArray)): raise TypeError('source_image must be of type ndarray' ' or a masked array.') # Calculate number of segments if needed if segments is None: rows = target_area_def.y_size cut_off = 500 if rows > cut_off: segments = int(rows / cut_off) else: segments = 1 if segments > 1: # Iterate through segments for i, target_slice in enumerate(geometry._get_slice(segments, target_area_def.shape)): # Select data from segment with slice lons, lats = target_area_def.get_lonlats( nprocs=nprocs, data_slice=target_slice) # Calculate partial result next_result = get_image_from_lonlats(lons, lats, source_area_def, source_image_data, fill_value, nprocs) # Build result iteratively if i == 0: # First iteration result = next_result else: result = np.row_stack((result, next_result)) return result else: # Get lon lat arrays of target area lons, lats = target_area_def.get_lonlats(nprocs) # Get target image return get_image_from_lonlats(lons, lats, source_area_def, source_image_data, fill_value, nprocs) pyresample-1.2.9/pyresample/image.py000066400000000000000000000254321302372600000175200ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2015 Esben S. Nielsen # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """Handles resampling of images with assigned geometry definitions""" from __future__ import absolute_import import numpy as np from pyresample import geometry, grid, kd_tree class ImageContainer(object): """Holds image with geometry definition. Allows indexing with linesample arrays. Parameters ---------- image_data : numpy array Image data geo_def : object Geometry definition fill_value : int or None, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked nprocs : int, optional Number of processor cores to be used Attributes ---------- image_data : numpy array Image data geo_def : object Geometry definition fill_value : int or None Resample result fill value nprocs : int Number of processor cores to be used for geometry operations """ def __init__(self, image_data, geo_def, fill_value=0, nprocs=1): if not isinstance(image_data, (np.ndarray, np.ma.core.MaskedArray)): raise TypeError('image_data must be either an ndarray' ' or a masked array') elif ((image_data.ndim > geo_def.ndim + 1) or (image_data.ndim < geo_def.ndim)): raise ValueError(('Unexpected number of dimensions for ' 'image_data: ') % image_data.ndim) for i, size in enumerate(geo_def.shape): if image_data.shape[i] != size: raise ValueError(('Size mismatch for image_data. Expected ' 'size %s for dimension %s and got %s') % (size, i, image_data.shape[i])) self.shape = geo_def.shape self.size = geo_def.size self.ndim = geo_def.ndim self.image_data = image_data if image_data.ndim > geo_def.ndim: self.channels = image_data.shape[-1] else: self.channels = 1 self.geo_def = geo_def self.fill_value = fill_value self.nprocs = nprocs def __str__(self): return 'Image:\n %s' % self.image_data.__str__() def __repr__(self): return self.image_data.__repr__() def resample(self, target_geo_def): """Base method for resampling""" raise NotImplementedError('Method "resample" is not implemented ' 'in class %s' % self.__class__.__name__) def get_array_from_linesample(self, row_indices, col_indices): """Samples from image based on index arrays. Parameters ---------- row_indices : numpy array Row indices. Dimensions must match col_indices col_indices : numpy array Col indices. Dimensions must match row_indices Returns ------- image_data : numpy_array Resampled image data """ if self.geo_def.ndim != 2: raise TypeError('Resampling from linesamples only makes sense ' 'on 2D data') return grid.get_image_from_linesample(row_indices, col_indices, self.image_data, self.fill_value) def get_array_from_neighbour_info(self, *args, **kwargs): """Base method for resampling from preprocessed data.""" raise NotImplementedError('Method "get_array_from_neighbour_info" is ' 'not implemented in class %s' % self.__class__.__name__) class ImageContainerQuick(ImageContainer): """Holds image with area definition. ' Allows quick resampling within area. Parameters ---------- image_data : numpy array Image data geo_def : object Area definition as AreaDefinition object fill_value : int or None, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked nprocs : int, optional Number of processor cores to be used for geometry operations segments : int or None Number of segments to use when resampling. If set to None an estimate will be calculated Attributes ---------- image_data : numpy array Image data geo_def : object Area definition as AreaDefinition object fill_value : int or None Resample result fill value If fill_value is None a masked array is returned with undetermined pixels masked nprocs : int Number of processor cores to be used segments : int or None Number of segments to use when resampling """ def __init__(self, image_data, geo_def, fill_value=0, nprocs=1, segments=None): if not isinstance(geo_def, geometry.AreaDefinition): raise TypeError('area_def must be of type ' 'geometry.AreaDefinition') super(ImageContainerQuick, self).__init__(image_data, geo_def, fill_value=fill_value, nprocs=nprocs) self.segments = segments def resample(self, target_area_def): """Resamples image to area definition using nearest neighbour approach in projection coordinates. Parameters ---------- target_area_def : object Target area definition as AreaDefinition object Returns ------- image_container : object ImageContainerQuick object of resampled area """ resampled_image = grid.get_resampled_image(target_area_def, self.geo_def, self.image_data, fill_value=self.fill_value, nprocs=self.nprocs, segments=self.segments) return ImageContainerQuick(resampled_image, target_area_def, fill_value=self.fill_value, nprocs=self.nprocs, segments=self.segments) class ImageContainerNearest(ImageContainer): """Holds image with geometry definition. Allows nearest neighbour resampling to new geometry definition. Parameters ---------- image_data : numpy array Image data geo_def : object Geometry definition radius_of_influence : float Cut off distance in meters epsilon : float, optional Allowed uncertainty in meters. Increasing uncertainty reduces execution time fill_value : int or None, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked reduce_data : bool, optional Perform coarse data reduction before resampling in order to reduce execution time nprocs : int, optional Number of processor cores to be used for geometry operations segments : int or None Number of segments to use when resampling. If set to None an estimate will be calculated Attributes ---------- image_data : numpy array Image data geo_def : object Geometry definition radius_of_influence : float Cut off distance in meters epsilon : float Allowed uncertainty in meters fill_value : int or None Resample result fill value reduce_data : bool Perform coarse data reduction before resampling nprocs : int Number of processor cores to be used segments : int or None Number of segments to use when resampling """ def __init__(self, image_data, geo_def, radius_of_influence, epsilon=0, fill_value=0, reduce_data=True, nprocs=1, segments=None): super(ImageContainerNearest, self).__init__(image_data, geo_def, fill_value=fill_value, nprocs=nprocs) self.radius_of_influence = radius_of_influence self.epsilon = epsilon self.reduce_data = reduce_data self.segments = segments def resample(self, target_geo_def): """Resamples image to area definition using nearest neighbour approach Parameters ---------- target_geo_def : object Target geometry definition Returns ------- image_container : object ImageContainerNearest object of resampled geometry """ if self.image_data.ndim > 2 and self.ndim > 1: image_data = self.image_data.reshape(self.image_data.shape[0] * self.image_data.shape[1], self.image_data.shape[2]) else: image_data = self.image_data.ravel() resampled_image = \ kd_tree.resample_nearest(self.geo_def, image_data, target_geo_def, self.radius_of_influence, epsilon=self.epsilon, fill_value=self.fill_value, nprocs=self.nprocs, reduce_data=self.reduce_data, segments=self.segments) return ImageContainerNearest(resampled_image, target_geo_def, self.radius_of_influence, epsilon=self.epsilon, fill_value=self.fill_value, reduce_data=self.reduce_data, nprocs=self.nprocs, segments=self.segments) pyresample-1.2.9/pyresample/kd_tree.py000066400000000000000000001057711302372600000200600ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2014, 2015 Esben S. Nielsen # Adam.Dybbroe # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or #(at your option) any later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """Handles reprojection of geolocated data. Several types of resampling are supported""" from __future__ import absolute_import import types import warnings import sys import numpy as np from pyresample import geometry, data_reduce, _spatial_mp if sys.version < '3': range = xrange else: long = int kd_tree_name = None try: from pykdtree.kdtree import KDTree kd_tree_name = 'pykdtree' except ImportError: try: import scipy.spatial as sp kd_tree_name = 'scipy.spatial' except ImportError: raise ImportError('Either pykdtree or scipy must be available') class EmptyResult(Exception): pass def which_kdtree(): """Returns the name of the kdtree used for resampling """ return kd_tree_name def resample_nearest(source_geo_def, data, target_geo_def, radius_of_influence, epsilon=0, fill_value=0, reduce_data=True, nprocs=1, segments=None): """Resamples data using kd-tree nearest neighbour approach Parameters ---------- source_geo_def : object Geometry definition of source data : numpy array 1d array of single channel data points or (source_size, k) array of k channels of datapoints target_geo_def : object Geometry definition of target radius_of_influence : float Cut off distance in meters epsilon : float, optional Allowed uncertainty in meters. Increasing uncertainty reduces execution time fill_value : int or None, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked reduce_data : bool, optional Perform initial coarse reduction of source dataset in order to reduce execution time nprocs : int, optional Number of processor cores to be used segments : int or None Number of segments to use when resampling. If set to None an estimate will be calculated Returns ------- data : numpy array Source data resampled to target geometry """ return _resample(source_geo_def, data, target_geo_def, 'nn', radius_of_influence, neighbours=1, epsilon=epsilon, fill_value=fill_value, reduce_data=reduce_data, nprocs=nprocs, segments=segments) def resample_gauss(source_geo_def, data, target_geo_def, radius_of_influence, sigmas, neighbours=8, epsilon=0, fill_value=0, reduce_data=True, nprocs=1, segments=None, with_uncert=False): """Resamples data using kd-tree gaussian weighting neighbour approach Parameters ---------- source_geo_def : object Geometry definition of source data : numpy array Array of single channel data points or (source_geo_def.shape, k) array of k channels of datapoints target_geo_def : object Geometry definition of target radius_of_influence : float Cut off distance in meters sigmas : list of floats or float List of sigmas to use for the gauss weighting of each channel 1 to k, w_k = exp(-dist^2/sigma_k^2). If only one channel is resampled sigmas is a single float value. neighbours : int, optional The number of neigbours to consider for each grid point epsilon : float, optional Allowed uncertainty in meters. Increasing uncertainty reduces execution time fill_value : {int, None}, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked reduce_data : bool, optional Perform initial coarse reduction of source dataset in order to reduce execution time nprocs : int, optional Number of processor cores to be used segments : int or None Number of segments to use when resampling. If set to None an estimate will be calculated with_uncert : bool, optional Calculate uncertainty estimates Returns ------- data : numpy array (default) Source data resampled to target geometry data, stddev, counts : numpy array, numpy array, numpy array (if with_uncert == True) Source data resampled to target geometry. Weighted standard devaition for all pixels having more than one source value Counts of number of source values used in weighting per pixel """ def gauss(sigma): # Return gauss function object return lambda r: np.exp(-r ** 2 / float(sigma) ** 2) # Build correct sigma argument is_multi_channel = False try: sigmas.__iter__() sigma_list = sigmas is_multi_channel = True except: sigma_list = [sigmas] for sigma in sigma_list: if not isinstance(sigma, (long, int, float)): raise TypeError('sigma must be number') # Get gauss function objects if is_multi_channel: weight_funcs = list(map(gauss, sigma_list)) else: weight_funcs = gauss(sigmas) return _resample(source_geo_def, data, target_geo_def, 'custom', radius_of_influence, neighbours=neighbours, epsilon=epsilon, weight_funcs=weight_funcs, fill_value=fill_value, reduce_data=reduce_data, nprocs=nprocs, segments=segments, with_uncert=with_uncert) def resample_custom(source_geo_def, data, target_geo_def, radius_of_influence, weight_funcs, neighbours=8, epsilon=0, fill_value=0, reduce_data=True, nprocs=1, segments=None, with_uncert=False): """Resamples data using kd-tree custom radial weighting neighbour approach Parameters ---------- source_geo_def : object Geometry definition of source data : numpy array Array of single channel data points or (source_geo_def.shape, k) array of k channels of datapoints target_geo_def : object Geometry definition of target radius_of_influence : float Cut off distance in meters weight_funcs : list of function objects or function object List of weight functions f(dist) to use for the weighting of each channel 1 to k. If only one channel is resampled weight_funcs is a single function object. neighbours : int, optional The number of neigbours to consider for each grid point epsilon : float, optional Allowed uncertainty in meters. Increasing uncertainty reduces execution time fill_value : {int, None}, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked reduce_data : bool, optional Perform initial coarse reduction of source dataset in order to reduce execution time nprocs : int, optional Number of processor cores to be used segments : {int, None} Number of segments to use when resampling. If set to None an estimate will be calculated Returns ------- data : numpy array (default) Source data resampled to target geometry data, stddev, counts : numpy array, numpy array, numpy array (if with_uncert == True) Source data resampled to target geometry. Weighted standard devaition for all pixels having more than one source value Counts of number of source values used in weighting per pixel """ try: for weight_func in weight_funcs: if not isinstance(weight_func, types.FunctionType): raise TypeError('weight_func must be function object') except: if not isinstance(weight_funcs, types.FunctionType): raise TypeError('weight_func must be function object') return _resample(source_geo_def, data, target_geo_def, 'custom', radius_of_influence, neighbours=neighbours, epsilon=epsilon, weight_funcs=weight_funcs, fill_value=fill_value, reduce_data=reduce_data, nprocs=nprocs, segments=segments, with_uncert=with_uncert) def _resample(source_geo_def, data, target_geo_def, resample_type, radius_of_influence, neighbours=8, epsilon=0, weight_funcs=None, fill_value=0, reduce_data=True, nprocs=1, segments=None, with_uncert=False): """Resamples swath using kd-tree approach""" valid_input_index, valid_output_index, index_array, distance_array = \ get_neighbour_info(source_geo_def, target_geo_def, radius_of_influence, neighbours=neighbours, epsilon=epsilon, reduce_data=reduce_data, nprocs=nprocs, segments=segments) return get_sample_from_neighbour_info(resample_type, target_geo_def.shape, data, valid_input_index, valid_output_index, index_array, distance_array=distance_array, weight_funcs=weight_funcs, fill_value=fill_value, with_uncert=with_uncert) def get_neighbour_info(source_geo_def, target_geo_def, radius_of_influence, neighbours=8, epsilon=0, reduce_data=True, nprocs=1, segments=None): """Returns neighbour info Parameters ---------- source_geo_def : object Geometry definition of source target_geo_def : object Geometry definition of target radius_of_influence : float Cut off distance in meters neighbours : int, optional The number of neigbours to consider for each grid point epsilon : float, optional Allowed uncertainty in meters. Increasing uncertainty reduces execution time fill_value : int or None, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked reduce_data : bool, optional Perform initial coarse reduction of source dataset in order to reduce execution time nprocs : int, optional Number of processor cores to be used segments : int or None Number of segments to use when resampling. If set to None an estimate will be calculated Returns ------- (valid_input_index, valid_output_index, index_array, distance_array) : tuple of numpy arrays Neighbour resampling info """ if source_geo_def.size < neighbours: warnings.warn('Searching for %s neighbours in %s data points' % (neighbours, source_geo_def.size)) if segments is None: cut_off = 3000000 if target_geo_def.size > cut_off: segments = int(target_geo_def.size / cut_off) else: segments = 1 # Find reduced input coordinate set valid_input_index, source_lons, source_lats = _get_valid_input_index(source_geo_def, target_geo_def, reduce_data, radius_of_influence, nprocs=nprocs) # Create kd-tree try: resample_kdtree = _create_resample_kdtree(source_lons, source_lats, valid_input_index, nprocs=nprocs) except EmptyResult: # Handle if all input data is reduced away valid_output_index, index_array, distance_array = \ _create_empty_info(source_geo_def, target_geo_def, neighbours) return (valid_input_index, valid_output_index, index_array, distance_array) if segments > 1: # Iterate through segments for i, target_slice in enumerate(geometry._get_slice(segments, target_geo_def.shape)): # Query on slice of target coordinates next_voi, next_ia, next_da = \ _query_resample_kdtree(resample_kdtree, source_geo_def, target_geo_def, radius_of_influence, target_slice, neighbours=neighbours, epsilon=epsilon, reduce_data=reduce_data, nprocs=nprocs) # Build result iteratively if i == 0: # First iteration valid_output_index = next_voi index_array = next_ia distance_array = next_da else: valid_output_index = np.append(valid_output_index, next_voi) if neighbours > 1: index_array = np.row_stack((index_array, next_ia)) distance_array = np.row_stack((distance_array, next_da)) else: index_array = np.append(index_array, next_ia) distance_array = np.append(distance_array, next_da) else: # Query kd-tree with full target coordinate set full_slice = slice(None) valid_output_index, index_array, distance_array = \ _query_resample_kdtree(resample_kdtree, source_geo_def, target_geo_def, radius_of_influence, full_slice, neighbours=neighbours, epsilon=epsilon, reduce_data=reduce_data, nprocs=nprocs) # Check if number of neighbours is potentially too low if neighbours > 1: if not np.all(np.isinf(distance_array[:, -1])): warnings.warn(('Possible more than %s neighbours ' 'within %s m for some data points') % (neighbours, radius_of_influence)) return valid_input_index, valid_output_index, index_array, distance_array def _get_valid_input_index(source_geo_def, target_geo_def, reduce_data, radius_of_influence, nprocs=1): """Find indices of reduced inputput data""" source_lons, source_lats = source_geo_def.get_lonlats(nprocs=nprocs) source_lons = source_lons.ravel() source_lats = source_lats.ravel() if source_lons.size == 0 or source_lats.size == 0: raise ValueError('Cannot resample empty data set') elif source_lons.size != source_lats.size or \ source_lons.shape != source_lats.shape: raise ValueError('Mismatch between lons and lats') # Remove illegal values valid_data = ((source_lons >= -180) & (source_lons <= 180) & (source_lats <= 90) & (source_lats >= -90)) valid_input_index = np.ones(source_geo_def.size, dtype=np.bool) if reduce_data: # Reduce dataset if (isinstance(source_geo_def, geometry.CoordinateDefinition) and isinstance(target_geo_def, (geometry.GridDefinition, geometry.AreaDefinition))) or \ (isinstance(source_geo_def, (geometry.GridDefinition, geometry.AreaDefinition)) and isinstance(target_geo_def, (geometry.GridDefinition, geometry.AreaDefinition))): # Resampling from swath to grid or from grid to grid lonlat_boundary = target_geo_def.get_boundary_lonlats() valid_input_index = \ data_reduce.get_valid_index_from_lonlat_boundaries( lonlat_boundary[0], lonlat_boundary[1], source_lons, source_lats, radius_of_influence) # Combine reduced and legal values valid_input_index = (valid_data & valid_input_index) if(isinstance(valid_input_index, np.ma.core.MaskedArray)): # Make sure valid_input_index is not a masked array valid_input_index = valid_input_index.filled(False) return valid_input_index, source_lons, source_lats def _get_valid_output_index(source_geo_def, target_geo_def, target_lons, target_lats, reduce_data, radius_of_influence): """Find indices of reduced output data""" valid_output_index = np.ones(target_lons.size, dtype=np.bool) if reduce_data: if isinstance(source_geo_def, (geometry.GridDefinition, geometry.AreaDefinition)) and \ isinstance(target_geo_def, geometry.CoordinateDefinition): # Resampling from grid to swath lonlat_boundary = source_geo_def.get_boundary_lonlats() valid_output_index = \ data_reduce.get_valid_index_from_lonlat_boundaries( lonlat_boundary[0], lonlat_boundary[1], target_lons, target_lats, radius_of_influence) valid_output_index = valid_output_index.astype(np.bool) # Remove illegal values valid_out = ((target_lons >= -180) & (target_lons <= 180) & (target_lats <= 90) & (target_lats >= -90)) # Combine reduced and legal values valid_output_index = (valid_output_index & valid_out) return valid_output_index def _create_resample_kdtree(source_lons, source_lats, valid_input_index, nprocs=1): """Set up kd tree on input""" """ if not isinstance(source_geo_def, geometry.BaseDefinition): raise TypeError('source_geo_def must be of geometry type') #Get reduced cartesian coordinates and flatten them source_cartesian_coords = source_geo_def.get_cartesian_coords(nprocs=nprocs) input_coords = geometry._flatten_cartesian_coords(source_cartesian_coords) input_coords = input_coords[valid_input_index] """ source_lons_valid = source_lons[valid_input_index] source_lats_valid = source_lats[valid_input_index] if nprocs > 1: cartesian = _spatial_mp.Cartesian_MP(nprocs) else: cartesian = _spatial_mp.Cartesian() input_coords = cartesian.transform_lonlats( source_lons_valid, source_lats_valid) if input_coords.size == 0: raise EmptyResult('No valid data points in input data') # Build kd-tree on input if kd_tree_name == 'pykdtree': resample_kdtree = KDTree(input_coords) elif nprocs > 1: resample_kdtree = _spatial_mp.cKDTree_MP(input_coords, nprocs=nprocs) else: resample_kdtree = sp.cKDTree(input_coords) return resample_kdtree def _query_resample_kdtree(resample_kdtree, source_geo_def, target_geo_def, radius_of_influence, data_slice, neighbours=8, epsilon=0, reduce_data=True, nprocs=1): """Query kd-tree on slice of target coordinates""" # Check validity of input if not isinstance(target_geo_def, geometry.BaseDefinition): raise TypeError('target_geo_def must be of geometry type') elif not isinstance(radius_of_influence, (long, int, float)): raise TypeError('radius_of_influence must be number') elif not isinstance(neighbours, int): raise TypeError('neighbours must be integer') elif not isinstance(epsilon, (long, int, float)): raise TypeError('epsilon must be number') # Get sliced target coordinates target_lons, target_lats = target_geo_def.get_lonlats(nprocs=nprocs, data_slice=data_slice, dtype=source_geo_def.dtype) # Find indiced of reduced target coordinates valid_output_index = _get_valid_output_index(source_geo_def, target_geo_def, target_lons.ravel(), target_lats.ravel(), reduce_data, radius_of_influence) # Get cartesian target coordinates and select reduced set if nprocs > 1: cartesian = _spatial_mp.Cartesian_MP(nprocs) else: cartesian = _spatial_mp.Cartesian() target_lons_valid = target_lons.ravel()[valid_output_index] target_lats_valid = target_lats.ravel()[valid_output_index] output_coords = cartesian.transform_lonlats( target_lons_valid, target_lats_valid) # pykdtree requires query points have same data type as kdtree. try: dt = resample_kdtree.data.dtype except AttributeError: # use a sensible default dt = np.dtype('d') output_coords = np.asarray(output_coords, dtype=dt) # Query kd-tree distance_array, index_array = resample_kdtree.query(output_coords, k=neighbours, eps=epsilon, distance_upper_bound=radius_of_influence) return valid_output_index, index_array, distance_array def _create_empty_info(source_geo_def, target_geo_def, neighbours): """Creates dummy info for empty result set""" valid_output_index = np.ones(target_geo_def.size, dtype=np.bool) if neighbours > 1: index_array = (np.ones((target_geo_def.size, neighbours), dtype=np.int32) * source_geo_def.size) distance_array = np.ones((target_geo_def.size, neighbours)) else: index_array = (np.ones(target_geo_def.size, dtype=np.int32) * source_geo_def.size) distance_array = np.ones(target_geo_def.size) return valid_output_index, index_array, distance_array def get_sample_from_neighbour_info(resample_type, output_shape, data, valid_input_index, valid_output_index, index_array, distance_array=None, weight_funcs=None, fill_value=0, with_uncert=False): """Resamples swath based on neighbour info Parameters ---------- resample_type : {'nn', 'custom'} 'nn': Use nearest neighbour resampling 'custom': Resample based on weight_funcs output_shape : (int, int) Shape of output as (rows, cols) data : numpy array Source data valid_input_index : numpy array valid_input_index from get_neighbour_info valid_output_index : numpy array valid_output_index from get_neighbour_info index_array : numpy array index_array from get_neighbour_info distance_array : numpy array, optional distance_array from get_neighbour_info Not needed for 'nn' resample type weight_funcs : list of function objects or function object, optional List of weight functions f(dist) to use for the weighting of each channel 1 to k. If only one channel is resampled weight_funcs is a single function object. Must be supplied when using 'custom' resample type fill_value : int or None, optional Set undetermined pixels to this value. If fill_value is None a masked array is returned with undetermined pixels masked Returns ------- result : numpy array Source data resampled to target geometry """ if data.ndim > 2 and data.shape[0] * data.shape[1] == valid_input_index.size: data = data.reshape(data.shape[0] * data.shape[1], data.shape[2]) elif data.shape[0] != valid_input_index.size: data = data.ravel() if valid_input_index.size != data.shape[0]: raise ValueError('Mismatch between geometry and dataset') is_multi_channel = (data.ndim > 1) valid_input_size = valid_input_index.sum() valid_output_size = valid_output_index.sum() # Handle empty result set if valid_input_size == 0 or valid_output_size == 0: if is_multi_channel: output_shape = list(output_shape) output_shape.append(data.shape[1]) if fill_value is None: # Use masked array for fill values return np.ma.array(np.zeros(output_shape, data.dtype), mask=np.ones(output_shape, dtype=np.bool)) else: # Return fill vaues for all pixels return np.ones(output_shape, dtype=data.dtype) * fill_value # Get size of output and reduced input input_size = valid_input_size if len(output_shape) > 1: output_size = output_shape[0] * output_shape[1] else: output_size = output_shape[0] # Check validity of input if not isinstance(data, np.ndarray): raise TypeError('data must be numpy array') elif valid_input_index.ndim != 1: raise TypeError('valid_index must be one dimensional array') elif data.shape[0] != valid_input_index.size: raise TypeError('Not the same number of datapoints in ' 'valid_input_index and data') valid_types = ('nn', 'custom') if not resample_type in valid_types: raise TypeError('Invalid resampling type: %s' % resample_type) if resample_type == 'custom' and weight_funcs is None: raise ValueError('weight_funcs must be supplied when using ' 'custom resampling') if not isinstance(fill_value, (long, int, float)) and fill_value is not None: raise TypeError('fill_value must be number or None') if index_array.ndim == 1: neighbours = 1 else: neighbours = index_array.shape[1] if resample_type == 'nn': raise ValueError('index_array contains more neighbours than ' 'just the nearest') # Reduce data new_data = data[valid_input_index] # Nearest neighbour resampling should conserve data type # Get data type conserve_input_data_type = False if resample_type == 'nn': conserve_input_data_type = True input_data_type = new_data.dtype # Handle masked array input is_masked_data = False if np.ma.is_masked(new_data): # Add the mask as channels to the dataset is_masked_data = True new_data = np.column_stack((new_data.data, new_data.mask)) if new_data.ndim > 1: # Multiple channels or masked input output_shape = list(output_shape) output_shape.append(new_data.shape[1]) # Prepare weight_funcs argument for handeling mask data if weight_funcs is not None and is_masked_data: if is_multi_channel: weight_funcs = weight_funcs * 2 else: weight_funcs = (weight_funcs,) * 2 # Handle request for masking intead of using fill values use_masked_fill_value = False if fill_value is None: use_masked_fill_value = True fill_value = _get_fill_mask_value(new_data.dtype) # Resample based on kd-tree query result if resample_type == 'nn' or neighbours == 1: # Get nearest neighbour using array indexing index_mask = (index_array == input_size) new_index_array = np.where(index_mask, 0, index_array) result = new_data[new_index_array] result[index_mask] = fill_value else: # Calculate result using weighting. # Note: the code below has low readability in order # to avoid looping over numpy arrays # Get neighbours and masks of valid indices ch_neighbour_list = [] index_mask_list = [] for i in range(neighbours): # Iterate over number of neighbours # Make working copy neighbour index and # set out of bounds indices to zero index_ni = index_array[:, i].copy() index_mask_ni = (index_ni == input_size) index_ni[index_mask_ni] = 0 # Get channel data for the corresponing indices ch_ni = new_data[index_ni] ch_neighbour_list.append(ch_ni) index_mask_list.append(index_mask_ni) # Calculate weights weight_list = [] for i in range(neighbours): # Iterate over number of neighbours # Make working copy of neighbour distances and # set out of bounds distance to 1 in order to avoid numerical Inf distance = distance_array[:, i].copy() distance[index_mask_list[i]] = 1 if new_data.ndim > 1: # More than one channel in data set. # Calculate weights for each channel weights = [] num_weights = valid_output_index.sum() num_channels = new_data.shape[1] for j in range(num_channels): calc_weight = weight_funcs[j](distance) # Turn a scalar weight into a numpy array # (no effect if calc_weight already is an array) expanded_calc_weight = np.ones(num_weights) * calc_weight weights.append(expanded_calc_weight) # Collect weights for all channels for neighbour number weight_list.append(np.column_stack(weights)) else: # Only one channel weights = weight_funcs(distance) weight_list.append(weights) result = 0 norm = 0 count = 0 norm_sqr = 0 stddev = 0 # Calculate result for i in range(neighbours): # Iterate over number of neighbours # Find invalid indices to be masked of from calculation if new_data.ndim > 1: # More than one channel in data set. inv_index_mask = np.expand_dims( np.invert(index_mask_list[i]), axis=1) else: # Only one channel inv_index_mask = np.invert(index_mask_list[i]) # Aggregate result and norm weights_tmp = inv_index_mask * weight_list[i] result += weights_tmp * ch_neighbour_list[i] norm += weights_tmp # Normalize result and set fillvalue result_valid_index = (norm > 0) result[result_valid_index] /= norm[result_valid_index] if with_uncert: # Calculate uncertainties # 2. pass to calculate standard deviation for i in range(neighbours): # Iterate over number of neighbours # Find invalid indices to be masked of from calculation if new_data.ndim > 1: # More than one channel in data set. inv_index_mask = np.expand_dims( np.invert(index_mask_list[i]), axis=1) else: # Only one channel inv_index_mask = np.invert(index_mask_list[i]) # Aggregate stddev information weights_tmp = inv_index_mask * weight_list[i] count += inv_index_mask norm_sqr += weights_tmp ** 2 values = inv_index_mask * ch_neighbour_list[i] stddev += weights_tmp * (values - result) ** 2 # Calculate final stddev new_valid_index = (count > 1) v1 = norm[new_valid_index] v2 = norm_sqr[new_valid_index] stddev[new_valid_index] = np.sqrt( (v1 / (v1 ** 2 - v2)) * stddev[new_valid_index]) stddev[~new_valid_index] = np.NaN # Add fill values result[np.invert(result_valid_index)] = fill_value # Create full result if new_data.ndim > 1: # More than one channel output_raw_shape = ((output_size, new_data.shape[1])) else: # One channel output_raw_shape = output_size full_result = np.ones(output_raw_shape) * fill_value full_result[valid_output_index] = result result = full_result if with_uncert: # Add fill values for uncertainty full_stddev = np.ones(output_raw_shape) * np.nan full_count = np.zeros(output_raw_shape) full_stddev[valid_output_index] = stddev full_count[valid_output_index] = count stddev = full_stddev count = full_count stddev = stddev.reshape(output_shape) count = count.reshape(output_shape) if is_masked_data: # Ignore uncert computation of masks stddev = _remask_data(stddev, is_to_be_masked=False) count = _remask_data(count, is_to_be_masked=False) # Set masks for invalid stddev stddev = np.ma.array(stddev, mask=np.isnan(stddev)) # Reshape resampled data to correct shape result = result.reshape(output_shape) # Remap mask channels to create masked output if is_masked_data: result = _remask_data(result) # Create masking of fill values if use_masked_fill_value: result = np.ma.masked_equal(result, fill_value) # Set output data type to input data type if relevant if conserve_input_data_type: result = result.astype(input_data_type) if with_uncert: if np.ma.isMA(result): stddev = np.ma.array(stddev, mask=(result.mask | stddev.mask)) count = np.ma.array(count, mask=result.mask) return result, stddev, count else: return result def _get_fill_mask_value(data_dtype): """Returns the maximum value of dtype""" if issubclass(data_dtype.type, np.floating): fill_value = np.finfo(data_dtype.type).max elif issubclass(data_dtype.type, np.integer): fill_value = np.iinfo(data_dtype.type).max else: raise TypeError('Type %s is unsupported for masked fill values' % data_dtype.type) return fill_value def _remask_data(data, is_to_be_masked=True): """Interprets half the array as mask for the other half""" channels = data.shape[-1] if is_to_be_masked: mask = data[..., (channels // 2):] # All pixels affected by masked pixels are masked out mask = (mask != 0) data = np.ma.array(data[..., :(channels // 2)], mask=mask) else: data = data[..., :(channels // 2)] if data.shape[-1] == 1: data = data.reshape(data.shape[:-1]) return data pyresample-1.2.9/pyresample/plot.py000066400000000000000000000231351302372600000174120ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010-2015 # # Authors: # Esben S. Nielsen # Thomas Lavergne # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . from __future__ import absolute_import import numpy as np def ellps2axis(ellps_name): """Get semi-major and semi-minor axis from ellipsis definition Parameters --------- ellps_name : str Standard name of ellipsis Returns ------- (a, b) : semi-major and semi-minor axis """ ellps = {'helmert': {'a': 6378200.0, 'b': 6356818.1696278909}, 'intl': {'a': 6378388.0, 'b': 6356911.9461279465}, 'merit': {'a': 6378137.0, 'b': 6356752.2982159676}, 'wgs72': {'a': 6378135.0, 'b': 6356750.5200160937}, 'sphere': {'a': 6370997.0, 'b': 6370997.0}, 'clrk66': {'a': 6378206.4000000004, 'b': 6356583.7999999998}, 'nwl9d': {'a': 6378145.0, 'b': 6356759.7694886839}, 'lerch': {'a': 6378139.0, 'b': 6356754.2915103417}, 'evrstss': {'a': 6377298.5559999999, 'b': 6356097.5503008962}, 'evrst30': {'a': 6377276.3449999997, 'b': 6356075.4131402401}, 'mprts': {'a': 6397300.0, 'b': 6363806.2827225132}, 'krass': {'a': 6378245.0, 'b': 6356863.0187730473}, 'walbeck': {'a': 6376896.0, 'b': 6355834.8466999996}, 'kaula': {'a': 6378163.0, 'b': 6356776.9920869097}, 'wgs66': {'a': 6378145.0, 'b': 6356759.7694886839}, 'evrst56': {'a': 6377301.2429999998, 'b': 6356100.2283681016}, 'new_intl': {'a': 6378157.5, 'b': 6356772.2000000002}, 'airy': {'a': 6377563.3959999997, 'b': 6356256.9100000001}, 'bessel': {'a': 6377397.1550000003, 'b': 6356078.9628181886}, 'seasia': {'a': 6378155.0, 'b': 6356773.3205000004}, 'aust_sa': {'a': 6378160.0, 'b': 6356774.7191953054}, 'wgs84': {'a': 6378137.0, 'b': 6356752.3142451793}, 'hough': {'a': 6378270.0, 'b': 6356794.3434343431}, 'wgs60': {'a': 6378165.0, 'b': 6356783.2869594367}, 'engelis': {'a': 6378136.0499999998, 'b': 6356751.3227215428}, 'apl4.9': {'a': 6378137.0, 'b': 6356751.796311819}, 'andrae': {'a': 6377104.4299999997, 'b': 6355847.4152333336}, 'sgs85': {'a': 6378136.0, 'b': 6356751.301568781}, 'delmbr': {'a': 6376428.0, 'b': 6355957.9261637237}, 'fschr60m': {'a': 6378155.0, 'b': 6356773.3204827355}, 'iau76': {'a': 6378140.0, 'b': 6356755.2881575283}, 'plessis': {'a': 6376523.0, 'b': 6355863.0}, 'cpm': {'a': 6375738.7000000002, 'b': 6356666.221912113}, 'fschr68': {'a': 6378150.0, 'b': 6356768.3372443849}, 'mod_airy': {'a': 6377340.1890000002, 'b': 6356034.4460000005}, 'grs80': {'a': 6378137.0, 'b': 6356752.3141403561}, 'bess_nam': {'a': 6377483.8650000002, 'b': 6356165.3829663256}, 'fschr60': {'a': 6378166.0, 'b': 6356784.2836071067}, 'clrk80': {'a': 6378249.1449999996, 'b': 6356514.9658284895}, 'evrst69': {'a': 6377295.6639999999, 'b': 6356094.6679152036}, 'grs67': {'a': 6378160.0, 'b': 6356774.5160907144}, 'evrst48': {'a': 6377304.0630000001, 'b': 6356103.0389931547}} try: ellps_axis = ellps[ellps_name.lower()] a = ellps_axis['a'] b = ellps_axis['b'] except KeyError as e: raise ValueError(('Could not determine semi-major and semi-minor axis ' 'of specified ellipsis %s') % ellps_name) return a, b def area_def2basemap(area_def, **kwargs): """Get Basemap object from AreaDefinition Parameters --------- area_def : object geometry.AreaDefinition object \*\*kwargs: Keyword arguments Additional initialization arguments for Basemap Returns ------- bmap : Basemap object """ from mpl_toolkits.basemap import Basemap try: