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DAMASK_EICMD
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DAMASK_EICMD/lib/damask/colormaps.py

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# -*- coding: UTF-8 no BOM -*-
import math,numpy as np
### --- COLOR CLASS --------------------------------------------------
class Color():
"""
Conversion of colors between different color-spaces.
Colors should be given in the form Color('model',[vector]).
To convert or copy color from one space to other, use the methods
convertTo('model') or expressAs('model'), respectively.
"""
__slots__ = [
'model',
'color',
'__dict__',
]
# ------------------------------------------------------------------
def __init__(self,
model = 'RGB',
color = np.zeros(3,'d')):
self.__transforms__ = \
{'HSL': {'index': 0, 'next': self._HSL2RGB},
'RGB': {'index': 1, 'next': self._RGB2XYZ, 'prev': self._RGB2HSL},
'XYZ': {'index': 2, 'next': self._XYZ2CIELAB, 'prev': self._XYZ2RGB},
'CIELAB': {'index': 3, 'next': self._CIELAB2MSH, 'prev': self._CIELAB2XYZ},
'MSH': {'index': 4, 'prev': self._MSH2CIELAB},
}
model = model.upper()
if model not in list(self.__transforms__.keys()): model = 'RGB'
if model == 'RGB' and max(color) > 1.0: # are we RGB255 ?
for i in range(3):
color[i] /= 255.0 # rescale to RGB
if model == 'HSL': # are we HSL ?
if abs(color[0]) > 1.0: color[0] /= 360.0 # with angular hue?
while color[0] >= 1.0: 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.color = np.array(color,'d')
# ------------------------------------------------------------------
def __repr__(self):
"""Color model and values"""
return 'Model: %s Color: %s'%(self.model,str(self.color))
# ------------------------------------------------------------------
def __str__(self):
"""Color model and values"""
return self.__repr__()
# ------------------------------------------------------------------
def convertTo(self,toModel = 'RGB'):
toModel = toModel.upper()
if toModel not in list(self.__transforms__.keys()): return
sourcePos = self.__transforms__[self.model]['index']
targetPos = self.__transforms__[toModel]['index']
while sourcePos < targetPos:
self.__transforms__[self.model]['next']()
sourcePos += 1
while sourcePos > targetPos:
self.__transforms__[self.model]['prev']()
sourcePos -= 1
return self
# ------------------------------------------------------------------
def expressAs(self,asModel = 'RGB'):
return self.__class__(self.model,self.color).convertTo(asModel)
def _HSL2RGB(self):
"""
Convert H(ue) S(aturation) L(uminance) to R(red) G(reen) B(lue)
with all values in the range of 0 to 1
from http://en.wikipedia.org/wiki/HSL_and_HSV
"""
if self.model != 'HSL': return
sextant = self.color[0]*6.0
c = (1.0 - abs(2.0 * self.color[2] - 1.0))*self.color[1]
x = c*(1.0 - abs(sextant%2 - 1.0))
m = self.color[2] - 0.5*c
converted = Color('RGB',np.array([
[c+m, x+m, m],
[x+m, c+m, m],
[m, c+m, x+m],
[m, x+m, c+m],
[x+m, m, c+m],
[c+m, m, x+m],
][int(sextant)],'d'))
self.model = converted.model
self.color = converted.color
def _RGB2HSL(self):
"""
Convert R(ed) G(reen) B(lue) to H(ue) S(aturation) L(uminance)
with all values in the range of 0 to 1
from http://130.113.54.154/~monger/hsl-rgb.html
"""
if self.model != 'RGB': return
HSL = np.zeros(3,'d')
maxcolor = self.color.max()
mincolor = self.color.min()
HSL[2] = (maxcolor + mincolor)/2.0
if(mincolor == maxcolor):
HSL[0] = 0.0
HSL[1] = 0.0
else:
if (HSL[2]<0.5):
HSL[1] = (maxcolor - mincolor)/(maxcolor + mincolor)
else:
HSL[1] = (maxcolor - mincolor)/(2.0 - maxcolor - mincolor)
if (maxcolor == self.color[0]):
HSL[0] = 0.0 + (self.color[1] - self.color[2])/(maxcolor - mincolor)
elif (maxcolor == self.color[1]):
HSL[0] = 2.0 + (self.color[2] - self.color[0])/(maxcolor - mincolor)
elif (maxcolor == self.color[2]):
