colour.algebra.vecmul#

colour.algebra.vecmul(m: ArrayLike, v: ArrayLike) → NDArrayFloat[source]#

Perform batched multiplication between the matrix array \(m\) and vector array \(v\).

This function is equivalent to numpy.matmul() but specifically designed for vector multiplication by a matrix. Vector dimensionality is automatically increased to enable broadcasting. The operation can be expressed using numpy.einsum() with subscripts ‘…ij,…j->…i’.

Parameters:

m (ArrayLike) – Matrix array \(m\).
v (ArrayLike) – Vector array \(v\).

Returns:

Multiplied vector array \(v\).

Return type:

numpy.ndarray

Examples

>>> m = np.array(
...     [
...         [0.7328, 0.4296, -0.1624],
...         [-0.7036, 1.6975, 0.0061],
...         [0.0030, 0.0136, 0.9834],
...     ]
... )
>>> m = np.reshape(np.tile(m, (6, 1)), (6, 3, 3))
>>> v = np.array([0.20654008, 0.12197225, 0.05136952])
>>> v = np.tile(v, (6, 1))
>>> vecmul(m, v)
array([[ 0.1954094...,  0.0620396...,  0.0527952...],
       [ 0.1954094...,  0.0620396...,  0.0527952...],
       [ 0.1954094...,  0.0620396...,  0.0527952...],
       [ 0.1954094...,  0.0620396...,  0.0527952...],
       [ 0.1954094...,  0.0620396...,  0.0527952...],
       [ 0.1954094...,  0.0620396...,  0.0527952...]])

colour.algebra.vecmul#

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