Merge remote-tracking branch 'matplotlib/v2.x'

tacaswell · tacaswell · commit cf83cd564250 · 2017-01-16T18:46:36.000-05:00
Conflicts:
	doc/users/whats_new.rst
	  - kept headings from 2.x
	lib/matplotlib/_color_data.py
	  - kept 2.x version
	lib/matplotlib/colors.py
	  - kept 2.x version
diff --git a/doc/users/whats_new.rst b/doc/users/whats_new.rst
@@ -213,7 +213,7 @@ removed.  Instead, images will obey the transform of the axes on which
 they are drawn.
 
 Non-linear scales on image plots
-````````````````````````````````
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 :func:`imshow` now draws data at the requested points in data space after the
 application of non-linear scales.
@@ -222,8 +222,6 @@ The image on the left demonstrates the new, correct behavior.
 The old behavior can be recreated using :func:`pcolormesh` as
 demonstrated on the right.
 
-Non-linear scale example
-````````````````````````
 
 .. plot::
 
diff --git a/lib/matplotlib/_color_data.py b/lib/matplotlib/_color_data.py
@@ -16,7 +16,7 @@
 
 
 # These colors are from Tableau
-TABLEAU_COLORS = OrderedDict((
+TABLEAU_COLORS = (
     ('blue', '#1f77b4'),
     ('orange', '#ff7f0e'),
     ('green', '#2ca02c'),
@@ -26,12 +26,12 @@
     ('pink', '#e377c2'),
     ('gray', '#7f7f7f'),
     ('olive', '#bcbd22'),
-    ('cyan', '#17becf'))
+    ('cyan', '#17becf'),
 )
 
 # Normalize name to "tab:<name>" to avoid name collisions.
 TABLEAU_COLORS = OrderedDict(
-    ('tab:' + name, value) for name, value in TABLEAU_COLORS.items())
+    ('tab:' + name, value) for name, value in TABLEAU_COLORS)
 
 # This mapping of color names -> hex values is taken from
 # a survey run by Randel Monroe see:
diff --git a/lib/matplotlib/colors.py b/lib/matplotlib/colors.py
@@ -259,7 +259,6 @@ def to_hex(c, keep_alpha=False):
 ### Backwards-compatible color-conversion API
 
 cnames = CSS4_COLORS
-COLOR_NAMES = {'xkcd': XKCD_COLORS, 'css4': CSS4_COLORS, 'tc': TABLEAU_COLORS}
 hexColorPattern = re.compile("\A#[a-fA-F0-9]{6}\Z")
 
 
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
@@ -368,8 +368,11 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
                     # values to carry the over/under/bad information
                     rgba = np.empty((A.shape[0], A.shape[1], 4), dtype=A.dtype)
                     rgba[..., 0] = A  # normalized data
-                    rgba[..., 1] = A < 0  # under data
-                    rgba[..., 2] = A > 1  # over data
+                    # this is to work around spurious warnings coming
+                    # out of masked arrays.
+                    with np.errstate(invalid='ignore'):
+                        rgba[..., 1] = A < 0  # under data
+                        rgba[..., 2] = A > 1  # over data
                     rgba[..., 3] = ~A.mask  # bad data
                     A = rgba
                     output = np.zeros((out_height, out_width, 4),
diff --git a/lib/matplotlib/tests/test_image.py b/lib/matplotlib/tests/test_image.py
@@ -4,6 +4,7 @@
 import six
 import io
 import os
+import warnings
 
 from nose.plugins.attrib import attr
 
@@ -746,5 +747,13 @@ def test_imshow_endianess():
     ax2.imshow(Z.astype('>f8'), **kwargs)
 
 
+@cleanup
+def test_imshow_no_warn_invalid():
+    with warnings.catch_warnings(record=True) as warns:
+        warnings.simplefilter("always")
+        plt.imshow([[1, 2], [3, np.nan]])
+    assert len(warns) == 0
+
+
 if __name__ == '__main__':
     nose.runmodule(argv=['-s', '--with-doctest'], exit=False)
