checked with prospector, adopted mainly docstrings
This commit is contained in:
Martin Diehl
parent
f13ba71f6e
commit
24391b5398
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@ -5,11 +5,12 @@ import math,numpy as np
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### --- COLOR CLASS --------------------------------------------------
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class Color():
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'''
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Conversion of colors between different color-spaces. Colors should be given in the form
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Color('model',[vector]).To convert and copy color from one space to other, use the methods
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convertTo('model') and expressAs('model')spectively
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'''
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"""Conversion of colors between different color-spaces.
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Colors should be given in the form
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Color('model',[vector]).To convert and copy color from one space to other, use the methods
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convertTo('model') and expressAs('model')spectively
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"""
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__slots__ = [
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'model',
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@ -17,7 +18,7 @@ class Color():
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]
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def __init__(self,
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model = 'RGB',
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color = np.zeros(3,'d')):
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@ -32,30 +33,32 @@ class Color():
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model = model.upper()
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if model not in self.__transforms__.keys(): model = 'RGB'
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if model == 'RGB' and max(color) > 1.0: # are we RGB255 ?
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if model == 'RGB' and max(color) > 1.0: # are we RGB255 ?
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for i in range(3):
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color[i] /= 255.0 # rescale to RGB
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color[i] /= 255.0 # rescale to RGB
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if model == 'HSL': # are we HSL ?
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if abs(color[0]) > 1.0: color[0] /= 360.0 # with angular hue?
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while color[0] >= 1.0: color[0] -= 1.0 # rewind to proper range
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while color[0] < 0.0: color[0] += 1.0 # rewind to proper range
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if model == 'HSL': # are we HSL ?
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if abs(color[0]) > 1.0: color[0] /= 360.0 # with angular hue?
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while color[0] >= 1.0: color[0] -= 1.0 # rewind to proper range
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while color[0] < 0.0: color[0] += 1.0 # rewind to proper range
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self.model = model
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self.color = np.array(color,'d')
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def __repr__(self):
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"""Color model and values"""
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return 'Model: %s Color: %s'%(self.model,str(self.color))
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def __str__(self):
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"""Color model and values"""
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return self.__repr__()
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def convertTo(self,toModel = 'RGB'):
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toModel = toModel.upper()
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if toModel not in self.__transforms__.keys(): return
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@ -73,17 +76,19 @@ class Color():
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return self
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def expressAs(self,asModel = 'RGB'):
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return self.__class__(self.model,self.color).convertTo(asModel)
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# ------------------------------------------------------------------
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# convert H(ue) S(aturation) L(uminance) to R(red) G(reen) B(lue)
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# with S,L,H,R,G,B running from 0 to 1
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# from http://en.wikipedia.org/wiki/HSL_and_HSV
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def _HSL2RGB(self):
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def _HSL2RGB(self):
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"""
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convert H(ue) S(aturation) L(uminance) to R(red) G(reen) B(lue)
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with S,L,H,R,G,B running from 0 to 1
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from http://en.wikipedia.org/wiki/HSL_and_HSV
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"""
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if self.model != 'HSL': return
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sextant = self.color[0]*6.0
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@ -102,13 +107,14 @@ class Color():
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self.model = converted.model
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self.color = converted.color
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# ------------------------------------------------------------------
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# convert R(ed) G(reen) B(lue) to H(ue) S(aturation) L(uminance)
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# with S,L,H,R,G,B running from 0 to 1
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# from http://130.113.54.154/~monger/hsl-rgb.html
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def _RGB2HSL(self):
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"""
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convert R(ed) G(reen) B(lue) to H(ue) S(aturation) L(uminance)
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with S,L,H,R,G,B running from 0 to 1
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from http://130.113.54.154/~monger/hsl-rgb.html
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"""
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if self.model != 'RGB': return
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HSL = np.zeros(3,'d')
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@ -129,7 +135,7 @@ class Color():
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HSL[0] = 2.0 + (self.color[2] - self.color[0])/(maxcolor - mincolor)
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elif (maxcolor == self.color[2]):
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HSL[0] = 4.0 + (self.color[0] - self.color[1])/(maxcolor - mincolor)
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HSL[0] = HSL[0]*60.0 # is it necessary to scale to 360 hue values? might be dangerous for small values <1..!
