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Add power-law normalization #1204

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Merged
tacaswell merged 5 commits into from
Apr 4, 2014
Merged

Add power-law normalization #1204

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9b29988
colors: Replace docstring ''' with """
bgamari Sep 11, 2012
ddd5899
test_colors: Fix typo
bgamari Nov 27, 2013
1b9fc6c
colors: Add power-law normalization
bgamari Sep 11, 2012
48998c1
power_norm_demo: Initial commit
bgamari Jan 22, 2013
d5343c0
hist2d: Add a note mentioning PowerNorm
bgamari Jan 22, 2013
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colors: Replace docstring ''' with """
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@bgamari
bgamari committed Mar 10, 2014
commit 9b29988f3ff6f0655aa2036202c308d896ce6e3a
34 changes: 17 additions & 17 deletions lib/matplotlib/colors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -625,24 +625,24 @@ def __call__(self, X, alpha=None, bytes=False):
return rgba

def set_bad(self, color='k', alpha=None):
'''Set color to be used for masked values.
'''
"""Set color to be used for masked values.
"""
self._rgba_bad = colorConverter.to_rgba(color, alpha)
if self._isinit:
self._set_extremes()

def set_under(self, color='k', alpha=None):
'''Set color to be used for low out-of-range values.
"""Set color to be used for low out-of-range values.
Requires norm.clip = False
'''
"""
self._rgba_under = colorConverter.to_rgba(color, alpha)
if self._isinit:
self._set_extremes()

def set_over(self, color='k', alpha=None):
'''Set color to be used for high out-of-range values.
"""Set color to be used for high out-of-range values.
Requires norm.clip = False
'''
"""
self._rgba_over = colorConverter.to_rgba(color, alpha)
if self._isinit:
self._set_extremes()
Expand All @@ -659,7 +659,7 @@ def _set_extremes(self):
self._lut[self._i_bad] = self._rgba_bad

def _init(self):
'''Generate the lookup table, self._lut'''
"""Generate the lookup table, self._lut"""
raise NotImplementedError("Abstract class only")

def is_gray(self):
Expand Down Expand Up @@ -945,9 +945,9 @@ def inverse(self, value):
return vmin + value * (vmax - vmin)

def autoscale(self, A):
'''
"""
Set *vmin*, *vmax* to min, max of *A*.
'''
"""
self.vmin = ma.min(A)
self.vmax = ma.max(A)

Expand Down Expand Up @@ -1016,9 +1016,9 @@ def inverse(self, value):
return vmin * pow((vmax / vmin), value)

def autoscale(self, A):
'''
"""
Set *vmin*, *vmax* to min, max of *A*.
'''
"""
A = ma.masked_less_equal(A, 0, copy=False)
self.vmin = ma.min(A)
self.vmax = ma.max(A)
Expand Down Expand Up @@ -1149,7 +1149,7 @@ def autoscale_None(self, A):


class BoundaryNorm(Normalize):
'''
"""
Generate a colormap index based on discrete intervals.

Unlike :class:`Normalize` or :class:`LogNorm`,
Expand All @@ -1160,9 +1160,9 @@ class BoundaryNorm(Normalize):
piece-wise linear interpolation, but using integers seems
simpler, and reduces the number of conversions back and forth
between integer and floating point.
'''
"""
def __init__(self, boundaries, ncolors, clip=False):
'''
"""
*boundaries*
a monotonically increasing sequence
*ncolors*
Expand All @@ -1179,7 +1179,7 @@ def __init__(self, boundaries, ncolors, clip=False):
Out-of-range values are mapped to -1 if low and ncolors
if high; these are converted to valid indices by
:meth:`Colormap.__call__` .
'''
"""
self.clip = clip
self.vmin = boundaries[0]
self.vmax = boundaries[-1]
Expand Down Expand Up @@ -1217,11 +1217,11 @@ def inverse(self, value):


class NoNorm(Normalize):
'''
"""
Dummy replacement for Normalize, for the case where we
want to use indices directly in a
:class:`~matplotlib.cm.ScalarMappable` .
'''
"""
def __call__(self, value, clip=None):
return value

Expand Down