colour.LUTOperatorMatrix#

class colour.LUTOperatorMatrix(matrix: Optional[ArrayLike] = None, offset: Optional[ArrayLike] = None, *args: Any, **kwargs: Any)[source]#

Bases: AbstractLUTSequenceOperator

Define the LUT operator supporting a 3x3 or 4x4 matrix and an offset vector.

Parameters:
  • matrix (Optional[ArrayLike]) – 3x3 or 4x4 matrix for the operator.

  • offset (Optional[ArrayLike]) – Offset for the operator.

  • nameLUT operator name.

  • comments – Comments to add to the LUT operator.

  • args (Any) –

  • kwargs (Any) –

Attributes

Methods

Notes

  • The internal colour.io.Matrix.matrix and colour.io.Matrix.offset properties are reshaped to (4, 4) and (4, ) respectively.

Examples

Instantiating an identity matrix:

>>> print(LUTOperatorMatrix(name="Identity"))
LUTOperatorMatrix - Identity
----------------------------

Matrix     : [[ 1.  0.  0.  0.]
              [ 0.  1.  0.  0.]
              [ 0.  0.  1.  0.]
              [ 0.  0.  0.  1.]]
Offset     : [ 0.  0.  0.  0.]

Instantiating a matrix with comments:

>>> matrix = np.array(
...     [
...         [1.45143932, -0.23651075, -0.21492857],
...         [-0.07655377, 1.1762297, -0.09967593],
...         [0.00831615, -0.00603245, 0.9977163],
...     ]
... )
>>> print(
...     LUTOperatorMatrix(
...         matrix,
...         name="AP0 to AP1",
...         comments=["A first comment.", "A second comment."],
...     )
... )
LUTOperatorMatrix - AP0 to AP1
------------------------------

Matrix     : [[ 1.45143932 -0.23651075 -0.21492857  0.        ]
              [-0.07655377  1.1762297  -0.09967593  0.        ]
              [ 0.00831615 -0.00603245  0.9977163   0.        ]
              [ 0.          0.          0.          1.        ]]
Offset     : [ 0.  0.  0.  0.]

A first comment.
A second comment.
__init__(matrix: Optional[ArrayLike] = None, offset: Optional[ArrayLike] = None, *args: Any, **kwargs: Any) None[source]#
Parameters:
Return type:

None

__hash__ = None#
property matrix: ndarray#

Getter and setter property for the LUT operator matrix.

Parameters:

value – Value to set the LUT operator matrix with.

Returns:

Operator matrix.

Return type:

numpy.ndarray

property offset: ndarray#

Getter and setter property for the LUT operator offset.

Parameters:

value – Value to set the LUT operator offset with.

Returns:

Operator offset.

Return type:

numpy.ndarray

__str__() str[source]#

Return a formatted string representation of the LUT operator.

Returns:

Formatted string representation.

Return type:

str

Examples

>>> print(LUTOperatorMatrix())  
LUTOperatorMatrix - LUT Sequence Operator ...
------------------------------------------...

Matrix     : [[ 1.  0.  0.  0.]
              [ 0.  1.  0.  0.]
              [ 0.  0.  1.  0.]
              [ 0.  0.  0.  1.]]
Offset     : [ 0.  0.  0.  0.]
__repr__() str[source]#

Return an evaluable string representation of the LUT operator.

Returns:

Evaluable string representation.

Return type:

str

Examples

>>> LUTOperatorMatrix(
...     comments=["A first comment.", "A second comment."]
... )
... 
LUTOperatorMatrix([[ 1.,  0.,  0.,  0.],
                   [ 0.,  1.,  0.,  0.],
                   [ 0.,  0.,  1.,  0.],
                   [ 0.,  0.,  0.,  1.]],
                  [ 0.,  0.,  0.,  0.],
                  name='LUT Sequence Operator ...',
                  comments=['A first comment.', 'A second comment.'])
__eq__(other: Any) bool[source]#

Return whether the LUT operator is equal to given other object.

Parameters:

other (Any) – Object to test whether it is equal to the LUT operator.

Returns:

Whether given object equal to the LUT operator.

Return type:

bool

Examples

>>> LUTOperatorMatrix() == LUTOperatorMatrix()
True
__ne__(other: Any) bool[source]#

Return whether the LUT operator is not equal to given other object.

Parameters:

other (Any) – Object to test whether it is not equal to the LUT operator.

Returns:

Whether given object is not equal to the LUT operator.

Return type:

bool

Examples

>>> LUTOperatorMatrix() != LUTOperatorMatrix(
...     np.linspace(0, 1, 16).reshape([4, 4])
... )
True
apply(RGB: ArrayLike, *args: Any, **kwargs: Any) ndarray[source]#

Apply the LUT operator to given RGB array.

Parameters:
  • RGB (ArrayLike) – RGB array to apply the LUT operator transform to.

  • apply_offset_first – Whether to apply the offset first and then the matrix.

  • args (Any) –

  • kwargs (Any) –

Returns:

Transformed RGB array.

Return type:

numpy.ndarray

Examples

>>> matrix = np.array(
...     [
...         [1.45143932, -0.23651075, -0.21492857],
...         [-0.07655377, 1.1762297, -0.09967593],
...         [0.00831615, -0.00603245, 0.9977163],
...     ]
... )
>>> M = LUTOperatorMatrix(matrix)
>>> RGB = np.array([0.3, 0.4, 0.5])
>>> M.apply(RGB)  
array([ 0.2333632...,  0.3976877...,  0.4989400...])