HSL[0] = 4.0 + (self.color[0] - self.color[1])/(maxcolor - mincolor)
HSL[0] = HSL[0]*60.0 # scaling to 360 might be dangerous for small values
if (HSL[0] < 0.0):
HSL[0] = HSL[0] + 360.0
for i in range(2):
HSL[i+1] = min(HSL[i+1],1.0)
HSL[i+1] = max(HSL[i+1],0.0)
converted = Color('HSL', HSL)
self.model = converted.model
self.color = converted.color
def _RGB2XYZ(self):
"""
Convert R(ed) G(reen) B(lue) to CIE XYZ
with all values in the range of 0 to 1
from http://www.cs.rit.edu/~ncs/color/t_convert.html
"""
if self.model != 'RGB': return
XYZ = np.zeros(3,'d')
RGB_lin = np.zeros(3,'d')
convert = np.array([[0.412453,0.357580,0.180423],
[0.212671,0.715160,0.072169],
[0.019334,0.119193,0.950227]])
for i in range(3):
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
XYZ = np.dot(convert,RGB_lin)
for i in range(3):
XYZ[i] = max(XYZ[i],0.0)
converted = Color('XYZ', XYZ)
self.model = converted.model
self.color = converted.color
def _XYZ2RGB(self):
"""
Convert CIE XYZ to R(ed) G(reen) B(lue)
with all values in the range of 0 to 1
from http://www.cs.rit.edu/~ncs/color/t_convert.html
"""
if self.model != 'XYZ':
return
convert = np.array([[ 3.240479,-1.537150,-0.498535],
[-0.969256, 1.875992, 0.041556],
[ 0.055648,-0.204043, 1.057311]])
RGB_lin = np.dot(convert,self.color)
RGB = np.zeros(3,'d')
for i in range(3):
if (RGB_lin[i] > 0.0031308): RGB[i] = ((RGB_lin[i])**(1.0/2.4))*1.0555-0.0555
else: RGB[i] = RGB_lin[i] *12.92
for i in range(3):
RGB[i] = min(RGB[i],1.0)
RGB[i] = max(RGB[i],0.0)
maxVal = max(RGB) # clipping colors according to the display gamut
if (maxVal > 1.0): RGB /= maxVal
converted = Color('RGB', RGB)
self.model = converted.model
self.color = converted.color
def _CIELAB2XYZ(self):
"""
Convert CIE Lab to CIE XYZ
with XYZ in the range of 0 to 1
from http://www.easyrgb.com/index.php?X=MATH&H=07#text7
"""
if self.model != 'CIELAB': return
ref_white = np.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65
XYZ = np.zeros(3,'d')
XYZ[1] = (self.color[0] + 16.0 ) / 116.0
XYZ[0] = XYZ[1] + self.color[1]/ 500.0
XYZ[2] = XYZ[1] - self.color[2]/ 200.0
for i in range(len(XYZ)):
if (XYZ[i] > 6./29. ): XYZ[i] = XYZ[i]**3.
else: XYZ[i] = 108./841. * (XYZ[i] - 4./29.)
converted = Color('XYZ', XYZ*ref_white)
self.model = converted.model
self.color = converted.color
def _XYZ2CIELAB(self):
"""
Convert CIE XYZ to CIE Lab
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
"""
if self.model != 'XYZ': return
ref_white = np.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65
XYZ = self.color/ref_white
for i in range(len(XYZ)):
if (XYZ[i] > 216./24389 ): XYZ[i] = XYZ[i]**(1.0/3.0)
else: XYZ[i] = (841./108. * XYZ[i]) + 16.0/116.0
converted = Color('CIELAB', np.array([ 116.0 * XYZ[1] - 16.0,
500.0 * (XYZ[0] - XYZ[1]),
200.0 * (XYZ[1] - XYZ[2]) ]))
self.model = converted.model
self.color = converted.color
def _CIELAB2MSH(self):
"""
Convert CIE Lab to Msh colorspace
from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls
"""
if self.model != 'CIELAB': return
Msh = np.zeros(3,'d')
Msh[0] = math.sqrt(np.dot(self.color,self.color))
if (Msh[0] > 0.001):
Msh[1] = math.acos(self.color[0]/Msh[0])
if (self.color[1] != 0.0):
Msh[2] = math.atan2(self.color[2],self.color[1])
converted = Color('MSH', Msh)
self.model = converted.model
self.color = converted.color
def _MSH2CIELAB(self):
"""
Convert Msh colorspace to CIE Lab
with s,h in radians
from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls
"""
if self.model != 'MSH': return
Lab = np.zeros(3,'d')
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[2] = self.color[0] * math.sin(self.color[1]) * math.sin(self.color[2])
converted = Color('CIELAB', Lab)
self.model = converted.model
self.color = converted.color
class Colormap():
"""Perceptually uniform diverging or sequential colormaps."""
