mojolearn.solve#

mojolearn.solve(a, b, *, numeric_mode=None)[source]#

Solve the square linear system a @ x = b.

Follows numpy.linalg.solve, computed by LU factorization with partial pivoting (as lu_factor() and lu_solve()). A singular matrix gives a RuntimeWarning rather than an exception.

Parameters:

  • a (array-like of shape (n, n))

  • b (array-like of shape (n,) or (n, nrhs))

  • 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)

Raises:

ValueError – If a is not square or b has the wrong number of rows.

Examples

>>> import numpy as np, mojolearn
>>> A = np.random.default_rng(0).random((8, 8), dtype=np.float32) + 8 * np.eye(8, dtype=np.float32)
>>> x = mojolearn.solve(A, np.ones(8, dtype=np.float32))
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