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‎.github/workflows/cygwin.yml‎

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python38-cython python38-pip python38-wheel python38-cffi
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python38-pytz python38-setuptools python38-pytest
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python38-hypothesis liblapack-devel libopenblas
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gcc-fortran git dash
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gcc-fortran gcc-g++ git dash
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- name: Set Windows PATH
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uses: egor-tensin/cleanup-path@v1
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with:

‎doc/changelog/1.21.3-changelog.rst‎

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Contributors
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============
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A total of 7 people contributed to this release. People with a "+" by their
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names contributed a patch for the first time.
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* Aaron Meurer
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* Bas van Beek
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* Charles Harris
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* Developer-Ecosystem-Engineering +
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* Kevin Sheppard
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* Sebastian Berg
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* Warren Weckesser
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Pull requests merged
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====================
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A total of 8 pull requests were merged for this release.
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* `#19745 <https://github.com/numpy/numpy/pull/19745>`__: ENH: Add dtype-support to 3 `generic`/`ndarray` methods
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* `#19955 <https://github.com/numpy/numpy/pull/19955>`__: BUG: Resolve Divide by Zero on Apple silicon + test failures...
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* `#19958 <https://github.com/numpy/numpy/pull/19958>`__: MAINT: Mark type-check-only ufunc subclasses as ufunc aliases...
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* `#19994 <https://github.com/numpy/numpy/pull/19994>`__: BUG: np.tan(np.inf) test failure
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* `#20080 <https://github.com/numpy/numpy/pull/20080>`__: BUG: Correct incorrect advance in PCG with emulated int128
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* `#20081 <https://github.com/numpy/numpy/pull/20081>`__: BUG: Fix NaT handling in the PyArray_CompareFunc for datetime...
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* `#20082 <https://github.com/numpy/numpy/pull/20082>`__: DOC: Ensure that we add documentation also as to the dict for...
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* `#20106 <https://github.com/numpy/numpy/pull/20106>`__: BUG: core: result_type(0, np.timedelta64(4)) would seg. fault.

‎doc/source/release.rst‎

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:maxdepth: 3
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1.22.0 <release/1.22.0-notes>
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1.21.3 <release/1.21.3-notes>
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1.21.2 <release/1.21.2-notes>
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1.21.1 <release/1.21.1-notes>
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1.21.0 <release/1.21.0-notes>

‎doc/source/release/1.21.3-notes.rst‎

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.. currentmodule:: numpy
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==========================
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NumPy 1.21.3 Release Notes
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==========================
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NumPy 1.21.3 is a maintenance release that fixes a few bugs discovered after
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1.21.2. It also provides 64 bit Python 3.10.0 wheels. Note a few oddities about
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Python 3.10:
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* There are no 32 bit wheels for Windows, Mac, or Linux.
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* The Mac Intel builds are only available in universal2 wheels.
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The Python versions supported in this release are 3.7-3.10. If you want to
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compile your own version using gcc-11, you will need to use gcc-11.2+ to avoid
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problems.
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Contributors
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============
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A total of 7 people contributed to this release. People with a "+" by their
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names contributed a patch for the first time.
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* Aaron Meurer
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* Bas van Beek
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* Charles Harris
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* Developer-Ecosystem-Engineering +
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* Kevin Sheppard
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* Sebastian Berg
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* Warren Weckesser
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Pull requests merged
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====================
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A total of 8 pull requests were merged for this release.
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* `#19745 <https://github.com/numpy/numpy/pull/19745>`__: ENH: Add dtype-support to 3 ```generic``/``ndarray`` methods
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* `#19955 <https://github.com/numpy/numpy/pull/19955>`__: BUG: Resolve Divide by Zero on Apple silicon + test failures...
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* `#19958 <https://github.com/numpy/numpy/pull/19958>`__: MAINT: Mark type-check-only ufunc subclasses as ufunc aliases...
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* `#19994 <https://github.com/numpy/numpy/pull/19994>`__: BUG: np.tan(np.inf) test failure
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* `#20080 <https://github.com/numpy/numpy/pull/20080>`__: BUG: Correct incorrect advance in PCG with emulated int128
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* `#20081 <https://github.com/numpy/numpy/pull/20081>`__: BUG: Fix NaT handling in the PyArray_CompareFunc for datetime...
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* `#20082 <https://github.com/numpy/numpy/pull/20082>`__: DOC: Ensure that we add documentation also as to the dict for...
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* `#20106 <https://github.com/numpy/numpy/pull/20106>`__: BUG: core: result_type(0, np.timedelta64(4)) would seg. fault.

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.. image:: images/np_matrix_aggregation.png
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You can aggregate all the values in a matrix and you can aggregate them across
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columns or rows using the ``axis`` parameter::
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columns or rows using the ``axis`` parameter. To illustrate this point, let's
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look at a slightly modified dataset::
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>>> data = np.array([[1, 2], [5, 3], [4, 6]])
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>>> data
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array([[1, 2],
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[5, 3],
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[4, 6]])
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>>> data.max(axis=0)
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array([5, 6])
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>>> data.max(axis=1)
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array([2, 4, 6])
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array([2, 5, 6])
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.. image:: images/np_matrix_aggregation_row.png
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table of elements (usually numbers), all of the same type, indexed by a
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tuple of non-negative integers. In NumPy dimensions are called *axes*.
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For example, the coordinates of a point in 3D space ``[1, 2, 1]`` has
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one axis. That axis has 3 elements in it, so we say it has a length
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of 3. In the example pictured below, the array has 2 axes. The first
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axis has a length of 2, the second axis has a length of 3.
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For example, the array for the coordinates of a point in 3D space,
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``[1, 2, 1]``, has one axis. That axis has 3 elements in it, so we say
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it has a length of 3. In the example pictured below, the array has 2
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axes. The first axis has a length of 2, the second axis has a length of
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3.
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::
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- pandas
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- matplotlib
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- pydata-sphinx-theme
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- breathe
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# For linting
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- pycodestyle=2.7.0
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- gitpython