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Document auto-init behavior of colors.Normalize and cm.ScalarMappable. #3628

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Merged
merged 4 commits into from
Oct 16, 2014
Merged

Document auto-init behavior of colors.Normalize and cm.ScalarMappable. #3628

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828bc58
Document auto-init behavior of colors.Normalize and cm.ScalarMappable.
Oct 10, 2014
7145d19
Merge branch 'master' of https://github.com/matplotlib/matplotlib
switham Oct 15, 2014
0385071
Tweaks to colors.Normalize and cm.ScalarMappable docstrings.
switham Oct 15, 2014
1f07ab1
rm trailing whitespace added in 828bc58 or 0385071
switham Oct 15, 2014
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3 changes: 2 additions & 1 deletion lib/matplotlib/cm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -178,9 +178,10 @@ def __init__(self, norm=None, cmap=None):
norm : :class:`matplotlib.colors.Normalize` instance
The normalizing object which scales data, typically into the
interval ``[0, 1]``.
If *None*, *norm* defaults to a *colors.Normalize* object which
initializes its scaling based on the first data processed.
cmap : str or :class:`~matplotlib.colors.Colormap` instance
The colormap used to map normalized data values to RGBA colors.

"""

self.callbacksSM = cbook.CallbackRegistry()
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17 changes: 13 additions & 4 deletions lib/matplotlib/colors.py
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Expand Up @@ -851,10 +851,12 @@ class Normalize(object):
"""
def __init__(self, vmin=None, vmax=None, clip=False):
"""
If *vmin* or *vmax* is not given, they are taken from the input's
minimum and maximum value respectively. If *clip* is *True* and
the given value falls outside the range, the returned value
will be 0 or 1, whichever is closer. Returns 0 if::
If *vmin* or *vmax* is not given, they are initialized from the
minimum and maximum value respectively of the first input
processed. That is, *__call__(A)* calls *autoscale_None(A)*.
If *clip* is *True* and the given value falls outside the range,
the returned value will be 0 or 1, whichever is closer.
Returns 0 if::

vmin==vmax

Expand Down Expand Up @@ -902,6 +904,13 @@ def process_value(value):
return result, is_scalar

def __call__(self, value, clip=None):
"""
Normalize *value* data in the ``[vmin, vmax]`` interval into
the ``[0.0, 1.0]`` interval and return it. *clip* defaults
to *self.clip* (which defaults to *False*). If not already
initialized, *vmin* and *vmax* are initialized using
*autoscale_None(value)*.
"""
if clip is None:
clip = self.clip

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