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fixed and condensed lo,hi range assignment

This commit is contained in:
Philip Eisenlohr 2020-08-04 20:29:27 +02:00
parent e07c00a592
commit e73ffd6da9
1 changed files with 6 additions and 8 deletions
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12
python/damask/_colormap.py
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@ -171,7 +171,7 @@ class Colormap(mpl.colors.ListedColormap):
field : np.array of shape(:,:)
Data to be shaded.
bounds : iterable of len(2), optional
Lower and upper bound of value range.
Colormap value range (low,high).
gap : field.dtype, optional
Transparent value. NaN will always be rendered transparent.
@ -183,16 +183,14 @@ class Colormap(mpl.colors.ListedColormap):
"""
N = len(self.colors)
mask = np.logical_not(np.isnan(field) if gap is None else \
np.logical_or (np.isnan(field), field == gap)) # mask gap and NaN (if gap present)
np.logical_or (np.isnan(field), field == gap)) # mask NaN (and gap if present)
if bounds is None:
hi,lo = field[mask].min(),field[mask].max()
else:
hi,lo = bounds[::-1]
lo,hi = (field[mask].min(),field[mask].max()) if bounds is None else \
(min(bounds[:2]),max(bounds[:2]))
delta,avg = hi-lo,0.5*(hi+lo)
if delta * 1e8 <= avg: # delta around numerical noise
if delta * 1e8 <= avg: # delta is similar to numerical noise
hi,lo = hi+0.5*avg,lo-0.5*avg # extend range to have actual data centered within
return Image.fromarray((np.dstack((self.colors[(np.clip((field-lo)/(hi-lo),0.0,1.0)*(N-1)).astype(np.uint8),:3],