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HSL[0] = HSL[0]*60.0 # scaling to 360 might be dangerous for small values
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if (HSL[0] < 0.0):
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HSL[0] = HSL[0] + 360.0
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for i in xrange(2):
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@ -141,12 +147,14 @@ class Color():
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self.color = converted.color
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# ------------------------------------------------------------------
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# convert R(ed) G(reen) B(lue) to CIE XYZ
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# with all values in the range of 0 to 1
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# from http://www.cs.rit.edu/~ncs/color/t_convert.html
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def _RGB2XYZ(self):
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def _RGB2XYZ(self):
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"""
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convert R(ed) G(reen) B(lue) to CIE XYZ
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with all values in the range of 0 to 1
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from http://www.cs.rit.edu/~ncs/color/t_convert.html
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"""
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if self.model != 'RGB': return
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XYZ = np.zeros(3,'d')
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@ -168,12 +176,14 @@ class Color():
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self.color = converted.color
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# ------------------------------------------------------------------
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# convert CIE XYZ to R(ed) G(reen) B(lue)
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# with all values in the range of 0 to 1
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# from http://www.cs.rit.edu/~ncs/color/t_convert.html
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def _XYZ2RGB(self):
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def _XYZ2RGB(self):
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"""
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convert CIE XYZ to R(ed) G(reen) B(lue)
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with all values in the range of 0 to 1
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from http://www.cs.rit.edu/~ncs/color/t_convert.html
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"""
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if self.model != 'XYZ': return
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convert = np.array([[ 3.240479,-1.537150,-0.498535],
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@ -189,7 +199,7 @@ class Color():
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RGB[i] = min(RGB[i],1.0)
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RGB[i] = max(RGB[i],0.0)
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maxVal = max(RGB) # clipping colors according to the display gamut
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maxVal = max(RGB) # clipping colors according to the display gamut
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if (maxVal > 1.0): RGB /= maxVal
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converted = Color('RGB', RGB)
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@ -197,15 +207,17 @@ class Color():
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self.color = converted.color
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# ------------------------------------------------------------------
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# convert CIE Lab to CIE XYZ
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# with XYZ in the range of 0 to 1
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# from http://www.easyrgb.com/index.php?X=MATH&H=07#text7
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def _CIELAB2XYZ(self):
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def _CIELAB2XYZ(self):
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"""
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convert CIE Lab to CIE XYZ
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with XYZ in the range of 0 to 1
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from http://www.easyrgb.com/index.php?X=MATH&H=07#text7
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"""
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if self.model != 'CIELAB': return
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ref_white = np.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65
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ref_white = np.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65
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XYZ = np.zeros(3,'d')
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XYZ[1] = (self.color[0] + 16.0 ) / 116.0
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@ -220,16 +232,16 @@ class Color():
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self.model = converted.model
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self.color = converted.color
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# ------------------------------------------------------------------
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# convert CIE XYZ to CIE Lab
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# with XYZ in the range of 0 to 1
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# from http://en.wikipedia.org/wiki/Lab_color_space, http://www.cs.rit.edu/~ncs/color/t_convert.html
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def _XYZ2CIELAB(self):
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"""
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convert CIE XYZ to CIE Lab
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with XYZ in the range of 0 to 1
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from http://en.wikipedia.org/wiki/Lab_color_space, http://www.cs.rit.edu/~ncs/color/t_convert.html
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"""
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if self.model != 'XYZ': return
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ref_white = np.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65
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ref_white = np.array([.95047, 1.00000, 1.08883],'d') # Observer = 2, Illuminant = D65
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XYZ = self.color/ref_white
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for i in xrange(len(XYZ)):
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@ -242,12 +254,13 @@ class Color():
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self.model = converted.model
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self.color = converted.color
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# ------------------------------------------------------------------
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# convert CIE Lab to Msh colorspace
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# from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls
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def _CIELAB2MSH(self):
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"""
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convert CIE Lab to Msh colorspace
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from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls
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"""
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if self.model != 'CIELAB': return
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Msh = np.zeros(3,'d')
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@ -261,13 +274,14 @@ class Color():
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self.model = converted.model
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self.color = converted.color
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# ------------------------------------------------------------------
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# convert Msh colorspace to CIE Lab
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# s,h in radians
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# from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls
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def _MSH2CIELAB(self):
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def _MSH2CIELAB(self):
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"""
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convert Msh colorspace to CIE Lab
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s,h in radians
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from http://www.cs.unm.edu/~kmorel/documents/ColorMaps/DivergingColorMapWorkshop.xls
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"""
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if self.model != 'MSH': return
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Lab = np.zeros(3,'d')
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@ -280,13 +294,8 @@ class Color():
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self.color = converted.color
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### --- COLORMAP CLASS -----------------------------------------------
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class Colormap():
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'''
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perceptually uniform diverging or sequential colormaps.
