def test_luminous_efficacy(self):
"""
Test :func:`colour.colorimetry.photometry.luminous_efficacy`
definition.
"""
self.assertAlmostEqual(
luminous_efficacy(SDS_ILLUMINANTS["FL2"].copy().normalise()),
336.83937176,
places=7,
)
self.assertAlmostEqual(
luminous_efficacy(SDS_LIGHT_SOURCES["Neodimium Incandescent"]),
136.21708032,
places=7,
)
self.assertAlmostEqual(
luminous_efficacy(SDS_LIGHT_SOURCES["F32T8/TL841 (Triphosphor)"]),
348.88267549,
places=7,
)
sd = sd_zeros()
sd[555] = 1
self.assertAlmostEqual(luminous_efficacy(sd), 683.00000000, places=7)
def test_luminous_efficacy(self):
"""
Tests :func:`colour.colorimetry.photometry.luminous_efficacy`
definition.
"""
self.assertAlmostEqual(
luminous_efficacy(ILLUMINANTS_SDS['FL2'].copy().normalise()),
336.83937176,
places=7)
self.assertAlmostEqual(
luminous_efficacy(LIGHT_SOURCES_SDS['Neodimium Incandescent']),
136.21708032,
places=7)
self.assertAlmostEqual(
luminous_efficacy(LIGHT_SOURCES_SDS['F32T8/TL841 (Triphosphor)']),
348.88267549,
places=7)
sd = sd_zeros()
sd[555] = 1
self.assertAlmostEqual(luminous_efficacy(sd), 683.00000000, places=7)
def XYZ_to_spectral(
XYZ,
cmfs=colour.STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'],
interval=5,
tolerance=1e-10,
maximum_iterations=5000,
illuminant=sd_ones(),
max_refl=1.0):
XYZ = to_domain_1(XYZ)
shape = SpectralShape(cmfs.shape.start, cmfs.shape.end, interval)
cmfs = cmfs.copy().align(shape)
illuminant = illuminant.copy().align(shape)
spd = sd_zeros(shape)
def function_objective(a):
"""
Objective function.
"""
return np.sum(np.diff(a)**2)
def function_constraint(a):
"""
Function defining the constraint for XYZ=XYZ.
"""
spd[:] = np.exp(a)
return (XYZ -
(colour.colorimetry.spectral_to_XYZ_integration(
spd, cmfs=cmfs, illuminant=illuminant)))
def function_constraint2(a):
"""
Function defining constraint on emission/reflectance
"""
if max_refl <= 0.0:
return 0.0
return max_refl - np.exp(np.max(a)) * 100.
wavelengths = spd.wavelengths
bins = wavelengths.size
constraints = ({'type': 'eq', 'fun': function_constraint},
{'type': 'ineq', 'fun': function_constraint2})
result = minimize(
function_objective,
spd.values,
method='SLSQP',
constraints=constraints,
options={
'ftol': tolerance,
'maxiter': maximum_iterations,
'disp': True
})
if not result.success:
raise RuntimeError(
'Optimization failed for {0} after {1} iterations: "{2}".'.format(
XYZ, result.nit, result.message))
return SpectralDistribution(
from_range_100(np.exp(result.x) * 100),
wavelengths,
name='Meng (2015) - {0}'.format(XYZ))