Defines ATD (1995) colour vision model objects:
Notes
References
[1]  Mark D. Fairchild, Color Appearance Models, 3nd Edition, The WileyIS&T Series in Imaging Science and Technology, published June 2013, ASIN: B00DAYO8E2, Locations 58415991. 
[2]  S. Lee Guth, Further applications of the ATD model for color vision, IS&T/SPIE’s Symposium on Electronic Imaging: Science & Technology, International Society for Optics and Photonics, pages 1226, DOI: https://doi.org/10.1117/12.206546 
Bases: colour.appearance.atd95.ATD95_ReferenceSpecification
Defines the ATD (1995) colour vision model reference specification.
This specification has field names consistent with Mark D. Fairchild reference.
Parameters: 


Bases: colour.appearance.atd95.ATD95_Specification
Defines the ATD (1995) colour vision model specification.
This specification has field names consistent with the remaining colour appearance models in colour.appearance but diverge from Mark D. Fairchild reference.
Notes
Parameters: 


Computes the ATD (1995) colour vision model correlates.
Parameters: 


Returns:  ATD (1995) colour vision model specification. 
Return type:  ATD95_Specification 
Warning
The input domain of that definition is non standard!
Notes
Examples
>>> XYZ = np.array([19.01, 20.00, 21.78])
>>> XYZ_0 = np.array([95.05, 100.00, 108.88])
>>> Y_0 = 318.31
>>> k_1 = 0.0
>>> k_2 = 50.0
>>> XYZ_to_ATD95(XYZ, XYZ_0, Y_0, k_1, k_2)
ATD95_Specification(h=1.9089869..., C=1.2064060..., Q=0.1814003..., A_1=0.1787931... T_1=0.0286942..., D_1=0.0107584..., A_2=0.0192182..., T_2=0.0205377..., D_2=0.0107584...)
Converts from luminance in \(cd/m^2\) to retinal illuminance in trolands.
Parameters: 


Returns:  Converted CIE XYZ colourspace matrix in trolands. 
Return type:  ndarray 
Examples
>>> XYZ = np.array([19.01, 20., 21.78])
>>> Y_0 = 318.31
>>> luminance_to_retinal_illuminance(XYZ, Y_0)
array([ 479.4445924..., 499.3174313..., 534.5631673...])
Converts from CIE XYZ colourspace to LMS cone responses.
Parameters:  XYZ (array_like, (3,)) – CIE XYZ colourspace matrix. 

Returns:  LMS cone responses. 
Return type:  ndarray, (3,) 
Examples
>>> XYZ = np.array([19.01, 20., 21.78])
>>> Y_0 = 318.31
>>> luminance_to_retinal_illuminance(XYZ, Y_0)
array([ 479.4445924..., 499.3174313..., 534.5631673...])
Returns opponent colour dimensions from given post adaptation cone signals matrix.
Parameters:  LMS_g (array_like, (3,)) – Post adaptation cone signals matrix. 

Returns:  Opponent colour dimensions. 
Return type:  tuple 
Examples
>>> from pprint import pprint
>>> LMS_g = np.array([6.95457922, 7.08945043, 6.44069316])
>>> pprint(opponent_colour_dimensions(LMS_g))
(0.1787931...,
0.0286942...,
0.0107584...,
0.0192182...,
0.0205377...,
0.0107584...)
Returns the final response of given opponent colour dimension.
Parameters:  value (numeric) – Opponent colour dimension. 

Returns:  Final response of opponent colour dimension. 
Return type:  numeric 
Examples
>>> final_response(43.54399695501678)
0.1787931...