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Constant_Values.py
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import numpy as np
cie1931raw =np.array([
360,0.000129900000,0.000003917000,0.000606100000,
365,0.000232100000,0.000006965000,0.001086000000,
370,0.000414900000,0.000012390000,0.001946000000,
375,0.000741600000,0.000022020000,0.003486000000,
380,0.001368000000,0.000039000000,0.006450001000,
385,0.002236000000,0.000064000000,0.010549990000,
390,0.004243000000,0.000120000000,0.020050010000,
395,0.007650000000,0.000217000000,0.036210000000,
400,0.014310000000,0.000396000000,0.067850010000,
405,0.023190000000,0.000640000000,0.110200000000,
410,0.043510000000,0.001210000000,0.207400000000,
415,0.077630000000,0.002180000000,0.371300000000,
420,0.134380000000,0.004000000000,0.645600000000,
425,0.214770000000,0.007300000000,1.039050100000,
430,0.283900000000,0.011600000000,1.385600000000,
435,0.328500000000,0.016840000000,1.622960000000,
440,0.348280000000,0.023000000000,1.747060000000,
445,0.348060000000,0.029800000000,1.782600000000,
450,0.336200000000,0.038000000000,1.772110000000,
455,0.318700000000,0.048000000000,1.744100000000,
460,0.290800000000,0.060000000000,1.669200000000,
465,0.251100000000,0.073900000000,1.528100000000,
470,0.195360000000,0.090980000000,1.287640000000,
475,0.142100000000,0.112600000000,1.041900000000,
480,0.095640000000,0.139020000000,0.812950100000,
485,0.057950010000,0.169300000000,0.616200000000,
490,0.032010000000,0.208020000000,0.465180000000,
495,0.014700000000,0.258600000000,0.353300000000,
500,0.004900000000,0.323000000000,0.272000000000,
505,0.002400000000,0.407300000000,0.212300000000,
510,0.009300000000,0.503000000000,0.158200000000,
515,0.029100000000,0.608200000000,0.111700000000,
520,0.063270000000,0.710000000000,0.078249990000,
525,0.109600000000,0.793200000000,0.057250010000,
530,0.165500000000,0.862000000000,0.042160000000,
535,0.225749900000,0.914850100000,0.029840000000,
540,0.290400000000,0.954000000000,0.020300000000,
545,0.359700000000,0.980300000000,0.013400000000,
550,0.433449900000,0.994950100000,0.008749999000,
555,0.512050100000,1.000000000000,0.005749999000,
560,0.594500000000,0.995000000000,0.003900000000,
565,0.678400000000,0.978600000000,0.002749999000,
570,0.762100000000,0.952000000000,0.002100000000,
575,0.842500000000,0.915400000000,0.001800000000,
580,0.916300000000,0.870000000000,0.001650001000,
585,0.978600000000,0.816300000000,0.001400000000,
590,1.026300000000,0.757000000000,0.001100000000,
595,1.056700000000,0.694900000000,0.001000000000,
600,1.062200000000,0.631000000000,0.000800000000,
605,1.045600000000,0.566800000000,0.000600000000,
610,1.002600000000,0.503000000000,0.000340000000,
615,0.938400000000,0.441200000000,0.000240000000,
620,0.854449900000,0.381000000000,0.000190000000,
625,0.751400000000,0.321000000000,0.000100000000,
630,0.642400000000,0.265000000000,0.000049999990,
635,0.541900000000,0.217000000000,0.000030000000,
