scipy 1.8.0 Pypi GitHub Homepage
Other Docs
ParametersReturnsBackRef
lu_solve(lu_and_piv, b, trans=0, overwrite_b=False, check_finite=True)

Parameters

(lu, piv) :

Factorization of the coefficient matrix a, as given by lu_factor

b : array

Right-hand side

trans : {0, 1, 2}, optional

Type of system to solve:

===== ========= trans system ===== ========= 0 a x = b 1 a^T x = b 2 a^H x = b ===== =========

overwrite_b : bool, optional

Whether to overwrite data in b (may increase performance)

check_finite : bool, optional

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.

Returns

x : array

Solution to the system

Solve an equation system, a x = b, given the LU factorization of a

See Also

lu_factor

LU factorize a matrix

Examples

>>> from scipy.linalg import lu_factor, lu_solve
... A = np.array([[2, 5, 8, 7], [5, 2, 2, 8], [7, 5, 6, 6], [5, 4, 4, 8]])
... b = np.array([1, 1, 1, 1])
... lu, piv = lu_factor(A)
... x = lu_solve((lu, piv), b)
... np.allclose(A @ x - b, np.zeros((4,))) True
See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

scipy.linalg._decomp_lu.lu_solve scipy.linalg._decomp_lu.lu_factor

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /scipy/linalg/_decomp_lu.py#87
type: <class 'function'>
Commit: