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Commit92b5c95

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Merge pull request#7284 from QuLogic/backports-2.0
Backports for 2.0
2 parentsa869cc0 +734b702 commit92b5c95

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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 [[ $DELETE_FONT_CACHE == 1 ]]; then
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rm -rf ~/.cache/matplotlib
129+
fi
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export MPL_REPO_DIR=$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
23+
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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27+
import pandas as pd
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29+
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
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@@ -0,0 +1,7 @@
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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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@@ -24,4 +24,5 @@
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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
11-
the same parameters as a matplotlibrc_ file.
11+
the same parameters as a matplotlibrc_ file (which is read at startup to
12+
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
19-
These are akin tothe web browserforward and backbuttons. They
20-
are used to navigate back and forth between previously defined
21-
views. They have no meaning unless you have already navigated
22-
somewhere else using the pan and zoom buttons. This is analogous
18+
The ``Home``, ``Forward`` and ``Back`` buttons
19+
These are akin toa web browser's home,forward and backcontrols.
20+
``Forward`` and ``Back``are used to navigate back and forth between
21+
previously definedviews. They have no meaning unless you have already
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navigatedsomewhere 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 takesyou tothe
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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
27-
the pan and zoomtorectangle to define new views.
24+
new pageor ``Forward``beforeyouhave gone backtoa page --
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nothing happens. ``Home`` always takes you to the
26+
first, default view of your data. Again, all of these buttons should
27+
feel very familiartoany user of a web browser.
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.. image:: ../../lib/matplotlib/mpl-data/images/move_large.png
3030

@@ -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.
40-
The x axis will be zoomed inproportionate to the rightward
41-
movement and zoomed outproportionate to the leftward movement.
42-
Ditto for the y axis and up/down motions. The point under your
40+
The x axis will be zoomed inproportionately to the rightward
41+
movement and zoomed outproportionately to the leftward movement.
42+
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
44-
zoomto an arbitrarypointin the figure. You can use the
44+
zoomin or out around thatpointas much as you wish. You can use the
4545
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
57-
somewhere overand axes and press the left mouse button. Drag the
57+
somewhere overan 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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@@ -3,22 +3,25 @@
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Text introduction
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=================
55

6-
matplotlib has excellent text support, including mathematical
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expressions, truetype support for raster and vector outputs, newline
8-
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
6+
matplotlib has extensive text support, including support for
7+
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.
1112
`FreeType <http://www.freetype.org/>`_ support
1213
produces very nice, antialiased fonts, that look good even at small
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raster sizes. matplotlib includes its own
14-
:mod:`matplotlib.font_manager`, thanks to Paul Barrett, which
15-
implements a cross platform, W3C compliant font finding algorithm.
16-
17-
You have total control over every text property (font size, font
18-
weight, text location and color, etc) with sensible defaults set in
19-
the rc file. And significantly for those interested in mathematical
15+
:mod:`matplotlib.font_manager` (thanks to Paul Barrett), which
16+
implements a cross platform, `W3C <http://www.w3.org/>`
17+
compliant font finding algorithm.
18+
19+
The user has a great deal of control over text properties (font size, font
20+
weight, text location and color, etc.) with sensible defaults set in
21+
the `rc file <http://matplotlib.org/users/customizing.html>`.
22+
And significantly, for those interested in mathematical
2023
or scientific figures, matplotlib implements a large number of TeX
21-
math symbols and commands,to support :ref:`mathematical expressions
24+
math symbols and commands,supporting :ref:`mathematical expressions
2225
<mathtext-tutorial>` anywhere in your figure.
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@@ -31,10 +34,10 @@ interface
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* :func:`~matplotlib.pyplot.text` - add text at an arbitrary location to the ``Axes``;
3235
:meth:`matplotlib.axes.Axes.text` in the API.
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34-
* :func:`~matplotlib.pyplot.xlabel` - addan axis label to the x-axis;
37+
* :func:`~matplotlib.pyplot.xlabel` - adda label to the x-axis;
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:meth:`matplotlib.axes.Axes.set_xlabel` in the API.
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37-
* :func:`~matplotlib.pyplot.ylabel` - addan axis label to the y-axis;
40+
* :func:`~matplotlib.pyplot.ylabel` - adda 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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@@ -2,7 +2,7 @@
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33

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def draw_text(ax):
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frommpl_toolkits.axes_grid1.anchored_artists import AnchoredText
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frommatplotlib.offsetbox import AnchoredText
66
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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@@ -609,6 +609,9 @@ def destroy(*args):
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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.
613+
self.canvas.manager.window.attributes('-topmost', 1)
614+
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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@@ -896,7 +896,6 @@ def __init__(self, *args, **kwargs):
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self.fontmap = {}
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# Include Stix sized alternatives for glyphs
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self._fontmap.update({
899-
0 : 'STIXGeneral',
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1 : 'STIXSizeOneSym',
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2 : 'STIXSizeTwoSym',
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3 : 'STIXSizeThreeSym',
@@ -938,6 +937,7 @@ class DejaVuSerifFonts(DejaVuFonts):
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'sf' : 'DejaVu Sans',
939938
'tt' : 'DejaVu Sans Mono',
940939
'ex' : 'DejaVu Serif Display',
940+
0 : 'DejaVu Serif',
941941
}
942942

943943
class DejaVuSansFonts(DejaVuFonts):
@@ -952,6 +952,7 @@ class DejaVuSansFonts(DejaVuFonts):
952952
'sf' : 'DejaVu Sans',
953953
'tt' : 'DejaVu Sans Mono',
954954
'ex' : 'DejaVu Sans Display',
955+
0 : 'DejaVu Sans',
955956
}
956957

957958
class StixFonts(UnicodeFonts):
@@ -2003,20 +2004,28 @@ def __init__(self, c, height, depth, state, always=False, factor=None):
20032004
alternatives = state.font_output.get_sized_alternatives_for_symbol(
20042005
state.font, c)
20052006

2007+
xHeight = state.font_output.get_xheight(
2008+
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
20132019

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)
20182028

2019-
shift = (depth - char.depth)
20202029
Hlist.__init__(self, [char])
20212030
self.shift_amount = shift
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‎lib/matplotlib/patches.py

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@@ -1195,7 +1195,7 @@ def __init__(self, x, y, dx, dy, width=0.001, length_includes_head=False,
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"""
11971197
if head_width is None:
1198-
head_width =20 * width
1198+
head_width =3 * width
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if head_length is None:
12001200
head_length = 1.5 * head_width
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