640,0.447900000000,0.175000000000,0.000020000000,
645,0.360800000000,0.138200000000,0.000010000000,
650,0.283500000000,0.107000000000,0.000000000000,
655,0.218700000000,0.081600000000,0.000000000000,
660,0.164900000000,0.061000000000,0.000000000000,
665,0.121200000000,0.044580000000,0.000000000000,
670,0.087400000000,0.032000000000,0.000000000000,
675,0.063600000000,0.023200000000,0.000000000000,
680,0.046770000000,0.017000000000,0.000000000000,
685,0.032900000000,0.011920000000,0.000000000000,
690,0.022700000000,0.008210000000,0.000000000000,
695,0.015840000000,0.005723000000,0.000000000000,
700,0.011359160000,0.004102000000,0.000000000000,
705,0.008110916000,0.002929000000,0.000000000000,
710,0.005790346000,0.002091000000,0.000000000000,
715,0.004109457000,0.001484000000,0.000000000000,
720,0.002899327000,0.001047000000,0.000000000000,
725,0.002049190000,0.000740000000,0.000000000000,
730,0.001439971000,0.000520000000,0.000000000000,
735,0.000999949300,0.000361100000,0.000000000000,
740,0.000690078600,0.000249200000,0.000000000000,
745,0.000476021300,0.000171900000,0.000000000000,
750,0.000332301100,0.000120000000,0.000000000000,
755,0.000234826100,0.000084800000,0.000000000000,
760,0.000166150500,0.000060000000,0.000000000000,
765,0.000117413000,0.000042400000,0.000000000000,
770,0.000083075270,0.000030000000,0.000000000000,
775,0.000058706520,0.000021200000,0.000000000000,
780,0.000041509940,0.000014990000,0.000000000000,
785,0.000029353260,0.000010600000,0.000000000000,
790,0.000020673830,0.000007465700,0.000000000000,
795,0.000014559770,0.000005257800,0.000000000000,
800,0.000010253980,0.000003702900,0.000000000000,
805,0.000007221456,0.000002607800,0.000000000000,
810,0.000005085868,0.000001836600,0.000000000000,
815,0.000003581652,0.000001293400,0.000000000000,
820,0.000002522525,0.000000910930,0.000000000000,
825,0.000001776509,0.000000641530,0.000000000000,
830,0.000001251141,0.000000451810,0.000000000000])
cie1931raw=cie1931raw.reshape((-1,4))
Illuminantraw=np.array([360,46.638300,
365,49.363700,
370,52.089100,
375,51.032300,
380,49.975500,
385,52.311800,
390,54.648200,
395,68.701500,
400,82.754900,
405,87.120400,
410,91.486000,
415,92.458900,
420,93.431800,
425,90.057000,
430,86.682300,
435,95.773600,
440,104.865000,
445,110.936000,
450,117.008000,
455,117.410000,
460,117.812000,
465,116.336000,
470,114.861000,
475,115.392000,
480,115.923000,
485,112.367000,
490,108.811000,
495,109.082000,
500,109.354000,
505,108.578000,
510,107.802000,
515,106.296000,
520,104.790000,
525,106.239000,
530,107.689000,
535,106.047000,
540,104.405000,
545,104.225000,
550,104.046000,
555,102.023000,
560,100.000000,
565,98.167100,
570,96.334200,
575,96.061100,
580,95.788000,
585,92.236800,
590,88.685600,
595,89.345900,
600,90.006200,
605,89.802600,
610,89.599100,
615,88.648900,
620,87.698700,
625,85.493600,
630,83.288600,
635,83.493900,
640,83.699200,
645,81.863000,
650,80.026800,
655,80.120700,
660,80.214600,
665,81.246200,
670,82.277800,
675,80.281000,
