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Merge branch 'matplotlib:main' into tk_toolbar_tooltips
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‎.flake8

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tutorials/introductory/images.py: E402, E501
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tutorials/introductory/pyplot.py: E402, E501
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tutorials/introductory/sample_plots.py: E501
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tutorials/introductory/usage.py: E703
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tutorials/introductory/quick_start.py: E703
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tutorials/text/annotations.py: E402, E501
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tutorials/text/text_intro.py: E402
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tutorials/text/text_props.py: E501

‎.github/workflows/tests.yml

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env:
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NO_AT_BRIDGE: 1 # Necessary for GTK3 interactive test.
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NPY_DISABLE_CPU_FEATURES: "AVX512F,AVX512CD,AVX512VL,AVX512BW,AVX512DQ,AVX512_SKX"
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OPENBLAS_NUM_THREADS: 1
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PYTHONFAULTHANDLER: 1
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‎azure-pipelines.yml

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displayName: 'print env'
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- bash: |
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export NPY_DISABLE_CPU_FEATURES="AVX512F,AVX512CD,AVX512VL,AVX512BW,AVX512DQ,AVX512_SKX"
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PYTHONFAULTHANDLER=1 python -m pytest --junitxml=junit/test-results.xml -raR --maxfail=50 --timeout=300 --durations=25 --cov-report= --cov=lib -n 2 ||
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[[ "$PYTHON_VERSION" = 'Pre' ]]
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displayName: 'pytest'

‎doc/api/next_api_changes/behavior/21026-DS.rst

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3D contourf polygons placed between levels
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------------------------------------------
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The polygons used in a 3D `~mpl_toolkits.mplot3d.Axes3D.contourf` plot are
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The polygons used in a 3D `~.Axes3D.contourf` plot are
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now placed halfway between the contour levels, as each polygon represents the
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location of values that lie between two levels.

‎doc/api/next_api_changes/behavior/22063-SR.rst

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Move Axes title to not overlap with y axis offset
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Previously, Axes titles could overlap the y-axis offset text, which is often
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in the upper left corner of the axes. Now titles are moved above the offset
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text if overlapping, and autopositioning is in effect (i.e. if *y* in
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`.Axes.set_title` is *None* and :rc:`axes.titley` is also *None*).

‎doc/api/next_api_changes/removals/00001-DS.rst

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Removal of mplot3d deprecations
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The deprecated ``renderer`` arguments have been removed from:
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- `.Line3DCollection.do_3d_projection`
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- `.Patch3D.do_3d_projection`
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- `.PathPatch3D.do_3d_projection`
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- `.Path3DCollection.do_3d_projection`
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- `.Patch3DCollection.do_3d_projection`
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- `.Poly3DCollection.do_3d_projection`
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The deprecated ``project`` argument has also been removed from
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``Line3DCollection.draw()``.
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Passing arguments not specifically listed in the signatures of
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`.Axes3D.plot_surface` and `.Axes3D.plot_wireframe` is no longer supported.
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Pass any extra arguments as keyword arguments instead.
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These properties of the 3D Axes that were placed on the Renderer during draw
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have been removed:
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* ``renderer.M``
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* ``renderer.eye``
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* ``renderer.vvec``
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* ``renderer.get_axis_position``
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These attributes are all available via `.Axes3D`, which can be accessed via
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``self.axes`` on all `.Artist`\s.

‎doc/api/next_api_changes/removals/22081-AL.rst

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colorbar defaults to stealing space from the mappable's axes rather than the current axes
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Pass ``ax=plt.gca()`` to restore the previous behavior.
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Removal of deprecated ``colorbar`` APIs
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The following deprecated :mod:`.colorbar` APIs have been removed:
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``ColorbarPatch`` and ``colorbar_factory`` (use `.Colorbar` instead);
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``colorbar_doc``, ``colorbar_kw_doc``, ``make_axes_kw_doc``.

