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Module « numpy.linalg »

Fonction tensorsolve - module numpy.linalg

Signature de la fonction tensorsolve

def tensorsolve(a, b, axes=None) 

Description

help(numpy.linalg.tensorsolve)

Solve the tensor equation ``a x = b`` for x.

It is assumed that all indices of `x` are summed over in the product,
together with the rightmost indices of `a`, as is done in, for example,
``tensordot(a, x, axes=x.ndim)``.

Parameters
----------
a : array_like
    Coefficient tensor, of shape ``b.shape + Q``. `Q`, a tuple, equals
    the shape of that sub-tensor of `a` consisting of the appropriate
    number of its rightmost indices, and must be such that
    ``prod(Q) == prod(b.shape)`` (in which sense `a` is said to be
    'square').
b : array_like
    Right-hand tensor, which can be of any shape.
axes : tuple of ints, optional
    Axes in `a` to reorder to the right, before inversion.
    If None (default), no reordering is done.

Returns
-------
x : ndarray, shape Q

Raises
------
LinAlgError
    If `a` is singular or not 'square' (in the above sense).

See Also
--------
numpy.tensordot, tensorinv, numpy.einsum

Examples
--------
>>> import numpy as np
>>> a = np.eye(2*3*4)
>>> a.shape = (2*3, 4, 2, 3, 4)
>>> rng = np.random.default_rng()
>>> b = rng.normal(size=(2*3, 4))
>>> x = np.linalg.tensorsolve(a, b)
>>> x.shape
(2, 3, 4)
>>> np.allclose(np.tensordot(a, x, axes=3), b)
True

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