8000 PiecewiseLinearNorm by OceanWolf · Pull Request #5061 · matplotlib/matplotlib · GitHub
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PiecewiseLinearNorm #5061

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PiecewiseLinearNorm #5061

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05c1b76
ENH: Add OffsetNorm and tests
phobson Nov 27, 2014
8ad54f3
fix OffsetNorm docstring to numpydoc spec
phobson Mar 30, 2015
03e506c
OffsetNorm blurb in whats_new
phobson Mar 30, 2015
04ea107
removed OffsetNorm.inverse method
phobson Jun 6, 2015
62c9efc
attempting to create a baseline image
phobson Jun 6, 2015
d95db3c
fix bad indexing when returning a scalar
phobson Jun 8, 2015
3cc84a6
the real test image
phobson Jun 8, 2015
47c447a
refactor tests a bit to handle non-invertable Norms
phobson Jun 8, 2015
36042b6
OffsetNorm -> PiecewiseLinearNorm
dopplershift Jul 11, 2015
56cbae2
Propagate mask from input data
jkseppan Sep 3, 2015
1d1ff98
Remove unused clip parameter
jkseppan Sep 3, 2015
14b6837
Use process_value in PiecewiseLinearNorm
jkseppan Sep 3, 2015
a8d4956
Return a scalar when passed in a scalar
jkseppan Sep 3, 2015
31bfd2a
Return 0.5 for vcenter == vmax
jkseppan Sep 3, 2015
a68fff3
pep8 fixes
jkseppan Sep 3, 2015
8000 3293971
PiecewiseLinearNorm
OceanWolf Sep 14, 2015
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Remove unused clip parameter 
Need to allow it in __call__ since colorbar can pass a value for clip.
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@jkseppan @OceanWolf
jkseppan authored and OceanWolf committed Sep 13, 2015
commit 1d1ff98f7ac1ca4f0cb31fbbeadb41c9c2f70be3
15 changes: 2 additions & 13 deletions lib/matplotlib/colors.py
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Original file line number Diff line number Diff line change
Expand Up @@ -970,7 +970,7 @@ class PiecewiseLinearNorm(Normalize):

Normalizes data into the ``[0.0, 1.0]`` interval.
"""
def __init__(self, vmin=None, vcenter=None, vmax=None, clip=False):
def __init__(self, vmin=None, vcenter=None, vmax=None):
"""Normalize data with an offset midpoint

Useful when mapping data unequally centered around a conceptual
Expand All @@ -990,11 +990,6 @@ def __init__(self, vmin=None, vcenter=None, vmax=None, clip=False):
The data value that defines ``1.0`` in the normalized data.
Defaults to the the max value of the dataset.

clip : bool, optional (default is False)
If *clip* is True, values beyond *vmin* and *vmax* will be set
to ``0.0`` or ``1.0``, respectively. Otherwise, values outside
the ``[0.0, 1.0]`` will be returned.

Examples
--------
>>> import matplotlib.colors as mcolors
Expand All @@ -1008,11 +1003,9 @@ def __init__(self, vmin=None, vcenter=None, vmax=None, clip=False):
self.vmin = vmin
self.vcenter = vcenter
self.vmax = vmax
self.clip = clip

def __call__(self, value, clip=None):
if clip is None:
clip = self.clip
"""Map value to the interval [0, 1]. The clip argument is unused."""

result, is_scalar = self.process_value(value)

Expand All @@ -1028,10 +1021,6 @@ def __call__(self, value, clip=None):
vmin = float(vmin)
vcenter = float(vcenter)
vmax = float(vmax)
if clip:
mask = ma.getmask(result)
result = ma.array(np.clip(result.filled(vmax), vmin, vmax),
mask=mask)

x, y = [vmin, vcenter, vmax], [0, 0.5, 1]
# returns a scalar if shape == (1,)
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