10000 Merge pull request #10 from lobpcg/master · glemaitre/scikit-learn@19cbe70 · GitHub
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Merge pull request #10 from lobpcg/master
update from latest master
2 parents c874474 + 9426b4b commit 19cbe70

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‎.circleci/config.yml

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@@ -109,9 +109,13 @@ workflows:
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version: 2
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build-doc-and-deploy:
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jobs:
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- doc
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- doc-min-dependencies
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- lint
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- doc:
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requires:
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- lint
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- doc-min-dependencies:
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requires:
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- lint
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- pypy3:
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filters:
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branches:

‎.gitignore

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# Used by mypy
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.mypy_cache/
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# files generated from a template
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sklearn/utils/seq_dataset.pyx
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sklearn/utils/seq_dataset.pxd
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sklearn/linear_model/sag_fast.pyx

‎.travis.yml

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matrix:
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include:
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# Latest dependencies on macOS with MKL
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- env: DISTRIB="conda" PYTHON_VERSION="*" INSTALL_MKL="true"
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NUMPY_VERSION="*" SCIPY_VERSION="*" CYTHON_VERSION="*"
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PILLOW_VERSION="*" JOBLIB_VERSION="*" COVERAGE=true
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language: generic
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if: type != cron
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os: osx
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# Linux environment to test that scikit-learn can be built against
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# versions of numpy, scipy with ATLAS that comes with Ubuntu Xenial 16.04
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# i.e. numpy 1.11 and scipy 0.17
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- env: DISTRIB="ubuntu" PYTHON_VERSION="3.5"
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NUMPY_VERSION="1.11.0" SCIPY_VERSION="0.17.0"
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PILLOW_VERSION="4.0.0" COVERAGE=true
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SKLEARN_SITE_JOBLIB=1 JOBLIB_VERSION="0.11"
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if: type != cron
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addons:
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apt:
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packages:
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# these only required by the DISTRIB="ubuntu" builds:
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- python3-scipy
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- libatlas3-base
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- libatlas-base-dev
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- libatlas-dev
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# Linux + Python 3.5 build with OpenBLAS and without SITE_JOBLIB
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- env: DISTRIB="conda" PYTHON_VERSION="3.5" INSTALL_MKL="false"
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NUMPY_VERSION="1.11.0" SCIPY_VERSION="0.17.0" CYTHON_VERSION="*"
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PILLOW_VERSION="4.0.0" COVERAGE=true
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if: type != cron
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# Linux environment to test the latest available dependencies and MKL.
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# It runs tests requiring pandas and PyAMG.
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# It also runs with the site joblib instead of the vendored copy of joblib.
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- env: DISTRIB="conda" PYTHON_VERSION="*" INSTALL_MKL="true"
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NUMPY_VERSION="*" SCIPY_VERSION="*" PANDAS_VERSION="*"
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CYTHON_VERSION="*" PYAMG_VERSION="*" PILLOW_VERSION="*"
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JOBLIB_VERSION="*" COVERAGE=true
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CHECK_PYTEST_SOFT_DEPENDENCY="true" TEST_DOCSTRINGS="true"
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SKLEARN_SITE_JOBLIB=1 CHECK_WARNINGS="true"
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if: type != cron
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# Linux environment to test scikit-learn against numpy and scipy master
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# installed from their CI wheels in a virtualenv with the Python
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# interpreter provided by travis.
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if: type = cron OR commit_message =~ /\[scipy-dev\]/
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install: source build_tools/travis/install.sh
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script:
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script:
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- bash build_tools/travis/test_script.sh
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- bash build_tools/travis/test_docs.sh
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- bash build_tools/travis/test_pytest_soft_dependency.sh

‎appveyor.yml

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# Install the generated wheel package to test it
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- "pip install --pre --no-index --find-links dist/ scikit-learn"
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# If there is a newer build queued for the same PR, cancel this one.
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# credits: JuliaLang developers.
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- ps: if ($env:APPVEYOR_PULL_REQUEST_NUMBER -and $env:APPVEYOR_BUILD_NUMBER -ne ((Invoke-RestMethod `
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https://ci.appveyor.com/api/projects/$env:APPVEYOR_ACCOUNT_NAME/$env:APPVEYOR_PROJECT_SLUG/history?recordsNumber=500).builds | `
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Where-Object pullRequestId -eq $env:APPVEYOR_PULL_REQUEST_NUMBER)[0].buildNumber) { `
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throw "There are newer queued builds for this pull request, failing early." }
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# Not a .NET project, we build scikit-learn in the install step instead
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build: false
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‎azure-pipelines.yml

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# Adapted from https://github.com/pandas-dev/pandas/blob/master/azure-pipelines.yml
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jobs:
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- template: build_tools/azure/posix.yml
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parameters:
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name: Linux
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vmImage: ubuntu-16.04
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matrix:
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# Linux environment to test that scikit-learn can be built against
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# versions of numpy, scipy with ATLAS that comes with Ubuntu Xenial 16.04
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# i.e. numpy 1.11 and scipy 0.17
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py35_np_atlas:
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DISTRIB: 'ubuntu'
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PYTHON_VERSION: '3.5'
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SKLEARN_SITE_JOBLIB: '1'
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JOBLIB_VERSION: '0.11'
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# Linux + Python 3.5 build with OpenBLAS and without SITE_JOBLIB
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py35_conda_openblas:
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DISTRIB: 'conda'
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PYTHON_VERSION: '3.5'
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INSTALL_MKL: 'false'
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NUMPY_VERSION: '1.11.0'
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SCIPY_VERSION: '0.17.0'
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CYTHON_VERSION: '*'
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PILLOW_VERSION: '4.0.0'
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COVERAGE: 'true'
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# Linux environment to test the latest available dependencies and MKL.
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# It runs tests requiring pandas and PyAMG.
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# It also runs with the site joblib instead of the vendored copy of joblib.
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pylatest_conda:
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DISTRIB: 'conda'
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PYTHON_VERSION: '*'
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INSTALL_MKL: 'true'
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NUMPY_VERSION: '*'
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SCIPY_VERSION: '*'
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PANDAS_VERSION: '*'
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CYTHON_VERSION: '*'
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PYAMG_VERSION: '*'
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PILLOW_VERSION: '*'
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JOBLIB_VERSION: '*'
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COVERAGE: 'true'
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CHECK_PYTEST_SOFT_DEPENDENCY: 'true'
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TEST_DOCSTRINGS: 'true'
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SKLEARN_SITE_JOBLIB: '1'
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CHECK_WARNINGS: 'true'
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- template: build_tools/azure/posix.yml
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parameters:
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name: macOS
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vmImage: xcode9-macos10.13
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matrix:
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pylatest_conda:
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DISTRIB: 'conda'
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PYTHON_VERSION: '*'
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INSTALL_MKL: 'true'
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NUMPY_VERSION: '*'
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SCIPY_VERSION: '*'
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CYTHON_VERSION: '*'
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PILLOW_VERSION: '*'
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JOBLIB_VERSION: '*'
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COVERAGE: 'true'
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- template: build_tools/azure/windows.yml
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parameters:
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name: Windows
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vmImage: vs2017-win2016
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matrix:
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py37_64:
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PYTHON_VERSION: '3.7'
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CHECK_WARNINGS: 'true'
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PYTHON_ARCH: '64'
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COVERAGE: 'true'
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py35_32:
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PYTHON_VERSION: '3.5'
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PYTHON_ARCH: '32'

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