680,78.284200,
685,74.002700,
690,69.721300,
695,70.665200,
700,71.609100,
705,72.979000,
710,74.349000,
715,67.976500,
720,61.604000,
725,65.744800,
730,69.885600,
735,72.486300,
740,75.087000,
745,69.339800,
750,63.592700,
755,55.005400,
760,46.418200,
765,56.611800,
770,66.805400,
775,65.094100,
780,63.382800,
785,63.843400,
790,64.304000,
795,61.877900,
800,59.451900,
805,55.705400,
810,51.959000,
815,54.699800,
820,57.440600,
825,58.876500,
830,60.312500])
Illuminantraw=Illuminantraw.reshape((-1,2))
# max_val=Illuminantraw[:,1].max()
# max_val=255.0
# Illuminantraw[:,1]/=max_val
cyantonerraw=np.array([
380,2.16,0.126644737,
390,1.28,0.113486842,
400,0.76,0.097039474,
410,0.5,0.079495614,
420,0.41,0.063596491,
430,0.31,0.054276316,
440,0.22,0.049342105,
450,0.14,0.041666667,
460,0.12,0.033442982,
470,0.12,0.025767544,
480,0.13,0.019736842,
490,0.15,0.015350877,
500,0.2,0.012061404,
510,0.26,0.010416667,
520,0.38,0.010416667,
530,0.55,0.012609649,
540,0.8,0.01754386,
550,1.18,0.026864035,
560,1.73,0.039473684,
570,2.3,0.050986842,
580,2.72,0.058662281,
590,2.98,0.061951754,
600,3.22,0.069078947,
610,3.41,0.07620614,
620,3.44,0.079495614,
630,3.37,0.08004386,
640,3.24,0.076754386,
650,3.05,0.069627193,
660,2.84,0.061951754,
670,2.8,0.057017544,
680,2.9,0.057017544,
690,2.99,0.063596491,
700,3.1,0.075657895])
cyantonerraw=cyantonerraw.reshape((-1,3))
magentatonerraw=np.array([
380,0.83,0.033442982,
390,0.95,0.031798246,
400,1.04,0.030701754,
410,1.06,0.029057018,
420,1.04,0.026864035,
430,0.98,0.024671053,
440,0.92,0.023574561,
450,0.93,0.025767544,
460,1.05,0.027960526,
470,1.23,0.030701754,
480,1.45,0.035635965,
490,1.69,0.040570175,
500,1.95,0.047149123,
510,2.29,0.054824561,
520,2.75,0.061403509,
530,3.04,0.064692982,
540,3.16,0.065241228,
550,3.35,0.074561404,
560,3.84,0.099780702,
570,4.2,0.151864035,
580,3.27,0.216008772,
590,1.36,0.203947368,
600,0.41,0.13870614,
610,0.13,0.097039474,
620,0.05,0.072916667,
630,0.001,0.055921053,
640,0.001,0.042214912,
650,0.001,0.030701754,
660,0.001,0.025219298,
670,0.001,0.02247807,
680,0.001,0.018092105,
690,0.001,0.016995614,
700,0.001,0.01370614])
magentatonerraw=magentatonerraw.reshape((-1,3))
yellowtonerraw=np.array([
380,3.45,0.080592105,
390,3.69,0.076754386,
400,3.76,0.086074561,
410,3.82,0.079495614,
420,3.82,0.077302632,
430,3.74,0.072916667,
440,3.57,0.069627193,
450,3.28,0.064144737,
460,2.91,0.059758772,
470,2.39,0.057565789,
480,1.65,0.050986842,
490,0.86,0.043311404,
500,0.37,0.038377193,
510,0.13,0.038925439,
520,0.04,0.04002193,
530,0.001,0.040570175,
540,0.001,0.040570175,
550,0.001,0.040570175,
560,0.001,0.039473684,
570,0.001,0.04002193,
580,0.001,0.038925439,
590,0.001,0.033991228,
600,0.001,0.028508772,
610,0.001,0.024671053,
620,0.001,0.020833333,
630,0.001,0.023574561,
640,0.001,0.023026316,
650,0.001,0.020285088,
660,0.001,0.020833333,
670,0.001,0.01754386,
680,0.001,0.012609649,
690,0.001,0.014254386,
700,0.001,0.018640351])
yellowtonerraw=yellowtonerraw.reshape((-1,3))
