def performance_comparison_from():
import perfplot
def setup(n):
out = numpy.empty((3, n))
rgb = numpy.random.rand(3)
for k in range(3):
out[k] = rgb[k]
return out
Y_b = 20
L_A = 64 / numpy.pi / 5
c = 0.69 # average
cam16 = colorio.CAM16(c, Y_b, L_A)
cam16_legacy = CAM16Legacy(c, Y_b, L_A)
perfplot.show(
setup=setup,
kernels=[cam16.from_xyz100, cam16_legacy.from_xyz100],
labels=["new", "legacy"],
n_range=1000 * numpy.arange(6),
equality_check=False,
)
return
def performance_comparison_to():
import perfplot
Y_b = 20
L_A = 64 / numpy.pi / 5
c = 0.69 # average
cam16 = colorio.CAM16(c, Y_b, L_A)
def cio(x):
return cam16.to_xyz100(x, "JCh")
cam16_legacy = CAM16Legacy(c, Y_b, L_A)
def cio_legacy(x):
return cam16_legacy.to_xyz100(x, "JCh")
perfplot.plot(
setup=lambda n: numpy.random.rand(3, n),
kernels=[cio, cio_legacy],
n_range=100000 * numpy.arange(11),
xlabel="Number of input samples",
)
# import matplotlib2tikz
# matplotlib2tikz.save('fig.tikz')
return
def test_conversion(xyz):
# test with srgb conditions
L_A = 64 / numpy.pi / 5
cam16 = colorio.CAM16(0.69, 20, L_A)
J, C, H, h, M, s, Q = cam16.from_xyz100(xyz)
out = cam16.to_xyz100(numpy.array([J, C, H]), 'JCH')
assert numpy.all(abs(xyz - out) < 1.0e-13 * abs(xyz))
out = cam16.to_xyz100(numpy.array([Q, M, h]), 'QMh')
assert numpy.all(abs(xyz - out) < 1.0e-13 * abs(xyz))
out = cam16.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
cam16 = colorio.CAM16(0.69, 20, L_A)
J, C, H, h, M, s, Q = cam16.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 = cam16.to_xyz100(numpy.array([J, C, H]), 'JCH')
assert numpy.all(abs(out) < 1.0e-13)
out = cam16.to_xyz100(numpy.array([Q, M, h]), 'QMh')
assert numpy.all(abs(out) < 1.0e-13)
out = cam16.to_xyz100(numpy.array([J, s, h]), 'Jsh')
assert numpy.all(abs(out) < 1.0e-13)
return
def test_0():
Y_b = 20
L_A = 64 / numpy.pi / 5
c = 0.69 # average
cam16 = colorio.CAM16(c, Y_b, L_A)
xyz = numpy.zeros(3)
J, C, _, h, M, s, Q = cam16.from_xyz100(xyz)
assert J == 0.0
assert C == 0.0
assert h == 0.0
assert M == 0.0
assert s == 0.0
assert Q == 0.0
# Comparison with other schemes
cam16_legacy = CAM16Legacy(c, Y_b, L_A)
ref2 = cam16_legacy.from_xyz100(xyz)
print(ref2)
return