__slots__ = [
'left',
'right',
'interpolate',
]
__predefined__ = {
'gray': {'left': Color('HSL',[0,1,1]),
'right': Color('HSL',[0,0,0.15]),
'interpolate': 'perceptualuniform'},
'grey': {'left': Color('HSL',[0,1,1]),
'right': Color('HSL',[0,0,0.15]),
'interpolate': 'perceptualuniform'},
'red': {'left': Color('HSL',[0,1,0.14]),
'right': Color('HSL',[0,0.35,0.91]),
'interpolate': 'perceptualuniform'},
'green': {'left': Color('HSL',[0.33333,1,0.14]),
'right': Color('HSL',[0.33333,0.35,0.91]),
'interpolate': 'perceptualuniform'},
'blue': {'left': Color('HSL',[0.66,1,0.14]),
'right': Color('HSL',[0.66,0.35,0.91]),
'interpolate': 'perceptualuniform'},
'seaweed': {'left': Color('HSL',[0.78,1.0,0.1]),
'right': Color('HSL',[0.40000,0.1,0.9]),
'interpolate': 'perceptualuniform'},
'bluebrown': {'left': Color('HSL',[0.65,0.53,0.49]),
'right': Color('HSL',[0.11,0.75,0.38]),
'interpolate': 'perceptualuniform'},
'redgreen': {'left': Color('HSL',[0.97,0.96,0.36]),
'right': Color('HSL',[0.33333,1.0,0.14]),
'interpolate': 'perceptualuniform'},
'bluered': {'left': Color('HSL',[0.65,0.53,0.49]),
'right': Color('HSL',[0.97,0.96,0.36]),
'interpolate': 'perceptualuniform'},
'blueredrainbow':{'left': Color('HSL',[2.0/3.0,1,0.5]),
'right': Color('HSL',[0,1,0.5]),
'interpolate': 'linear' },
'orientation': {'left': Color('RGB',[0.933334,0.878432,0.878431]),
'right': Color('RGB',[0.250980,0.007843,0.000000]),
'interpolate': 'perceptualuniform'},
'strain': {'left': Color('RGB',[0.941177,0.941177,0.870588]),
'right': Color('RGB',[0.266667,0.266667,0.000000]),
'interpolate': 'perceptualuniform'},
'stress': {'left': Color('RGB',[0.878432,0.874511,0.949019]),
'right': Color('RGB',[0.000002,0.000000,0.286275]),
'interpolate': 'perceptualuniform'},
}
# ------------------------------------------------------------------
def __init__(self,
left = Color('RGB',[1,1,1]),
right = Color('RGB',[0,0,0]),
interpolate = 'perceptualuniform',
predefined = None
):
if predefined is not None:
left = self.__predefined__[predefined.lower()]['left']
right= self.__predefined__[predefined.lower()]['right']
interpolate = self.__predefined__[predefined.lower()]['interpolate']
if left.__class__.__name__ != 'Color':
left = Color()
if right.__class__.__name__ != 'Color':
right = Color()
self.left = left
self.right = right
self.interpolate = interpolate
# ------------------------------------------------------------------
def __repr__(self):
"""Left and right value of colormap"""
return 'Left: %s Right: %s'%(self.left,self.right)
# ------------------------------------------------------------------
def invert(self):
(self.left, self.right) = (self.right, self.left)
return self
# ------------------------------------------------------------------
def color(self,fraction = 0.5):
def interpolate_Msh(lo, hi, frac):
def rad_diff(a,b):
return abs(a[2]-b[2])
# if saturation of one of the two colors is too less than the other, hue of the less
def adjust_hue(Msh_sat, Msh_unsat):
if Msh_sat[0] >= Msh_unsat[0]:
return Msh_sat[2]
else:
hSpin = Msh_sat[1]/math.sin(Msh_sat[1])*math.sqrt(Msh_unsat[0]**2.0-Msh_sat[0]**2)/Msh_sat[0]
if Msh_sat[2] < - math.pi/3.0: hSpin *= -1.0
return Msh_sat[2] + hSpin
Msh1 = np.array(lo[:])
Msh2 = np.array(hi[:])
if (Msh1[1] > 0.05 and Msh2[1] > 0.05 and rad_diff(Msh1,Msh2) > math.pi/3.0):
M_mid = max(Msh1[0],Msh2[0],88.0)
if frac < 0.5:
Msh2 = np.array([M_mid,0.0,0.0],'d')
frac *= 2.0
else:
Msh1 = np.array([M_mid,0.0,0.0],'d')
frac = 2.0*frac - 1.0
if Msh1[1] < 0.05 and Msh2[1] > 0.05: Msh1[2] = adjust_hue(Msh2,Msh1)
elif Msh1[1] > 0.05 and Msh2[1] < 0.05: Msh2[2] = adjust_hue(Msh1,Msh2)
Msh = (1.0 - frac) * Msh1 + frac * Msh2
return Color('MSH',Msh)
def interpolate_linear(lo, hi, frac):
"""
Linearly interpolate color at given fraction between lower and
higher color using model of lower color.
"""
interpolation = (1.0 - frac) * np.array(lo.color[:]) \
+ frac * np.array(hi.expressAs(lo.model).color[:])
return Color(lo.model,interpolation)
if self.interpolate == 'perceptualuniform':
return interpolate_Msh(self.left.expressAs('MSH').color,
self.right.expressAs('MSH').color,fraction)
elif self.interpolate == 'linear':
return interpolate_linear(self.left,
self.right,fraction)
else:
raise NameError('unknown color interpolation method')
# ------------------------------------------------------------------
def export(self,name = 'uniformPerceptualColorMap',\
format = 'paraview',\
steps = 2,\
crop = [-1.0,1.0],
model = 'RGB'):
"""
[RGB] colormap for use in paraview or gmsh, or as raw string, or array.
Arguments: name, format, steps, crop.
Format is one of (paraview, gmsh, raw, list).
Crop selects a (sub)range in [-1.0,1.0].
Generates sequential map if one limiting color is either white or black,
diverging map otherwise.
"""
format = format.lower() # consistent comparison basis
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 range(steps)]
if format == 'paraview':
colormap = ['[\n {{\n "ColorSpace" : "RGB", "Name" : "{}",\n "RGBPoints" : ['.format(name)] \
+ [' {:4d},{:8.6f},{:8.6f},{:8.6f},'.format(i,color[0],color[1],color[2],)
for i,color in enumerate(colors[:-1])]\
+ [' {:4d},{:8.6f},{:8.6f},{:8.6f} '.format(len(colors),colors[-1][0],colors[-1][1],colors[-1][2],)]\
+ [' ]\n }\n]']
elif format == 'gmsh':
colormap = ['View.ColorTable = {'] \
+ [',\n'.join(['{%s}'%(','.join([str(x*255.0) for x in color])) for color in colors])] \
+ ['}']
elif format == 'gom':
colormap = ['1 1 ' + str(name) \
+ ' 9 ' + str(name) \
+ ' 0 1 0 3 0 0 -1 9 \ 0 0 0 255 255 255 0 0 255 ' \
+ '30 NO_UNIT 1 1 64 64 64 255 1 0 0 0 0 0 0 3 0 ' + str(len(colors)) \
+ ' '.join([' 0 %s 255 1'%(' '.join([str(int(x*255.0)) for x in color])) for color in reversed(colors)])]
elif format == 'raw':
colormap = ['\t'.join(map(str,color)) for color in colors]
elif format == 'list':
colormap = colors
else:
raise NameError('unknown color export format')
return '\n'.join(colormap) + '\n' if type(colormap[0]) is str else colormap
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