Linear algebra (`cupyx.scipy.linalg`)#

Hint

SciPy API Reference: Linear algebra (scipy.linalg)

Basics#

`solve_triangular`(a, b[, trans, lower, ...])	Solve the equation a x = b for x, assuming a is a triangular matrix.
`kron`(a, b)	Kronecker product.
`khatri_rao`(a, b)	Khatri-rao product
`bandwidth`(a)	Return the lower and upper bandwidth of a 2D numeric array.

Matrix Functions#

Compute the matrix exponential.

Decompositions#

`lu`(a[, permute_l, overwrite_a, check_finite])	LU decomposition.
`lu_factor`(a[, overwrite_a, check_finite])	LU decomposition.
`lu_solve`(lu_and_piv, b[, trans, ...])	Solve an equation system, `a * x = b`, given the LU factorization of `a`

Special Matrices#

`block_diag`(*arrs)	Create a block diagonal matrix from provided arrays.
`circulant`(c)	Construct a circulant matrix.
`companion`(a)	Create a companion matrix.
`convolution_matrix`(a, n[, mode])	Construct a convolution matrix.
`dft`(n[, scale])	Discrete Fourier transform matrix.
`fiedler`(a)	Returns a symmetric Fiedler matrix
`fiedler_companion`(a)	Returns a Fiedler companion matrix
`hadamard`(n[, dtype])	Construct an Hadamard matrix.
`hankel`(c[, r])	Construct a Hankel matrix.
`helmert`(n[, full])	Create an Helmert matrix of order `n`.
`hilbert`(n)	Create a Hilbert matrix of order `n`.
`leslie`(f, s)	Create a Leslie matrix.
`toeplitz`(c[, r])	Construct a Toeplitz matrix.