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
- __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