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matrix :
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include :
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- # This environment tests that scikit-learn can be built against
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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"
@@ -36,18 +43,12 @@ matrix:
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- libatlas3-base
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- libatlas-base-dev
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- libatlas-dev
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- # Python 3.5 build without SITE_JOBLIB
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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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- # Python 3.5 build
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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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- SKLEARN_SITE_JOBLIB=1 JOBLIB_VERSION="0.11"
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- if : type != cron
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- # This environment tests the latest available dependencies.
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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"
@@ -57,7 +58,7 @@ matrix:
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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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- # This environment tests scikit-learn against numpy and scipy master
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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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- python : 3.7
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