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DAMASK_EICMD
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condensed multiple import statements into general one at module start.

This commit is contained in:
Philip Eisenlohr 2015-06-15 15:36:58 +00:00
parent a5b3e9d64c
commit 83547ce29f
1 changed files with 45 additions and 47 deletions
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64
lib/damask/colormaps.py
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@ -1,5 +1,7 @@
# -*- coding: UTF-8 no BOM -*- # -*- coding: UTF-8 no BOM -*-
import math,numpy as np
### --- COLOR CLASS -------------------------------------------------- ### --- COLOR CLASS --------------------------------------------------
class Color(): class Color():
@ -8,7 +10,6 @@ class Color():
Color('model',[vector]).To convert and copy color from one space to other, use the methods Color('model',[vector]).To convert and copy color from one space to other, use the methods
convertTo('model') and expressAs('model')spectively convertTo('model') and expressAs('model')spectively
''' '''
import numpy
__slots__ = [ __slots__ = [
'model', 'model',
@ -19,8 +20,7 @@ class Color():
# ------------------------------------------------------------------ # ------------------------------------------------------------------
def __init__(self, def __init__(self,
model = 'RGB', model = 'RGB',
color = numpy.zeros(3,'d')): color = np.zeros(3,'d')):
import numpy
self.__transforms__ = \ self.__transforms__ = \
{'HSL': {'index': 0, 'next': self._HSL2RGB}, {'HSL': {'index': 0, 'next': self._HSL2RGB},
@ -42,7 +42,7 @@ class Color():
while color[0] < 0.0: color[0] += 1.0 # rewind to proper range while color[0] < 0.0: color[0] += 1.0 # rewind to proper range
self.model = model self.model = model
self.color = numpy.array(color,'d') self.color = np.array(color,'d')
# ------------------------------------------------------------------ # ------------------------------------------------------------------
@ -83,7 +83,7 @@ class Color():
# with S,L,H,R,G,B running from 0 to 1 # with S,L,H,R,G,B running from 0 to 1
# from http://en.wikipedia.org/wiki/HSL_and_HSV # from http://en.wikipedia.org/wiki/HSL_and_HSV
def _HSL2RGB(self): def _HSL2RGB(self):
import numpy
if self.model != 'HSL': return if self.model != 'HSL': return
sextant = self.color[0]*6.0 sextant = self.color[0]*6.0
@ -91,7 +91,7 @@ class Color():
x = c*(1.0 - abs(sextant%2 - 1.0)) x = c*(1.0 - abs(sextant%2 - 1.0))
m = self.color[2] - 0.5*c m = self.color[2] - 0.5*c
converted = Color('RGB',numpy.array([ converted = Color('RGB',np.array([
[c+m, x+m, m], [c+m, x+m, m],
[x+m, c+m, m], [x+m, c+m, m],
[m, c+m, x+m], [m, c+m, x+m],
@ -108,10 +108,10 @@ class Color():
# with S,L,H,R,G,B running from 0 to 1 # with S,L,H,R,G,B running from 0 to 1
# from http://130.113.54.154/~monger/hsl-rgb.html # from http://130.113.54.154/~monger/hsl-rgb.html
def _RGB2HSL(self): def _RGB2HSL(self):
import numpy
if self.model != 'RGB': return if self.model != 'RGB': return
HSL = numpy.zeros(3,'d') HSL = np.zeros(3,'d')
maxcolor = self.color.max() maxcolor = self.color.max()
mincolor = self.color.min() mincolor = self.color.min()
HSL[2] = (maxcolor + mincolor)/2.0 HSL[2] = (maxcolor + mincolor)/2.0
@ -146,19 +146,19 @@ class Color():
