maxframe.tensor.linalg.solve#

maxframe.tensor.linalg.solve(a, b, sym_pos=False, sparse=None)[source]#

Solve the equation a x = b for x.

Parameters:

a ((M, M) array_like) – A square matrix.
b ((M,) or (M, N) array_like) – Right-hand side matrix in a x = b.
sym_pos (bool) – Assume a is symmetric and positive definite. If True, use Cholesky decomposition.
sparse (bool, optional) – Return sparse value or not.

Returns:

x ((M,) or (M, N) ndarray)
Solution to the system a x = b. Shape of the return matches the
shape of b.

Raises:

LinAlgError –
If a is singular. –

Examples

Given a and b, solve for x:

>>> import maxframe.tensor as mt
>>> a = mt.array([[3, 2, 0], [1, -1, 0], [0, 5, 1]])
>>> b = mt.array([2, 4, -1])
>>> x = mt.linalg.solve(a, b)
>>> x.execute()
array([ 2., -2.,  9.])

>>> mt.dot(a, x).execute()  # Check the result
array([ 2., 4., -1.])