def test_breakdown():
bad_xyz = [8.71292997, 2.02183974, 83.26198455]
L_A = 64 / numpy.pi / 5
ciecam02 = colorio.CIECAM02(0.69, 20, L_A)
with pytest.raises(colorio.ciecam02.NegativeAError):
ciecam02.from_xyz100(bad_xyz)
return
def test_speed(N=2):
numpy.random.seed(1)
osa = colorio.OsaUcs()
cielab = colorio.CIELAB()
# cam16 = colorio.CAM16(0.69, 20, L_A=64 / numpy.pi / 5)
ciecam02 = colorio.CIECAM02(0.69, 20, L_A=64 / numpy.pi / 5)
# This close probably means that another figure hasn't been properly closed.
import matplotlib.pyplot as plt
plt.close()
perfplot.show(
# Don't use numpy.random.rand(3, n) to avoid the CIECAM breakdown
setup=lambda n: numpy.outer(numpy.random.rand(3), numpy.ones(n)) * 10,
equality_check=None,
kernels=[
osa.to_xyz100,
cielab.to_xyz100,
# cam16.to_xyz100,
lambda Jsh: ciecam02.to_xyz100(Jsh, "Jsh"),
numpy.cbrt,
],
labels=["OSA-UCS", "CIELAB", "CIECAM02", "cbrt"],
n_range=[2 ** n for n in range(N)],
logx=True,
logy=True,
# relative_to=3
)
def test_from():
"""Compare colorio with colorspacius and colour."""
xyz = 100 * numpy.random.rand(3)
Y_b = 20
whitepoint = colorio.illuminants.whitepoints_cie1931["D65"]
L_A = 64 / numpy.pi / 5
c = 0.69 # average
cs2 = colorio.CIECAM02(c, Y_b, L_A)
J, C, H, h, M, s, Q = cs2.from_xyz100(xyz)
# compare with colorspacious
cs1 = colorspacious.ciecam02.CIECAM02Space(
whitepoint, Y_b, L_A, surround=colorspacious.CIECAM02Surround.AVERAGE)
ref1 = cs1.XYZ100_to_CIECAM02(xyz)
assert abs(ref1.J - J) < 1.0e-14 * J
assert abs(ref1.C - C) < 1.0e-14 * C
assert abs(ref1.H - H) < 1.0e-14 * H
assert abs(ref1.h - h) < 1.0e-14 * h
assert abs(ref1.M - M) < 1.0e-14 * M
assert abs(ref1.s - s) < 1.0e-14 * s
assert abs(ref1.Q - Q) < 1.0e-14 * Q
# compare with color
# TODO reinstate once https://github.com/colour-science/colour/issues/467 is fixed
# ref2 = colour.appearance.ciecam02.XYZ_to_CIECAM02(xyz, whitepoint, L_A, Y_b)
# assert abs(ref2.J - J) < 1.0e-14 * J
# assert abs(ref2.C - C) < 1.0e-14 * C
# # assert abs(ref2.H - H) < 1.0e-14 * H
# assert abs(ref2.h - h) < 1.0e-14 * h
# assert abs(ref2.M - M) < 1.0e-14 * M
# assert abs(ref2.s - s) < 1.0e-14 * s
# assert abs(ref2.Q - Q) < 1.0e-14 * Q
return
def test_conversion(xyz):
# test with srgb conditions
L_A = 64 / numpy.pi / 5
ciecam02 = colorio.CIECAM02(0.69, 20, L_A)
J, C, H, h, M, s, Q = ciecam02.from_xyz100(xyz)
out = ciecam02.to_xyz100(numpy.array([J, C, H]), 'JCH')
assert numpy.all(abs(xyz - out) < 1.0e-13 * abs(xyz))
out = ciecam02.to_xyz100(numpy.array([Q, M, h]), 'QMh')
assert numpy.all(abs(xyz - out) < 1.0e-13 * abs(xyz))
out = ciecam02.to_xyz100(numpy.array([J, s, h]), 'Jsh')
assert numpy.all(abs(xyz - out) < 1.0e-13 * abs(xyz))
return
def test_zero(xyz):
L_A = 64 / numpy.pi / 5
cs = colorio.CIECAM02(0.69, 20, L_A)
