def web_to_ucs(RGB, conds):
"""Converts from the web colorspace to CAM02-UCS."""
XYZ = web_to_XYZ(RGB)
XYZ_w = web_to_XYZ([1, 1, 1])
Y_w, L_A, Y_b, surround = conds
cam02 = colour.XYZ_to_CIECAM02(XYZ * Y_w, XYZ_w * Y_w, L_A, Y_b, surround)
JMh = tstack([cam02.J, cam02.M, cam02.h])
return colour.models.JMh_CIECAM02_to_CAM02UCS(JMh)
"""
import colour
from colour.utilities.verbose import message_box
message_box('"CIECAM02" Colour Appearance Model Computations')
XYZ = (19.01, 20.00, 21.78)
XYZ_w = (95.05, 100.00, 108.88)
L_A = 318.31
Y_b = 20.0
surround = colour.CIECAM02_VIEWING_CONDITIONS['Average']
message_box(('Converting to "CIECAM02" colour appearance model specification '
'using given parameters:\n'
'\n\tXYZ: {0}\n\tXYZ_w: {1}\n\tL_A: {2}\n\tY_b: {3}'
'\n\tSurround: {4}').format(XYZ, XYZ_w, L_A, Y_b, surround))
specification = colour.XYZ_to_CIECAM02(XYZ, XYZ_w, L_A, Y_b, surround)
print(specification)
print('\n')
J = 41.73109113
C = 0.10470776
h = 219.04843266
specification = colour.CIECAM02_Specification(J, C, h)
message_box(('Converting to "CIE XYZ" tristimulus values using given '
'parameters:\n'
'\n\tJ: {0}\n\tC: {1}\n\th: {2}\n\tXYZ_w: {3}\n\tL_A: {4}'
'\n\tY_b: {5}').format(J, C, h, XYZ_w, L_A, Y_b))
print(colour.CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b))
XYZ_w = np.array([Xw,Yw,Zw])
XYZ_d_ = np.array(XYZ_d)
N_A = Light[:,0]/np.max(Light[:,0])*198.261
t1 = np.arange(400, 710, 10)
plt.plot(t1,N_A, color='red', marker="", linestyle='dashdot')
plt.plot(t1,Light[:,1], marker="", linestyle='dashdot')
plt.plot(t1,Light[:,2], marker="", linestyle='dashdot')
plt.xlabel('Wavelength')
plt.ylabel('Relative power')
plt.legend(['A', 'D50', 'D65'], loc='upper left')
plt.show()
#/ Generate input data with CIECAM02 model
La = Yw/5
Yb = 20
Jab_ = []
viewing_condition = ['Average', 'Dim', 'Dark']
for j in viewing_condition:
surround = colour.CIECAM02_VIEWING_CONDITIONS[j]
ans = colour.XYZ_to_CIECAM02(XYZ_d_, XYZ_w.T, La, Yb, surround)
J = ans[0].T
a = ans[1].T*np.cos(ans[2].T/(180/math.pi))
b = ans[1].T*np.sin(ans[2].T/(180/math.pi))
Jab = np.c_[J,a,b]
Jab_.append(Jab)
Jab_o = np.concatenate((Jab_[0],Jab_[1],Jab_[2]),axis=0)
