8000 Merged changes from #14545 and further improvements · arpanchowdhry/scikit-learn@47d24af · GitHub
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Merged changes from scikit-learn#14545 and further improvements
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‎.circleci/config.yml

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@@ -49,7 +49,8 @@ jobs:
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- MKL_NUM_THREADS: 2
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- MINICONDA_PATH: ~/miniconda
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- CONDA_ENV_NAME: testenv
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- PYTHON_VERSION: 3
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# TODO: Revert to 3 when wheel issue with conda installation of python 3.7.4
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- PYTHON_VERSION: 3.7.3
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steps:
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- checkout
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- run: ./build_tools/circle/checkout_merge_commit.sh

‎benchmarks/bench_plot_nmf.py

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@@ -213,13 +213,13 @@ def fit(self, X, y=None, **params):
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return self
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def transform(self, X):
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check_is_fitted(self, 'components_')
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check_is_fitted(self)
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H = self.components_
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W, _, self.n_iter_ = self._fit_transform(X, H=H, update_H=False)
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return W
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def inverse_transform(self, W):
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check_is_fitted(self, 'components_')
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check_is_fitted(self)
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return np.dot(W, self.components_)
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def fit_transform(self, X, y=None, W=None, H=None):

‎build_tools/azure/install.sh

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@@ -24,9 +24,26 @@ make_conda() {
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source activate $VIRTUALENV
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}
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version_ge() {
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# The two version numbers are seperated with a new line is piped to sort
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# -rV. The -V activates for version number sorting and -r sorts in
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# decending order. If the first argument is the top element of the sort, it
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# is greater than or equal to the second argument.
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test "$(printf "${1}\n${2}" | sort -rV | head -n 1)" == "$1"
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}
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if [[ "$DISTRIB" == "conda" ]]; then
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TO_INSTALL="python=$PYTHON_VERSION pip pytest=$PYTEST_VERSION pytest-cov \
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numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
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# TODO
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# Remove when wheel issue is fixed with conda installations of python 3.7.4
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if [[ "$PYTHON_VERSION" == "*" ]]; then
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PINNED_PYTHON_VERSION="3.7.3"
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else
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PINNED_PYTHON_VERSION=$PYTHON_VERSION
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fi
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TO_INSTALL="python=$PINNED_PYTHON_VERSION pip pytest=$PYTEST_VERSION \
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pytest-cov numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION \
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cython=$CYTHON_VERSION joblib=$JOBLIB_VERSION"
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if [[ "$INSTALL_MKL" == "true" ]]; then
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TO_INSTALL="$TO_INSTALL matplotlib=$MATPLOTLIB_VERSION"
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fi
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# Old packages coming from the 'free' conda channel have been removed but
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# we are using them for testing Python 3.5. See
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# https://www.anaconda.com/why-we-removed-the-free-channel-in-conda-4-7/
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# for more details. restore_free_channel is defined starting from conda 4.7
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conda_version=$(conda -V | awk '{print $2}')
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if version_ge "$conda_version" "4.7.0" && [[ "$PYTHON_VERSION" == "3.5" ]]; then
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conda config --set restore_free_channel true
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fi
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make_conda $TO_INSTALL
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if [[ "$PYTHON_VERSION" == "*" ]]; then
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pip install pytest-xdist

‎build_tools/azure/test_pytest_soft_dependency.sh

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@@ -7,6 +7,8 @@ source activate $VIRTUALENV
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conda remove -y py pytest || pip uninstall -y py pytest
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if [[ "$COVERAGE" == "true" ]]; then
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# conda may remove coverage when uninstall pytest and py
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pip install coverage
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# Need to append the coverage to the existing .coverage generated by
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# running the tests. Make sure to reuse the same coverage
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# configuration as the one used by the main pytest run to be

‎build_tools/circle/build_doc.sh

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# The pipefail is requested to propagate exit code
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set -o pipefail && cd doc && make $make_args 2>&1 | tee ~/log.txt
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# Insert the version warning for deployment
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find _build/html/stable -name "*.html" | xargs sed -i '/<\/body>/ i \
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\ <script src="https://scikit-learn.org/versionwarning.js"></script>'
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cd -
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set +o pipefail
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‎doc/developers/contributing.rst

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@@ -659,6 +659,60 @@ If you often need to look at the documentation generated by CircleCI, e.g. when
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reviewing pull requests, you may find :ref:`this tip
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<viewing_rendered_html_documentation>` very handy.
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.. _testing_coverage:
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Testing and improving test coverage
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===================================
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High-quality `unit testing <https://en.wikipedia.org/wiki/Unit_testing>`_
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is a corner-stone of the scikit-learn development process. For this
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purpose, we use the `pytest <https://docs.pytest.org>`_
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package. The tests are functions appropriately named, located in `tests`
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subdirectories, that check the validity of the algorithms and the
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different options of the code.
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The full scikit-learn tests can be run using 'make' in the root folder.
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Alternatively, running 'pytest' in a folder will run all the tests of
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the corresponding subpackages.
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We expect code coverage of new features to be at least around 90%.
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For guidelines on how to use ``pytest`` efficiently, see the
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:ref:`pytest_tips`.
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Writing matplotlib related tests
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--------------------------------
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Test fixtures ensure that a set of tests will be executing with the appropriate
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initialization and cleanup. The scikit-learn test suite implements a fixture
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which can be used with ``matplotlib``.
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``pyplot``
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The ``pyplot`` fixture should be used when a test function is dealing with
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``matplotlib``. ``matplotlib`` is a soft dependency and is not required.
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This fixture is in charge of skipping the tests if ``matplotlib`` is not
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installed. In addition, figures created during the tests will be
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automatically closed once the test function has been executed.
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To use this fixture in a test function, one needs to pass it as an
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argument::
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def test_requiring_mpl_fixture(pyplot):
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# you can now safely use matplotlib
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Workflow to improve test coverage
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---------------------------------
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To test code coverage, you need to install the `coverage
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<https://pypi.org/project/coverage/>`_ package in addition to pytest.
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1. Run 'make test-coverage'. The output lists for each file the line
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numbers that are not tested.
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2. Find a low hanging fruit, looking at which lines are not tested,
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write or adapt a test specifically for these lines.
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3. Loop.
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