# print cie1931raw.shape
# print Illuminantraw.shape
# print cyantonerraw.shape
# print magentatonerraw.shape
# print yellowtonerraw.shape
cie1931new=np.ones((cyantonerraw.shape[0],cie1931raw.shape[1]))
Illuminantnew=np.ones((cyantonerraw.shape[0], Illuminantraw.shape[1]))
cie1931new[:,0]=cyantonerraw[:,0]
Illuminantnew[:,0]=cyantonerraw[:,0]
k=0
for i in xrange(len(cie1931raw)):
if cie1931raw[i,0]==cie1931new[k,0]: ###if same wavelength
cie1931new[k,:]=cie1931raw[i,:]
Illuminantnew[k,:]=Illuminantraw[i,:]
k+=1
if k==len(cie1931new):
break
# print cie1931new
# print Illuminantnew
def sample_by_average_wavelength(raw, length): ### like 32 to 16, 8, 4
L=raw.shape[0]
ratio=L/length
samples=np.zeros((length, raw.shape[1]))
for i in xrange(len(samples)):
for j in xrange(ratio):
samples[i]+=raw[i*ratio+j]
samples[i]/=ratio
return samples
def sample_by_interpolation(raw, length): #### like 16 to 14, 14 to 12, 12 to 10, 8 to 6, or 4 to 3 ?
L=raw.shape[0]
ratio=(L-1)*1.0/(length+1)
samples=np.zeros((length, raw.shape[1]))
j=1
for i in xrange(L-1):
if (i<(ratio*j)) and ((ratio*j)<=(i+1)) and j<=length:
# print (ratio*j)
samples[j-1]=raw[i]+((ratio*j)-i)*(raw[i+1]-raw[i])
j+=1
return samples
####sample data from cie1931new, Illuminantnew, cyantonerraw, magentatonerraw and yellowtonerraw.
option=3
if option==0:
pass
else:
if option==1: ### 32 wavelength
length=32
if option==2: ### 16 wavelength
length=16
if option==3: ### 8 wavelength
length=8
if option==4: ### 4 wavelength
length=4
cie1931new=sample_by_average_wavelength(cie1931new[1:,:],length)
Illuminantnew=sample_by_average_wavelength(Illuminantnew[1:,:],length)
cyantonerraw=sample_by_average_wavelength(cyantonerraw[1:,:],length)
magentatonerraw=sample_by_average_wavelength(magentatonerraw[1:,:],length)
yellowtonerraw=sample_by_average_wavelength(yellowtonerraw[1:,:],length)
# ###### use 3 wavelength (OLD)
# # length2=3
# # cie1931new=sample_by_interpolation(cie1931new,length2)
# # Illuminantnew=sample_by_interpolation(Illuminantnew,length2)
# # cyantonerraw=sample_by_interpolation(cyantonerraw,length2)
# # magentatonerraw=sample_by_interpolation(magentatonerraw,length2)
# # yellowtonerraw=sample_by_interpolation(yellowtonerraw,length2)
# ###### use 3 wavelength (NEW)
# length2=3
# cie1931new=np.ones((length2,4))
# cie1931new[:,1:]= np.identity(length2)
# Illuminantnew=np.ones((length2,2))
# print "#####using wavelength number: ", len(cie1931new[:,1:])
# print cie1931new[:,1:]
# print Illuminantnew[:,1]
#### cmf function
R_xyzcoeff=cie1931new[:,1:].transpose()
# ### xyz to linear rgb
xyztorgb=np.array([[3.2404542, -1.5371385, -0.4985314],
[-0.9692660, 1.8760108, 0.0415560],
[0.0556434, -0.2040259, 1.0572252]
])
import os,sys
import subprocess
import errno
def make_sure_path_exists(path):
try:
os.makedirs(path)
except OSError as exception:
if exception.errno != errno.EEXIST:
raise
MODEL='normal'
# MODEL='infinite'
#### only used in one variable Q recovering.
# S_Constant=1.0
S_Constant=0.1