colour.adaptation.chromatic_adaptation_VonKries#

colour.adaptation.chromatic_adaptation_VonKries(XYZ: ArrayLike, XYZ_w: ArrayLike, XYZ_wr: ArrayLike, transform: Union[Literal['Bianco 2010', 'Bianco PC 2010', 'Bradford', 'CAT02 Brill 2008', 'CAT02', 'CAT16', 'CMCCAT2000', 'CMCCAT97', 'Fairchild', 'Sharp', 'Von Kries', 'XYZ Scaling'], str] = 'CAT02') ndarray[source]#

Adapt given stimulus from test viewing conditions to reference viewing conditions.

Parameters:
  • XYZ (ArrayLike) – CIE XYZ tristimulus values of stimulus to adapt.

  • XYZ_w (ArrayLike) – Test viewing conditions CIE XYZ tristimulus values of whitepoint.

  • XYZ_wr (ArrayLike) – Reference viewing conditions CIE XYZ tristimulus values of whitepoint.

  • transform (Union[Literal['Bianco 2010', 'Bianco PC 2010', 'Bradford', 'CAT02 Brill 2008', 'CAT02', 'CAT16', 'CMCCAT2000', 'CMCCAT97', 'Fairchild', 'Sharp', 'Von Kries', 'XYZ Scaling'], str]) – Chromatic adaptation transform.

Returns:

CIE XYZ_c tristimulus values of the stimulus corresponding colour.

Return type:

numpy.ndarray

Notes

Domain

Scale - Reference

Scale - 1

XYZ

[0, 1]

[0, 1]

XYZ_n

[0, 1]

[0, 1]

XYZ_r

[0, 1]

[0, 1]

Range

Scale - Reference

Scale - 1

XYZ_c

[0, 1]

[0, 1]

References

[Fai13a]

Examples

>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
>>> XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])
>>> XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])
>>> chromatic_adaptation_VonKries(XYZ, XYZ_w, XYZ_wr)  
array([ 0.2163881...,  0.1257    ,  0.0384749...])

Using Bradford method:

>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
>>> XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])
>>> XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])
>>> transform = "Bradford"
>>> chromatic_adaptation_VonKries(XYZ, XYZ_w, XYZ_wr, transform)
... 
array([ 0.2166600...,  0.1260477...,  0.0385506...])