‎doc/api/prev_api_changes/api_changes_3.5.0/behaviour.rst

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3D contourf polygons placed between levels
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The polygons used in a 3D `~mpl_toolkits.mplot3d.Axes3D.contourf` plot are now
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The polygons used in a 3D `~.Axes3D.contourf` plot are now
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placed halfway between the contour levels, as each polygon represents the
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location of values that lie between two levels.
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``AxesDivider`` now defaults to rcParams-specified pads
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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`.AxesDivider.append_axes`, `.AxesDivider.new_horizontal`, and
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`.AxesDivider.new_vertical` now default to paddings specified by
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`.AxesDivider.append_axes`, ``AxesDivider.new_horizontal``, and
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``AxesDivider.new_vertical`` now default to paddings specified by
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:rc:`figure.subplot.wspace` and :rc:`figure.subplot.hspace` rather than zero.

‎doc/devel/contributing.rst

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All these helpers take a first parameter *since*, which should be set to
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the next point release, e.g. "3.x".
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You can use standard rst cross references in *alternative*.
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Expiring
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~~~~~~~~
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‎doc/devel/documenting_mpl.rst

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See the :doc:`/users/installing/index`
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See the tutorial :doc:`/tutorials/introductory/usage`
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See the tutorial :doc:`/tutorials/introductory/quick_start`
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See the example :doc:`/gallery/lines_bars_and_markers/simple_plot`
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will render as:
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See the :doc:`/users/installing/index`
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See the tutorial :doc:`/tutorials/introductory/usage`
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See the tutorial :doc:`/tutorials/introductory/quick_start`
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See the example :doc:`/gallery/lines_bars_and_markers/simple_plot`
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Tutorials are made with the exact same mechanism, except they are longer, and
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typically have more than one comment block (i.e.
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:doc:`/tutorials/introductory/usage`). The first comment block
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:doc:`/tutorials/introductory/quick_start`). The first comment block
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can be the same as the example above. Subsequent blocks of ReST text
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are delimited by a line of ``###`` characters:
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‎doc/index.rst

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Tutorials
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^^^^^^^^^
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- :doc:`Quick-start guide <tutorials/introductory/usage>`
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- :doc:`Quick-start guide <tutorials/introductory/quick_start>`
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- :doc:`Plot types <plot_types/index>`
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- `Introductory tutorials <../tutorials/index.html#introductory>`_
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- :doc:`External learning resources <users/resources/index>`
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How-tos
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^^^^^^^
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- :doc:`Example gallery <gallery/index>`
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- :doc:`Matplotlib FAQ <faq/index>`
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- :doc:`Matplotlib FAQ <users/faq/index>`
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---
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‎doc/users/getting_started/index.rst

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ax.plot(x, y)
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plt.show()
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If a plot does not show up please check :ref:`troubleshooting-faq`.
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If a plot does not show up please check :ref:`troubleshooting-faq`.
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Where to go next
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----------------
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- Check out :doc:`Plot types </plot_types/index>` to get an overview of the
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types of plots you can create with Matplotlib.
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- Learn Matplotlib from the ground up in the
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:doc:`Quick-start guide </tutorials/introductory/usage>`.
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:doc:`Quick-start guide </tutorials/introductory/quick_start>`.

‎doc/users/next_whats_new/color_support_for_math_to_image.rst

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``math_to_image`` now has a *color* keyword argument
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--------------------------------------------------------
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To easily support external libraries that rely on the MathText rendering of
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Matplotlib to generate equation images, a *color* keyword argument was added
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to `~matplotlib.mathtext.math_to_image`.
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.. code-block:: python
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from matplotlib import mathtext
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mathtext.math_to_image('$x^2$', 'filename.png', color='Maroon')

‎doc/users/next_whats_new/polygon_selector_box.rst

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PolygonSelector bounding boxes
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------------------------------
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`~matplotlib.widgets.PolygonSelector` now has a *draw_bounding_box* argument, which
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when set to `True` will draw a bounding box around the polygon once it is
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complete. The bounding box can be resized and moved, allowing the points of
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the polygon to be easily resized.