a, b = ellps2axis(area_def.proj_dict['ellps']) rsphere = (a, b) except KeyError: try: a = float(area_def.proj_dict['a']) try: b = float(area_def.proj_dict['b']) rsphere = (a, b) except KeyError: rsphere = a except KeyError: # Default to WGS84 ellipsoid a, b = ellps2axis('wgs84') rsphere = (a, b) # Add projection specific basemap args to args passed to function basemap_args = kwargs basemap_args['rsphere'] = rsphere if area_def.proj_dict['proj'] in ('ortho', 'geos', 'nsper'): llcrnrx, llcrnry, urcrnrx, urcrnry = area_def.area_extent basemap_args['llcrnrx'] = llcrnrx basemap_args['llcrnry'] = llcrnry basemap_args['urcrnrx'] = urcrnrx basemap_args['urcrnry'] = urcrnry else: llcrnrlon, llcrnrlat, urcrnrlon, urcrnrlat = area_def.area_extent_ll basemap_args['llcrnrlon'] = llcrnrlon basemap_args['llcrnrlat'] = llcrnrlat basemap_args['urcrnrlon'] = urcrnrlon basemap_args['urcrnrlat'] = urcrnrlat if area_def.proj_dict['proj'] == 'eqc': basemap_args['projection'] = 'cyl' else: basemap_args['projection'] = area_def.proj_dict['proj'] # Try adding potentially remaining args for key in ('lon_0', 'lat_0', 'lon_1', 'lat_1', 'lon_2', 'lat_2', 'lat_ts'): try: basemap_args[key] = float(area_def.proj_dict[key]) except KeyError: pass return Basemap(**basemap_args) def _get_quicklook(area_def, data, vmin=None, vmax=None, label='Variable (units)', num_meridians=45, num_parallels=10, coast_res='c', cmap='jet'): """Get default Basemap matplotlib plot """ if area_def.shape != data.shape: raise ValueError('area_def shape %s does not match data shape %s' % (list(area_def.shape), list(data.shape))) import matplotlib.pyplot as plt bmap = area_def2basemap(area_def, resolution=coast_res) bmap.drawcoastlines() if num_meridians > 0: bmap.drawmeridians(np.arange(-180, 180, num_meridians)) if num_parallels > 0: bmap.drawparallels(np.arange(-90, 90, num_parallels)) if not (np.ma.isMaskedArray(data) and data.mask.all()): col = bmap.imshow(data, origin='upper', vmin=vmin, vmax=vmax, cmap=cmap) plt.colorbar(col, shrink=0.5, pad=0.05).set_label(label) return plt def show_quicklook(area_def, data, vmin=None, vmax=None, label='Variable (units)', num_meridians=45, num_parallels=10, coast_res='c', cmap='jet'): """Display default quicklook plot Parameters --------- area_def : object geometry.AreaDefinition object data : numpy array | numpy masked array 2D array matching area_def. Use masked array for transparent values vmin : float, optional Min value for luminescence scaling vmax : float, optional Max value for luminescence scaling label : str, optional Label for data num_meridians : int, optional Number of meridians to plot on the globe num_parallels : int, optional Number of parallels to plot on the globe coast_res : {'c', 'l', 'i', 'h', 'f'}, optional Resolution of coastlines Returns ------- bmap : Basemap object """ plt = _get_quicklook(area_def, data, vmin=vmin, vmax=vmax, label=label, num_meridians=num_meridians, num_parallels=num_parallels, coast_res=coast_res, cmap=cmap) plt.show() plt.close() def save_quicklook(filename, area_def, data, vmin=None, vmax=None, label='Variable (units)', num_meridians=45, num_parallels=10, coast_res='c', backend='AGG', cmap='jet'): """Display default quicklook plot Parameters ---------- filename : str path to output file area_def : object geometry.AreaDefinition object data : numpy array | numpy masked array 2D array matching area_def. Use masked array for transparent values vmin : float, optional Min value for luminescence scaling vmax : float, optional Max value for luminescence scaling label : str, optional Label for data num_meridians : int, optional Number of meridians to plot on the globe num_parallels : int, optional Number of parallels to plot on the globe coast_res : {'c', 'l', 'i', 'h', 'f'}, optional Resolution of coastlines backend : str, optional matplotlib backend to use' """ import matplotlib matplotlib.use(backend, warn=False) plt = _get_quicklook(area_def, data, vmin=vmin, vmax=vmax, label=label, num_meridians=num_meridians, num_parallels=num_parallels, coast_res=coast_res) plt.savefig(filename, bbox_inches='tight') plt.close() pyresample-1.2.9/pyresample/spherical_geometry.py000066400000000000000000000335551302372600000223300ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2015 Martin Raspaud # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """Classes for spherical geometry operations""" from __future__ import absolute_import import math import numpy as np try: range = xrange except NameError: pass EPSILON = 0.0000001 # FIXME: this has not been tested with R != 1 class Coordinate(object): """Point on earth in terms of lat and lon. """ lat = None lon = None x__ = None y__ = None z__ = None def __init__(self, lon=None, lat=None, x__=None, y__=None, z__=None, R__=1): self.R__ = R__ if lat is not None and lon is not None: if not(-180 <= lon <= 180 and -90 <= lat <= 90): raise ValueError('Illegal (lon, lat) coordinates: (%s, %s)' % (lon, lat)) self.lat = math.radians(lat) self.lon = math.radians(lon) self._update_cart() else: self.x__ = x__ self.y__ = y__ self.z__ = z__ self._update_lonlat() def _update_cart(self): """Convert lon/lat to cartesian coordinates. """ self.x__ = math.cos(self.lat) * math.cos(self.lon) self.y__ = math.cos(self.lat) * math.sin(self.lon) self.z__ = math.sin(self.lat) def _update_lonlat(self): """Convert cartesian to lon/lat. """ self.lat = math.degrees(math.asin(self.z__ / self.R__)) self.lon = math.degrees(math.atan2(self.y__, self.x__)) def __ne__(self, other): if(abs(self.lat - other.lat) < EPSILON and abs(self.lon - other.lon) < EPSILON): return 0 else: return 1 def __eq__(self, other): return not self.__ne__(other) def __str__(self): return str((math.degrees(self.lon), math.degrees(self.lat))) def __repr__(self): return str((math.degrees(self.lon), math.degrees(self.lat))) def cross2cart(self, point): """Compute the cross product, and convert to cartesian coordinates (assuming radius 1). """ lat1 = self.lat lon1 = self.lon lat2 = point.lat lon2 = point.lon res = Coordinate( x__=(math.sin(lat1 - lat2) * math.sin((lon1 + lon2) / 2) * math.cos((lon1 - lon2) / 2) - math.sin(lat1 + lat2) * math.cos((lon1 + lon2) / 2) * math.sin((lon1 - lon2) / 2)), y__=(math.sin(lat1 - lat2) * math.cos((lon1 + lon2) / 2) * math.cos((lon1 - lon2) / 2) + math.sin(lat1 + lat2) * math.sin((lon1 + lon2) / 2) * math.sin((lon1 - lon2) / 2)), z__=(math.cos(lat1) * math.cos(lat2) * math.sin(lon1 - lon2))) return res def distance(self, point): """Vincenty formula. """ dlambda = self.lon - point.lon num = ((math.cos(point.lat) * math.sin(dlambda)) ** 2 + (math.cos(self.lat) * math.sin(point.lat) - math.sin(self.lat) * math.cos(point.lat) * math.cos(dlambda)) ** 2) den = (math.sin(self.lat) * math.sin(point.lat) + math.cos(self.lat) * math.cos(point.lat) * math.cos(dlambda)) return math.atan2(math.sqrt(num), den) def norm(self): """Return the norm of the vector. """ return math.sqrt(self.x__ ** 2 + self.y__ ** 2 + self.z__ ** 2) def normalize(self): """normalize the vector. """ norm = self.norm() self.x__ /= norm self.y__ /= norm self.z__ /= norm return self def cross(self, point): """cross product with another vector. """ x__ = self.y__ * point.z__ - self.z__ * point.y__ y__ = self.z__ * point.x__ - self.x__ * point.z__ z__ = self.x__ * point.y__ - self.y__ * point.x__ return Coordinate(x__=x__, y__=y__, z__=z__) def dot(self, point): """dot product with another vector. """ return (self.x__ * point.x__ + self.y__ * point.y__ + self.z__ * point.z__) class Arc(object): """An arc of the great circle between two points. """ start = None end = None def __init__(self, start, end): self.start, self.end = start, end def center_angle(self): """Angle of an arc at the center of the sphere. """ val = (math.cos(self.start.lat - self.end.lat) + math.cos(self.start.lon - self.end.lon) - 1) if val > 1: val = 1 elif val < -1: val = -1 return math.acos(val) def __eq__(self, other): if(self.start == other.start and self.end == other.end): return 1 return 0 def __ne__(self, other): return not self.__eq__(other) def __str__(self): return str((str(self.start), str(self.end))) def angle(self, other_arc, snap=True): """Oriented angle between two arcs. Parameters ---------- other_arc : Arc snap : boolean Snap small angles to 0. Allows for detecting colinearity. Disable snapping when calculating polygon areas as it might lead to negative area values. """ if self.start == other_arc.start: a__ = self.start b__ = self.end c__ = other_arc.end elif self.start == other_arc.end: a__ = self.start b__ = self.end c__ = other_arc.start elif self.end == other_arc.end: a__ = self.end b__ = self.start c__ = other_arc.start elif self.end == other_arc.start: a__ = self.end b__ = self.start c__ = other_arc.end else: raise ValueError("No common point in angle computation.") ua_ = a__.cross(b__) ub_ = a__.cross(c__) val = ua_.dot(ub_) / (ua_.norm() * ub_.norm()) if snap: if abs(val - 1) < EPSILON: angle = 0 elif abs(val + 1) < EPSILON: angle = math.pi else: angle = math.acos(val) else: if 0 <= val - 1 < EPSILON: angle = 0 elif -EPSILON < val + 1 <= 0: angle = math.pi else: angle = math.acos(val) n__ = ua_.normalize() if n__.dot(c__) > 0: return -angle else: return angle def intersections(self, other_arc): """Gives the two intersections of the greats circles defined by the current arc and *other_arc*. """ if self.end.lon - self.start.lon > math.pi: self.end.lon -= 2 * math.pi if other_arc.end.lon - other_arc.start.lon > math.pi: other_arc.end.lon -= 2 * math.pi if self.end.lon - self.start.lon < -math.pi: self.end.lon += 2 * math.pi if other_arc.end.lon - other_arc.start.lon < -math.pi: other_arc.end.lon += 2 * math.pi ea_ = self.start.cross2cart(self.end).normalize() eb_ = other_arc.start.cross2cart(other_arc.end).normalize() cross = ea_.cross(eb_) lat = math.atan2(cross.z__, math.sqrt(cross.x__ ** 2 + cross.y__ ** 2)) lon = math.atan2(-cross.y__, cross.x__) return (Coordinate(math.degrees(lon), math.degrees(lat)), Coordinate(math.degrees(modpi(lon + math.pi)), math.degrees(-lat))) def intersects(self, other_arc): """Says if two arcs defined by the current arc and the *other_arc* intersect. An arc is defined as the shortest tracks between two points. """ return bool(self.intersection(other_arc)) def intersection(self, other_arc): """Says where, if two arcs defined by the current arc and the *other_arc* intersect. An arc is defined as the shortest tracks between two points. """ for i in self.intersections(other_arc): a__ = self.start b__ = self.end c__ = other_arc.start d__ = other_arc.end ab_ = a__.distance(b__) cd_ = c__.distance(d__) if(abs(a__.distance(i) + b__.distance(i) - ab_) < EPSILON and abs(c__.distance(i) + d__.distance(i) - cd_) < EPSILON): return i return None def modpi(val): """Puts *val* between -pi and pi. """ return (val + math.pi) % (2 * math.pi) - math.pi def get_polygon_area(corners): """Get the area of the convex area defined by *corners*. """ # We assume the earth is spherical !!! # Should be the radius of the earth at the observed position R = 1 c1_ = corners[0] area = 0 for idx in range(1, len(corners) - 1): b1_ = Arc(c1_, corners[idx]) b2_ = Arc(c1_, corners[idx + 1]) b3_ = Arc(corners[idx], corners[idx + 1]) e__ = (abs(b1_.angle(b2_, snap=False)) + abs(b2_.angle(b3_, snap=False)) + abs(b3_.angle(b1_, snap=False))) area += e__ - math.pi return R ** 2 * area def get_intersections(b__, boundaries): """Get the intersections of *b__* with *boundaries*. Returns both the intersection coordinates and the concerned boundaries. """ intersections = [] bounds = [] for other_b in boundaries: inter = b__.intersection(other_b) if inter is not None: intersections.append(inter) bounds.append(other_b) return intersections, bounds def get_first_intersection(b__, boundaries): """Get the first intersection on *b__* with *boundaries*. """ intersections, bounds = get_intersections(b__, boundaries) del bounds dists = np.array([b__.start.distance(p__) for p__ in intersections]) indices = dists.argsort() if len(intersections) > 0: return intersections[indices[0]] return None def get_next_intersection(p__, b__, boundaries): """Get the next intersection from the intersection of arcs *p__* and *b__* along segment *b__* with *boundaries*. """ new_b = Arc(p__, b__.end) intersections, bounds = get_intersections(new_b, boundaries) dists = np.array([b__.start.distance(p2) for p2 in intersections]) indices = dists.argsort() if len(intersections) > 0 and intersections[indices[0]] != p__: return intersections[indices[0]], bounds[indices[0]] elif len(intersections) > 1: return intersections[indices[1]], bounds[indices[1]] return None, None def point_inside(point, corners): """Is a point inside the 4 corners ? This uses great circle arcs as area boundaries. """ arc1 = Arc(corners[0], corners[1]) arc2 = Arc(corners[1], corners[2]) arc3 = Arc(corners[2], corners[3]) arc4 = Arc(corners[3], corners[0]) arc5 = Arc(corners[1], point) arc6 = Arc(corners[3], point) angle1 = modpi(arc1.angle(arc2)) angle1bis = modpi(arc1.angle(arc5)) angle2 = modpi(arc3.angle(arc4)) angle2bis = modpi(arc3.angle(arc6)) return (np.sign(angle1) == np.sign(angle1bis) and abs(angle1) > abs(angle1bis) and np.sign(angle2) == np.sign(angle2bis) and abs(angle2) > abs(angle2bis)) def intersection_polygon(area_corners, segment_corners): """Get the intersection polygon between two areas. """ area_boundaries = [Arc(area_corners[0], area_corners[1]), Arc(area_corners[1], area_corners[2]), Arc(area_corners[2], area_corners[3]), Arc(area_corners[3], area_corners[0])] segment_boundaries = [Arc(segment_corners[0], segment_corners[1]), Arc(segment_corners[1], segment_corners[2]), Arc(segment_corners[2], segment_corners[3]), Arc(segment_corners[3], segment_corners[0])] angle1 = area_boundaries[0].angle(area_boundaries[1]) angle2 = segment_boundaries[0].angle(segment_boundaries[1]) if np.sign(angle1) != np.sign(angle2): segment_corners.reverse() segment_boundaries = [Arc(segment_corners[0], segment_corners[1]), Arc(segment_corners[1], segment_corners[2]), Arc(segment_corners[2], segment_corners[3]), Arc(segment_corners[3], segment_corners[0])] poly = [] boundaries = area_boundaries other_boundaries = segment_boundaries b__ = None for b__ in boundaries: if point_inside(b__.start, segment_corners): poly.append(b__.start) break else: inter = get_first_intersection(b__, other_boundaries) if inter is not None: poly.append(inter) break if len(poly) == 0: return None while len(poly) < 2 or poly[0] != poly[-1]: inter, b2_ = get_next_intersection(poly[-1], b__, other_boundaries) if inter is None: poly.append(b__.end) idx = (boundaries.index(b__) + 1) % len(boundaries) b__ = boundaries[idx] else: poly.append(inter) b__ = b2_ boundaries, other_boundaries = other_boundaries, boundaries return poly[:-1] pyresample-1.2.9/pyresample/test/000077500000000000000000000000001302372600000170355ustar00rootroot00000000000000pyresample-1.2.9/pyresample/test/__init__.py000066400000000000000000000032421302372600000211470ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2014, 2015 Martin Raspaud # Author(s): # Martin Raspaud # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """The test base. """ from pyresample.test import ( test_geometry, test_grid, test_image, test_kd_tree, test_plot, test_spherical_geometry, test_swath, test_utils, test_ewa_ll2cr, test_ewa_fornav, ) import unittest def suite(): """The global test suite. """ mysuite = unittest.TestSuite() # Use the unittests also mysuite.addTests(test_geometry.suite()) mysuite.addTests(test_grid.suite()) mysuite.addTests(test_image.suite()) mysuite.addTests(test_kd_tree.suite()) mysuite.addTests(test_plot.suite()) mysuite.addTests(test_spherical_geometry.suite()) mysuite.addTests(test_swath.suite()) mysuite.addTests(test_utils.suite()) mysuite.addTests(test_ewa_ll2cr.suite()) mysuite.addTests(test_ewa_fornav.suite()) return mysuite def load_tests(loader, tests, pattern): return suite() pyresample-1.2.9/pyresample/test/test_ewa_fornav.py000066400000000000000000000126601302372600000226020ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2016 # Author(s): # David Hoese # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # You should have received a copy of the GNU General Public License # along with this program. If not, see . """Test EWA fornav module. """ import sys import logging import numpy as np if sys.version_info < (2, 7): import unittest2 as unittest else: import unittest LOG = logging.getLogger(__name__) class TestFornav(unittest.TestCase): def test_fornav_swath_larger(self): """Test that a swath larger than the output grid fills the entire grid. """ from pyresample.ewa import _fornav swath_shape = (1600, 3200) data_type = np.float32 # Create a fake row and cols array rows = np.empty(swath_shape, dtype=np.float32) rows[:] = np.linspace(-500, 2500, 1600)[:, None] cols = np.empty(swath_shape, dtype=np.float32) cols[:] = np.linspace(-2500, 1500, 3200) rows_per_scan = 16 # Create a fake data swath data = np.ones(swath_shape, dtype=data_type) out = np.empty((1000, 1000), dtype=data_type) grid_points_covered = _fornav.fornav_wrapper(cols, rows, (data,), (out,), np.nan, np.nan, rows_per_scan) one_grid_points_covered = grid_points_covered[0] # The swath was larger than the grid, all of the grid should have # been covered by swath pixels self.assertEqual(one_grid_points_covered, out.size, msg="Not all grid pixels were filled") # The swath was all 1s so there shouldn't be any non-1 values in the # output except outside the swath self.assertTrue(((out == 1) | np.isnan(out)).all(), msg="Unexpected interpolation values were returned") def test_fornav_swath_smaller(self): """Test that a swath smaller than the output grid is entirely used. """ from pyresample.ewa import _fornav swath_shape = (1600, 3200) data_type = np.float32 # Create a fake row and cols array rows = np.empty(swath_shape, dtype=np.float32) rows[:] = np.linspace(500, 800, 1600)[:, None] cols = np.empty(swath_shape, dtype=np.float32) cols[:] = np.linspace(200, 600, 3200) rows_per_scan = 16 # Create a fake data swath data = np.ones(swath_shape, dtype=data_type) out = np.empty((1000, 1000), dtype=data_type) grid_points_covered = _fornav.fornav_wrapper(cols, rows, (data,), (out,), np.nan, np.nan, rows_per_scan) one_grid_points_covered = grid_points_covered[0] # The swath was smaller than the grid, make sure its whole area # was covered (percentage of grid rows/cols to overall size) self.assertAlmostEqual(one_grid_points_covered / float(out.size), 0.12, 2, msg="Not all input swath pixels were used") # The swath was all 1s so there shouldn't be any non-1 values in the # output except outside the swath self.assertTrue(((out == 1) | np.isnan(out)).all(), msg="Unexpected interpolation values were returned") def test_fornav_swath_smaller_int8(self): """Test that a swath smaller than the output grid is entirely used. """ from pyresample.ewa import _fornav swath_shape = (1600, 3200) data_type = np.int8 # Create a fake row and cols array rows = np.empty(swath_shape, dtype=np.float32) rows[:] = np.linspace(500, 800, 1600)[:, None] cols = np.empty(swath_shape, dtype=np.float32) cols[:] = np.linspace(200, 600, 3200) rows_per_scan = 16 # Create a fake data swath data = np.ones(swath_shape, dtype=data_type) out = np.empty((1000, 1000), dtype=data_type) grid_points_covered = _fornav.fornav_wrapper(cols, rows, (data,), (out,), -128, -128, rows_per_scan) one_grid_points_covered = grid_points_covered[0] # The swath was smaller than the grid, make sure its whole area # was covered (percentage of grid rows/cols to overall size) self.assertAlmostEqual(one_grid_points_covered / float(out.size), 0.12, 2, msg="Not all input swath pixels were used") # The swath was all 1s so there shouldn't be any non-1 values in the # output except outside the swath # import ipdb; ipdb.set_trace() self.assertTrue(((out == 1) | (out == -128)).all(), msg="Unexpected interpolation values were returned") def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(TestFornav)) return mysuite if __name__ == '__main__': unittest.main() pyresample-1.2.9/pyresample/test/test_ewa_ll2cr.py000066400000000000000000000176211302372600000223270ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2016 # Author(s): # David Hoese # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # You should have received a copy of the GNU General Public License # along with this program. If not, see . """Test the EWA ll2cr code. """ import sys import logging import numpy as np if sys.version_info < (2, 7): import unittest2 as unittest else: import unittest LOG = logging.getLogger(__name__) def create_test_longitude(start, stop, shape, twist_factor=0.0, dtype=np.float32): if start > stop: stop += 360.0 lon_row = np.linspace(start, stop, num=shape[1]).astype(dtype) twist_array = np.arange(shape[0]).reshape((shape[0], 1)) * twist_factor lon_array = np.repeat([lon_row], shape[0], axis=0) lon_array += twist_array if stop > 360.0: lon_array[lon_array > 360.0] -= 360 return lon_array def create_test_latitude(start, stop, shape, twist_factor=0.0, dtype=np.float32): lat_col = np.linspace(start, stop, num=shape[0]).astype(dtype).reshape((shape[0], 1)) twist_array = np.arange(shape[1]) * twist_factor lat_array = np.repeat(lat_col, shape[1], axis=1) lat_array += twist_array return lat_array dynamic_wgs84 = { "grid_name": "test_wgs84_fit", "origin_x": None, "origin_y": None, "width": None, "height": None, "cell_width": 0.0057, "cell_height": -0.0057, "proj4_definition": "+proj=latlong +datum=WGS84 +ellps=WGS84 +no_defs", } static_lcc = { "grid_name": "test_lcc", "origin_x": -1950510.636800, "origin_y": 4368587.226913, "width": 5120, "height": 5120, "cell_width": 1015.9, "cell_height": -1015.9, "proj4_definition": "+proj=lcc +a=6371200 +b=6371200 +lat_0=25 +lat_1=25 +lon_0=-95 +units=m +no_defs", } class TestLL2CRStatic(unittest.TestCase): def test_lcc_basic1(self): from pyresample.ewa import _ll2cr lon_arr = create_test_longitude(-95.0, -75.0, (50, 100), dtype=np.float64) lat_arr = create_test_latitude(18.0, 40.0, (50, 100), dtype=np.float64) grid_info = static_lcc.copy() fill_in = np.nan proj_str = grid_info["proj4_definition"] cw = grid_info["cell_width"] ch = grid_info["cell_height"] ox = grid_info["origin_x"] oy = grid_info["origin_y"] w = grid_info["width"] h = grid_info["height"] points_in_grid = _ll2cr.ll2cr_static(lon_arr, lat_arr, fill_in, proj_str, cw, ch, w, h, ox, oy) self.assertEqual(points_in_grid, lon_arr.size, "all these test points should fall in this grid") def test_lcc_fail1(self): from pyresample.ewa import _ll2cr lon_arr = create_test_longitude(-15.0, 15.0, (50, 100), dtype=np.float64) lat_arr = create_test_latitude(18.0, 40.0, (50, 100), dtype=np.float64) grid_info = static_lcc.copy() fill_in = np.nan proj_str = grid_info["proj4_definition"] cw = grid_info["cell_width"] ch = grid_info["cell_height"] ox = grid_info["origin_x"] oy = grid_info["origin_y"] w = grid_info["width"] h = grid_info["height"] points_in_grid = _ll2cr.ll2cr_static(lon_arr, lat_arr, fill_in, proj_str, cw, ch, w, h, ox, oy) self.assertEqual(points_in_grid, 0, "none of these test points should fall in this grid") class TestLL2CRDynamic(unittest.TestCase): def test_latlong_basic1(self): from pyresample.ewa import _ll2cr lon_arr = create_test_longitude(-95.0, -75.0, (50, 100), dtype=np.float64) lat_arr = create_test_latitude(15.0, 30.0, (50, 100), dtype=np.float64) grid_info = dynamic_wgs84.copy() fill_in = np.nan proj_str = grid_info["proj4_definition"] cw = grid_info["cell_width"] ch = grid_info["cell_height"] ox = grid_info["origin_x"] oy = grid_info["origin_y"] w = grid_info["width"] h = grid_info["height"] points_in_grid, lon_res, lat_res, ox, oy, w, h = _ll2cr.ll2cr_dynamic(lon_arr, lat_arr, fill_in, proj_str, cw, ch, w, h, ox, oy) self.assertEqual(points_in_grid, lon_arr.size, "all points should be contained in a dynamic grid") self.assertIs(lon_arr, lon_res) self.assertIs(lat_arr, lat_res) self.assertEqual(lon_arr[0, 0], 0, "ll2cr returned the wrong result for a dynamic latlong grid") self.assertEqual(lat_arr[-1, 0], 0, "ll2cr returned the wrong result for a dynamic latlong grid") def test_latlong_basic2(self): from pyresample.ewa import _ll2cr lon_arr = create_test_longitude(-95.0, -75.0, (50, 100), twist_factor=0.6, dtype=np.float64) lat_arr = create_test_latitude(15.0, 30.0, (50, 100), twist_factor=-0.1, dtype=np.float64) grid_info = dynamic_wgs84.copy() fill_in = np.nan proj_str = grid_info["proj4_definition"] cw = grid_info["cell_width"] ch = grid_info["cell_height"] ox = grid_info["origin_x"] oy = grid_info["origin_y"] w = grid_info["width"] h = grid_info["height"] points_in_grid, lon_res, lat_res, ox, oy, w, h = _ll2cr.ll2cr_dynamic(lon_arr, lat_arr, fill_in, proj_str, cw, ch, w, h, ox, oy) self.assertEqual(points_in_grid, lon_arr.size, "all points should be contained in a dynamic grid") self.assertIs(lon_arr, lon_res) self.assertIs(lat_arr, lat_res) self.assertEqual(lon_arr[0, 0], 0, "ll2cr returned the wrong result for a dynamic latlong grid") self.assertEqual(lat_arr[-1, 0], 0, "ll2cr returned the wrong result for a dynamic latlong grid") def test_latlong_dateline1(self): from pyresample.ewa import _ll2cr lon_arr = create_test_longitude(165.0, -165.0, (50, 100), twist_factor=0.6, dtype=np.float64) lat_arr = create_test_latitude(15.0, 30.0, (50, 100), twist_factor=-0.1, dtype=np.float64) grid_info = dynamic_wgs84.copy() fill_in = np.nan proj_str = grid_info["proj4_definition"] cw = grid_info["cell_width"] ch = grid_info["cell_height"] ox = grid_info["origin_x"] oy = grid_info["origin_y"] w = grid_info["width"] h = grid_info["height"] points_in_grid, lon_res, lat_res, ox, oy, w, h = _ll2cr.ll2cr_dynamic(lon_arr, lat_arr, fill_in, proj_str, cw, ch, w, h, ox, oy) self.assertEqual(points_in_grid, lon_arr.size, "all points should be contained in a dynamic grid") self.assertIs(lon_arr, lon_res) self.assertIs(lat_arr, lat_res) self.assertEqual(lon_arr[0, 0], 0, "ll2cr returned the wrong result for a dynamic latlong grid") self.assertEqual(lat_arr[-1, 0], 0, "ll2cr returned the wrong result for a dynamic latlong grid") self.assertTrue(np.all(np.diff(lon_arr[0]) >= 0), "ll2cr didn't return monotonic columns over the dateline") def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(TestLL2CRStatic)) mysuite.addTest(loader.loadTestsFromTestCase(TestLL2CRDynamic)) return mysuite if __name__ == '__main__': unittest.main() pyresample-1.2.9/pyresample/test/test_files/000077500000000000000000000000001302372600000211765ustar00rootroot00000000000000pyresample-1.2.9/pyresample/test/test_files/areas.cfg000066400000000000000000000020241302372600000227500ustar00rootroot00000000000000REGION: ease_sh { NAME: Antarctic EASE grid PCS_ID: ease_sh PCS_DEF: proj=laea, lat_0=-90, lon_0=0, a=6371228.0, units=m XSIZE: 425 YSIZE: 425 AREA_EXTENT: (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) }; REGION: ease_nh { NAME: Arctic EASE grid PCS_ID: ease_nh PCS_DEF: proj=laea, lat_0=90, lon_0=0, a=6371228.0, units=m XSIZE: 425 YSIZE: 425 AREA_EXTENT: (-5326849.0625,-5326849.0625,5326849.0625,5326849.0625) }; REGION: pc_world { NAME: Plate Carree world map PCS_ID: pc_world 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as unittest else: import unittest class Test(unittest.TestCase): """Unit testing the geometry and geo_filter modules""" def assert_raises(self, exception, call_able, *args): """assertRaises() has changed from py2.6 to 2.7! Here is an attempt to cover both""" import sys if sys.version_info < (2, 7): self.assertRaises(exception, call_able, *args) else: with self.assertRaises(exception): call_able(*args) def test_lonlat_precomp(self): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) lons, lats = area_def.get_lonlats() area_def2 = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001], lons=lons, lats=lats) lon, lat = area_def.get_lonlat(400, 400) self.assertAlmostEqual(lon, 5.5028467120975835, msg='lon retrieval from precomputated grid failed') self.assertAlmostEqual(lat, 52.566998432390619, msg='lat retrieval from precomputated grid failed') def test_cartesian(self): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) cart_coords = area_def.get_cartesian_coords() exp = 5872039989466.8457031 self.assertTrue((cart_coords.sum() - exp) < 1e-7 * exp, msg='Calculation of cartesian coordinates failed') def test_base_lat_invalid(self): lons = np.arange(-135., +135, 20.) lats = np.ones_like(lons) * 70. lats[0] = -95 lats[1] = +95 self.assertRaises( ValueError, geometry.BaseDefinition, lons=lons, lats=lats) def test_base_lon_wrapping(self): lons1 = np.arange(-135., +135, 50.) lats = np.ones_like(lons1) * 70. with catch_warnings() as w1: base_def1 = geometry.BaseDefinition(lons1, lats) self.assertFalse( len(w1) != 0, 'Got warning <%s>, but was not expecting one' % w1) lons2 = np.where(lons1 < 0, lons1 + 360, lons1) with catch_warnings() as w2: base_def2 = geometry.BaseDefinition(lons2, lats) self.assertFalse( len(w2) != 1, 'Failed to trigger a warning on longitude wrapping') self.assertFalse(('-180:+180' not in str(w2[0].message)), 'Failed to trigger correct warning about longitude wrapping') self.assertFalse( base_def1 != base_def2, 'longitude wrapping to [-180:+180] did not work') with catch_warnings() as w3: base_def3 = geometry.BaseDefinition(None, None) self.assertFalse( len(w3) != 0, 'Got warning <%s>, but was not expecting one' % w3) self.assert_raises(ValueError, base_def3.get_lonlats) def test_base_type(self): lons1 = np.arange(-135., +135, 50.) lats = np.ones_like(lons1) * 70. # Test dtype is preserved without longitude wrapping basedef = geometry.BaseDefinition(lons1, lats) lons, _ = basedef.get_lonlats() self.assertEqual(lons.dtype, lons1.dtype, "BaseDefinition did not maintain dtype of longitudes (in:%s out:%s)" % (lons1.dtype, lons.dtype,)) lons1_ints = lons1.astype('int') basedef = geometry.BaseDefinition(lons1_ints, lats) lons, _ = basedef.get_lonlats() self.assertEqual(lons.dtype, lons1_ints.dtype, "BaseDefinition did not maintain dtype of longitudes (in:%s out:%s)" % (lons1_ints.dtype, lons.dtype,)) # Test dtype is preserved with automatic longitude wrapping lons2 = np.where(lons1 < 0, lons1 + 360, lons1) with catch_warnings() as w: basedef = geometry.BaseDefinition(lons2, lats) lons, _ = basedef.get_lonlats() self.assertEqual(lons.dtype, lons2.dtype, "BaseDefinition did not maintain dtype of longitudes (in:%s out:%s)" % (lons2.dtype, lons.dtype,)) lons2_ints = lons2.astype('int') with catch_warnings() as w: basedef = geometry.BaseDefinition(lons2_ints, lats) lons, _ = basedef.get_lonlats() self.assertEqual(lons.dtype, lons2_ints.dtype, "BaseDefinition did not maintain dtype of longitudes (in:%s out:%s)" % (lons2_ints.dtype, lons.dtype,)) def test_swath(self): lons1 = np.fromfunction(lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats1 = np.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons1, lats1) lons2, lats2 = swath_def.get_lonlats() self.assertFalse(id(lons1) != id(lons2) or id(lats1) != id(lats2), msg='Caching of swath coordinates failed') def test_swath_wrap(self): lons1 = np.fromfunction(lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats1 = np.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) lons1 += 180. with catch_warnings() as w1: swath_def = geometry.BaseDefinition(lons1, lats1) self.assertFalse( len(w1) != 1, 'Failed to trigger a warning on longitude wrapping') self.assertFalse(('-180:+180' not in str(w1[0].message)), 'Failed to trigger correct warning about longitude wrapping') lons2, lats2 = swath_def.get_lonlats() self.assertTrue(id(lons1) != id(lons2), msg='Caching of swath coordinates failed with longitude wrapping') self.assertTrue(lons2.min() > -180 and lons2.max() < 180, 'Wrapping of longitudes failed for SwathDefinition') def test_area_equal(self): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) area_def2 = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) self.assertFalse( area_def != area_def2, 'area_defs are not equal as expected') def test_not_area_equal(self): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) msg_area = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', 'msg_full', {'a': '6378169.0', 'b': '6356584.0', 'h': '35785831.0', 'lon_0': '0', 'proj': 'geos'}, 3712, 3712, [-5568742.4000000004, -5568742.4000000004, 5568742.4000000004, 5568742.4000000004] ) self.assertFalse( area_def == msg_area, 'area_defs are not expected to be equal') def test_swath_equal(self): lons = np.array([1.2, 1.3, 1.4, 1.5]) lats = np.array([65.9, 65.86, 65.82, 65.78]) swath_def = geometry.SwathDefinition(lons, lats) swath_def2 = geometry.SwathDefinition(lons, lats) self.assertFalse( swath_def != swath_def2, 'swath_defs are not equal as expected') def test_swath_not_equal(self): lats1 = np.array([65.9, 65.86, 65.82, 65.78]) lons = np.array([1.2, 1.3, 1.4, 1.5]) lats2 = np.array([65.91, 65.85, 65.80, 65.75]) swath_def = geometry.SwathDefinition(lons, lats1) swath_def2 = geometry.SwathDefinition(lons, lats2) self.assertFalse( swath_def == swath_def2, 'swath_defs are not expected to be equal') def test_swath_equal_area(self): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) swath_def = geometry.SwathDefinition(*area_def.get_lonlats()) self.assertFalse( swath_def != area_def, "swath_def and area_def should be equal") area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) self.assertFalse( area_def != swath_def, "swath_def and area_def should be equal") def test_swath_not_equal_area(self): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) lons = np.array([1.2, 1.3, 1.4, 1.5]) lats = np.array([65.9, 65.86, 65.82, 65.78]) swath_def = geometry.SwathDefinition(lons, lats) self.assertFalse( swath_def == area_def, "swath_def and area_def should be different") area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) self.assertFalse( area_def == swath_def, "swath_def and area_def should be different") def test_concat_1d(self): lons1 = np.array([1, 2, 3]) lats1 = np.array([1, 2, 3]) lons2 = np.array([4, 5, 6]) lats2 = np.array([4, 5, 6]) swath_def1 = geometry.SwathDefinition(lons1, lats1) swath_def2 = geometry.SwathDefinition(lons2, lats2) swath_def_concat = swath_def1.concatenate(swath_def2) expected = np.array([1, 2, 3, 4, 5, 6]) self.assertTrue(np.array_equal(swath_def_concat.lons, expected) and np.array_equal(swath_def_concat.lons, expected), 'Failed to concatenate 1D swaths') def test_concat_2d(self): lons1 = np.array([[1, 2, 3], [3, 4, 5], [5, 6, 7]]) lats1 = np.array([[1, 2, 3], [3, 4, 5], [5, 6, 7]]) lons2 = np.array([[4, 5, 6], [6, 7, 8]]) lats2 = np.array([[4, 5, 6], [6, 7, 8]]) swath_def1 = geometry.SwathDefinition(lons1, lats1) swath_def2 = geometry.SwathDefinition(lons2, lats2) swath_def_concat = swath_def1.concatenate(swath_def2) expected = np.array( [[1, 2, 3], [3, 4, 5], [5, 6, 7], [4, 5, 6], [6, 7, 8]]) self.assertTrue(np.array_equal(swath_def_concat.lons, expected) and np.array_equal(swath_def_concat.lons, expected), 'Failed to concatenate 2D swaths') def test_append_1d(self): lons1 = np.array([1, 2, 3]) lats1 = np.array([1, 2, 3]) lons2 = np.array([4, 5, 6]) lats2 = np.array([4, 5, 6]) swath_def1 = geometry.SwathDefinition(lons1, lats1) swath_def2 = geometry.SwathDefinition(lons2, lats2) swath_def1.append(swath_def2) expected = np.array([1, 2, 3, 4, 5, 6]) self.assertTrue(np.array_equal(swath_def1.lons, expected) and np.array_equal(swath_def1.lons, expected), 'Failed to append 1D swaths') def test_append_2d(self): lons1 = np.array([[1, 2, 3], [3, 4, 5], [5, 6, 7]]) lats1 = np.array([[1, 2, 3], [3, 4, 5], [5, 6, 7]]) lons2 = np.array([[4, 5, 6], [6, 7, 8]]) lats2 = np.array([[4, 5, 6], [6, 7, 8]]) swath_def1 = geometry.SwathDefinition(lons1, lats1) swath_def2 = geometry.SwathDefinition(lons2, lats2) swath_def1.append(swath_def2) expected = np.array( [[1, 2, 3], [3, 4, 5], [5, 6, 7], [4, 5, 6], [6, 7, 8]]) self.assertTrue(np.array_equal(swath_def1.lons, expected) and np.array_equal(swath_def1.lons, expected), 'Failed to append 2D swaths') def test_grid_filter_valid(self): lons = np.array([-170, -30, 30, 170]) lats = np.array([20, -40, 50, -80]) swath_def = geometry.SwathDefinition(lons, lats) filter_area = geometry.AreaDefinition('test', 'test', 'test', {'proj': 'eqc', 'lon_0': 0.0, 'lat_0': 0.0}, 8, 8, (-20037508.34, -10018754.17, 20037508.34, 10018754.17)) filter = np.array([[1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], ]) grid_filter = geo_filter.GridFilter(filter_area, filter) valid_index = grid_filter.get_valid_index(swath_def) expected = np.array([1, 0, 0, 1]) self.assertTrue( np.array_equal(valid_index, expected), 'Failed to find grid filter') def test_grid_filter(self): lons = np.array([-170, -30, 30, 170]) lats = np.array([20, -40, 50, -80]) swath_def = geometry.SwathDefinition(lons, lats) data = np.array([1, 2, 3, 4]) filter_area = geometry.AreaDefinition('test', 'test', 'test', {'proj': 'eqc', 'lon_0': 0.0, 'lat_0': 0.0}, 8, 8, (-20037508.34, -10018754.17, 20037508.34, 10018754.17)) filter = np.array([[1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], ]) grid_filter = geo_filter.GridFilter(filter_area, filter) swath_def_f, data_f = grid_filter.filter(swath_def, data) expected = np.array([1, 4]) self.assertTrue( np.array_equal(data_f, expected), 'Failed grid filtering data') expected_lons = np.array([-170, 170]) expected_lats = np.array([20, -80]) self.assertTrue(np.array_equal(swath_def_f.lons[:], expected_lons) and np.array_equal(swath_def_f.lats[:], expected_lats), 'Failed finding grid filtering lon lats') def test_grid_filter2D(self): lons = np.array([[-170, -30, 30, 170], [-170, -30, 30, 170]]) lats = np.array([[20, -40, 50, -80], [25, -35, 55, -75]]) swath_def = geometry.SwathDefinition(lons, lats) data1 = np.ones((2, 4)) data2 = np.ones((2, 4)) * 2 data3 = np.ones((2, 4)) * 3 data = np.dstack((data1, data2, data3)) filter_area = geometry.AreaDefinition('test', 'test', 'test', {'proj': 'eqc', 'lon_0': 0.0, 'lat_0': 0.0}, 8, 8, (-20037508.34, -10018754.17, 20037508.34, 10018754.17)) filter = np.array([[1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [1, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], [0, 0, 0, 0, 1, 1, 1, 1], ]) grid_filter = geo_filter.GridFilter(filter_area, filter, nprocs=2) swath_def_f, data_f = grid_filter.filter(swath_def, data) expected = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]]) self.assertTrue( np.array_equal(data_f, expected), 'Failed 2D grid filtering data') expected_lons = np.array([-170, 170, -170, 170]) expected_lats = np.array([20, -80, 25, -75]) self.assertTrue(np.array_equal(swath_def_f.lons[:], expected_lons) and