def delta_e_matrix(self, lab_color_matrix, mode='cie2000', *args, **kwargs):
"""
Compares this object with all colors in lab_color_matrix via Delta E.
The matrix must be of shape (n,3) and must be composed of floats.
Returns a distance vector of shape (n,).
Valid modes:
cie2000
cie1976
cie1994
cmc
"""
lab_color_vector = np.array([self.lab_l, self.lab_a, self.lab_b])
mode = mode.lower()
if mode == 'cie2000':
return color_diff_matrix.delta_e_cie2000(lab_color_vector, lab_color_matrix)
elif mode == 'cie1994':
return color_diff_matrix.delta_e_cie1994(lab_color_vector, lab_color_matrix, **kwargs)
elif mode == 'cie1976':
return color_diff_matrix.delta_e_cie1976(lab_color_vector, lab_color_matrix)
elif mode == 'cmc':
return color_diff_matrix.delta_e_cmc(lab_color_vector, lab_color_matrix, **kwargs)
else:
raise InvalidDeltaEMode(mode)
def delta_e_cmc(color1, color2, pl=2, pc=1):
"""
Calculates the Delta E (CMC) of two colors.
CMC values
Acceptability: pl=2, pc=1
Perceptability: pl=1, pc=1
"""
color1_vector = _get_lab_color1_vector(color1)
color2_matrix = _get_lab_color2_matrix(color2)
delta_e = color_diff_matrix.delta_e_cmc(
color1_vector, color2_matrix, pl=pl, pc=pc)[0]
return numpy.asscalar(delta_e)
def delta_e_cmc(color1, color2, pl=2, pc=1):
"""
Calculates the Delta E (CMC) of two colors.
CMC values
Acceptability: pl=2, pc=1
Perceptability: pl=1, pc=1
"""
color1_vector = _get_lab_color1_vector(color1)
color2_matrix = _get_lab_color2_matrix(color2)
delta_e = color_diff_matrix.delta_e_cmc(
color1_vector, color2_matrix, pl=pl, pc=pc)[0]
return numpy.asscalar(delta_e)
