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import numpy as np
from colour import *
from colour.plotting import *
from colour.difference import *
from matplotlib import pyplot as plt
from jakob_hanika import jakob_hanika, model, remap, wvl
from test_colorchecker import plot_comparison
illuminant = "D65"
ill_xy = ILLUMINANTS["CIE 1931 2 Degree Standard Observer"][illuminant]
ill_sd = SpectralDistribution(ILLUMINANTS_SDS[illuminant])
# These numbers are taken from Jakob and Hanika's Jupyter notebook.
RGB_ref = np.array([0.79264853, 0.4, 0.63703843]) # *linear* sRGB
cc_ref = np.array([ 18.70184886, -13.19804478, 2.12180137])
if __name__ == "__main__":
XYZ = sRGB_to_XYZ(1.055 * RGB_ref ** (1/2.4) - 0.055, ill_xy)
target = XYZ_to_Lab(XYZ, ill_xy)
print("Target: X=%g, Y=%g, Z=%g, L=%g, a=%g, b=%g" % (*XYZ, *target))
cc, found_sd, error = jakob_hanika(target, ill_sd, ill_xy)
reference_sd = SpectralDistribution(model(remap(wvl), cc_ref), wvl)
reference_XYZ = sd_to_XYZ(reference_sd, illuminant=ill_sd)
reference_Lab = XYZ_to_Lab(reference_XYZ, ill_xy)
found_XYZ = sd_to_XYZ(found_sd, illuminant=ill_sd)
found_Lab = XYZ_to_Lab(found_XYZ, ill_xy)
print("Our results differ from the reference by ΔE = %g" \
% delta_E_CIE1976(reference_Lab, found_Lab))
plot_comparison(XYZ, found_sd, "Reference", error, ill_sd)
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