J, C, H, h, M, s, Q = cs.from_xyz100(xyz)
assert numpy.all(J == 0.0)
assert numpy.all(C == 0.0)
assert numpy.all(h == 0.0)
assert numpy.all(M == 0.0)
assert numpy.all(s == 0.0)
assert numpy.all(Q == 0.0)
out = cs.to_xyz100(numpy.array([J, C, H]), 'JCH')
assert numpy.all(abs(out) < 1.0e-13)
out = cs.to_xyz100(numpy.array([Q, M, h]), 'QMh')
assert numpy.all(abs(out) < 1.0e-13)
out = cs.to_xyz100(numpy.array([J, s, h]), 'Jsh')
assert numpy.all(abs(out) < 1.0e-13)
return
def test_speed(N=2):
numpy.random.seed(1)
osa = colorio.OsaUcs()
cielab = colorio.CIELAB()
# cam16 = colorio.CAM16(0.69, 20, L_A=64 / numpy.pi / 5)
ciecam02 = colorio.CIECAM02(0.69, 20, L_A=64 / numpy.pi / 5)
perfplot.plot(
# Don't use numpy.random.rand(3, n) to avoid the CIECAM breakdown
setup=lambda n: numpy.outer(numpy.random.rand(3), numpy.ones(n)) * 10,
equality_check=None,
kernels=[
osa.to_xyz100,
cielab.to_xyz100,
# cam16.to_xyz100,
lambda Jsh: ciecam02.to_xyz100(Jsh, "Jsh"),
numpy.cbrt,
],
labels=["OSA-UCS", "CIELAB", "CIECAM02", "cbrt"],
n_range=[2**n for n in range(N)],
logx=True,
logy=True,
# relative_to=3
)
def test_gold():
# See
# https://github.com/njsmith/colorspacious/blob/master/colorspacious/gold_values.py
xyz = [19.31, 23.93, 10.14]
ciecam02 = colorio.CIECAM02(0.69, 18, 200, whitepoint=[98.88, 90, 32.03])
values = ciecam02.from_xyz100(xyz)
reference_values = numpy.array([
# J, C, H, h, M, s, Q
48.0314,
38.7789,
240.8885,
191.0452,
38.7789,
46.0177,
183.1240
])
assert numpy.all(
abs(values - reference_values) < 1.0e-6 * reference_values)
# different L_A
xyz = [19.31, 23.93, 10.14]
ciecam02 = colorio.CIECAM02(0.69, 18, 20, whitepoint=[98.88, 90, 32.03])
values = ciecam02.from_xyz100(xyz)
reference_values = numpy.array([
# J, C, H, h, M, s, Q
47.6856,
36.0527,
232.6630,
185.3445,
29.7580,
51.1275,
113.8401
])
assert numpy.all(
abs(values - reference_values) < 1.0e-5 * reference_values)
# gold values from Mark Fairchild's spreadsheet at
# http://rit-mcsl.org/fairchild//files/AppModEx.xls
xyz = [19.01, 20.00, 21.78]
ciecam02 = colorio.CIECAM02(0.69,
20,
318.30988618379,
whitepoint=[95.05, 100.0, 108.88])
values = ciecam02.from_xyz100(xyz)
reference_values = numpy.array([
# J, C, H, h, M, s, Q
4.17310911e+01,
1.04707861e-01,
2.78060724e+02,
2.19048423e+02,
1.08842280e-01,
2.36030659e+00,
1.95371311e+02
])
assert numpy.all(
abs(values - reference_values) < 1.0e-8 * reference_values)
xyz = [57.06, 43.06, 31.96]
ciecam02 = colorio.CIECAM02(
0.69,
20,
31.830988618379,
whitepoint=[95.05, 100.0, 108.88],
)
values = ciecam02.from_xyz100(xyz)
reference_values = numpy.array([
# J, C, H, h, M, s, Q
65.95523,
48.57050,
399.38837,
19.55739,
41.67327,
52.24549,
152.67220
])
assert numpy.all(
abs(values - reference_values) < 1.0e-6 * reference_values)
return