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Merge pull request #7284 from QuLogic/backports-2.0
Backports for 2.0
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‎.travis.yml

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@@ -41,6 +41,7 @@ env:
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- PANDAS=
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- NPROC=2
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- TEST_ARGS=--no-pep8
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- DELETE_FONT_CACHE=
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language: python
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@@ -50,7 +51,7 @@ matrix:
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env: MOCK=mock NUMPY=numpy==1.6
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- python: 3.4
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- python: 3.5
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env: PANDAS=pandas
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env: PANDAS=pandas DELETE_FONT_CACHE=1
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- python: 2.7
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env: TEST_ARGS=--pep8
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- python: 2.7
@@ -123,6 +124,9 @@ script:
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echo Testing using $NPROC processes
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echo The following args are passed to nose $NOSE_ARGS
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if [[ $BUILD_DOCS == false ]]; then
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if [[ $DELETE_FONT_CACHE == 1 ]]; then
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rm -rf ~/.cache/matplotlib
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fi
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export MPL_REPO_DIR=$PWD # needed for pep8-conformance test of the examples
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gdb -return-child-result -batch -ex r -ex bt --args python tests.py -s --processes=$NPROC --process-timeout=300 $TEST_ARGS
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else

‎doc/faq/howto_faq.rst

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@@ -14,6 +14,35 @@ How-To
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Plotting: howto
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===============
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.. _howto-datetime64:
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Plot `numpy.datetime64` values
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------------------------------
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For matplotlib to plot dates (or any scalar with units) a converter
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to float needs to be registered with the `matplolib.units` module. The
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current best converters for `datetime64` values are in `pandas`. Simply
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importing `pandas` ::
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import pandas as pd
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should be sufficient as `pandas` will try to install the converters
30+
on import. If that does not work, or you need to reset `munits.registry`
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you can explicitly install the `pandas` converters by ::
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from pandas.tseries import converter as pdtc
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pdtc.register()
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If you only want to use the `pandas` converter for `datetime64` values ::
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from pandas.tseries import converter as pdtc
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import matplotlib.units as munits
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import numpy as np
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munits.registry[np.datetime64] = pdtc.DatetimeConverter()
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.. _howto-findobj:
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Find all objects in a figure of a certain type

‎doc/mpl_toolkits/axes_grid/api/anchored_artists_api.rst

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:mod:`mpl_toolkits.axes_grid1.anchored_artists`
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===============================================
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.. automodule:: mpl_toolkits.axes_grid1.anchored_artists
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:members:
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:undoc-members:
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:show-inheritance:

‎doc/mpl_toolkits/axes_grid/api/index.rst

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.. toctree::
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anchored_artists_api.rst
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inset_locator_api.rst

‎doc/users/customizing.rst

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@@ -8,7 +8,8 @@ Using style sheets
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==================
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The ``style`` package adds support for easy-to-switch plotting "styles" with
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the same parameters as a matplotlibrc_ file.
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the same parameters as a matplotlibrc_ file (which is read at startup to
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configure matplotlib).
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There are a number of pre-defined styles provided by matplotlib. For
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example, there's a pre-defined style called "ggplot", which emulates the

‎doc/users/navigation_toolbar.rst

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@@ -15,16 +15,16 @@ the buttons at the bottom of the toolbar
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.. image:: ../../lib/matplotlib/mpl-data/images/forward_large.png
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The ``Forward`` and ``Back`` buttons
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These are akin to the web browser forward and back buttons. They
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are used to navigate back and forth between previously defined
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views. They have no meaning unless you have already navigated
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somewhere else using the pan and zoom buttons. This is analogous
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The ``Home``, ``Forward`` and ``Back`` buttons
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These are akin to a web browser's home, forward and back controls.
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``Forward`` and ``Back`` are used to navigate back and forth between
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previously defined views. They have no meaning unless you have already
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navigated somewhere else using the pan and zoom buttons. This is analogous
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to trying to click ``Back`` on your web browser before visiting a
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new page --nothing happens. ``Home`` always takes you to the
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first, default view of your data. For ``Home``, ``Forward`` and
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``Back``, think web browser where data views are web pages. Use
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the pan and zoom to rectangle to define new views.
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new page or ``Forward`` before you have gone back to a page --
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nothing happens. ``Home`` always takes you to the
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first, default view of your data. Again, all of these buttons should
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feel very familiar to any user of a web browser.
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.. image:: ../../lib/matplotlib/mpl-data/images/move_large.png
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@@ -37,11 +37,11 @@ The ``Pan/Zoom`` button
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where you released. If you press 'x' or 'y' while panning the
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motion will be constrained to the x or y axis, respectively. Press
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the right mouse button to zoom, dragging it to a new position.
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The x axis will be zoomed in proportionate to the rightward
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movement and zoomed out proportionate to the leftward movement.
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Ditto for the y axis and up/down motions. The point under your
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The x axis will be zoomed in proportionately to the rightward
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movement and zoomed out proportionately to the leftward movement.
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The same is true for the y axis and up/down motions. The point under your
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mouse when you begin the zoom remains stationary, allowing you to
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zoom to an arbitrary point in the figure. You can use the
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zoom in or out around that point as much as you wish. You can use the
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modifier keys 'x', 'y' or 'CONTROL' to constrain the zoom to the x
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axis, the y axis, or aspect ratio preserve, respectively.
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@@ -54,7 +54,7 @@ The ``Pan/Zoom`` button
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The ``Zoom-to-rectangle`` button
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Click this toolbar button to activate this mode. Put your mouse
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somewhere over and axes and press the left mouse button. Drag the
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somewhere over an axes and press the left mouse button. Drag the
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mouse while holding the button to a new location and release. The
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axes view limits will be zoomed to the rectangle you have defined.
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There is also an experimental 'zoom out to rectangle' in this mode