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'''
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"""perceptually uniform diverging or sequential colormaps."""
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__slots__ = [
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'left',
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@ -294,20 +303,40 @@ class Colormap():
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'interpolate',
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]
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__predefined__ = {
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'gray': {'left': Color('HSL',[0,1,1]), 'right': Color('HSL',[0,0,0.15]), 'interpolate': 'perceptualuniform'},
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'grey': {'left': Color('HSL',[0,1,1]), 'right': Color('HSL',[0,0,0.15]), 'interpolate': 'perceptualuniform'},
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'red': {'left': Color('HSL',[0,1,0.14]), 'right': Color('HSL',[0,0.35,0.91]), 'interpolate': 'perceptualuniform'},
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'green': {'left': Color('HSL',[0.33333,1,0.14]), 'right': Color('HSL',[0.33333,0.35,0.91]), 'interpolate': 'perceptualuniform'},
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'blue': {'left': Color('HSL',[0.66,1,0.14]), 'right': Color('HSL',[0.66,0.35,0.91]), 'interpolate': 'perceptualuniform'},
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'seaweed': {'left': Color('HSL',[0.78,1.0,0.1]), 'right': Color('HSL',[0.40000,0.1,0.9]), 'interpolate': 'perceptualuniform'},
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'bluebrown': {'left': Color('HSL',[0.65,0.53,0.49]), 'right': Color('HSL',[0.11,0.75,0.38]), 'interpolate': 'perceptualuniform'},
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'redgreen': {'left': Color('HSL',[0.97,0.96,0.36]), 'right': Color('HSL',[0.33333,1.0,0.14]), 'interpolate': 'perceptualuniform'},
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'bluered': {'left': Color('HSL',[0.65,0.53,0.49]), 'right': Color('HSL',[0.97,0.96,0.36]), 'interpolate': 'perceptualuniform'},
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'blueredrainbow':{'left': Color('HSL',[2.0/3.0,1,0.5]), 'right': Color('HSL',[0,1,0.5]), 'interpolate': 'linear' },
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'gray': {'left': Color('HSL',[0,1,1]),
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'right': Color('HSL',[0,0,0.15]),
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'interpolate': 'perceptualuniform'},
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'grey': {'left': Color('HSL',[0,1,1]),
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'right': Color('HSL',[0,0,0.15]),
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'interpolate': 'perceptualuniform'},
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'red': {'left': Color('HSL',[0,1,0.14]),
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'right': Color('HSL',[0,0.35,0.91]),
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'interpolate': 'perceptualuniform'},
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'green': {'left': Color('HSL',[0.33333,1,0.14]),
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'right': Color('HSL',[0.33333,0.35,0.91]),
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'interpolate': 'perceptualuniform'},
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'blue': {'left': Color('HSL',[0.66,1,0.14]),
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'right': Color('HSL',[0.66,0.35,0.91]),
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'interpolate': 'perceptualuniform'},
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'seaweed': {'left': Color('HSL',[0.78,1.0,0.1]),
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'right': Color('HSL',[0.40000,0.1,0.9]),
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'interpolate': 'perceptualuniform'},
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'bluebrown': {'left': Color('HSL',[0.65,0.53,0.49]),
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'right': Color('HSL',[0.11,0.75,0.38]),
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'interpolate': 'perceptualuniform'},
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'redgreen': {'left': Color('HSL',[0.97,0.96,0.36]),
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'right': Color('HSL',[0.33333,1.0,0.14]),
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'interpolate': 'perceptualuniform'},
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'bluered': {'left': Color('HSL',[0.65,0.53,0.49]),
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'right': Color('HSL',[0.97,0.96,0.36]),
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'interpolate': 'perceptualuniform'},
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'blueredrainbow':{'left': Color('HSL',[2.0/3.0,1,0.5]),
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'right': Color('HSL',[0,1,0.5]),
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'interpolate': 'linear' },
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}
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def __init__(self,
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left = Color('RGB',[1,1,1]),
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right = Color('RGB',[0,0,0]),
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@ -330,26 +359,27 @@ class Colormap():
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self.interpolate = interpolate
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def __repr__(self):
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"""left and right value of colormap"""
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return 'Left: %s Right: %s'%(self.left,self.right)
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def invert(self):