np.array_equal(swath_def_f.lats[:], expected_lats), 'Failed finding 2D grid filtering lon lats') def test_boundary(self): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 10, 10, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) proj_x_boundary, proj_y_boundary = area_def.proj_x_coords, area_def.proj_y_coords expected_x = np.array([-1250912.72, -1010912.72, -770912.72, -530912.72, -290912.72, -50912.72, 189087.28, 429087.28, 669087.28, 909087.28]) expected_y = np.array([1370031.36, 1130031.36, 890031.36, 650031.36, 410031.36, 170031.36, -69968.64, -309968.64, -549968.64, -789968.64]) self.assertTrue(np.allclose(proj_x_boundary, expected_x), 'Failed to find projection x coords') self.assertTrue(np.allclose(proj_y_boundary, expected_y), 'Failed to find projection y coords') def test_area_extent_ll(self): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 10, 10, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) self.assertAlmostEqual(sum(area_def.area_extent_ll), 122.06448093539757, 5, 'Failed to get lon and lats of area extent') def test_latlong_area(self): area_def = geometry.AreaDefinition('', '', '', {'proj': 'latlong'}, 360, 180, [-180, -90, 180, 90]) lons, lats = area_def.get_lonlats() self.assertEqual(lons[0, 0], -179.5) self.assertEqual(lats[0, 0], 89.5) def test_lonlat2colrow(self): from pyresample import utils area_id = 'meteosat_0deg' area_name = 'Meteosat 0 degree Service' proj_id = 'geos0' x_size = 3712 y_size = 3712 area_extent = [-5570248.477339261, -5567248.074173444, 5567248.074173444, 5570248.477339261] proj_dict = {'a': '6378169.00', 'b': '6356583.80', 'h': '35785831.0', 'lon_0': '0.0', 'proj': 'geos'} area = utils.get_area_def(area_id, area_name, proj_id, proj_dict, x_size, y_size, area_extent) # Imatra, Wiesbaden longitudes = np.array([28.75242, 8.24932]) latitudes = np.array([61.17185, 50.08258]) cols__, rows__ = area.lonlat2colrow(longitudes, latitudes) # test arrays cols_expects = np.array([2304, 2040]) rows_expects = np.array([186, 341]) self.assertTrue((cols__ == cols_expects).all()) self.assertTrue((rows__ == rows_expects).all()) # test scalars lon, lat = (-8.125547604568746, -14.345524111874646) self.assertTrue(area.lonlat2colrow(lon,lat) == (1567, 2375)) def test_colrow2lonlat(self): from pyresample import utils area_id = 'meteosat_0deg' area_name = 'Meteosat 0 degree Service' proj_id = 'geos0' x_size = 3712 y_size = 3712 area_extent = [-5570248.477339261, -5567248.074173444, 5567248.074173444, 5570248.477339261] proj_dict = {'a': '6378169.00', 'b': '6356583.80', 'h': '35785831.0', 'lon_0': '0.0', 'proj': 'geos'} area = utils.get_area_def(area_id, area_name, proj_id, proj_dict, x_size, y_size, area_extent) # Imatra, Wiesbaden cols = np.array([2304, 2040]) rows = np.array([186, 341]) lons__, lats__ = area.colrow2lonlat(cols, rows) # test arrays lon_expects = np.array([28.77763033, 8.23765962]) lat_expects = np.array([61.20120556, 50.05836402]) self.assertTrue(np.allclose(lons__, lon_expects, rtol = 0, atol = 1e-7)) self.assertTrue(np.allclose(lats__, lat_expects, rtol = 0, atol = 1e-7)) # test scalars lon__, lat__ = area.colrow2lonlat(1567, 2375) lon_expect = -8.125547604568746 lat_expect = -14.345524111874646 self.assertTrue(np.allclose(lon__, lon_expect, rtol = 0, atol = 1e-7)) self.assertTrue(np.allclose(lat__, lat_expect, rtol = 0, atol = 1e-7)) def test_get_xy_from_lonlat(self): """Test the function get_xy_from_lonlat""" from pyresample import utils area_id = 'test' area_name = 'Test area with 2x2 pixels' proj_id = 'test' x_size = 2 y_size = 2 area_extent = [1000000, 0, 1050000, 50000] proj_dict = {"proj": 'laea', 'lat_0': '60', 'lon_0': '0', 'a': '6371228.0', 'units': 'm'} area_def = utils.get_area_def(area_id, area_name, proj_id, proj_dict, x_size, y_size, area_extent) import pyproj p__ = pyproj.Proj(proj_dict) lon_ul, lat_ul = p__(1000000, 50000, inverse=True) lon_ur, lat_ur = p__(1050000, 50000, inverse=True) lon_ll, lat_ll = p__(1000000, 0, inverse=True) lon_lr, lat_lr = p__(1050000, 0, inverse=True) eps_lonlat = 0.01 eps_meters = 100 x__, y__ = area_def.get_xy_from_lonlat(lon_ul + eps_lonlat, lat_ul - eps_lonlat) x_expect, y_expect = 0, 0 self.assertEqual(x__, x_expect) self.assertEqual(y__, y_expect) x__, y__ = area_def.get_xy_from_lonlat(lon_ur - eps_lonlat, lat_ur - eps_lonlat) self.assertEqual(x__, 1) self.assertEqual(y__, 0) x__, y__ = area_def.get_xy_from_lonlat(lon_ll + eps_lonlat, lat_ll + eps_lonlat) self.assertEqual(x__, 0) self.assertEqual(y__, 1) x__, y__ = area_def.get_xy_from_lonlat(lon_lr - eps_lonlat, lat_lr + eps_lonlat) self.assertEqual(x__, 1) self.assertEqual(y__, 1) lon, lat = p__(1025000 - eps_meters, 25000 - eps_meters, inverse=True) x__, y__ = area_def.get_xy_from_lonlat(lon, lat) self.assertEqual(x__, 0) self.assertEqual(y__, 1) lon, lat = p__(1025000 + eps_meters, 25000 - eps_meters, inverse=True) x__, y__ = area_def.get_xy_from_lonlat(lon, lat) self.assertEqual(x__, 1) self.assertEqual(y__, 1) lon, lat = p__(1025000 - eps_meters, 25000 + eps_meters, inverse=True) x__, y__ = area_def.get_xy_from_lonlat(lon, lat) self.assertEqual(x__, 0) self.assertEqual(y__, 0) lon, lat = p__(1025000 + eps_meters, 25000 + eps_meters, inverse=True) x__, y__ = area_def.get_xy_from_lonlat(lon, lat) self.assertEqual(x__, 1) self.assertEqual(y__, 0) lon, lat = p__(999000, -10, inverse=True) self.assert_raises(ValueError, area_def.get_xy_from_lonlat, lon, lat) self.assert_raises(ValueError, area_def.get_xy_from_lonlat, 0., 0.) # Test getting arrays back: lons = [lon_ll + eps_lonlat, lon_ur - eps_lonlat] lats = [lat_ll + eps_lonlat, lat_ur - eps_lonlat] x__, y__ = area_def.get_xy_from_lonlat(lons, lats) x_expects = np.array([0, 1]) y_expects = np.array([1, 0]) self.assertTrue((x__.data == x_expects).all()) self.assertTrue((y__.data == y_expects).all()) def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(Test)) return mysuite if __name__ == '__main__': unittest.main() pyresample-1.2.9/pyresample/test/test_grid.py000066400000000000000000000217221302372600000213770ustar00rootroot00000000000000import copy import unittest import numpy as np from pyresample import grid, geometry, utils def mp(f): f.mp = True return f def tmp(f): f.tmp = True return f class Test(unittest.TestCase): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) area_def2 = geometry.AreaDefinition('areaD2', 'Europe (3km, HRV, VTC)', 'areaD2', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 5, 5, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) msg_area = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', 'msg_full', {'a': '6378169.0', 'b': '6356584.0', 'h': '35785831.0', 'lon_0': '0', 'proj': 'geos'}, 3712, 3712, [-5568742.4000000004, -5568742.4000000004, 5568742.4000000004, 5568742.4000000004] ) def test_linesample(self): data = np.fromfunction(lambda y, x: y * x, (40, 40)) rows = np.array([[1, 2], [3, 4]]) cols = np.array([[25, 26], [27, 28]]) res = grid.get_image_from_linesample(rows, cols, data) expected = np.array([[25., 52.], [81., 112.]]) self.assertTrue(np.array_equal(res, expected), 'Linesample failed') def test_linesample_multi(self): data1 = np.fromfunction(lambda y, x: y * x, (40, 40)) data2 = np.fromfunction(lambda y, x: 2 * y * x, (40, 40)) data3 = np.fromfunction(lambda y, x: 3 * y * x, (40, 40)) data = np.zeros((40, 40, 3)) data[:, :, 0] = data1 data[:, :, 1] = data2 data[:, :, 2] = data3 rows = np.array([[1, 2], [3, 4]]) cols = np.array([[25, 26], [27, 28]]) res = grid.get_image_from_linesample(rows, cols, data) expected = np.array([[[25., 50., 75.], [52., 104., 156.]], [[81., 162., 243.], [112., 224., 336.]]]) self.assertTrue(np.array_equal(res, expected), 'Linesample failed') def test_from_latlon(self): data = np.fromfunction(lambda y, x: y * x, (800, 800)) lons = np.fromfunction(lambda y, x: x, (10, 10)) lats = np.fromfunction(lambda y, x: 50 - (5.0 / 10) * y, (10, 10)) #source_def = grid.AreaDefinition.get_from_area_def(self.area_def) source_def = self.area_def res = grid.get_image_from_lonlats(lons, lats, source_def, data) expected = np.array([[129276., 141032., 153370., 165804., 178334., 190575., 202864., 214768., 226176., 238080.], [133056., 146016., 158808., 171696., 184320., 196992., 209712., 222480., 234840., 247715.], [137026., 150150., 163370., 177215., 190629., 203756., 217464., 230256., 243048., 256373.], [140660., 154496., 168714., 182484., 196542., 210650., 224257., 238464., 251712., 265512.], [144480., 158484., 173148., 187912., 202776., 217358., 231990., 246240., 259920., 274170.], [147968., 163261., 178398., 193635., 208616., 223647., 238728., 253859., 268584., 283898.], [151638., 167121., 182704., 198990., 214775., 230280., 246442., 261617., 276792., 292574.], [154980., 171186., 187860., 204016., 220542., 237120., 253125., 269806., 285456., 301732.], [158500., 175536., 192038., 209280., 226626., 243697., 260820., 277564., 293664., 310408.], [161696., 179470., 197100., 214834., 232320., 250236., 267448., 285090., 302328., 320229.]]) self.assertTrue( np.array_equal(res, expected), 'Sampling from lat lon failed') def test_proj_coords(self): #res = grid.get_proj_coords(self.area_def2) res = self.area_def2.get_proj_coords() cross_sum = res[0].sum() + res[1].sum() expected = 2977965.9999999963 self.assertAlmostEqual( cross_sum, expected, msg='Calculation of proj coords failed') def test_latlons(self): #res = grid.get_lonlats(self.area_def2) res = self.area_def2.get_lonlats() cross_sum = res[0].sum() + res[1].sum() expected = 1440.8280578215431 self.assertAlmostEqual( cross_sum, expected, msg='Calculation of lat lons failed') @mp def test_latlons_mp(self): #res = grid.get_lonlats(self.area_def2, nprocs=2) res = self.area_def2.get_lonlats(nprocs=2) cross_sum = res[0].sum() + res[1].sum() expected = 1440.8280578215431 self.assertAlmostEqual( cross_sum, expected, msg='Calculation of lat lons failed') def test_resampled_image(self): data = np.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) target_def = self.area_def source_def = self.msg_area res = grid.get_resampled_image( target_def, source_def, data, segments=1) cross_sum = res.sum() expected = 399936.39392500359 self.assertAlmostEqual( cross_sum, expected, msg='Resampling of image failed') @tmp def test_generate_linesample(self): data = np.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) row_indices, col_indices = utils.generate_quick_linesample_arrays(self.msg_area, self.area_def) res = data[row_indices, col_indices] cross_sum = res.sum() expected = 399936.39392500359 self.assertAlmostEqual( cross_sum, expected, msg='Generate linesample failed') self.assertFalse(row_indices.dtype != np.uint16 or col_indices.dtype != np.uint16, 'Generate linesample failed. Downcast to uint16 expected') @mp def test_resampled_image_mp(self): data = np.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) target_def = self.area_def source_def = self.msg_area res = grid.get_resampled_image( target_def, source_def, data, nprocs=2, segments=1) cross_sum = res.sum() expected = 399936.39392500359 self.assertAlmostEqual( cross_sum, expected, msg='Resampling of image mp failed') def test_single_lonlat(self): lon, lat = self.area_def.get_lonlat(400, 400) self.assertAlmostEqual( lon, 5.5028467120975835, msg='Resampling of single lon failed') self.assertAlmostEqual( lat, 52.566998432390619, msg='Resampling of single lat failed') def test_proj4_string(self): proj4_string = self.area_def.proj4_string expected_string = '+a=6378144.0 +b=6356759.0 +lat_ts=50.00 +lon_0=8.00 +proj=stere +lat_0=50.00' self.assertEqual( frozenset(proj4_string.split()), frozenset(expected_string.split())) def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(Test)) return mysuite pyresample-1.2.9/pyresample/test/test_image.py000066400000000000000000000237141302372600000215370ustar00rootroot00000000000000import os import unittest import numpy from pyresample import image, geometry, grid, utils def mask(f): f.mask = True return f def tmp(f): f.tmp = True return f class Test(unittest.TestCase): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) msg_area = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', 'msg_full', {'a': '6378169.0', 'b': '6356584.0', 'h': '35785831.0', 'lon_0': '0', 'proj': 'geos'}, 3712, 3712, [-5568742.4000000004, -5568742.4000000004, 5568742.4000000004, 5568742.4000000004] ) msg_area_resize = geometry.AreaDefinition('msg_full', 'Full globe MSG image 0 degrees', 'msg_full', {'a': '6378169.0', 'b': '6356584.0', 'h': '35785831.0', 'lon_0': '0', 'proj': 'geos'}, 928, 928, [-5568742.4000000004, -5568742.4000000004, 5568742.4000000004, 5568742.4000000004] ) @tmp def test_image(self): data = numpy.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) msg_con = image.ImageContainerQuick(data, self.msg_area, segments=1) area_con = msg_con.resample(self.area_def) res = area_con.image_data cross_sum = res.sum() expected = 399936.39392500359 self.assertAlmostEqual( cross_sum, expected, msg='ImageContainer resampling quick failed') @tmp def test_image_segments(self): data = numpy.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) msg_con = image.ImageContainerQuick(data, self.msg_area, segments=8) area_con = msg_con.resample(self.area_def) res = area_con.image_data cross_sum = res.sum() expected = 399936.39392500359 self.assertAlmostEqual( cross_sum, expected, msg='ImageContainer resampling quick segments failed') def test_return_type(self): data = numpy.ones((3712, 3712)).astype('int') msg_con = image.ImageContainerQuick(data, self.msg_area, segments=1) area_con = msg_con.resample(self.area_def) res = area_con.image_data self.assertTrue( data.dtype is res.dtype, msg='Failed to maintain input data type') @mask def test_masked_image(self): data = numpy.zeros((3712, 3712)) mask = numpy.zeros((3712, 3712)) mask[:, 1865:] = 1 data_masked = numpy.ma.array(data, mask=mask) msg_con = image.ImageContainerQuick( data_masked, self.msg_area, segments=1) area_con = msg_con.resample(self.area_def) res = area_con.image_data resampled_mask = res.mask.astype('int') expected = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_grid.dat'), sep=' ').reshape((800, 800)) self.assertTrue(numpy.array_equal( resampled_mask, expected), msg='Failed to resample masked array') @mask def test_masked_image_fill(self): data = numpy.zeros((3712, 3712)) mask = numpy.zeros((3712, 3712)) mask[:, 1865:] = 1 data_masked = numpy.ma.array(data, mask=mask) msg_con = image.ImageContainerQuick(data_masked, self.msg_area, fill_value=None, segments=1) area_con = msg_con.resample(self.area_def) res = area_con.image_data resampled_mask = res.mask.astype('int') expected = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_grid.dat'), sep=' ').reshape((800, 800)) self.assertTrue(numpy.array_equal( resampled_mask, expected), msg='Failed to resample masked array') def test_nearest_neighbour(self): data = numpy.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) msg_con = image.ImageContainerNearest( data, self.msg_area, 50000, segments=1) area_con = msg_con.resample(self.area_def) res = area_con.image_data cross_sum = res.sum() expected = 399936.783062 self.assertAlmostEqual(cross_sum, expected, msg='ImageContainer resampling nearest neighbour failed') def test_nearest_resize(self): data = numpy.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) msg_con = image.ImageContainerNearest( data, self.msg_area, 50000, segments=1) area_con = msg_con.resample(self.msg_area_resize) res = area_con.image_data cross_sum = res.sum() expected = 2212023.0175830 self.assertAlmostEqual(cross_sum, expected, msg='ImageContainer resampling nearest neighbour failed') def test_nearest_neighbour_multi(self): data1 = numpy.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) data2 = numpy.fromfunction( lambda y, x: y * x * 10 ** -6, (3712, 3712)) * 2 data = numpy.dstack((data1, data2)) msg_con = image.ImageContainerNearest( data, self.msg_area, 50000, segments=1) area_con = msg_con.resample(self.area_def) res = area_con.image_data cross_sum1 = res[:, :, 0].sum() expected1 = 399936.783062 self.assertAlmostEqual(cross_sum1, expected1, msg='ImageContainer resampling nearest neighbour multi failed') cross_sum2 = res[:, :, 1].sum() expected2 = 399936.783062 * 2 self.assertAlmostEqual(cross_sum2, expected2, msg='ImageContainer resampling nearest neighbour multi failed') def test_nearest_neighbour_multi_preproc(self): data1 = numpy.fromfunction(lambda y, x: y * x * 10 ** -6, (3712, 3712)) data2 = numpy.fromfunction( lambda y, x: y * x * 10 ** -6, (3712, 3712)) * 2 data = numpy.dstack((data1, data2)) msg_con = image.ImageContainer(data, self.msg_area) #area_con = msg_con.resample_area_nearest_neighbour(self.area_def, 50000) row_indices, col_indices = \ utils.generate_nearest_neighbour_linesample_arrays(self.msg_area, self.area_def, 50000) res = msg_con.get_array_from_linesample(row_indices, col_indices) cross_sum1 = res[:, :, 0].sum() expected1 = 399936.783062 self.assertAlmostEqual(cross_sum1, expected1, msg='ImageContainer resampling nearest neighbour multi preproc failed') cross_sum2 = res[:, :, 1].sum() expected2 = 399936.783062 * 2 self.assertAlmostEqual(cross_sum2, expected2, msg='ImageContainer resampling nearest neighbour multi preproc failed') def test_nearest_swath(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) swath_con = image.ImageContainerNearest( data, swath_def, 50000, segments=1) area_con = swath_con.resample(self.area_def) res = area_con.image_data cross_sum = res.sum() expected = 15874591.0 self.assertEqual(cross_sum, expected, msg='ImageContainer swath resampling nearest failed') def test_nearest_swath_segments(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) data = numpy.dstack(3 * (data,)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) swath_con = image.ImageContainerNearest( data, swath_def, 50000, segments=2) area_con = swath_con.resample(self.area_def) res = area_con.image_data cross_sum = res.sum() expected = 3 * 15874591.0 self.assertEqual(cross_sum, expected, msg='ImageContainer swath segments resampling nearest failed') def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(Test)) return mysuite pyresample-1.2.9/pyresample/test/test_kd_tree.py000066400000000000000000001233231302372600000220670ustar00rootroot00000000000000from __future__ import with_statement import os import sys import numpy from pyresample.test.utils import catch_warnings from pyresample import kd_tree, utils, geometry, data_reduce if sys.version_info < (2, 7): import unittest2 as unittest else: import unittest class Test(unittest.TestCase): area_def = geometry.AreaDefinition('areaD', 'Europe (3km, HRV, VTC)', 'areaD', {'a': '6378144.0', 'b': '6356759.0', 'lat_0': '50.00', 'lat_ts': '50.00', 'lon_0': '8.00', 'proj': 'stere'}, 800, 800, [-1370912.72, -909968.64000000001, 1029087.28, 1490031.3600000001]) tdata = numpy.array([1, 2, 3]) tlons = numpy.array([11.280789, 12.649354, 12.080402]) tlats = numpy.array([56.011037, 55.629675, 55.641535]) tswath = geometry.SwathDefinition(lons=tlons, lats=tlats) tgrid = geometry.CoordinateDefinition(lons=numpy.array([12.562036]), lats=numpy.array([55.715613])) def test_nearest_base(self): res = kd_tree.resample_nearest(self.tswath, self.tdata.ravel(), self.tgrid, 100000, reduce_data=False, segments=1) self.assertTrue(res[0] == 2, 'Failed to calculate nearest neighbour') def test_gauss_base(self): with catch_warnings() as w: res = kd_tree.resample_gauss(self.tswath, self.tdata.ravel(), self.tgrid, 50000, 25000, reduce_data=False, segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour warning') self.assertFalse(('Searching' not in str( w[0].message)), 'Failed to create correct neighbour warning') self.assertAlmostEqual(res[0], 2.2020729, 5, 'Failed to calculate gaussian weighting') def test_custom_base(self): def wf(dist): return 1 - dist / 100000.0 with catch_warnings() as w: res = kd_tree.resample_custom(self.tswath, self.tdata.ravel(), self.tgrid, 50000, wf, reduce_data=False, segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour warning') self.assertFalse(('Searching' not in str( w[0].message)), 'Failed to create correct neighbour warning') self.assertAlmostEqual(res[0], 2.4356757, 5, 'Failed to calculate custom weighting') def test_gauss_uncert(self): sigma = utils.fwhm2sigma(41627.730557884883) with catch_warnings() as w: res, stddev, count = kd_tree.resample_gauss(self.tswath, self.tdata, self.tgrid, 100000, sigma, with_uncert=True) self.assertTrue( len(w) > 0, 'Failed to create neighbour warning') self.assertTrue((any('Searching' in str(_w.message) for _w in w)), 'Failed to create correct neighbour warning') expected_res = 2.20206560694 expected_stddev = 0.707115076173 expected_count = 3 self.assertAlmostEqual(res[0], expected_res, 5, 'Failed to calculate gaussian weighting with uncertainty') self.assertAlmostEqual(stddev[0], expected_stddev, 5, 'Failed to calculate uncertainty for gaussian weighting') self.assertEqual( count[0], expected_count, 'Wrong data point count for gaussian weighting with uncertainty') def test_custom_uncert(self): def wf(dist): return 1 - dist / 100000.0 with catch_warnings() as w: res, stddev, counts = kd_tree.resample_custom(self.tswath, self.tdata, self.tgrid, 100000, wf, with_uncert=True) self.assertTrue( len(w) > 0, 'Failed to create neighbour warning') self.assertTrue((any('Searching' in str(_w.message) for _w in w)), 'Failed to create correct neighbour warning') self.assertAlmostEqual(res[0], 2.32193149, 5, 'Failed to calculate custom weighting with uncertainty') self.assertAlmostEqual(stddev[0], 0.81817972, 5, 'Failed to calculate custom for gaussian weighting') self.assertEqual( counts[0], 3, 'Wrong data point count for custom weighting with uncertainty') def test_nearest(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data.ravel(), self.area_def, 50000, segments=1) cross_sum = res.sum() expected = 15874591.0 self.assertEqual(cross_sum, expected, msg='Swath resampling nearest failed') def test_nearest_1d(self): data = numpy.fromfunction(lambda x, y: x * y, (800, 800)) lons = numpy.fromfunction(lambda x: 3 + x / 100., (500,)) lats = numpy.fromfunction(lambda x: 75 - x / 10., (500,)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(self.area_def, data.ravel(), swath_def, 50000, segments=1) cross_sum = res.sum() expected = 35821299.0 self.assertEqual(res.shape, (500,), msg='Swath resampling nearest 1d failed') self.assertEqual(cross_sum, expected, msg='Swath resampling nearest 1d failed') def test_nearest_empty(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 165 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data.ravel(), self.area_def, 50000, segments=1) cross_sum = res.sum() expected = 0 self.assertEqual(cross_sum, expected, msg='Swath resampling nearest empty failed') def test_nearest_empty_multi(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 165 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data_multi, self.area_def, 50000, segments=1) self.assertEqual(res.shape, (800, 800, 3), msg='Swath resampling nearest empty multi failed') def test_nearest_empty_multi_masked(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 165 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data_multi, self.area_def, 50000, segments=1, fill_value=None) self.assertEqual(res.shape, (800, 800, 3), msg='Swath resampling nearest empty multi masked failed') def test_nearest_empty_masked(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 165 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data.ravel(), self.area_def, 50000, segments=1, fill_value=None) cross_sum = res.mask.sum() expected = res.size self.assertTrue(cross_sum == expected, msg='Swath resampling nearest empty masked failed') def test_nearest_segments(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data.ravel(), self.area_def, 50000, segments=2) cross_sum = res.sum() expected = 15874591.0 self.assertEqual(cross_sum, expected, msg='Swath resampling nearest segments failed') def test_nearest_remap(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data.ravel(), self.area_def, 50000, segments=1) remap = kd_tree.resample_nearest(self.area_def, res.ravel(), swath_def, 5000, segments=1) cross_sum = remap.sum() expected = 22275.0 self.assertEqual(cross_sum, expected, msg='Grid remapping nearest failed') def test_nearest_mp(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data.ravel(), self.area_def, 50000, nprocs=2, segments=1) cross_sum = res.sum() expected = 15874591.0 self.assertEqual(cross_sum, expected, msg='Swath resampling mp nearest failed') def test_nearest_multi(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) res = kd_tree.resample_nearest(swath_def, data_multi, self.area_def, 50000, segments=1) cross_sum = res.sum() expected = 3 * 15874591.0 self.assertEqual(cross_sum, expected, msg='Swath multi channel resampling nearest failed') def test_nearest_multi_unraveled(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.dstack((data, data, data)) res = kd_tree.resample_nearest(swath_def, data_multi, self.area_def, 50000, segments=1) cross_sum = res.sum() expected = 3 * 15874591.0 self.assertEqual(cross_sum, expected, msg='Swath multi channel resampling nearest failed') def test_gauss_sparse(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_gauss(swath_def, data.ravel(), self.area_def, 50000, 25000, fill_value=-1, segments=1) cross_sum = res.sum() expected = 15387753.9852 self.assertAlmostEqual(cross_sum, expected, places=3, msg='Swath gauss sparse nearest failed') def test_gauss(self): data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -5, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) with catch_warnings() as w: res = kd_tree.resample_gauss(swath_def, data.ravel(), self.area_def, 50000, 25000, segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') cross_sum = res.sum() expected = 4872.81050892 self.assertAlmostEqual(cross_sum, expected, msg='Swath resampling gauss failed') def test_gauss_fwhm(self): data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -5, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) with catch_warnings() as w: res = kd_tree.resample_gauss(swath_def, data.ravel(), self.area_def, 50000, utils.fwhm2sigma(41627.730557884883), segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') cross_sum = res.sum() expected = 4872.81050892 self.assertAlmostEqual(cross_sum, expected, msg='Swath resampling gauss failed') def test_gauss_multi(self): data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -6, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) with catch_warnings() as w: res = kd_tree.resample_gauss(swath_def, data_multi, self.area_def, 50000, [25000, 15000, 10000], segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') cross_sum = res.sum() expected = 1461.84313918 self.assertAlmostEqual(cross_sum, expected, msg='Swath multi channel resampling gauss failed') def test_gauss_multi_uncert(self): data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -6, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) with catch_warnings() as w: # The assertion below checks if there is only one warning raised # and whether it contains a specific message from pyresample # On python 2.7.9+ the resample_gauss method raises multiple deprecation warnings # that cause to fail, so we ignore the unrelated warnings. res, stddev, counts = kd_tree.resample_gauss(swath_def, data_multi, self.area_def, 50000, [ 25000, 15000, 10000], segments=1, with_uncert=True) self.assertTrue( len(w) >= 1, 'Failed to create neighbour radius warning') self.assertTrue(any(['Possible more' in str( x.message) for x in w]), 'Failed to create correct neighbour radius warning') cross_sum = res.sum() cross_sum_stddev = stddev.sum() cross_sum_counts = counts.sum() expected = 1461.84313918 expected_stddev = 0.446204424799 expected_counts = 4934802.0 self.assertTrue(res.shape == stddev.shape and stddev.shape == counts.shape and counts.shape == (800, 800, 3)) self.assertAlmostEqual(cross_sum, expected, msg='Swath multi channel resampling gauss failed on data') self.assertAlmostEqual(cross_sum_stddev, expected_stddev, msg='Swath multi channel resampling gauss failed on stddev') self.assertAlmostEqual(cross_sum_counts, expected_counts, msg='Swath multi channel resampling gauss failed on counts') def test_gauss_multi_mp(self): data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -6, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) with catch_warnings() as w: res = kd_tree.resample_gauss(swath_def, data_multi, self.area_def, 50000, [ 25000, 15000, 10000], nprocs=2, segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') cross_sum = res.sum() expected = 1461.84313918 self.assertAlmostEqual(cross_sum, expected, msg='Swath multi channel resampling gauss failed') def test_gauss_multi_mp_segments(self): data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -6, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) with catch_warnings() as w: res = kd_tree.resample_gauss(swath_def, data_multi, self.area_def, 50000, [ 25000, 15000, 10000], nprocs=2, segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') cross_sum = res.sum() expected = 1461.84313918 self.assertAlmostEqual(cross_sum, expected, msg='Swath multi channel segments resampling gauss failed') def test_gauss_multi_mp_segments_empty(self): data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -6, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 165 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) res = kd_tree.resample_gauss(swath_def, data_multi, self.area_def, 50000, [ 25000, 15000, 10000], nprocs=2, segments=1) cross_sum = res.sum() self.assertTrue(cross_sum == 0, msg=('Swath multi channel segments empty ' 'resampling gauss failed')) def test_custom(self): def wf(dist): return 1 - dist / 100000.0 data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -5, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) with catch_warnings() as w: res = kd_tree.resample_custom(swath_def, data.ravel(), self.area_def, 50000, wf, segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') cross_sum = res.sum() expected = 4872.81050729 self.assertAlmostEqual(cross_sum, expected, msg='Swath custom resampling failed') def test_custom_multi(self): def wf1(dist): return 1 - dist / 100000.0 def wf2(dist): return 1 def wf3(dist): return numpy.cos(dist) ** 2 data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -6, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) with catch_warnings() as w: res = kd_tree.resample_custom(swath_def, data_multi, self.area_def, 50000, [wf1, wf2, wf3], segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') cross_sum = res.sum() expected = 1461.842980746 self.assertAlmostEqual(cross_sum, expected, msg='Swath multi channel custom resampling failed') def test_reduce(self): data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) lons = numpy.fromfunction( lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) lats = numpy.fromfunction( lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) grid_lons, grid_lats = self.area_def.get_lonlats() lons, lats, data = data_reduce.swath_from_lonlat_grid(grid_lons, grid_lats, lons, lats, data, 7000) cross_sum = data.sum() expected = 20514375.0 self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') def test_reduce_boundary(self): data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) lons = numpy.fromfunction( lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) lats = numpy.fromfunction( lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) boundary_lonlats = self.area_def.get_boundary_lonlats() lons, lats, data = data_reduce.swath_from_lonlat_boundaries(boundary_lonlats[0], boundary_lonlats[ 1], lons, lats, data, 7000) cross_sum = data.sum() expected = 20514375.0 self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') def test_cartesian_reduce(self): data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) lons = numpy.fromfunction( lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) lats = numpy.fromfunction( lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) #grid = utils.generate_cartesian_grid(self.area_def) grid = self.area_def.get_cartesian_coords() lons, lats, data = data_reduce.swath_from_cartesian_grid(grid, lons, lats, data, 7000) cross_sum = data.sum() expected = 20514375.0 self.assertAlmostEqual( cross_sum, expected, msg='Cartesian reduce data failed') def test_area_con_reduce(self): data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) lons = numpy.fromfunction( lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) lats = numpy.fromfunction( lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) grid_lons, grid_lats = self.area_def.get_lonlats() valid_index = data_reduce.get_valid_index_from_lonlat_grid(grid_lons, grid_lats, lons, lats, 7000) data = data[valid_index] cross_sum = data.sum() expected = 20514375.0 self.assertAlmostEqual(cross_sum, expected, msg='Reduce data failed') def test_area_con_cartesian_reduce(self): data = numpy.fromfunction(lambda y, x: (y + x), (1000, 1000)) lons = numpy.fromfunction( lambda y, x: -180 + (360.0 / 1000) * x, (1000, 1000)) lats = numpy.fromfunction( lambda y, x: -90 + (180.0 / 1000) * y, (1000, 1000)) cart_grid = self.area_def.get_cartesian_coords() valid_index = data_reduce.get_valid_index_from_cartesian_grid(cart_grid, lons, lats, 7000) data = data[valid_index] cross_sum = data.sum() expected = 20514375.0 self.assertAlmostEqual( cross_sum, expected, msg='Cartesian reduce data failed') def test_masked_nearest(self): data = numpy.ones((50, 10)) data[:, 5:] = 2 lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) mask = numpy.ones((50, 10)) mask[:, :5] = 0 masked_data = numpy.ma.array(data, mask=mask) res = kd_tree.resample_nearest(swath_def, masked_data.ravel(), self.area_def, 50000, segments=1) expected_mask = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_nearest_mask.dat'), sep=' ').reshape((800, 800)) expected_data = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_nearest_data.dat'), sep=' ').reshape((800, 800)) self.assertTrue(numpy.array_equal(expected_mask, res.mask), msg='Resampling of swath mask failed') self.assertTrue(numpy.array_equal(expected_data, res.data), msg='Resampling of swath masked data failed') def test_masked_nearest_1d(self): data = numpy.ones((800, 800)) data[:400, :] = 2 lons = numpy.fromfunction(lambda x: 3 + x / 100., (500,)) lats = numpy.fromfunction(lambda x: 75 - x / 10., (500,)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) mask = numpy.ones((800, 800)) mask[400:, :] = 0 masked_data = numpy.ma.array(data, mask=mask) res = kd_tree.resample_nearest(self.area_def, masked_data.ravel(), swath_def, 50000, segments=1) self.assertEqual(res.mask.sum(), 108, msg='Swath resampling masked nearest 1d failed') def test_masked_gauss(self): data = numpy.ones((50, 10)) data[:, 5:] = 2 lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) mask = numpy.ones((50, 10)) mask[:, :5] = 0 masked_data = numpy.ma.array(data, mask=mask) res = kd_tree.resample_gauss(swath_def, masked_data.ravel(), self.area_def, 50000, 25000, segments=1) expected_mask = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_mask.dat'), sep=' ').reshape((800, 800)) expected_data = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_data.dat'), sep=' ').reshape((800, 800)) expected = expected_data.sum() cross_sum = res.data.sum() self.assertTrue(numpy.array_equal(expected_mask, res.mask), msg='Gauss resampling of swath mask failed') self.assertAlmostEqual(cross_sum, expected, places=3, msg='Gauss resampling of swath masked data failed') def test_masked_fill_float(self): data = numpy.ones((50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data.ravel(), self.area_def, 50000, fill_value=None, segments=1) expected_fill_mask = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_fill_value.dat'), sep=' ').reshape((800, 800)) fill_mask = res.mask self.assertTrue(numpy.array_equal(fill_mask, expected_fill_mask), msg='Failed to create fill mask on float data') def test_masked_fill_int(self): data = numpy.ones((50, 10)).astype('int') lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, data.ravel(), self.area_def, 50000, fill_value=None, segments=1) expected_fill_mask = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_fill_value.dat'), sep=' ').reshape((800, 800)) fill_mask = res.mask self.assertTrue(numpy.array_equal(fill_mask, expected_fill_mask), msg='Failed to create fill mask on integer data') def test_masked_full(self): data = numpy.ones((50, 10)) data[:, 5:] = 2 mask = numpy.ones((50, 10)) mask[:, :5] = 0 masked_data = numpy.ma.array(data, mask=mask) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, masked_data.ravel( ), self.area_def, 50000, fill_value=None, segments=1) expected_fill_mask = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_full_fill.dat'), sep=' ').reshape((800, 800)) fill_mask = res.mask self.assertTrue(numpy.array_equal(fill_mask, expected_fill_mask), msg='Failed to create fill mask on masked data') def test_masked_full_multi(self): data = numpy.ones((50, 10)) data[:, 5:] = 2 mask1 = numpy.ones((50, 10)) mask1[:, :5] = 0 mask2 = numpy.ones((50, 10)) mask2[:, 5:] = 0 mask3 = numpy.ones((50, 10)) mask3[:25, :] = 0 data_multi = numpy.column_stack( (data.ravel(), data.ravel(), data.ravel())) mask_multi = numpy.column_stack( (mask1.ravel(), mask2.ravel(), mask3.ravel())) masked_data = numpy.ma.array(data_multi, mask=mask_multi) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) res = kd_tree.resample_nearest(swath_def, masked_data, self.area_def, 50000, fill_value=None, segments=1) expected_fill_mask = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_full_fill_multi.dat'), sep=' ').reshape((800, 800, 3)) fill_mask = res.mask cross_sum = res.sum() expected = 357140.0 self.assertAlmostEqual(cross_sum, expected, msg='Failed to resample masked data') self.assertTrue(numpy.array_equal(fill_mask, expected_fill_mask), msg='Failed to create fill mask on masked data') def test_dtype(self): lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) grid_def = geometry.GridDefinition(lons, lats) lons = numpy.asarray(lons, dtype='f4') lats = numpy.asarray(lats, dtype='f4') swath_def = geometry.SwathDefinition(lons=lons, lats=lats) valid_input_index, valid_output_index, index_array, distance_array = \ kd_tree.get_neighbour_info(swath_def, grid_def, 50000, neighbours=1, segments=1) def test_nearest_from_sample(self): data = numpy.fromfunction(lambda y, x: y * x, (50, 10)) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) valid_input_index, valid_output_index, index_array, distance_array = \ kd_tree.get_neighbour_info(swath_def, self.area_def, 50000, neighbours=1, segments=1) res = kd_tree.get_sample_from_neighbour_info('nn', (800, 800), data.ravel(), valid_input_index, valid_output_index, index_array) cross_sum = res.sum() expected = 15874591.0 self.assertEqual(cross_sum, expected, msg='Swath resampling from neighbour info nearest failed') def test_custom_multi_from_sample(self): def wf1(dist): return 1 - dist / 100000.0 def wf2(dist): return 1 def wf3(dist): return numpy.cos(dist) ** 2 data = numpy.fromfunction(lambda y, x: (y + x) * 10 ** -6, (5000, 100)) lons = numpy.fromfunction( lambda y, x: 3 + (10.0 / 100) * x, (5000, 100)) lats = numpy.fromfunction( lambda y, x: 75 - (50.0 / 5000) * y, (5000, 100)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) data_multi = numpy.column_stack((data.ravel(), data.ravel(), data.ravel())) with catch_warnings() as w: valid_input_index, valid_output_index, index_array, distance_array = \ kd_tree.get_neighbour_info(swath_def, self.area_def, 50000, segments=1) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') res = kd_tree.get_sample_from_neighbour_info('custom', (800, 800), data_multi, valid_input_index, valid_output_index, index_array, distance_array, weight_funcs=[wf1, wf2, wf3]) cross_sum = res.sum() expected = 1461.842980746 self.assertAlmostEqual(cross_sum, expected, msg='Swath multi channel custom resampling from neighbour info failed 1') res = kd_tree.get_sample_from_neighbour_info('custom', (800, 800), data_multi, valid_input_index, valid_output_index, index_array, distance_array, weight_funcs=[wf1, wf2, wf3]) # Look for error where input data has been manipulated cross_sum = res.sum() expected = 1461.842980746 self.assertAlmostEqual(cross_sum, expected, msg='Swath multi channel custom resampling from neighbour info failed 2') def test_masked_multi_from_sample(self): data = numpy.ones((50, 10)) data[:, 5:] = 2 mask1 = numpy.ones((50, 10)) mask1[:, :5] = 0 mask2 = numpy.ones((50, 10)) mask2[:, 5:] = 0 mask3 = numpy.ones((50, 10)) mask3[:25, :] = 0 data_multi = numpy.column_stack( (data.ravel(), data.ravel(), data.ravel())) mask_multi = numpy.column_stack( (mask1.ravel(), mask2.ravel(), mask3.ravel())) masked_data = numpy.ma.array(data_multi, mask=mask_multi) lons = numpy.fromfunction(lambda y, x: 3 + x, (50, 10)) lats = numpy.fromfunction(lambda y, x: 75 - y, (50, 10)) swath_def = geometry.SwathDefinition(lons=lons, lats=lats) valid_input_index, valid_output_index, index_array, distance_array = \ kd_tree.get_neighbour_info(swath_def, self.area_def, 50000, neighbours=1, segments=1) res = kd_tree.get_sample_from_neighbour_info('nn', (800, 800), masked_data, valid_input_index, valid_output_index, index_array, fill_value=None) expected_fill_mask = numpy.fromfile(os.path.join(os.path.dirname(__file__), 'test_files', 'mask_test_full_fill_multi.dat'), sep=' ').reshape((800, 800, 3)) fill_mask = res.mask self.assertTrue(numpy.array_equal(fill_mask, expected_fill_mask), msg='Failed to create fill mask on masked data') def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(Test)) return mysuite pyresample-1.2.9/pyresample/test/test_plot.py000066400000000000000000000071021302372600000214240ustar00rootroot00000000000000import unittest import os import numpy as np try: import matplotlib matplotlib.use('Agg') except ImportError: pass # Postpone fail to individual tests def tmp(f): f.tmp = True return f class Test(unittest.TestCase): filename = os.path.abspath(os.path.join(os.path.dirname(__file__), 'test_files', 'ssmis_swath.npz')) data = np.load(filename)['data'] lons = data[:, 0].astype(np.float64) lats = data[:, 1].astype(np.float64) tb37v = data[:, 2].astype(np.float64) # screen out the fill values fvalue = -10000000000.0 valid_fov = (lons != fvalue) * (lats != fvalue) * (tb37v != fvalue) lons = lons[valid_fov] lats = lats[valid_fov] tb37v = tb37v[valid_fov] def test_ellps2axis(self): from pyresample import plot a, b = plot.ellps2axis('WGS84') self.assertAlmostEqual(a, 6378137.0, msg='Failed to get semi-major axis of ellipsis') self.assertAlmostEqual(b, 6356752.3142451793, msg='Failed to get semi-minor axis of ellipsis') def test_area_def2basemap(self): from pyresample import plot, utils area_def = utils.parse_area_file(os.path.join(os.path.dirname(__file__), 'test_files', 'areas.cfg'), 'ease_sh')[0] bmap = plot.area_def2basemap(area_def) self.assertTrue(bmap.rmajor == bmap.rminor and bmap.rmajor == 6371228.0, 'Failed to create Basemap object') def test_plate_carreeplot(self): from pyresample import plot, utils, kd_tree, geometry area_def = utils.parse_area_file(os.path.join(os.path.dirname(__file__), 'test_files', 'areas.cfg'), 'pc_world')[0] swath_def = geometry.SwathDefinition(self.lons, self.lats) result = kd_tree.resample_nearest(swath_def, self.tb37v, area_def, radius_of_influence=20000, fill_value=None) plt = plot._get_quicklook(area_def, result, num_meridians=0, num_parallels=0) def test_easeplot(self): from pyresample import plot, utils, kd_tree, geometry area_def = utils.parse_area_file(os.path.join(os.path.dirname(__file__), 'test_files', 'areas.cfg'), 'ease_sh')[0] swath_def = geometry.SwathDefinition(self.lons, self.lats) result = kd_tree.resample_nearest(swath_def, self.tb37v, area_def, radius_of_influence=20000, fill_value=None) plt = plot._get_quicklook(area_def, result) def test_orthoplot(self): from pyresample import plot, utils, kd_tree, geometry area_def = utils.parse_area_file(os.path.join(os.path.dirname(__file__), 'test_files', 'areas.cfg'), 'ortho')[0] swath_def = geometry.SwathDefinition(self.lons, self.lats) result = kd_tree.resample_nearest(swath_def, self.tb37v, area_def, radius_of_influence=20000, fill_value=None) plt = plot._get_quicklook(area_def, result) def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(Test)) return mysuite pyresample-1.2.9/pyresample/test/test_spherical_geometry.py000066400000000000000000000345001302372600000243350ustar00rootroot00000000000000from __future__ import with_statement import numpy as np import unittest import math from pyresample.spherical_geometry import Coordinate, Arc from pyresample import geometry class TestOverlap(unittest.TestCase): """Testing overlapping functions in pyresample. """ def assert_raises(self, exception, call_able, *args): """assertRaises() has changed from py2.6 to 2.7! Here is an attempt to cover both""" import sys if sys.version_info < (2, 7): self.assertRaises(exception, call_able, *args) else: with self.assertRaises(exception): call_able(*args) def test_inside(self): """Testing if a point is inside an area. """ lons = np.array([[-11, 11], [-11, 11]]) lats = np.array([[11, 11], [-11, -11]]) area = geometry.SwathDefinition(lons, lats) point = Coordinate(0, 0) self.assertTrue(point in area) point = Coordinate(0, 12) self.assertFalse(point in area) lons = np.array([[-179, 179], [-179, 179]]) lats = np.array([[1, 1], [-1, -1]]) area = geometry.SwathDefinition(lons, lats) point = Coordinate(180, 0) self.assertTrue(point in area) point = Coordinate(180, 12) self.assertFalse(point in area) point = Coordinate(-180, 12) self.assertFalse(point in area) self.assert_raises(ValueError, Coordinate, 0, 192) self.assert_raises(ValueError, Coordinate, 15, -91) # case of the north pole lons = np.array([[0, 90], [-90, 180]]) lats = np.array([[89, 89], [89, 89]]) area = geometry.SwathDefinition(lons, lats) point = Coordinate(90, 90) self.assertTrue(point in area) def test_overlaps(self): """Test if two areas overlap. """ lons1 = np.array([[0, 90], [-90, 180]]) lats1 = np.array([[89, 89], [89, 89]]) area1 = geometry.SwathDefinition(lons1, lats1) lons2 = np.array([[45, 135], [-45, -135]]) lats2 = np.array([[89, 89], [89, 89]]) area2 = geometry.SwathDefinition(lons2, lats2) self.assertTrue(area1.overlaps(area2)) self.assertTrue(area2.overlaps(area1)) lons1 = np.array([[0, 45], [135, 90]]) lats1 = np.array([[89, 89], [89, 89]]) area1 = geometry.SwathDefinition(lons1, lats1) lons2 = np.array([[180, -135], [-45, -90]]) lats2 = np.array([[89, 89], [89, 89]]) area2 = geometry.SwathDefinition(lons2, lats2) self.assertFalse(area1.overlaps(area2)) self.assertFalse(area2.overlaps(area1)) lons1 = np.array([[-1, 1], [-1, 1]]) lats1 = np.array([[1, 1], [-1, -1]]) area1 = geometry.SwathDefinition(lons1, lats1) lons2 = np.array([[0, 2], [0, 2]]) lats2 = np.array([[0, 0], [2, 2]]) area2 = geometry.SwathDefinition(lons2, lats2) self.assertTrue(area1.overlaps(area2)) self.assertTrue(area2.overlaps(area1)) lons1 = np.array([[-1, 0], [-1, 0]]) lats1 = np.array([[1, 2], [-1, 0]]) area1 = geometry.SwathDefinition(lons1, lats1) lons2 = np.array([[1, 2], [1, 2]]) lats2 = np.array([[1, 2], [-1, 0]]) area2 = geometry.SwathDefinition(lons2, lats2) self.assertFalse(area1.overlaps(area2)) self.assertFalse(area2.overlaps(area1)) def test_overlap_rate(self): """Test how much two areas overlap. """ lons1 = np.array([[-1, 1], [-1, 1]]) lats1 = np.array([[1, 1], [-1, -1]]) area1 = geometry.SwathDefinition(lons1, lats1) lons2 = np.array([[0, 2], [0, 2]]) lats2 = np.array([[0, 0], [2, 2]]) area2 = geometry.SwathDefinition(lons2, lats2) self.assertAlmostEqual(area1.overlap_rate(area2), 0.25, 3) self.assertAlmostEqual(area2.overlap_rate(area1), 0.25, 3) lons1 = np.array([[82.829699999999974, 36.888300000000001], [98.145499999999984, 2.8773]]) lats1 = np.array([[60.5944, 52.859999999999999], [80.395899999999997, 66.7547]]) area1 = geometry.SwathDefinition(lons1, lats1) lons2 = np.array([[7.8098183315148422, 26.189349044600252], [7.8098183315148422, 26.189349044600252]]) lats2 = np.array([[62.953206630716465, 62.953206630716465], [53.301561187195546, 53.301561187195546]]) area2 = geometry.SwathDefinition(lons2, lats2) self.assertAlmostEqual(area1.overlap_rate(area2), 0.07, 2) self.assertAlmostEqual(area2.overlap_rate(area1), 0.012, 3) lons1 = np.array([[82.829699999999974, 36.888300000000001], [98.145499999999984, 2.8773]]) lats1 = np.array([[60.5944, 52.859999999999999], [80.395899999999997, 66.7547]]) area1 = geometry.SwathDefinition(lons1, lats1) lons2 = np.array([[12.108984194981202, 30.490647126520301], [12.108984194981202, 30.490647126520301]]) lats2 = np.array([[65.98228561983025, 65.98228561983025], [57.304862819933433, 57.304862819933433]]) area2 = geometry.SwathDefinition(lons2, lats2) self.assertAlmostEqual(area1.overlap_rate(area2), 0.509, 2) self.assertAlmostEqual(area2.overlap_rate(area1), 0.0685, 3) class TestSphereGeometry(unittest.TestCase): """Testing sphere geometry from this module. """ def test_angle(self): """Testing the angle value between two arcs. """ base = 0 p0_ = Coordinate(base, base) p1_ = Coordinate(base, base + 1) p2_ = Coordinate(base + 1, base) p3_ = Coordinate(base, base - 1) p4_ = Coordinate(base - 1, base) arc1 = Arc(p0_, p1_) arc2 = Arc(p0_, p2_) arc3 = Arc(p0_, p3_) arc4 = Arc(p0_, p4_) self.assertAlmostEqual(arc1.angle(arc2), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc2.angle(arc3), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc3.angle(arc4), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc4.angle(arc1), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc1.angle(arc4), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc4.angle(arc3), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc3.angle(arc2), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc2.angle(arc1), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc1.angle(arc3), math.pi, msg="this should be pi") self.assertAlmostEqual(arc3.angle(arc1), math.pi, msg="this should be pi") self.assertAlmostEqual(arc2.angle(arc4), math.pi, msg="this should be pi") self.assertAlmostEqual(arc4.angle(arc2), math.pi, msg="this should be pi") p5_ = Coordinate(base + 1, base + 1) p6_ = Coordinate(base + 1, base - 1) p7_ = Coordinate(base - 1, base - 1) p8_ = Coordinate(base - 1, base + 1) arc5 = Arc(p0_, p5_) arc6 = Arc(p0_, p6_) arc7 = Arc(p0_, p7_) arc8 = Arc(p0_, p8_) self.assertAlmostEqual(arc1.angle(arc5), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(arc5.angle(arc2), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(arc2.angle(arc6), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(arc6.angle(arc3), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(arc3.angle(arc7), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(arc7.angle(arc4), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(arc4.angle(arc8), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(arc8.angle(arc1), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(arc1.angle(arc6), 3 * math.pi / 4, 3, msg="this should be 3pi/4") c0_ = Coordinate(180, 0) c1_ = Coordinate(180, 1) c2_ = Coordinate(-179, 0) c3_ = Coordinate(-180, -1) c4_ = Coordinate(179, 0) arc1 = Arc(c0_, c1_) arc2 = Arc(c0_, c2_) arc3 = Arc(c0_, c3_) arc4 = Arc(c0_, c4_) self.assertAlmostEqual(arc1.angle(arc2), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc2.angle(arc3), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc3.angle(arc4), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc4.angle(arc1), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc1.angle(arc4), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc4.angle(arc3), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc3.angle(arc2), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc2.angle(arc1), -math.pi / 2, msg="this should be -pi/2") # case of the north pole c0_ = Coordinate(0, 90) c1_ = Coordinate(0, 89) c2_ = Coordinate(-90, 89) c3_ = Coordinate(180, 89) c4_ = Coordinate(90, 89) arc1 = Arc(c0_, c1_) arc2 = Arc(c0_, c2_) arc3 = Arc(c0_, c3_) arc4 = Arc(c0_, c4_) self.assertAlmostEqual(arc1.angle(arc2), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc2.angle(arc3), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc3.angle(arc4), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc4.angle(arc1), math.pi / 2, msg="this should be pi/2") self.assertAlmostEqual(arc1.angle(arc4), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc4.angle(arc3), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc3.angle(arc2), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(arc2.angle(arc1), -math.pi / 2, msg="this should be -pi/2") self.assertAlmostEqual(Arc(c1_, c2_).angle(arc1), math.pi / 4, 3, msg="this should be pi/4") self.assertAlmostEqual(Arc(c4_, c3_).angle(arc4), -math.pi / 4, 3, msg="this should be -pi/4") self.assertAlmostEqual(Arc(c1_, c4_).angle(arc1), -math.pi / 4, 3, msg="this should be -pi/4") def test_intersects(self): """Test if two arcs intersect. """ p0_ = Coordinate(0, 0) p1_ = Coordinate(0, 1) p2_ = Coordinate(1, 0) p3_ = Coordinate(0, -1) p4_ = Coordinate(-1, 0) p5_ = Coordinate(1, 1) p6_ = Coordinate(1, -1) arc13 = Arc(p1_, p3_) arc24 = Arc(p2_, p4_) arc32 = Arc(p3_, p2_) arc41 = Arc(p4_, p1_) arc40 = Arc(p4_, p0_) arc56 = Arc(p5_, p6_) arc45 = Arc(p4_, p5_) arc02 = Arc(p0_, p2_) arc35 = Arc(p3_, p5_) self.assertTrue(arc13.intersects(arc24)) self.assertFalse(arc32.intersects(arc41)) self.assertFalse(arc56.intersects(arc40)) self.assertFalse(arc56.intersects(arc40)) self.assertFalse(arc45.intersects(arc02)) self.assertTrue(arc35.intersects(arc24)) p0_ = Coordinate(180, 0) p1_ = Coordinate(180, 1) p2_ = Coordinate(-179, 0) p3_ = Coordinate(-180, -1) p4_ = Coordinate(179, 0) p5_ = Coordinate(-179, 1) p6_ = Coordinate(-179, -1) arc13 = Arc(p1_, p3_) arc24 = Arc(p2_, p4_) arc32 = Arc(p3_, p2_) arc41 = Arc(p4_, p1_) arc40 = Arc(p4_, p0_) arc56 = Arc(p5_, p6_) arc45 = Arc(p4_, p5_) arc02 = Arc(p0_, p2_) arc35 = Arc(p3_, p5_) self.assertTrue(arc13.intersects(arc24)) self.assertFalse(arc32.intersects(arc41)) self.assertFalse(arc56.intersects(arc40)) self.assertFalse(arc56.intersects(arc40)) self.assertFalse(arc45.intersects(arc02)) self.assertTrue(arc35.intersects(arc24)) # case of the north pole p0_ = Coordinate(0, 90) p1_ = Coordinate(0, 89) p2_ = Coordinate(90, 89) p3_ = Coordinate(180, 89) p4_ = Coordinate(-90, 89) p5_ = Coordinate(45, 89) p6_ = Coordinate(135, 89) arc13 = Arc(p1_, p3_) arc24 = Arc(p2_, p4_) arc32 = Arc(p3_, p2_) arc41 = Arc(p4_, p1_) arc40 = Arc(p4_, p0_) arc56 = Arc(p5_, p6_) arc45 = Arc(p4_, p5_) arc02 = Arc(p0_, p2_) arc35 = Arc(p3_, p5_) self.assertTrue(arc13.intersects(arc24)) self.assertFalse(arc32.intersects(arc41)) self.assertFalse(arc56.intersects(arc40)) self.assertFalse(arc56.intersects(arc40)) self.assertFalse(arc45.intersects(arc02)) self.assertTrue(arc35.intersects(arc24)) def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(TestOverlap)) mysuite.addTest(loader.loadTestsFromTestCase(TestSphereGeometry)) return mysuite if __name__ == '__main__': unittest.main() pyresample-1.2.9/pyresample/test/test_swath.py000066400000000000000000000063541302372600000216040ustar00rootroot00000000000000from __future__ import with_statement import os import sys import unittest import warnings warnings.simplefilter("always") import numpy as np from pyresample.test.utils import catch_warnings from pyresample import kd_tree, geometry if sys.version_info < (2, 7): import unittest2 as unittest else: import unittest class Test(unittest.TestCase): filename = os.path.abspath(os.path.join(os.path.dirname(__file__), 'test_files', 'ssmis_swath.npz')) data = np.load(filename)['data'] lons = data[:, 0].astype(np.float64) lats = data[:, 1].astype(np.float64) tb37v = data[:, 2].astype(np.float64) # screen out the fill values fvalue = -10000000000.0 valid_fov = (lons != fvalue) * (lats != fvalue) * (tb37v != fvalue) lons = lons[valid_fov] lats = lats[valid_fov] tb37v = tb37v[valid_fov] def test_self_map(self): swath_def = geometry.SwathDefinition(lons=self.lons, lats=self.lats) with catch_warnings() as w: res = kd_tree.resample_gauss(swath_def, self.tb37v.copy(), swath_def, radius_of_influence=70000, sigmas=56500) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') if sys.platform == 'darwin': # OSX seems to get slightly different results for `_spatial_mp.Cartesian` truth_value = 668848.144817 else: truth_value = 668848.082208 self.assertAlmostEqual(res.sum() / 100., truth_value, 1, msg='Failed self mapping swath for 1 channel') def test_self_map_multi(self): data = np.column_stack((self.tb37v, self.tb37v, self.tb37v)) swath_def = geometry.SwathDefinition(lons=self.lons, lats=self.lats) with catch_warnings() as w: res = kd_tree.resample_gauss(swath_def, data, swath_def, radius_of_influence=70000, sigmas=[56500, 56500, 56500]) self.assertFalse( len(w) != 1, 'Failed to create neighbour radius warning') self.assertFalse(('Possible more' not in str( w[0].message)), 'Failed to create correct neighbour radius warning') if sys.platform == 'darwin': # OSX seems to get slightly different results for `_spatial_mp.Cartesian` truth_value = 668848.144817 else: truth_value = 668848.082208 self.assertAlmostEqual(res[:, 0].sum() / 100., truth_value, 1, msg='Failed self mapping swath multi for channel 1') self.assertAlmostEqual(res[:, 1].sum() / 100., truth_value, 1, msg='Failed self mapping swath multi for channel 2') self.assertAlmostEqual(res[:, 2].sum() / 100., truth_value, 1, msg='Failed self mapping swath multi for channel 3') def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(Test)) return mysuite pyresample-1.2.9/pyresample/test/test_utils.py000066400000000000000000000057111302372600000216120ustar00rootroot00000000000000import os import unittest from pyresample import utils import numpy as np def tmp(f): f.tmp = True return f class Test(unittest.TestCase): def test_area_parser(self): ease_nh, ease_sh = utils.parse_area_file(os.path.join(os.path.dirname(__file__), 'test_files', 'areas.cfg'), 'ease_nh', 'ease_sh') nh_found = (ease_nh.