Merge pull request #7284 from QuLogic/backports-2.0

Backports for 2.0

.travis.yml

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

doc/faq/howto_faq.rst

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

doc/mpl_toolkits/axes_grid/api/anchored_artists_api.rst

@@ -0,0 +1,7 @@
+:mod:`mpl_toolkits.axes_grid1.anchored_artists`
+===============================================
+
+.. automodule:: mpl_toolkits.axes_grid1.anchored_artists
+   :members:
+   :undoc-members:
+   :show-inheritance:

doc/mpl_toolkits/axes_grid/api/index.rst

@@ -24,4 +24,5 @@
 
 .. toctree::
 
+    anchored_artists_api.rst
     inset_locator_api.rst

doc/users/customizing.rst

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

doc/users/navigation_toolbar.rst

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

doc/users/text_intro.rst

@@ -3,22 +3,25 @@
 Text introduction
 =================
 
-matplotlib has excellent text support, including mathematical
-expressions, truetype support for raster and vector outputs, newline
-separated text with arbitrary rotations, and unicode support.  Because
-we embed the fonts directly in the output documents, e.g., for postscript
+matplotlib has extensive text support, including support for
+mathematical expressions, truetype support for raster and
+vector outputs, newline separated text with arbitrary
+rotations, and unicode support.  Because it embeds
+fonts directly in output documents, e.g., for postscript
 or PDF, what you see on the screen is what you get in the hardcopy.
 `FreeType <http://www.freetype.org/>`_ support
 produces very nice, antialiased fonts, that look good even at small
 raster sizes.  matplotlib includes its own
-:mod:`matplotlib.font_manager`, thanks to Paul Barrett, which
-implements a cross platform, W3C compliant font finding algorithm.
-
-You have total control over every text property (font size, font
-weight, text location and color, etc) with sensible defaults set in
-the rc file.  And significantly for those interested in mathematical
+:mod:`matplotlib.font_manager` (thanks to Paul Barrett), which
+implements a cross platform, `W3C <http://www.w3.org/>`
+compliant font finding algorithm.
+
+The user has a great deal of control over text properties (font size, font
+weight, text location and color, etc.) with sensible defaults set in
+the `rc file <http://matplotlib.org/users/customizing.html>`.
+And significantly, for those interested in mathematical
 or scientific figures, matplotlib implements a large number of TeX
-math symbols and commands, to support :ref:`mathematical expressions
+math symbols and commands, supporting :ref:`mathematical expressions
 <mathtext-tutorial>` anywhere in your figure.
 
 
@@ -31,10 +34,10 @@ interface
 * :func:`~matplotlib.pyplot.text` - add text at an arbitrary location to the ``Axes``;
   :meth:`matplotlib.axes.Axes.text` in the API.
 
-* :func:`~matplotlib.pyplot.xlabel` - add an axis label to the x-axis;
+* :func:`~matplotlib.pyplot.xlabel` - add a label to the x-axis;
   :meth:`matplotlib.axes.Axes.set_xlabel` in the API.
 
-* :func:`~matplotlib.pyplot.ylabel` - add an axis label to the y-axis;
+* :func:`~matplotlib.pyplot.ylabel` - add a label to the y-axis;
   :meth:`matplotlib.axes.Axes.set_ylabel` in the API.
 
 * :func:`~matplotlib.pyplot.title` - add a title to the ``Axes``;

examples/axes_grid/simple_anchored_artists.py

@@ -2,7 +2,7 @@
 
 
 def draw_text(ax):
-    from mpl_toolkits.axes_grid1.anchored_artists import AnchoredText
+    from matplotlib.offsetbox import AnchoredText
     at = AnchoredText("Figure 1a",
                       loc=2, prop=dict(size=8), frameon=True,
                       )

lib/matplotlib/backends/backend_tkagg.py

@@ -609,6 +609,9 @@ def destroy(*args):
             self.window.update()
         else:
             self.canvas.draw_idle()
+        # Raise the new window.
+        self.canvas.manager.window.attributes('-topmost', 1)
+        self.canvas.manager.window.attributes('-topmost', 0)
         self._shown = True
 
     def destroy(self, *args):

lib/matplotlib/mathtext.py

@@ -896,7 +896,6 @@ def __init__(self, *args, **kwargs):
         self.fontmap = {}
         # Include Stix sized alternatives for glyphs
         self._fontmap.update({
-                 0 : 'STIXGeneral',
                  1 : 'STIXSizeOneSym',
                  2 : 'STIXSizeTwoSym',
                  3 : 'STIXSizeThreeSym',
@@ -938,6 +937,7 @@ class DejaVuSerifFonts(DejaVuFonts):
                  'sf'  : 'DejaVu Sans',
                  'tt'  : 'DejaVu Sans Mono',
                  'ex'  : 'DejaVu Serif Display',
+                 0     : 'DejaVu Serif',
                  }
 
 class DejaVuSansFonts(DejaVuFonts):
@@ -952,6 +952,7 @@ class DejaVuSansFonts(DejaVuFonts):
                  'sf'  : 'DejaVu Sans',
                  'tt'  : 'DejaVu Sans Mono',
                  'ex'  : 'DejaVu Sans Display',
+                 0     : 'DejaVu Sans',
                  }
 
 class StixFonts(UnicodeFonts):
@@ -2003,20 +2004,28 @@ def __init__(self, c, height, depth, state, always=False, factor=None):
         alternatives = state.font_output.get_sized_alternatives_for_symbol(
             state.font, c)
 
+        xHeight = state.font_output.get_xheight(
+            state.font, state.fontsize, state.dpi)
+
         state = state.copy()
         target_total = height + depth
         for fontname, sym in alternatives:
             state.font = fontname
             char = Char(sym, state)
-            if char.height + char.depth >= target_total:
+            # Ensure that size 0 is chosen when the text is regular sized but
+            # with descender glyphs by subtracting 0.2 * xHeight
+            if char.height + char.depth >= target_total - 0.2 * xHeight:
                 break
 
-        if factor is None:
-            factor = target_total / (char.height + char.depth)
-        state.fontsize *= factor
-        char = Char(sym, state)
+        shift = 0
+        if state.font != 0:
+            if factor is None:
+                factor = (target_total) / (char.height + char.depth)
+            state.fontsize *= factor
+            char = Char(sym, state)
+
+            shift = (depth - char.depth)
 
-        shift = (depth - char.depth)
         Hlist.__init__(self, [char])
         self.shift_amount = shift
 

lib/matplotlib/patches.py

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