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(self.left, self.right) = (self.right, self.left)
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return self
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def color(self,fraction = 0.5):
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def interpolate_Msh(lo, hi, frac):
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def rad_diff(a,b):
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return abs(a[2]-b[2])
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def adjust_hue(Msh_sat, Msh_unsat): # if saturation of one of the two colors is too less than the other, hue of the less
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# if saturation of one of the two colors is too less than the other, hue of the less
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def adjust_hue(Msh_sat, Msh_unsat):
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if Msh_sat[0] >= Msh_unsat[0]:
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return Msh_sat[2]
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else:
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@ -375,10 +405,11 @@ class Colormap():
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return Color('MSH',Msh)
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def interpolate_linear(lo, hi, frac):
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'''
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linearly interpolate color at given fraction between lower and higher color in model of lower color
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'''
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"""
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linearly interpolate color at given fraction between lower and
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higher color in model of lower color
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"""
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interpolation = (1.0 - frac) * np.array(lo.color[:]) \
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+ frac * np.array(hi.expressAs(lo.model).color[:])
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@ -393,23 +424,23 @@ class Colormap():
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else:
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raise NameError('unknown color interpolation method')
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# ------------------------------------------------------------------
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# ------------------------------------------------------------------
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def export(self,name = 'uniformPerceptualColorMap',\
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format = 'paraview',\
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steps = 2,\
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crop = [-1.0,1.0],
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model = 'RGB'):
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'''
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"""
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[RGB] colormap for use in paraview or gmsh, or as raw string, or array.
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arguments: name, format, steps, crop.
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format is one of (paraview, gmsh, raw, list).
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crop selects a (sub)range in [-1.0,1.0].
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generates sequential map if one limiting color is either white or black,
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diverging map otherwise.
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'''
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format = format.lower() # consistent comparison basis
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frac = 0.5*(np.array(crop) + 1.0) # rescale crop range to fractions
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"""
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format = format.lower() # consistent comparison basis
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frac = 0.5*(np.array(crop) + 1.0) # rescale crop range to fractions
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colors = [self.color(float(i)/(steps-1)*(frac[1]-frac[0])+frac[0]).expressAs(model).color for i in xrange(steps)]
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if format == 'paraview':
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@ -439,4 +470,4 @@ class Colormap():
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raise NameError('unknown color export format')
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return '\n'.join(colormap) + '\n' if type(colormap[0]) is str else colormap
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@ -2,7 +2,7 @@
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# $Id$
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import os,sys,string,re,subprocess,shlex
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import os,subprocess,shlex
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|
||||
class Environment():
|
||||
__slots__ = [ \
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
# -*- coding: UTF-8 no BOM -*-
|
||||
|
||||
# $Id$
|
||||
"""Test functionality"""
|
||||
|
||||
from .test import Test
|
||||
from .test import Test "noqa
|
||||
|
|
|
|||
|
|
@ -2,17 +2,19 @@
|
|||
|
||||
# $Id$
|
||||
|
||||
import os, sys, shlex, inspect
|
||||
import subprocess,shutil,string
|
||||
import logging, logging.config
|
||||
import os,sys,shutil
|
||||
import logging,logging.config
|
||||
import damask
|
||||
import numpy as np
|
||||
from collections import Iterable
|
||||
from optparse import OptionParser
|
||||
|
||||
class Test():
|
||||
'''
|
||||
General class for testing.
