colour.CAM_Specification_ATD95

class colour.CAM_Specification_ATD95(h: Union[float, list, tuple, numpy.ndarray] = <factory>, C: Union[float, list, tuple, numpy.ndarray] = <factory>, Q: Union[float, list, tuple, numpy.ndarray] = <factory>, A_1: Union[float, list, tuple, numpy.ndarray] = <factory>, T_1: Union[float, list, tuple, numpy.ndarray] = <factory>, D_1: Union[float, list, tuple, numpy.ndarray] = <factory>, A_2: Union[float, list, tuple, numpy.ndarray] = <factory>, T_2: Union[float, list, tuple, numpy.ndarray] = <factory>, D_2: Union[float, list, tuple, numpy.ndarray] = <factory>)[source]

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 Fairchild (2013) reference.

Parameters
  • h (numeric or array_like) – Hue angle \(H\) in degrees.

  • C (numeric or array_like) – Correlate of saturation \(C\). Guth (1995) incorrectly uses the terms saturation and chroma interchangeably. However, \(C\) is here a measure of saturation rather than chroma since it is measured relative to the achromatic response for the stimulus rather than that of a similarly illuminated white.

  • Q (numeric or array_like) – Correlate of brightness \(Br\).

  • A_1 (numeric or array_like) – First stage \(A_1\) response.

  • T_1 (numeric or array_like) – First stage \(T_1\) response.

  • D_1 (numeric or array_like) – First stage \(D_1\) response.

  • A_2 (numeric or array_like) – Second stage \(A_2\) response.

  • T_2 (numeric or array_like) – Second stage \(A_2\) response.

  • D_2 (numeric or array_like) – Second stage \(D_2\) response.

Notes

  • This specification is the one used in the current model implementation.

References

[Fai13a], [Gut95]

__init__(h: Union[float, list, tuple, numpy.ndarray] = <factory>, C: Union[float, list, tuple, numpy.ndarray] = <factory>, Q: Union[float, list, tuple, numpy.ndarray] = <factory>, A_1: Union[float, list, tuple, numpy.ndarray] = <factory>, T_1: Union[float, list, tuple, numpy.ndarray] = <factory>, D_1: Union[float, list, tuple, numpy.ndarray] = <factory>, A_2: Union[float, list, tuple, numpy.ndarray] = <factory>, T_2: Union[float, list, tuple, numpy.ndarray] = <factory>, D_2: Union[float, list, tuple, numpy.ndarray] = <factory>) None

Methods

__init__([h, C, Q, A_1, T_1, D_1, A_2, T_2, D_2])

arithmetical_operation(a, operation[, in_place])

Performs given arithmetical operation with \(a\) operand on the dataclass_like.

Attributes

h

C

Q

A_1

T_1

D_1

A_2

T_2

D_2