def planckian_locus(T):
"""XYZ colour coordinates of a theoretical incadescent black body
radiator at a given temperature, or something like that.
Can be used to calculate the chromaticity coordinates of, say, a
6500K light source
http://en.wikipedia.org/wiki/Planckian_locus
Argument T is in Kelvin, return value is a CIE XYZ value
"""
samples = (780-380)/5 # values every 5 nm are stored
from colour_matching_functions import get_colour_matching_functions
X, Y, Z = get_colour_matching_functions(two_degree = True)
# Integrated between 380nm and 780nm, as that is the range of
# values contained in the colour-matching functions
X_T = integrate(lambda wavelen: plancks_law(wavelen, T) * X(wavelen), 380, 780, samples)
Y_T = integrate(lambda wavelen: plancks_law(wavelen, T) * Y(wavelen), 380, 780, samples)
Z_T = integrate(lambda wavelen: plancks_law(wavelen, T) * Z(wavelen), 380, 780, samples)
return (X_T, Y_T, Z_T)
def main():
from matplotlib import pyplot
# Plot CIE XYZ colour matching curves
print "Calculating"
from colour_matching_functions import get_colour_matching_functions
X, Y, Z = get_colour_matching_functions(two_degree = True)
print "Test"
wavelens =[x for x in range(380, 780, 5)]
sampled_x = [X(T) for T in wavelens]
sampled_x = [x/max(sampled_x) for x in sampled_x]
pyplot.plot(sampled_x)
sampled_y = [Y(T) for T in wavelens]
sampled_y = [x/max(sampled_y) for x in sampled_y]
pyplot.plot(sampled_y)
sampled_z = [Z(T) for T in wavelens]
sampled_z = [x/max(sampled_z) for x in sampled_z]
pyplot.plot(sampled_z)
pyplot.show()
# Plot spectral locus
# As explained on http://www.photo-mark.com/notes/2010/sep/08/deconstructing-chromaticity/
spectral_locus_x = []
spectral_locus_y = []
for x, y, z in zip(sampled_x, sampled_y, sampled_z):
spectral_locus_x.append(
x / (x+y+z))
spectral_locus_y.append(
y / (x+y+z))
pyplot.plot(spectral_locus_x, spectral_locus_y)
# Also plot Plankian locus
T_and_radiance = []
for T in range(1000, 15000, 350):
# Calculate plankian locus
T_and_radiance.append([T, planckian_locus(T)])
to_plot_x, to_plot_y = [], []
for (TT, XYZ) in T_and_radiance:
# Calculate x,y chromaticity coordinate
# http://en.wikipedia.org/wiki/CIE_1931_color_space#The_CIE_xy_chromaticity_diagram_and_the_CIE_xyY_color_space
XT, YT, ZT = XYZ
x = XT / (XT+YT+ZT)
y = YT / (XT+YT+ZT)
to_plot_x.append(x)
to_plot_y.append(y)
pyplot.plot(to_plot_x, to_plot_y)
pyplot.axis(xmin = 0, xmax = 0.8, ymin = 0, ymax = 0.9)
pyplot.show()
print "Checking against approximation"
test_plankian_locus_against_approximation()
print "..okay"