|
||||
Is sub-classed by the individual tests.
|
||||
'''
|
||||
"""
|
||||
General class for testing.
|
||||
|
||||
Is sub-classed by the individual tests.
|
||||
"""
|
||||
|
||||
variants = []
|
||||
|
||||
|
|
@ -24,7 +26,7 @@ class Test():
|
|||
fh.setLevel(logging.DEBUG)
|
||||
full = logging.Formatter('%(asctime)s - %(levelname)s: \n%(message)s')
|
||||
fh.setFormatter(full)
|
||||
ch = logging.StreamHandler(stream=sys.stdout) # create console handler with a higher log level
|
||||
ch = logging.StreamHandler(stream=sys.stdout) # create console handler with a higher log level
|
||||
ch.setLevel(logging.INFO)
|
||||
# create formatter and add it to the handlers
|
||||
plain = logging.Formatter('%(message)s')
|
||||
|
|
@ -52,9 +54,7 @@ class Test():
|
|||
accept=False)
|
||||
|
||||
def execute(self):
|
||||
'''
|
||||
Run all variants and report first failure.
|
||||
'''
|
||||
"""Run all variants and report first failure."""
|
||||
if self.options.debug:
|
||||
for variant in xrange(len(self.variants)):
|
||||
try:
|
||||
|
|
@ -84,15 +84,11 @@ class Test():
|
|||
return 0
|
||||
|
||||
def testPossible(self):
|
||||
'''
|
||||
Check if test is possible or not (e.g. no license available).
|
||||
'''
|
||||
"""Check if test is possible or not (e.g. no license available)."""
|
||||
return True
|
||||
|
||||
def clean(self):
|
||||
'''
|
||||
Delete directory tree containing current results.
|
||||
'''
|
||||
"""Delete directory tree containing current results."""
|
||||
status = True
|
||||
|
||||
try:
|
||||
|
|
@ -110,103 +106,77 @@ class Test():
|
|||
return status
|
||||
|
||||
def prepareAll(self):
|
||||
'''
|
||||
Do all necessary preparations for the whole test
|
||||
'''
|
||||
"""Do all necessary preparations for the whole test"""
|
||||
return True
|
||||
|
||||
def prepare(self,variant):
|
||||
'''
|
||||
Do all necessary preparations for the run of each test variant
|
||||
'''
|
||||
"""Do all necessary preparations for the run of each test variant"""
|
||||
return True
|
||||
|
||||
|
||||
def run(self,variant):
|
||||
'''
|
||||
Execute the requested test variant.
|
||||
'''
|
||||
"""Execute the requested test variant."""
|
||||
return True
|
||||
|
||||
|
||||
def postprocess(self,variant):
|
||||
'''
|
||||
Perform post-processing of generated results for this test variant.
|
||||
'''
|
||||
"""Perform post-processing of generated results for this test variant."""
|
||||
return True
|
||||
|
||||
|
||||
def compare(self,variant):
|
||||
'''
|
||||
Compare reference to current results.
|
||||
'''
|
||||
"""Compare reference to current results."""
|
||||
return True
|
||||
|
||||
|
||||
def update(self,variant):
|
||||
'''
|
||||
Update reference with current results.
|
||||
'''
|
||||
"""Update reference with current results."""
|
||||
logging.debug('Update not necessary')
|
||||
return True
|
||||
|
||||
|
||||
def dirReference(self):
|
||||
'''
|
||||
Directory containing reference results of the test.
|
||||
'''
|
||||
"""Directory containing reference results of the test."""
|
||||
return os.path.normpath(os.path.join(self.dirBase,'reference/'))
|
||||
|
||||
|
||||
def dirCurrent(self):
|
||||
'''
|
||||
Directory containing current results of the test.
|
||||
'''
|
||||
"""Directory containing current results of the test."""
