# colour.delta_E¶

colour.delta_E(a, b, method='CIE 2000', **kwargs)[source]

Returns the difference $$\Delta E_{ab}$$ between two given CIE L*a*b* or $$J'a'b'$$ colourspace arrays using given method.

Parameters: Other Parameters: a (array_like) – CIE L*a*b* or $$J'a'b'$$ colourspace array $$a$$. b (array_like) – CIE L*a*b* or $$J'a'b'$$ colourspace array $$b$$. method (unicode, optional) – {‘CIE 2000’, ‘CIE 1976’, ‘CIE 1994’, ‘CMC’, ‘CAM02-LCD’, ‘CAM02-SCD’, ‘CAM02-UCS’, ‘CAM16-LCD’, ‘CAM16-SCD’, ‘CAM16-UCS’, ‘DIN99’} Computation method. textiles (bool, optional) – {colour.difference.delta_E_CIE1994(), colour.difference.delta_E_CIE2000(), colour.difference.delta_E_DIN99()}, Textiles application specific parametric factors $$k_L=2,\ k_C=k_H=1,\ k_1=0.048,\ k_2=0.014,\ k_E=2,\ k_CH=0.5$$ weights are used instead of $$k_L=k_C=k_H=1,\ k_1=0.045,\ k_2=0.015,\ k_E=k_CH=1.0$$. l (numeric, optional) – {colour.difference.delta_E_CIE2000()}, Lightness weighting factor. c (numeric, optional) – {colour.difference.delta_E_CIE2000()}, Chroma weighting factor. Colour difference $$\Delta E_{ab}$$. numeric or ndarray

References

Examples

>>> import numpy as np
>>> a = np.array([100.00000000, 21.57210357, 272.22819350])
>>> b = np.array([100.00000000, 426.67945353, 72.39590835])
>>> delta_E(a, b)  # doctest: +ELLIPSIS
94.0356490...
>>> delta_E(a, b, method='CIE 2000')  # doctest: +ELLIPSIS
94.0356490...
>>> delta_E(a, b, method='CIE 1976')  # doctest: +ELLIPSIS
451.7133019...
>>> delta_E(a, b, method='CIE 1994')  # doctest: +ELLIPSIS
83.7792255...
>>> delta_E(a, b, method='CIE 1994', textiles=False)
... # doctest: +ELLIPSIS
83.7792255...
>>> delta_E(a, b, method='DIN99')  # doctest: +ELLIPSIS
66.1119282...
>>> a = np.array([54.90433134, -0.08450395, -0.06854831])
>>> b = np.array([54.90433134, -0.08442362, -0.06848314])
>>> delta_E(a, b, method='CAM02-UCS')  # doctest: +ELLIPSIS
0.0001034...
>>> delta_E(a, b, method='CAM16-LCD')  # doctest: +ELLIPSIS
0.0001034...