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solve — SciPy v1.15.3 Manual

scipy.linalg.

scipy.linalg.solve(a, b, lower=False, overwrite_a=False, overwrite_b=False, check_finite=True, assume_a=None, transposed=False)[source]#

Solves the linear equation set a @ x == b for the unknown x for square a matrix.

If the data matrix is known to be a particular type then supplying the corresponding string to assume_a key chooses the dedicated solver. The available options are

diagonal

‘diagonal’

tridiagonal

‘tridiagonal’

banded

‘banded’

upper triangular

‘upper triangular’

lower triangular

‘lower triangular’

symmetric

‘symmetric’ (or ‘sym’)

hermitian

‘hermitian’ (or ‘her’)

positive definite

‘positive definite’ (or ‘pos’)

general

‘general’ (or ‘gen’)

Parameters:

a(N, N) array_like

Square input data

b(N, NRHS) array_like

Input data for the right hand side.

lowerbool, default: False

Ignored unless assume_a is one of 'sym', 'her', or 'pos'. If True, the calculation uses only the data in the lower triangle of a; entries above the diagonal are ignored. If False (default), the calculation uses only the data in the upper triangle of a; entries below the diagonal are ignored.

overwrite_abool, default: False

Allow overwriting data in a (may enhance performance).

overwrite_bbool, default: False

Allow overwriting data in b (may enhance performance).

check_finitebool, default: True

Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (crashes, non-termination) if the inputs do contain infinities or NaNs.

assume_astr, optional

Valid entries are described above. If omitted or None, checks are performed to identify structure so the appropriate solver can be called.

transposedbool, default: False

If True, solve a.T @ x == b. Raises NotImplementedError for complex a.

Returns:

x(N, NRHS) ndarray

The solution array.

Raises:

ValueError

If size mismatches detected or input a is not square.

LinAlgError

If the matrix is singular.

LinAlgWarning

If an ill-conditioned input a is detected.

NotImplementedError

If transposed is True and input a is a complex matrix.

Notes

If the input b matrix is a 1-D array with N elements, when supplied together with an NxN input a, it is assumed as a valid column vector despite the apparent size mismatch. This is compatible with the numpy.dot() behavior and the returned result is still 1-D array.

The general, symmetric, Hermitian and positive definite solutions are obtained via calling ?GESV, ?SYSV, ?HESV, and ?POSV routines of LAPACK respectively.

The datatype of the arrays define which solver is called regardless of the values. In other words, even when the complex array entries have precisely zero imaginary parts, the complex solver will be called based on the data type of the array.

Examples

Given a and b, solve for x:

>>> import numpy as np
>>> a = np.array([[3, 2, 0], [1, -1, 0], [0, 5, 1]])
>>> b = np.array([2, 4, -1])
>>> from scipy import linalg
>>> x = linalg.solve(a, b)
>>> x
array([ 2., -2.,  9.])
>>> np.dot(a, x) == b
array([ True,  True,  True], dtype=bool)

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