# colour.difference.delta_e Module¶

## $$\Delta E_{ab}$$ - Delta E Colour Difference¶

Defines $$\Delta E_{ab}$$ colour difference computation objects:

The following methods are available:

References

 [1] Wikipedia. (n.d.). Color difference. Retrieved August 29, 2014, from http://en.wikipedia.org/wiki/Color_difference
colour.difference.delta_e.delta_E_CIE1976(Lab1, Lab2, **kwargs)[source]

Returns the difference $$\Delta E_{ab}$$ between two given CIE Lab colourspace arrays using CIE 1976 recommendation.

Parameters: Lab1 (array_like) – CIE Lab colourspace array 1. Lab2 (array_like) – CIE Lab colourspace array 2. **kwargs (**, optional) – Unused parameter provided for signature compatibility with other $$\Delta E_{ab}$$ computation objects. Colour difference $$\Delta E_{ab}$$. numeric or ndarray

References

 [2] Lindbloom, B. (2003). Delta E (CIE 1976). Retrieved February 24, 2014, from http://brucelindbloom.com/Eqn_DeltaE_CIE76.html

Examples

>>> Lab1 = np.array([100.00000000, 21.57210357, 272.22819350])
>>> Lab2 = np.array([100.00000000, 426.67945353, 72.39590835])
>>> delta_E_CIE1976(Lab1, Lab2)
451.7133019...
colour.difference.delta_e.delta_E_CIE1994(Lab1, Lab2, textiles=True, **kwargs)[source]

Returns the difference $$\Delta E_{ab}$$ between two given CIE Lab colourspace arrays using CIE 1994 recommendation.

Parameters: Lab1 (array_like) – CIE Lab colourspace array 1. Lab2 (array_like) – CIE Lab colourspace array 2. textiles (bool, optional) – Application specific weights. **kwargs (**, optional) – Unused parameter provided for signature compatibility with other $$\Delta E_{ab}$$ computation objects. Colour difference $$\Delta E_{ab}$$. numeric or ndarray

References

 [3] Lindbloom, B. (2011). Delta E (CIE 1994). Retrieved February 24, 2014, from http://brucelindbloom.com/Eqn_DeltaE_CIE94.html

Examples

>>> Lab1 = np.array([100.00000000, 21.57210357, 272.22819350])
>>> Lab2 = np.array([100.00000000, 426.67945353, 72.39590835])
>>> delta_E_CIE1994(Lab1, Lab2)
88.3355530...
>>> delta_E_CIE1994(Lab1, Lab2, textiles=False)
83.7792255...
colour.difference.delta_e.delta_E_CIE2000(Lab1, Lab2, **kwargs)[source]

Returns the difference $$\Delta E_{ab}$$ between two given CIE Lab colourspace arrays using CIE 2000 recommendation.

Parameters: Lab1 (array_like) – CIE Lab colourspace array 1. Lab2 (array_like) – CIE Lab colourspace array 2. **kwargs (**, optional) – Unused parameter provided for signature compatibility with other $$\Delta E_{ab}$$ computation objects. Colour difference $$\Delta E_{ab}$$. numeric or ndarray

References

 [4] Lindbloom, B. (2009). Delta E (CIE 2000). Retrieved February 24, 2014, from http://brucelindbloom.com/Eqn_DeltaE_CIE2000.html

Examples

>>> Lab1 = np.array([100.00000000, 21.57210357, 272.22819350])
>>> Lab2 = np.array([100.00000000, 426.67945353, 72.39590835])
>>> delta_E_CIE2000(Lab1, Lab2)
94.0356490...
colour.difference.delta_e.delta_E_CMC(Lab1, Lab2, l=2, c=1)[source]

Returns the difference $$\Delta E_{ab}$$ between two given CIE Lab 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: Lab1 (array_like) – CIE Lab colourspace array 1. Lab2 (array_like) – CIE Lab colourspace array 2. l (numeric, optional) – Lightness weighting factor. c (numeric, optional) – Chroma weighting factor. Colour difference $$\Delta E_{ab}$$. numeric or ndarray

References

 [5] Lindbloom, B. (2009). Delta E (CMC). Retrieved February 24, 2014, from http://brucelindbloom.com/Eqn_DeltaE_CMC.html

Examples

>>> Lab1 = np.array([100.00000000, 21.57210357, 272.22819350])
>>> Lab2 = np.array([100.00000000, 426.67945353, 72.39590835])
>>> delta_E_CMC(Lab1, Lab2)
172.7047712...
colour.difference.delta_e.DELTA_E_METHODS = CaseInsensitiveMapping({u'cie1994': <function delta_E_CIE1994 at 0x2adc37bea758>, u'CIE 1994': <function delta_E_CIE1994 at 0x2adc37bea758>, u'cie1976': <function delta_E_CIE1976 at 0x2adc37bd5c80>, u'CMC': <function delta_E_CMC at 0x2adc37bea848>, u'CIE 1976': <function delta_E_CIE1976 at 0x2adc37bd5c80>, u'cie2000': <function delta_E_CIE2000 at 0x2adc37bea7d0>, u'CIE 2000': <function delta_E_CIE2000 at 0x2adc37bea7d0>})

Supported Delta E computations methods.

DELTA_E_METHODS : CaseInsensitiveMapping
{‘CIE 1976’, ‘CIE 1994’, ‘CIE 2000’, ‘CMC’}

Aliases:

• ‘cie1976’: ‘CIE 1976’
• ‘cie1994’: ‘CIE 1994’
• ‘cie2000’: ‘CIE 2000’
colour.difference.delta_e.delta_E(Lab1, Lab2, method=u'CMC', **kwargs)[source]

Returns the Lightness $$L^*$$ using given method.

Parameters: Lab1 (array_like) – CIE Lab colourspace array 1. Lab2 (array_like) – CIE Lab colourspace array 2. method (unicode, optional) – {‘CMC’, ‘CIE 1976’, ‘CIE 1994’, ‘CIE 2000’} Computation method. **kwargs (**) – Keywords arguments. Colour difference $$\Delta E_{ab}$$. numeric or ndarray

Examples

>>> Lab1 = np.array([100.00000000, 21.57210357, 272.22819350])
>>> Lab2 = np.array([100.00000000, 426.67945353, 72.39590835])
>>> delta_E(Lab1, Lab2)
172.7047712...
>>> delta_E(Lab1, Lab2, method='CIE 1976')
451.7133019...
>>> delta_E(Lab1, Lab2, method='CIE 1994')
88.3355530...
>>> delta_E(Lab1, Lab2, method='CIE 1994', textiles=False)
83.7792255...
>>> delta_E(Lab1, Lab2, method='CIE 2000')
94.0356490...