colour.CAM_Specification_LLAB#

class colour.CAM_Specification_LLAB(J: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, C: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, h: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, s: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, M: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, HC: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, a: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, b: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>)[source]#

Define the :math:`LLAB(l:c)` colour appearance model specification.

This specification has field names consistent with the remaining colour appearance models in colour.appearance but diverge from Fairchild (2013) reference.

Parameters:

J (Optional[Union[float, numpy.ndarray[Any, numpy.dtype[Union[numpy.float16, numpy.float32, numpy.float64]]]]]) – Correlate of Lightness \(L_L\).
C (Optional[Union[float, numpy.ndarray[Any, numpy.dtype[Union[numpy.float16, numpy.float32, numpy.float64]]]]]) – Correlate of chroma \(Ch_L\).
h (Optional[Union[float, numpy.ndarray[Any, numpy.dtype[Union[numpy.float16, numpy.float32, numpy.float64]]]]]) – Hue angle \(h_L\) in degrees.
s (Optional[Union[float, numpy.ndarray[Any, numpy.dtype[Union[numpy.float16, numpy.float32, numpy.float64]]]]]) – Correlate of saturation \(s_L\).
M (Optional[Union[float, numpy.ndarray[Any, numpy.dtype[Union[numpy.float16, numpy.float32, numpy.float64]]]]]) – Correlate of colourfulness \(C_L\).
HC (Optional[Union[float, numpy.ndarray[Any, numpy.dtype[Union[numpy.float16, numpy.float32, numpy.float64]]]]]) – Hue \(h\) composition \(H^C\).
a (Optional[Union[float, numpy.ndarray[Any, numpy.dtype[Union[numpy.float16, numpy.float32, numpy.float64]]]]]) – Opponent signal \(A_L\).
b (Optional[Union[float, numpy.ndarray[Any, numpy.dtype[Union[numpy.float16, numpy.float32, numpy.float64]]]]]) – Opponent signal \(B_L\).

Notes

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

References

[Fai13h], [LLK96], [LM96]

__init__(J: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, C: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, h: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, s: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, M: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, HC: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, a: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>, b: ~typing.Optional[~typing.Union[float, ~numpy.ndarray[~typing.Any, ~numpy.dtype[~typing.Union[~numpy.float16, ~numpy.float32, ~numpy.float64]]]]] = <factory>) → None#

Parameters:

J (Optional[Union[float, ndarray[Any, dtype[Union[float16, float32, float64]]]]]) –
C (Optional[Union[float, ndarray[Any, dtype[Union[float16, float32, float64]]]]]) –
h (Optional[Union[float, ndarray[Any, dtype[Union[float16, float32, float64]]]]]) –
s (Optional[Union[float, ndarray[Any, dtype[Union[float16, float32, float64]]]]]) –
M (Optional[Union[float, ndarray[Any, dtype[Union[float16, float32, float64]]]]]) –
HC (Optional[Union[float, ndarray[Any, dtype[Union[float16, float32, float64]]]]]) –
a (Optional[Union[float, ndarray[Any, dtype[Union[float16, float32, float64]]]]]) –
b (Optional[Union[float, ndarray[Any, dtype[Union[float16, float32, float64]]]]]) –

Return type:

None

Methods

`__init__`([J, C, h, s, M, HC, a, b])
`arithmetical_operation`(a, operation[, in_place])	Perform given arithmetical operation with \(a\) operand on the `dataclass`-like class.

Attributes

`fields`	Getter property for the fields of the `dataclass`-like class.
`items`	Getter property for the `dataclass`-like class items, i.e. the field names and values.
`keys`	Getter property for the `dataclass`-like class keys, i.e. the field names.
`values`	Getter property for the `dataclass`-like class values, i.e. the field values.
`J`
`C`
`h`
`s`
`M`
`HC`
`a`
`b`