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FAIL: matplotlib.tests.test_transforms.test_pre_transform_plotting.test on Python 3.x #1120

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merged 1 commit into from Sep 5, 2012
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FAIL: matplotlib.tests.test_transforms.test_pre_transform_plotting.test on Python 3.x #1120

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4 changes: 2 additions & 2 deletions lib/matplotlib/_cm.py
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Expand Up @@ -4,7 +4,7 @@

"""

from __future__ import print_function
from __future__ import print_function, division
import numpy as np

_binary_data = {
Expand Down Expand Up @@ -1625,7 +1625,7 @@ def gfunc32(x):
}

# This bipolar color map was generated from CoolWarmFloat33.csv of
# "Diverging Color Maps for Scientific Visualization" by Kenneth Moreland.
# "Diverging Color Maps for Scientific Visualization" by Kenneth Moreland.
# <http://www.cs.unm.edu/~kmorel/documents/ColorMaps/>
_coolwarm_data = {
'red': [
Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/cm.py
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Expand Up @@ -4,7 +4,7 @@
and a mixin class for adding color mapping functionality.

"""
from __future__ import print_function
from __future__ import print_function, division

import os

Expand Down
2 changes: 1 addition & 1 deletion lib/matplotlib/collections.py
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Expand Up @@ -158,7 +158,7 @@ def get_transforms(self):

def get_offset_transform(self):
t = self._transOffset
if (not isinstance(t, transforms.Transform)
if (not isinstance(t, transforms.Transform)
and hasattr(t, '_as_mpl_transform')):
t = t._as_mpl_transform(self.axes)
return t
Expand Down
4 changes: 2 additions & 2 deletions lib/matplotlib/colors.py
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Expand Up @@ -48,7 +48,7 @@
Finally, legal html names for colors, like 'red', 'burlywood' and
'chartreuse' are supported.
"""
from __future__ import print_function
from __future__ import print_function, division
import re
import numpy as np
from numpy import ma
Expand Down Expand Up @@ -219,7 +219,7 @@ def is_color_like(c):

def rgb2hex(rgb):
'Given an rgb or rgba sequence of 0-1 floats, return the hex string'
return '#%02x%02x%02x' % tuple([round(val*255) for val in rgb[:3]])
return '#%02x%02x%02x' % tuple([np.round(val*255) for val in rgb[:3]])
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Micro-optimization: the part on the right is a bit quicker and perhaps more readable as
tuple(np.round(np.asarray(rgb[:3]) * 255)).

Or tuple((np.asarray(rgb[:3]) * 255).round()), which is slightly more efficient. Not that efficiency matters at this microsecond level.

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watch out when doing asarray(). We support masked arrays, so it really should be asanyarray(). Although, admittedly, in this context, it probably makes no difference.

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Agreed, but I don't think either version would work sensibly with rgb as a masked array. And the docstring says "floats", with no mention of masked array support.


hexColorPattern = re.compile("\A#[a-fA-F0-9]{6}\Z")

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2 changes: 1 addition & 1 deletion lib/matplotlib/quiver.py
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Expand Up @@ -15,7 +15,7 @@
"""


from __future__ import print_function
from __future__ import print_function, division
import numpy as np
from numpy import ma
import matplotlib.collections as collections
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