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Merge remote-tracking branch 'matplotlib/v2.0.x'
Conflicts: .travis.yml - kept extra lines from 2.0.x to print a few more diagnostics lib/matplotlib/tests/test_backend_pgf.py - keep master version of test decorators lib/matplotlib/tests/test_image.py - kept addational tests from 2.0.x - removed a @cleanup lib/matplotlib/tests/test_ticker.py - conflict from b03b71a kept master version Other: lib/matplotlib/tests/test_axes.py - remove @cleanup
2 parents f5b6246 + b6f17f3 commit fcace6c

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-47
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‎.travis.yml‎

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@@ -102,9 +102,12 @@ before_install:
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fi
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install:
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# Upgrade pip and setuptools. Mock has issues with the default version of
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# setuptools
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- |
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# Setup environment
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ccache -s
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git describe
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# Upgrade pip and setuptools and wheel to get as clean an install as possible
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pip install --upgrade pip
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pip install --upgrade wheel

‎doc/users/dflt_style_changes.rst‎

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@@ -18,6 +18,7 @@ values is a single line of python
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See :ref:`customizing-with-matplotlibrc-files` for details about how to
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persistently and selectively revert many of these changes.
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.. contents:: Table of Contents
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:depth: 2
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:local:

‎lib/matplotlib/axes/_axes.py‎

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@@ -2829,6 +2829,9 @@ def errorbar(self, x, y, yerr=None, xerr=None,
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fmt_style_kwargs = {k: v for k, v in
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zip(('linestyle', 'marker', 'color'),
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_process_plot_format(fmt)) if v is not None}
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if fmt == 'none':
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# Remove alpha=0 color that _process_plot_format returns
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fmt_style_kwargs.pop('color')
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if ('color' in kwargs or 'color' in fmt_style_kwargs or
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ecolor is not None):

‎lib/matplotlib/axes/_base.py‎

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@@ -718,10 +718,12 @@ def get_xaxis_text1_transform(self, pad_points):
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place axis elements in different locations.
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"""
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labels_align = matplotlib.rcParams["xtick.alignment"]
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return (self.get_xaxis_transform(which='tick1') +
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mtransforms.ScaledTranslation(0, -1 * pad_points / 72.0,
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self.figure.dpi_scale_trans),
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"top", "center")
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"top", labels_align)
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def get_xaxis_text2_transform(self, pad_points):
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"""
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place axis elements in different locations.
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"""
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labels_align = matplotlib.rcParams["xtick.alignment"]
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return (self.get_xaxis_transform(which='tick2') +
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mtransforms.ScaledTranslation(0, pad_points / 72.0,
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self.figure.dpi_scale_trans),
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"bottom", "center")
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"bottom", labels_align)
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def get_yaxis_transform(self, which='grid'):
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"""
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place axis elements in different locations.
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"""
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labels_align = matplotlib.rcParams["ytick.alignment"]
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return (self.get_yaxis_transform(which='tick1') +
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mtransforms.ScaledTranslation(-1 * pad_points / 72.0, 0,
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self.figure.dpi_scale_trans),
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"center_baseline", "right")
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labels_align, "right")
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def get_yaxis_text2_transform(self, pad_points):
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"""
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place axis elements in different locations.
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"""
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labels_align = matplotlib.rcParams["ytick.alignment"]
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return (self.get_yaxis_transform(which='tick2') +
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mtransforms.ScaledTranslation(pad_points / 72.0, 0,
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self.figure.dpi_scale_trans),
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"center_baseline", "left")
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labels_align, "left")
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def _update_transScale(self):
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self.transScale.set(
@@ -2541,13 +2547,10 @@ def ticklabel_format(self, **kwargs):
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raise ValueError("scilimits must be a sequence of 2 integers")
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if style[:3] == 'sci':
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sb = True
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elif style in ['plain', 'comma']:
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elif style == 'plain':
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sb = False
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if style == 'plain':
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cb = False
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else:
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cb = True
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raise NotImplementedError("comma style remains to be added")
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elif style == 'comma':
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raise NotImplementedError("comma style remains to be added")
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elif style == '':
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sb = None
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else:

‎lib/matplotlib/backends/backend_pgf.py‎

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@@ -191,10 +191,9 @@ def make_pdf_to_png_converter():
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# pick converter
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if "pdftocairo" in tools_available:
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def cairo_convert(pdffile, pngfile, dpi):
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cmd = [str("pdftocairo"), "-singlefile", "-png",
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"-r %d" % dpi, pdffile, os.path.splitext(pngfile)[0]]
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# for some reason this doesn't work without shell
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check_output(cmd, shell=True, stderr=subprocess.STDOUT)
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cmd = [str("pdftocairo"), "-singlefile", "-png", "-r", "%d" % dpi,
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pdffile, os.path.splitext(pngfile)[0]]
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check_output(cmd, stderr=subprocess.STDOUT)
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return cairo_convert
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elif "gs" in tools_available:
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def gs_convert(pdffile, pngfile, dpi):

‎lib/matplotlib/image.py‎

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@@ -375,9 +375,20 @@ def _make_image(self, A, in_bbox, out_bbox, clip_bbox, magnification=1.0,
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# this is to work around spurious warnings coming
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# out of masked arrays.
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with np.errstate(invalid='ignore'):
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rgba[..., 1] = A < 0 # under data
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rgba[..., 2] = A > 1 # over data
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rgba[..., 3] = ~A.mask # bad data
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rgba[..., 1] = np.where(A < 0, np.nan, 1) # under data
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rgba[..., 2] = np.where(A > 1, np.nan, 1) # over data
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# Have to invert mask, Agg knows what alpha means
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# so if you put this in as 0 for 'good' points, they
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# all get zeroed out
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rgba[..., 3] = 1
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if A.mask.shape == A.shape:
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# this is the case of a nontrivial mask
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mask = np.where(A.mask, np.nan, 1)
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else:
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# this is the case that the mask is a
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# numpy.bool_ of False
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mask = A.mask
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# ~A.mask # masked data
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A = rgba
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output = np.zeros((out_height, out_width, 4),
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dtype=A.dtype)
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# Convert back to a masked greyscale array so
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# colormapping works correctly
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hid_output = output
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# any pixel where the a masked pixel is included
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# in the kernel (pulling this down from 1) needs to
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# be masked in the output
435+
if len(mask.shape) == 2:
436+
out_mask = np.empty((out_height, out_width),
437+
dtype=mask.dtype)
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_image.resample(mask, out_mask, t,
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_interpd_[self.get_interpolation()],
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True, 1,
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self.get_filternorm() or 0.0,
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self.get_filterrad() or 0.0)
443+
out_mask = np.isnan(out_mask)
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else:
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out_mask = mask
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# we need to mask both pixels which came in as masked
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# and the pixels that Agg is telling us to ignore (relavent
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# to non-affine transforms)
449+
# Use half alpha as the threshold for pixels to mask.
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out_mask = out_mask | (hid_output[..., 3] < .5)
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output = np.ma.masked_array(
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hid_output[..., 0], hid_output[..., 3] < 0.5)
423-
# relabel under data
424-
output[hid_output[..., 1] > .5] = -1
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hid_output[..., 0],
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out_mask)
454+
# 'unshare' the mask array to
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# needed to suppress numpy warning
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del out_mask
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invalid_mask = ~output.mask * ~np.isnan(output.data)
458+
# relabel under data. If any of the input data for
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# the pixel has input out of the norm bounds,
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output[np.isnan(hid_output[..., 1]) * invalid_mask] = -1
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# relabel over data
426-
output[hid_output[..., 2] > .5] = 2
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output[np.isnan(hid_output[..., 2]) * invalid_mask] = 2
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output = self.to_rgba(output, bytes=True, norm=False)
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