‎doc/users/prev_whats_new/whats_new_1.4.rst

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A team of students in an *Engineering Large Software Systems* course, taught
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by Prof. Anya Tafliovich at the University of Toronto, implemented a simple
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version of a quiver plot in 3D space for the mplot3d toolkit as one of their
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term project. This feature is documented in :func:`~mpl_toolkits.mplot3d.Axes3D.quiver`.
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term project. This feature is documented in `~.Axes3D.quiver`.
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The team members are: Ryan Steve D'Souza, Victor B, xbtsw, Yang Wang, David,
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Caradec Bisesar and Vlad Vassilovski.
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‎doc/users/prev_whats_new/whats_new_1.5.rst

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Support for alternate pivots in mplot3d quiver plot
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```````````````````````````````````````````````````
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Added a :code:`pivot` kwarg to :func:`~mpl_toolkits.mplot3d.Axes3D.quiver`
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Added a :code:`pivot` kwarg to `~.Axes3D.quiver`
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that controls the pivot point around which the quiver line rotates. This also
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determines the placement of the arrow head along the quiver line.
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‎doc/users/resources/index.rst

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* `Anatomy of Matplotlib - IPython Notebooks
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<https://github.com/WeatherGod/AnatomyOfMatplotlib>`_
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by Benjamin Root
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* `Beyond the Basics: Data Visualization in Python
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<https://github.com/stefmolin/python-data-viz-workshop>`_
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by Stefanie Molin

‎environment.yml

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- numpydoc>=0.8
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- packaging
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- pydata-sphinx-theme
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- scipy
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- sphinx>=1.8.1,!=2.0.0
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- sphinx-copybutton
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- sphinx-gallery>=0.10

‎examples/animation/double_pendulum.py

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from numpy import sin, cos
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import numpy as np
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import matplotlib.pyplot as plt
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import scipy.integrate as integrate
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import matplotlib.animation as animation
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from collections import deque
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L = L1 + L2 # maximal length of the combined pendulum
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M1 = 1.0 # mass of pendulum 1 in kg
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M2 = 1.0 # mass of pendulum 2 in kg
25-
t_stop = 5 # how many seconds to simulate
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t_stop = 2.5 # how many seconds to simulate
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history_len = 500 # how many trajectory points to display
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def derivs(state, t):
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def derivs(t, state):
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dydx = np.zeros_like(state)
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3231
dydx[0] = state[1]
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delta = state[2] - state[0]
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return dydx
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# create a time array from 0..t_stop sampled at 0.02 second steps
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dt = 0.02
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dt = 0.01
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t = np.arange(0, t_stop, dt)
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# th1 and th2 are the initial angles (degrees)
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# initial state
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state = np.radians([th1, w1, th2, w2])
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67-
# integrate your ODE using scipy.integrate.
68-
y = integrate.odeint(derivs, state, t)
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# integrate the ODE using Euler's method
67+
y = np.empty((len(t), 4))
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y[0] = state
69+
for i in range(1, len(t)):
70+
y[i] = y[i - 1] + derivs(t[i - 1], y[i - 1]) * dt
71+
72+
# A more accurate estimate could be obtained e.g. using scipy:
73+
#
74+
# y = scipy.integrate.solve_ivp(derivs, t[[0, -1]], state, t_eval=t).y.T
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x1 = L1*sin(y[:, 0])
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y1 = -L1*cos(y[:, 0])

‎examples/axes_grid1/demo_axes_divider.py

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ax_cb = divider.new_horizontal(size="5%", pad=0.05)
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ax_cb = divider.append_axes("right", size="5%", pad=0.05)
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divider = make_axes_locatable(ax)
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Z, extent = get_demo_image()
89-
ax2 = divider.new_horizontal(size="100%", pad=0.05)
89+
ax2 = divider.append_axes("right", size="100%", pad=0.05)
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fig1.add_axes(ax2)
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‎examples/axes_grid1/make_room_for_ylabel_using_axesgrid.py

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ax1 = plt.axes([0, 0, 1, 1])
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43-
ax2 = divider.new_horizontal("100%", pad=0.3, sharey=ax1)
43+
ax2 = divider.append_axes("right", "100%", pad=0.3, sharey=ax1)
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ax2.tick_params(labelleft=False)
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fig.add_axes(ax2)
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‎examples/lines_bars_and_markers/lines_with_ticks_demo.py