__str__() == """Area ID: ease_nh Name: Arctic EASE grid Projection ID: ease_nh Projection: {'a': '6371228.0', 'lat_0': '90', 'lon_0': '0', 'proj': 'laea', 'units': 'm'} Number of columns: 425 Number of rows: 425 Area extent: (-5326849.0625, -5326849.0625, 5326849.0625, 5326849.0625)""") sh_found = (ease_sh.__str__() == """Area ID: ease_sh Name: Antarctic EASE grid Projection ID: ease_sh Projection: {'a': '6371228.0', 'lat_0': '-90', 'lon_0': '0', 'proj': 'laea', 'units': 'm'} Number of columns: 425 Number of rows: 425 Area extent: (-5326849.0625, -5326849.0625, 5326849.0625, 5326849.0625)""") self.assertTrue( nh_found and sh_found, msg='Failed to parse areas correctly') def test_load_area(self): ease_nh = utils.load_area(os.path.join(os.path.dirname(__file__), 'test_files', 'areas.cfg'), 'ease_nh') nh_found = (ease_nh.__str__() == """Area ID: ease_nh Name: Arctic EASE grid Projection ID: ease_nh Projection: {'a': '6371228.0', 'lat_0': '90', 'lon_0': '0', 'proj': 'laea', 'units': 'm'} Number of columns: 425 Number of rows: 425 Area extent: (-5326849.0625, -5326849.0625, 5326849.0625, 5326849.0625)""") self.assertTrue(nh_found, msg='Failed to load area correctly') def test_not_found_exception(self): self.assertRaises(utils.AreaNotFound, utils.parse_area_file, os.path.join( os.path.dirname(__file__), 'test_files', 'areas.cfg'), 'no_area') def test_wrap_longitudes(self): # test that we indeed wrap to [-180:+180[ step = 60 lons = np.arange(-360, 360 + step, step) self.assertTrue( (lons.min() < -180) and (lons.max() >= 180) and (+180 in lons)) wlons = utils.wrap_longitudes(lons) self.assertFalse( (wlons.min() < -180) or (wlons.max() >= 180) or (+180 in wlons)) def test_unicode_proj4_string(self): """Test that unicode is accepted for area creation. """ utils.get_area_def(u"eurol", u"eurol", u"bla", u'+proj=stere +a=6378273 +b=6356889.44891 +lat_0=90 +lat_ts=70 +lon_0=-45', 1000, 1000, (-1000, -1000, 1000, 1000)) def suite(): """The test suite. """ loader = unittest.TestLoader() mysuite = unittest.TestSuite() mysuite.addTest(loader.loadTestsFromTestCase(Test)) return mysuite pyresample-1.2.9/pyresample/test/utils.py000066400000000000000000000124251302372600000205530ustar00rootroot00000000000000#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright (c) 2016 David Hoese # Author(s): # David Hoese # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """Utilities for testing. This mostly takes from astropy's method for checking warnings during tests. """ import sys import six import types import warnings _deprecations_as_exceptions = False _include_astropy_deprecations = False AstropyDeprecationWarning = None AstropyPendingDeprecationWarning = None def treat_deprecations_as_exceptions(): """ Turn all DeprecationWarnings (which indicate deprecated uses of Python itself or Numpy, but not within Astropy, where we use our own deprecation warning class) into exceptions so that we find out about them early. This completely resets the warning filters and any "already seen" warning state. """ # First, totally reset the warning state for module in list(six.itervalues(sys.modules)): # We don't want to deal with six.MovedModules, only "real" # modules. if (isinstance(module, types.ModuleType) and hasattr(module, '__warningregistry__')): del module.__warningregistry__ if not _deprecations_as_exceptions: return warnings.resetwarnings() # Hide the next couple of DeprecationWarnings warnings.simplefilter('ignore', DeprecationWarning) # Here's the wrinkle: a couple of our third-party dependencies # (py.test and scipy) are still using deprecated features # themselves, and we'd like to ignore those. Fortunately, those # show up only at import time, so if we import those things *now*, # before we turn the warnings into exceptions, we're golden. try: # A deprecated stdlib module used by py.test import compiler # pylint: disable=W0611 except ImportError: pass try: import scipy # pylint: disable=W0611 except ImportError: pass # Now, start over again with the warning filters warnings.resetwarnings() # Now, turn DeprecationWarnings into exceptions warnings.filterwarnings("error", ".*", DeprecationWarning) # Only turn astropy deprecation warnings into exceptions if requested if _include_astropy_deprecations: warnings.filterwarnings("error", ".*", AstropyDeprecationWarning) warnings.filterwarnings("error", ".*", AstropyPendingDeprecationWarning) if sys.version_info[:2] >= (3, 4): # py.test reads files with the 'U' flag, which is now # deprecated in Python 3.4. warnings.filterwarnings( "ignore", r"'U' mode is deprecated", DeprecationWarning) # BeautifulSoup4 triggers a DeprecationWarning in stdlib's # html module.x warnings.filterwarnings( "ignore", r"The strict argument and mode are deprecated\.", DeprecationWarning) warnings.filterwarnings( "ignore", r"The value of convert_charrefs will become True in 3\.5\. " r"You are encouraged to set the value explicitly\.", DeprecationWarning) if sys.version_info[:2] >= (3, 5): # py.test raises this warning on Python 3.5. # This can be removed when fixed in py.test. # See https://github.com/pytest-dev/pytest/pull/1009 warnings.filterwarnings( "ignore", r"inspect\.getargspec\(\) is deprecated, use " r"inspect\.signature\(\) instead", DeprecationWarning) class catch_warnings(warnings.catch_warnings): """ A high-powered version of warnings.catch_warnings to use for testing and to make sure that there is no dependence on the order in which the tests are run. This completely blitzes any memory of any warnings that have appeared before so that all warnings will be caught and displayed. ``*args`` is a set of warning classes to collect. If no arguments are provided, all warnings are collected. Use as follows:: with catch_warnings(MyCustomWarning) as w: do.something.bad() assert len(w) > 0 """ def __init__(self, *classes): super(catch_warnings, self).__init__(record=True) self.classes = classes def __enter__(self): warning_list = super(catch_warnings, self).__enter__() treat_deprecations_as_exceptions() if len(self.classes) == 0: warnings.simplefilter('always') else: warnings.simplefilter('ignore') for cls in self.classes: warnings.simplefilter('always', cls) return warning_list def __exit__(self, type, value, traceback): treat_deprecations_as_exceptions() pyresample-1.2.9/pyresample/utils.py000066400000000000000000000252151302372600000175750ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010-2015 # # Authors: # Esben S. Nielsen # Thomas Lavergne # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . """Utility functions for pyresample""" from __future__ import absolute_import import numpy as np from configobj import ConfigObj import pyresample as pr import six class AreaNotFound(Exception): """Exception raised when specified are is no found in file""" pass def load_area(area_file_name, *regions): """Load area(s) from area file Parameters ----------- area_file_name : str Path to area definition file regions : str argument list Regions to parse. If no regions are specified all regions in the file are returned Returns ------- area_defs : object or list If one area name is specified a single AreaDefinition object is returned If several area names are specified a list of AreaDefinition objects is returned Raises ------ AreaNotFound: If a specified area name is not found """ area_list = parse_area_file(area_file_name, *regions) if len(area_list) == 1: return area_list[0] else: return area_list def parse_area_file(area_file_name, *regions): """Parse area information from area file Parameters ----------- area_file_name : str Path to area definition file regions : str argument list Regions to parse. If no regions are specified all regions in the file are returned Returns ------- area_defs : list List of AreaDefinition objects Raises ------ AreaNotFound: If a specified area is not found """ area_file = open(area_file_name, 'r') area_list = list(regions) if len(area_list) == 0: select_all_areas = True area_defs = [] else: select_all_areas = False area_defs = [None for i in area_list] # Extract area from file in_area = False for line in area_file.readlines(): if not in_area: if 'REGION' in line: area_id = line.replace('REGION:', ''). \ replace('{', '').strip() if area_id in area_list or select_all_areas: in_area = True area_content = '' elif '};' in line: in_area = False if select_all_areas: area_defs.append(_create_area(area_id, area_content)) else: area_defs[area_list.index(area_id)] = _create_area(area_id, area_content) else: area_content += line area_file.close() # Check if all specified areas were found if not select_all_areas: for i, area in enumerate(area_defs): if area is None: raise AreaNotFound('Area "%s" not found in file "%s"' % (area_list[i], area_file_name)) return area_defs def _create_area(area_id, area_content): """Parse area configuration""" config_obj = area_content.replace('{', '').replace('};', '') config_obj = ConfigObj([line.replace(':', '=', 1) for line in config_obj.splitlines()]) config = config_obj.dict() config['REGION'] = area_id try: string_types = basestring except NameError: string_types = str if not isinstance(config['NAME'], string_types): config['NAME'] = ', '.join(config['NAME']) config['XSIZE'] = int(config['XSIZE']) config['YSIZE'] = int(config['YSIZE']) config['AREA_EXTENT'][0] = config['AREA_EXTENT'][0].replace('(', '') config['AREA_EXTENT'][3] = config['AREA_EXTENT'][3].replace(')', '') for i, val in enumerate(config['AREA_EXTENT']): config['AREA_EXTENT'][i] = float(val) config['PCS_DEF'] = _get_proj4_args(config['PCS_DEF']) return pr.geometry.AreaDefinition(config['REGION'], config['NAME'], config['PCS_ID'], config['PCS_DEF'], config['XSIZE'], config['YSIZE'], config['AREA_EXTENT']) def get_area_def(area_id, area_name, proj_id, proj4_args, x_size, y_size, area_extent): """Construct AreaDefinition object from arguments Parameters ----------- area_id : str ID of area proj_id : str ID of projection area_name :str Description of area proj4_args : list or str Proj4 arguments as list of arguments or string x_size : int Number of pixel in x dimension y_size : int Number of pixel in y dimension area_extent : list Area extent as a list of ints (LL_x, LL_y, UR_x, UR_y) Returns ------- area_def : object AreaDefinition object """ proj_dict = _get_proj4_args(proj4_args) return pr.geometry.AreaDefinition(area_id, area_name, proj_id, proj_dict, x_size, y_size, area_extent) def generate_quick_linesample_arrays(source_area_def, target_area_def, nprocs=1): """Generate linesample arrays for quick grid resampling Parameters ----------- source_area_def : object Source area definition as AreaDefinition object target_area_def : object Target area definition as AreaDefinition object nprocs : int, optional Number of processor cores to be used Returns ------- (row_indices, col_indices) : tuple of numpy arrays """ if not (isinstance(source_area_def, pr.geometry.AreaDefinition) and isinstance(target_area_def, pr.geometry.AreaDefinition)): raise TypeError('source_area_def and target_area_def must be of type ' 'geometry.AreaDefinition') lons, lats = target_area_def.get_lonlats(nprocs) source_pixel_y, source_pixel_x = pr.grid.get_linesample(lons, lats, source_area_def, nprocs=nprocs) source_pixel_x = _downcast_index_array(source_pixel_x, source_area_def.shape[1]) source_pixel_y = _downcast_index_array(source_pixel_y, source_area_def.shape[0]) return source_pixel_y, source_pixel_x def generate_nearest_neighbour_linesample_arrays(source_area_def, target_area_def, radius_of_influence, nprocs=1): """Generate linesample arrays for nearest neighbour grid resampling Parameters ----------- source_area_def : object Source area definition as AreaDefinition object target_area_def : object Target area definition as AreaDefinition object radius_of_influence : float Cut off distance in meters nprocs : int, optional Number of processor cores to be used Returns ------- (row_indices, col_indices) : tuple of numpy arrays """ if not (isinstance(source_area_def, pr.geometry.AreaDefinition) and isinstance(target_area_def, pr.geometry.AreaDefinition)): raise TypeError('source_area_def and target_area_def must be of type ' 'geometry.AreaDefinition') valid_input_index, valid_output_index, index_array, distance_array = \ pr.kd_tree.get_neighbour_info(source_area_def, target_area_def, radius_of_influence, neighbours=1, nprocs=nprocs) # Enumerate rows and cols rows = np.fromfunction(lambda i, j: i, source_area_def.shape, dtype=np.int32).ravel() cols = np.fromfunction(lambda i, j: j, source_area_def.shape, dtype=np.int32).ravel() # Reduce to match resampling data set rows_valid = rows[valid_input_index] cols_valid = cols[valid_input_index] # Get result using array indexing number_of_valid_points = valid_input_index.sum() index_mask = (index_array == number_of_valid_points) index_array[index_mask] = 0 row_sample = rows_valid[index_array] col_sample = cols_valid[index_array] row_sample[index_mask] = -1 col_sample[index_mask] = -1 # Reshape to correct shape row_indices = row_sample.reshape(target_area_def.shape) col_indices = col_sample.reshape(target_area_def.shape) row_indices = _downcast_index_array(row_indices, source_area_def.shape[0]) col_indices = _downcast_index_array(col_indices, source_area_def.shape[1]) return row_indices, col_indices def fwhm2sigma(fwhm): """Calculate sigma for gauss function from FWHM (3 dB level) Parameters ---------- fwhm : float FWHM of gauss function (3 dB level of beam footprint) Returns ------- sigma : float sigma for use in resampling gauss function """ return fwhm / (2 * np.sqrt(np.log(2))) def _get_proj4_args(proj4_args): """Create dict from proj4 args """ if isinstance(proj4_args, (str, six.text_type)): proj_config = ConfigObj(str(proj4_args).replace('+', '').split()) else: proj_config = ConfigObj(proj4_args) return proj_config.dict() def _downcast_index_array(index_array, size): """Try to downcast array to uint16 """ if size <= np.iinfo(np.uint16).max: mask = (index_array < 0) | (index_array >= size) index_array[mask] = size index_array = index_array.astype(np.uint16) return index_array def wrap_longitudes(lons): """Wrap longitudes to the [-180:+180[ validity range (preserves dtype) Parameters ---------- lons : numpy array Longitudes in degrees Returns ------- lons : numpy array Longitudes wrapped into [-180:+180[ validity range """ lons_wrap = (lons + 180) % (360) - 180 return lons_wrap.astype(lons.dtype) pyresample-1.2.9/pyresample/version.py000066400000000000000000000014261302372600000201200ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2010, 2014, 2015 Esben S. Nielsen # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or (at your option) any # later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . __version__ = '1.2.9' pyresample-1.2.9/readthedocs.yml000066400000000000000000000001151302372600000167020ustar00rootroot00000000000000requirements_file: "docs/requirements.txt" python: setup_py_install: truepyresample-1.2.9/requirements.txt000066400000000000000000000000561302372600000171620ustar00rootroot00000000000000git+https://github.com/matplotlib/basemap.git pyresample-1.2.9/setup.cfg000066400000000000000000000001731302372600000155170ustar00rootroot00000000000000[bdist_rpm] requires=numpy pykdtree numexpr pyproj python-configobj release=1 doc_files = docs/Makefile docs/source/*.rst pyresample-1.2.9/setup.py000066400000000000000000000110301302372600000154020ustar00rootroot00000000000000# pyresample, Resampling of remote sensing image data in python # # Copyright (C) 2012, 2014, 2015 Esben S. Nielsen # # This program is free software: you can redistribute it and/or modify it under # the terms of the GNU Lesser General Public License as published by the Free # Software Foundation, either version 3 of the License, or #(at your option) any later version. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more # details. # # You should have received a copy of the GNU Lesser General Public License along # with this program. If not, see . import imp # workaround python bug: http://bugs.python.org/issue15881#msg170215 import multiprocessing import os import sys from setuptools import Extension, find_packages, setup from setuptools.command.build_ext import build_ext as _build_ext version = imp.load_source('pyresample.version', 'pyresample/version.py') requirements = ['setuptools>=3.2', 'pyproj', 'numpy', 'configobj', 'pykdtree>=1.1.1'] extras_require = {'pykdtree': ['pykdtree>=1.1.1'], 'numexpr': ['numexpr'], 'quicklook': ['matplotlib', 'basemap', 'pillow']} if sys.version_info < (2, 6): # multiprocessing is not in the standard library requirements.append('multiprocessing') if sys.platform.startswith("win"): extra_compile_args = [] else: extra_compile_args = ["-O3", "-Wno-unused-function"] extensions = [ Extension("pyresample.ewa._ll2cr", sources=["pyresample/ewa/_ll2cr.pyx"], extra_compile_args=extra_compile_args), Extension("pyresample.ewa._fornav", sources=["pyresample/ewa/_fornav.pyx", "pyresample/ewa/_fornav_templates.cpp"], language="c++", extra_compile_args=extra_compile_args, depends=["pyresample/ewa/_fornav_templates.h"]) ] try: from Cython.Build import cythonize except ImportError: cythonize = None def set_builtin(name, value): if isinstance(__builtins__, dict): __builtins__[name] = value else: setattr(__builtins__, name, value) class build_ext(_build_ext): """Work around to bootstrap numpy includes in to extensions. Copied from: http://stackoverflow.com/questions/19919905/how-to-bootstrap-numpy-installation-in-setup-py """ def finalize_options(self): _build_ext.finalize_options(self) # Prevent numpy from thinking it is still in its setup process: set_builtin('__NUMPY_SETUP__', False) import numpy self.include_dirs.append(numpy.get_include()) if __name__ == "__main__": if not os.getenv("USE_CYTHON", False) or cythonize is None: print( "Cython will not be used. Use environment variable 'USE_CYTHON=True' to use it") def cythonize(extensions, **_ignore): """Fake function to compile from C/C++ files instead of compiling .pyx files with cython. """ for extension in extensions: sources = [] for sfile in extension.sources: path, ext = os.path.splitext(sfile) if ext in ('.pyx', '.py'): if extension.language == 'c++': ext = '.cpp' else: ext = '.c' sfile = path + ext sources.append(sfile) extension.sources[:] = sources return extensions setup(name='pyresample', version=version.__version__, description='Resampling of remote sensing data in Python', author='Thomas Lavergne', author_email='t.lavergne@met.no', package_dir={'pyresample': 'pyresample'}, packages=find_packages(), setup_requires=['numpy'], install_requires=requirements, extras_require=extras_require, cmdclass={'build_ext': build_ext}, ext_modules=cythonize(extensions), test_suite='pyresample.test.suite', zip_safe=False, classifiers=[ 'Development Status :: 5 - Production/Stable', 'License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)', 'Programming Language :: Python', 'Operating System :: OS Independent', 'Intended Audience :: Science/Research', 'Topic :: Scientific/Engineering' ] )