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colour.quality.cqs Module

Colour Quality Scale

Defines colour quality scale computation objects:

See also

Colour Quality Scale IPython Notebook

References

[1]Davis, W., & Ohno, Y. (2010). Color quality scale. Optical Engineering, 49(3), 33602–33616. doi:10.1117/1.3360335
[2]Ohno, Y., & Davis, W. (2008). NIST CQS simulation 7.4. Retrieved from http://cie2.nist.gov/TC1-69/NIST CQS simulation 7.4.xls
class colour.quality.cqs.VS_ColorimetryData[source]

Bases: colour.quality.cqs.VS_ColorimetryData

Defines the the class holding VS test colour samples colorimetry data.

class colour.quality.cqs.VS_ColourQualityScaleData[source]

Bases: colour.quality.cqs.VS_ColourQualityScaleData

Defines the the class holding VS test colour samples colour quality scale data.

class colour.quality.cqs.CQS_Specification[source]

Bases: colour.quality.cqs.CQS_Specification

Defines the CQS colour quality specification.

Parameters:
  • Q_a (numeric) – Colour quality scale Qa.
  • Q_f (numeric) – Colour fidelity scale Qf intended to evaluate the fidelity of object colour appearances (compared to the reference illuminant of the same correlated colour temperature and illuminance).
  • Q_p (numeric) – Colour preference scale Qp similar to colour quality scale Qa but placing additional weight on preference of object colour appearance. This metric is based on the notion that increases in chroma are generally preferred and should be rewarded.
  • Q_g (numeric) – Gamut area scale Qg representing the relative gamut formed by the (a∗, b∗) coordinates of the 15 samples illuminated by the test light source in the CIE LAB object colourspace.
  • Q_d (numeric) – Relative gamut area scale Qd.
  • Q_as (dict) – Individual CQS data for each sample.
  • colorimetry_data (tuple) – Colorimetry data for the test and reference computations.
colour.quality.cqs.colour_quality_scale(spd_test, additional_data=False)[source]

Returns the colour quality scale of given spectral power distribution.

Parameters:
  • spd_test (SpectralPowerDistribution) – Test spectral power distribution.
  • additional_data (bool, optional) – Output additional data.
Returns:

Color quality scale.
Return type:

numeric or CQS_Specification

Examples

>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> spd = ILLUMINANTS_RELATIVE_SPDS.get('F2')
>>> colour_quality_scale(spd)  
64.6860580...
colour.quality.cqs.gamut_area(Labs)[source]

Returns the gamut area G covered by given CIE Lab matrices.

Parameters:Labs (array_like) – CIE Lab colourspace matrices.
Returns:Gamut area G.
Return type:numeric

Examples

>>> Labs = [
...     np.array([39.94996006, 34.59018231, -19.86046321]),
...     np.array([38.88395498, 21.44348519, -34.87805301]),
...     np.array([36.60576301, 7.06742454, -43.21461177]),
...     np.array([46.60142558, -15.90481586, -34.64616865]),
...     np.array([56.50196523, -29.5465555, -20.50177194]),
...     np.array([55.73912101, -43.39520959, -5.08956953]),
...     np.array([56.2077687, -53.68997662, 20.2113441]),
...     np.array([66.16683122, -38.64600327, 42.77396631]),
...     np.array([76.7295211, -23.9214821, 61.04740432]),
...     np.array([82.85370708, -3.98679065, 75.43320144]),
...     np.array([69.26458861, 13.11066359, 68.83858372]),
...     np.array([69.63154351, 28.24532497, 59.45609803]),
...     np.array([61.26281449, 40.87950839, 44.97606172]),
...     np.array([41.62567821, 57.34129516, 27.4671817]),
...     np.array([40.52565174, 48.87449192, 3.4512168])]
>>> gamut_area(Labs)  
8335.9482018...