colour.difference.delta_E_CMC#

colour.difference.delta_E_CMC(Lab_1: ArrayLike, Lab_2: ArrayLike, l: float = 2, c: float = 1) NDArrayFloat[source]#

Return the difference $$\Delta E_{CMC}$$ between two given CIE L*a*b* colourspace arrays using Colour Measurement Committee recommendation.

The quasimetric has two parameters: Lightness (l) and chroma (c), allowing the users to weight the difference based on the ratio of l:c. Commonly used values are 2:1 for acceptability and 1:1 for the threshold of imperceptibility.

Parameters:
• Lab_1 (ArrayLike) – CIE L*a*b* colourspace array 1.

• Lab_2 (ArrayLike) – CIE L*a*b* colourspace array 2.

• l (float) – Lightness weighting factor.

• c (float) – Chroma weighting factor.

Returns:

Colour difference $$\Delta E_{CMC}$$.

Return type:

numpy.ndarray

Notes

Domain

Scale - Reference

Scale - 1

Lab_1

L_1 : [0, 100]

a_1 : [-100, 100]

b_1 : [-100, 100]

L_1 : [0, 1]

a_1 : [-1, 1]

b_1 : [-1, 1]

Lab_2

L_2 : [0, 100]

a_2 : [-100, 100]

b_2 : [-100, 100]

L_2 : [0, 1]

a_2 : [-1, 1]

b_2 : [-1, 1]

References

[Lin09b]

Examples

>>> Lab_1 = np.array([100.00000000, 21.57210357, 272.22819350])
>>> Lab_2 = np.array([100.00000000, 426.67945353, 72.39590835])
>>> delta_E_CMC(Lab_1, Lab_2)
172.7047712...