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import matplotlib.pyplot as plt
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from matplotlib import patheffects
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# Plot a straight diagonal line with ticked style path
1819
fig, ax = plt.subplots(figsize=(6, 6))
1920
ax.plot([0, 1], [0, 1], label="Line",
2021
path_effects=[patheffects.withTickedStroke(spacing=7, angle=135)])
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# Plot a curved line with ticked style path
2224
nx = 101
2325
x = np.linspace(0.0, 1.0, nx)
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y = 0.3*np.sin(x*8) + 0.4

‎examples/lines_bars_and_markers/scatter_demo2.py

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import matplotlib.pyplot as plt
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import matplotlib.cbook as cbook
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# Load a numpy record array from yahoo csv data with fields date, open, close,
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# volume, adj_close from the mpl-data/example directory. The record array
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# stores the date as an np.datetime64 with a day unit ('D') in the date column.
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# Load a numpy record array from yahoo csv data with fields date, open, high,
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# low, close, volume, adj_close from the mpl-data/sample_data directory. The
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# record array stores the date as an np.datetime64 with a day unit ('D') in
15+
# the date column.
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price_data = (cbook.get_sample_data('goog.npz', np_load=True)['price_data']
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.view(np.recarray))
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price_data = price_data[-250:] # get the most recent 250 trading days

‎examples/mplot3d/lorenz_attractor.py

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import matplotlib.pyplot as plt
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def lorenz(x, y, z, s=10, r=28, b=2.667):
21+
def lorenz(xyz, *, s=10, r=28, b=2.667):
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"""
23-
Given:
24-
x, y, z: a point of interest in three dimensional space
25-
s, r, b: parameters defining the lorenz attractor
26-
Returns:
27-
x_dot, y_dot, z_dot: values of the lorenz attractor's partial
28-
derivatives at the point x, y, z
23+
Parameters
24+
----------
25+
xyz : array-like, shape (3,)
26+
Point of interest in three dimensional space.
27+
s, r, b : float
28+
Parameters defining the Lorenz attractor.
29+
30+
Returns
31+
-------
32+
xyz_dot : array, shape (3,)
33+
Values of the Lorenz attractor's partial derivatives at *xyz*.
2934
"""
35+
x, y, z = xyz
3036
x_dot = s*(y - x)
3137
y_dot = r*x - y - x*z
3238
z_dot = x*y - b*z
33-
return x_dot, y_dot, z_dot
39+
return np.array([x_dot, y_dot, z_dot])
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3541

3642
dt = 0.01
3743
num_steps = 10000
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39-
# Need one more for the initial values
40-
xs = np.empty(num_steps + 1)
41-
ys = np.empty(num_steps + 1)
42-
zs = np.empty(num_steps + 1)
43-
44-
# Set initial values
45-
xs[0], ys[0], zs[0] = (0., 1., 1.05)
46-
45+
xyzs = np.empty((num_steps + 1, 3)) # Need one more for the initial values
46+
xyzs[0] = (0., 1., 1.05) # Set initial values
4747
# Step through "time", calculating the partial derivatives at the current point
4848
# and using them to estimate the next point
4949
for i in range(num_steps):
50-
x_dot, y_dot, z_dot = lorenz(xs[i], ys[i], zs[i])
51-
xs[i + 1] = xs[i] + (x_dot * dt)
52-
ys[i + 1] = ys[i] + (y_dot * dt)
53-
zs[i + 1] = zs[i] + (z_dot * dt)
54-
50+
xyzs[i + 1] = xyzs[i] + lorenz(xyzs[i]) * dt
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5652
# Plot
5753
ax = plt.figure().add_subplot(projection='3d')
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59-
ax.plot(xs, ys, zs, lw=0.5)
55+
ax.plot(*xyzs.T, lw=0.5)
6056
ax.set_xlabel("X Axis")
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ax.set_ylabel("Y Axis")
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ax.set_zlabel("Z Axis")

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