|
||||
return os.path.normpath(os.path.join(self.dirBase,'current/'))
|
||||
|
||||
|
||||
def dirProof(self):
|
||||
'''
|
||||
Directory containing human readable proof of correctness for the test.
|
||||
'''
|
||||
"""Directory containing human readable proof of correctness for the test."""
|
||||
return os.path.normpath(os.path.join(self.dirBase,'proof/'))
|
||||
|
||||
|
||||
def fileInRoot(self,dir,file):
|
||||
'''
|
||||
Path to a file in the root directory of DAMASK.
|
||||
'''
|
||||
"""Path to a file in the root directory of DAMASK."""
|
||||
return os.path.join(damask.Environment().rootDir(),dir,file)
|
||||
|
||||
|
||||
def fileInReference(self,file):
|
||||
'''
|
||||
Path to a file in the refrence directory for the test.
|
||||
'''
|
||||
"""Path to a file in the refrence directory for the test."""
|
||||
return os.path.join(self.dirReference(),file)
|
||||
|
||||
|
||||
def fileInCurrent(self,file):
|
||||
'''
|
||||
Path to a file in the current results directory for the test.
|
||||
'''
|
||||
"""Path to a file in the current results directory for the test."""
|
||||
return os.path.join(self.dirCurrent(),file)
|
||||
|
||||
|
||||
def fileInProof(self,file):
|
||||
'''
|
||||
Path to a file in the proof directory for the test.
|
||||
'''
|
||||
"""Path to a file in the proof directory for the test."""
|
||||
return os.path.join(self.dirProof(),file)
|
||||
|
||||
|
||||
|
||||
def copy(self, mapA, mapB,
|
||||
A = [], B = []):
|
||||
'''
|
||||
"""
|
||||
copy list of files from (mapped) source to target.
|
||||
|
||||
mapA/B is one of self.fileInX.
|
||||
'''
|
||||
|
||||
"""
|
||||
if not B or len(B) == 0: B = A
|
||||
|
||||
for source,target in zip(map(mapA,A),map(mapB,B)):
|
||||
|
|
@ -328,7 +298,8 @@ class Test():
|
|||
logging.info('comparing ASCII Tables\n %s \n %s'%(file0,file1))
|
||||
if normHeadings == '': normHeadings = headings0
|
||||
|
||||
if len(headings0) == len(headings1) == len(normHeadings): #check if comparison is possible and determine lenght of columns
|
||||
# check if comparison is possible and determine lenght of columns
|
||||
if len(headings0) == len(headings1) == len(normHeadings):
|
||||
dataLength = len(headings0)
|
||||
length = [1 for i in xrange(dataLength)]
|
||||
shape = [[] for i in xrange(dataLength)]
|
||||
|
|
@ -431,15 +402,11 @@ class Test():
|
|||
meanTol = 1.0e-4,
|
||||
stdTol = 1.0e-6,
|
||||
preFilter = 1.0e-9):
|
||||
|
||||
'''
|
||||
calculate statistics of tables
|
||||
threshold can be used to ignore small values (a negative number disables this feature)
|
||||
'''
|
||||
|
||||
import numpy as np
|
||||
from collections import Iterable
|
||||
"""
|
||||
calculate statistics of tables
|
||||
|
||||
threshold can be used to ignore small values (a negative number disables this feature)
|
||||
"""
|
||||
if not (isinstance(files, Iterable) and not isinstance(files, str)): # check whether list of files is requested
|
||||
files = [str(files)]
|
||||
|
||||
|
|
@ -491,15 +458,11 @@ class Test():
|
|||
preFilter = -1.0,
|
||||
postFilter = -1.0,
|
||||
debug = False):
|
||||
|
||||
'''
|
||||
compare tables with np.allclose
|
||||
threshold can be used to ignore small values (a negative number disables this feature)
|
||||
'''
|
||||
|
||||
import numpy as np
|
||||
from collections import Iterable
|
||||
"""
|
||||
compare tables with np.allclose
|
||||
|
||||
threshold can be used to ignore small values (a negative number disables this feature)
|
||||
"""
|
||||
if not (isinstance(files, Iterable) and not isinstance(files, str)): # check whether list of files is requested
|
||||
files = [str(files)]
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue