mojolearn.lu_solve#

mojolearn.lu_solve(lu_and_piv, b, *, trans=0, numeric_mode=None)[source]#

Solve a linear system from an LU factorization.

Follows scipy.linalg.lu_solve: solves A x = b (trans=0) or A.T x = b (trans=1 or 2; the same for a real matrix) with the pair returned by lu_factor(). A zero pivot gives 0 in that component of x, never infinity or NaN.

Parameters:

  • lu_and_piv (tuple (lu, piv)) – The output of lu_factor().

  • b (array-like of shape (n,) or (n, nrhs)) – Right-hand side.

  • trans ({0, 1, 2}, default 0) – Which system to solve.

  • numeric_mode ({“identical”, “fast”} or None, default None) – Numeric mode for this call. None uses the package default ("identical" unless changed). "identical" gives the same bits on NVIDIA and AMD GPUs; "fast" applies on Apple GPUs.

Returns:

x (ndarray of shape (n,) or (n, nrhs), float32) – Same shape as b.

Raises:

ValueError – If trans is not 0, 1 or 2, piv holds an index outside [0, n), b has the wrong number of rows, or b is not finite.

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