# with all values in the range of 0 to 1 # with all values in the range of 0 to 1
# from http://www.cs.rit.edu/~ncs/color/t_convert.html # from http://www.cs.rit.edu/~ncs/color/t_convert.html
def _RGB2XYZ(self): def _RGB2XYZ(self):
import numpy
if self.model != 'RGB': return if self.model != 'RGB': return
XYZ = numpy.zeros(3,'d') XYZ = np.zeros(3,'d')
RGB_lin = numpy.zeros(3,'d') RGB_lin = np.zeros(3,'d')
convert = numpy.array([[0.412453,0.357580,0.180423], convert = np.array([[0.412453,0.357580,0.180423],
[0.212671,0.715160,0.072169], [0.212671,0.715160,0.072169],
[0.019334,0.119193,0.950227]]) [0.019334,0.119193,0.950227]])
for i in xrange(3): for i in xrange(3):
if (self.color[i] > 0.04045): RGB_lin[i] = ((self.color[i]+0.0555)/1.0555)**2.4 if (self.color[i] > 0.04045): RGB_lin[i] = ((self.color[i]+0.0555)/1.0555)**2.4
else: RGB_lin[i] = self.color[i] /12.92 else: RGB_lin[i] = self.color[i] /12.92
XYZ = numpy.dot(convert,RGB_lin) XYZ = np.dot(convert,RGB_lin)
for i in xrange(3): for i in xrange(3):
XYZ[i] = max(XYZ[i],0.0) XYZ[i] = max(XYZ[i],0.0)
@ -173,14 +173,14 @@ class Color():
# with all values in the range of 0 to 1 # with all values in the range of 0 to 1
# from http://www.cs.rit.edu/~ncs/color/t_convert.html # from http://www.cs.rit.edu/~ncs/color/t_convert.html
def _XYZ2RGB(self): def _XYZ2RGB(self):
import numpy
if self.model != 'XYZ': return if self.model != 'XYZ': return
convert = numpy.array([[ 3.240479,-1.537150,-0.498535], convert = np.array([[ 3.240479,-1.537150,-0.498535],
[-0.969256, 1.875992, 0.041556], [-0.969256, 1.875992, 0.041556],
[ 0.055648,-0.204043, 1.057311]]) [ 0.055648,-0.204043, 1.057311]])
RGB_lin = numpy.dot(convert,self.color) RGB_lin = np.dot(convert,self.color)
RGB = numpy.zeros(3,'d') RGB = np.zeros(3,'d')
for i in xrange(3): for i in xrange(3):
if (RGB_lin[i] > 0.0031308): RGB[i] = ((RGB_lin[i])**(1.0/2.4))*1.0555-0.0555 if (RGB_lin[i] > 0.0031308): RGB[i] = ((RGB_lin[i])**(1.0/2.4))*1.0555-0.0555
@ -202,11 +202,11 @@ class Color():
# with XYZ in the range of 0 to 1 # with XYZ in the range of 0 to 1
# from http://www.easyrgb.com/index.php?X=MATH&H=07#text7 # from http://www.easyrgb.com/index.php?X=MATH&H=07#text7
def _CIELAB2XYZ(self): def _CIELAB2XYZ(self):
import numpy
if self.model != 'CIELAB': return if self.model != 'CIELAB': return
ref_white = numpy.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65 ref_white = np.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65
XYZ = numpy.zeros(3,'d') XYZ = np.zeros(3,'d')
XYZ[1] = (self.color[0] + 16.0 ) / 116.0 XYZ[1] = (self.color[0] + 16.0 ) / 116.0
XYZ[0] = XYZ[1] + self.color[1]/ 500.0 XYZ[0] = XYZ[1] + self.color[1]/ 500.0
@ -226,17 +226,17 @@ class Color():
# with XYZ in the range of 0 to 1 # with XYZ in the range of 0 to 1
# from http://en.wikipedia.org/wiki/Lab_color_space, http://www.cs.rit.edu/~ncs/color/t_convert.html # from http://en.wikipedia.org/wiki/Lab_color_space, http://www.cs.rit.edu/~ncs/color/t_convert.html
def _XYZ2CIELAB(self): def _XYZ2CIELAB(self):
import numpy
if self.model != 'XYZ': return if self.model != 'XYZ': return
ref_white = numpy.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65 ref_white = np.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65
XYZ = self.color/ref_white XYZ = self.color/ref_white
for i in xrange(len(XYZ)): for i in xrange(len(XYZ)):
if (XYZ[i] > 216./24389 ): XYZ[i] = XYZ[i]**(1.0/3.0) if (XYZ[i] > 216./24389 ): XYZ[i] = XYZ[i]**(1.0/3.0)
else: XYZ[i] = (841./108. * XYZ[i]) + 16.0/116.0 else: XYZ[i] = (841./108. * XYZ[i]) + 16.0/116.0
converted = Color('CIELAB', numpy.array([ 116.0 * XYZ[1] - 16.0, converted = Color('CIELAB', np.array([ 116.0 * XYZ[1] - 16.0,
500.0 * (XYZ[0] - XYZ[1]), 500.0 * (XYZ[0] - XYZ[1]),
200.0 * (XYZ[1] - XYZ[2]) ])) 200.0 * (XYZ[1] - XYZ[2]) ]))
self.model = converted.model self.model = converted.model
@ -247,11 +247,11 @@ class Color():
# convert CIE Lab to Msh colorspace # convert CIE Lab to Msh colorspace
# from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls # from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls
def _CIELAB2MSH(self): def _CIELAB2MSH(self):
import numpy, math
if self.model != 'CIELAB': return if self.model != 'CIELAB': return
Msh = numpy.zeros(3,'d') Msh = np.zeros(3,'d')
Msh[0] = math.sqrt(numpy.dot(self.color,self.color)) Msh[0] = math.sqrt(np.dot(self.color,self.color))
if (Msh[0] > 0.001): if (Msh[0] > 0.001):
Msh[1] = math.acos(self.color[0]/Msh[0]) Msh[1] = math.acos(self.color[0]/Msh[0])
if (self.color[1] != 0.0): if (self.color[1] != 0.0):
@ -267,10 +267,10 @@ class Color():
# s,h in radians # s,h in radians
# from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls # from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls
def _MSH2CIELAB(self): def _MSH2CIELAB(self):
import numpy, math
if self.model != 'MSH': return if self.model != 'MSH': return
Lab = numpy.zeros(3,'d') Lab = np.zeros(3,'d')
Lab[0] = self.color[0] * math.cos(self.color[1]) Lab[0] = self.color[0] * math.cos(self.color[1])
Lab[1] = self.color[0] * math.sin(self.color[1]) * math.cos(self.color[2]) Lab[1] = self.color[0] * math.sin(self.color[1]) * math.cos(self.color[2])
Lab[2] = self.color[0] * math.sin(self.color[1]) * math.sin(self.color[2]) Lab[2] = self.color[0] * math.sin(self.color[1]) * math.sin(self.color[2])
@ -346,8 +346,6 @@ class Colormap():
def interpolate_Msh(lo, hi, frac): def interpolate_Msh(lo, hi, frac):
import math,numpy as np
def rad_diff(a,b): def rad_diff(a,b):
return abs(a[2]-b[2]) return abs(a[2]-b[2])
@ -381,8 +379,8 @@ class Colormap():
linearly interpolate color at given fraction between lower and higher color in model of lower color linearly interpolate color at given fraction between lower and higher color in model of lower color
''' '''
interpolation = (1.0 - frac) * numpy.array(lo.color[:]) \ interpolation = (1.0 - frac) * np.array(lo.color[:]) \
+ frac * numpy.array(hi.expressAs(lo.model).color[:]) + frac * np.array(hi.expressAs(lo.model).color[:])
return Color(lo.model,interpolation) return Color(lo.model,interpolation)
@ -411,7 +409,7 @@ class Colormap():
''' '''
format = format.lower() # consistent comparison basis format = format.lower() # consistent comparison basis
frac = 0.5*(numpy.array(crop) + 1.0) # rescale crop range to fractions frac = 0.5*(np.array(crop) + 1.0) # rescale crop range to fractions
colors = [self.color(float(i)/(steps-1)*(frac[1]-frac[0])+frac[0]).expressAs(model).color for i in xrange(steps)] colors = [self.color(float(i)/(steps-1)*(frac[1]-frac[0])+frac[0]).expressAs(model).color for i in xrange(steps)]
if format == 'paraview': if format == 'paraview':