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DAMASK_EICMD
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added option to linearly interpolate colors to Colormap class

This commit is contained in:
Christoph Kords 2013-05-28 17:33:51 +00:00
parent a21dd816c7
commit 65c5090378
1 changed files with 18 additions and 6 deletions
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24
lib/damask/colormaps.py
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@ -317,8 +317,8 @@ class Colormap():
if right.__class__.__name__ != 'Color': if right.__class__.__name__ != 'Color':
right = Color() right = Color()
self.left = left.expressAs('MSH') self.left = left
self.right = right.expressAs('MSH') self.right = right
# ------------------------------------------------------------------ # ------------------------------------------------------------------
@ -333,8 +333,8 @@ class Colormap():
def usePredefined(self,name='bluered'): def usePredefined(self,name='bluered'):
if name.lower() not in self.__predefined__: if name.lower() not in self.__predefined__:
raise KeyError('colormap "%s" is not defined, use one of "%s"'%(name,'" "'.join(self.__predefined__.keys()))) raise KeyError('colormap "%s" is not defined, use one of "%s"'%(name,'" "'.join(self.__predefined__.keys())))
self.left = self.__predefined__[name.lower()][0].expressAs('MSH') self.left = self.__predefined__[name.lower()][0]
self.right= self.__predefined__[name.lower()][1].expressAs('MSH') self.right= self.__predefined__[name.lower()][1]
return self return self
@ -343,7 +343,8 @@ class Colormap():
format = 'paraview',\ format = 'paraview',\
steps = 10,\ steps = 10,\
crop = [-1.0,1.0], crop = [-1.0,1.0],
model = 'RGB'): model = 'RGB',
interpolate = 'perceptualuniform'):
''' '''
[RGB] colormap for use in paraview or gmsh, or as raw string, or array. [RGB] colormap for use in paraview or gmsh, or as raw string, or array.
arguments: name, format, steps, crop. arguments: name, format, steps, crop.
@ -385,6 +386,12 @@ class Colormap():
Msh = (1.0-frac)*Msh1 + frac*Msh2 Msh = (1.0-frac)*Msh1 + frac*Msh2
return Color('MSH',Msh).convertTo(model) return Color('MSH',Msh).convertTo(model)
def linearInterpolate(lo,hi,frac,model='RGB'):
color1 = numpy.array(lo.color[:])
color2 = numpy.array(hi.expressAs(lo.model).color[:])
color = (1.0 - frac) * color1 + frac * color2
return Color(lo.model,color).convertTo(model)
def write_paraview(RGB_vector): def write_paraview(RGB_vector):
colormap ='<ColorMap name="'+str(name)+'" space="RGB">\n' colormap ='<ColorMap name="'+str(name)+'" space="RGB">\n'
for i in range(len(RGB_vector)): for i in range(len(RGB_vector)):
@ -410,7 +417,12 @@ class Colormap():
totalSteps = int(2.0*steps/(crop[1] - crop[0])) totalSteps = int(2.0*steps/(crop[1] - crop[0]))
for i in range(totalSteps): for i in range(totalSteps):
color = interpolate_Msh(self.left.color,self.right.color,float(i)/(totalSteps-1),model) if interpolate == 'perceptualuniform':
color = interpolate_Msh(self.left.expressAs('MSH').color,self.right.expressAs('MSH').color,float(i)/(totalSteps-1),model)
elif interpolate == 'linear':
color = linearInterpolate(self.left,self.right,float(i)/(totalSteps-1),model)
else:
raise NameError('unknown interpolation method')
colors.append(color.color) colors.append(color.color)
leftIndex = int(round((crop[0]-(-1.0))/(2.0/(totalSteps-1)))) leftIndex = int(round((crop[0]-(-1.0))/(2.0/(totalSteps-1))))