‎doc/users/text_intro.rst

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Text introduction
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=================
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matplotlib has excellent text support, including mathematical
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expressions, truetype support for raster and vector outputs, newline
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separated text with arbitrary rotations, and unicode support. Because
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we embed the fonts directly in the output documents, e.g., for postscript
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matplotlib has extensive text support, including support for
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mathematical expressions, truetype support for raster and
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vector outputs, newline separated text with arbitrary
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rotations, and unicode support. Because it embeds
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fonts directly in output documents, e.g., for postscript
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or PDF, what you see on the screen is what you get in the hardcopy.
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`FreeType <http://www.freetype.org/>`_ support
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produces very nice, antialiased fonts, that look good even at small
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raster sizes. matplotlib includes its own
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:mod:`matplotlib.font_manager`, thanks to Paul Barrett, which
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implements a cross platform, W3C compliant font finding algorithm.
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You have total control over every text property (font size, font
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weight, text location and color, etc) with sensible defaults set in
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the rc file. And significantly for those interested in mathematical
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:mod:`matplotlib.font_manager` (thanks to Paul Barrett), which
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implements a cross platform, `W3C <http://www.w3.org/>`
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compliant font finding algorithm.
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19+
The user has a great deal of control over text properties (font size, font
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weight, text location and color, etc.) with sensible defaults set in
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the `rc file <http://matplotlib.org/users/customizing.html>`.
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And significantly, for those interested in mathematical
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or scientific figures, matplotlib implements a large number of TeX
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math symbols and commands, to support :ref:`mathematical expressions
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math symbols and commands, supporting :ref:`mathematical expressions
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<mathtext-tutorial>` anywhere in your figure.
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* :func:`~matplotlib.pyplot.text` - add text at an arbitrary location to the ``Axes``;
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:meth:`matplotlib.axes.Axes.text` in the API.
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* :func:`~matplotlib.pyplot.xlabel` - add an axis label to the x-axis;
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* :func:`~matplotlib.pyplot.xlabel` - add a label to the x-axis;
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:meth:`matplotlib.axes.Axes.set_xlabel` in the API.
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* :func:`~matplotlib.pyplot.ylabel` - add an axis label to the y-axis;
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* :func:`~matplotlib.pyplot.ylabel` - add a label to the y-axis;
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:meth:`matplotlib.axes.Axes.set_ylabel` in the API.
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* :func:`~matplotlib.pyplot.title` - add a title to the ``Axes``;

‎doc/users/whats_new/2015-11-05_hidpi.rst

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This file was deleted.

‎examples/axes_grid/simple_anchored_artists.py

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def draw_text(ax):
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from mpl_toolkits.axes_grid1.anchored_artists import AnchoredText
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from matplotlib.offsetbox import AnchoredText
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at = AnchoredText("Figure 1a",
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loc=2, prop=dict(size=8), frameon=True,
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)

‎lib/matplotlib/backends/backend_tkagg.py

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self.window.update()
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else:
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self.canvas.draw_idle()
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# Raise the new window.
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self.canvas.manager.window.attributes('-topmost', 1)
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self.canvas.manager.window.attributes('-topmost', 0)
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self._shown = True
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def destroy(self, *args):

‎lib/matplotlib/mathtext.py

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self.fontmap = {}
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# Include Stix sized alternatives for glyphs
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self._fontmap.update({
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0 : 'STIXGeneral',
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1 : 'STIXSizeOneSym',
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2 : 'STIXSizeTwoSym',
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3 : 'STIXSizeThreeSym',
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'sf' : 'DejaVu Sans',
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'tt' : 'DejaVu Sans Mono',
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'ex' : 'DejaVu Serif Display',
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0 : 'DejaVu Serif',
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}
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class DejaVuSansFonts(DejaVuFonts):
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'sf' : 'DejaVu Sans',
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'tt' : 'DejaVu Sans Mono',
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'ex' : 'DejaVu Sans Display',
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0 : 'DejaVu Sans',
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}
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class StixFonts(UnicodeFonts):
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alternatives = state.font_output.get_sized_alternatives_for_symbol(
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state.font, c)
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2007+
xHeight = state.font_output.get_xheight(
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state.font, state.fontsize, state.dpi)
2009+
20062010
state = state.copy()
20072011
target_total = height + depth
20082012
for fontname, sym in alternatives:
20092013
state.font = fontname
20102014
char = Char(sym, state)
2011-
if char.height + char.depth >= target_total:
2015+
# Ensure that size 0 is chosen when the text is regular sized but
2016+
# with descender glyphs by subtracting 0.2 * xHeight
2017+
if char.height + char.depth >= target_total - 0.2 * xHeight:
20122018
break
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2014-
if factor is None:
2015-
factor = target_total / (char.height + char.depth)
2016-
state.fontsize *= factor
2017-
char = Char(sym, state)
2020+
shift = 0
2021+
if state.font != 0:
2022+
if factor is None:
2023+
factor = (target_total) / (char.height + char.depth)
2024+
state.fontsize *= factor
2025+
char = Char(sym, state)
2026+
2027+
shift = (depth - char.depth)
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2019-
shift = (depth - char.depth)
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Hlist.__init__(self, [char])
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self.shift_amount = shift
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‎lib/matplotlib/patches.py

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"""
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if head_width is None:
1198-
head_width = 20 * width
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head_width = 3 * width
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if head_length is None:
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head_length = 1.5 * head_width
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‎lib/matplotlib/tests/baseline_images/test_mathtext/mathtext_cm_38.pdf

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‎lib/matplotlib/tests/baseline_images/test_mathtext/mathtext_cm_38.png

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