`scipy.linalg._basic:_validate_args_for_toeplitz_ops`

Signature

def _validate_args_for_toeplitz_ops(c_or_cr, b, check_finite, keep_b_shape, enforce_square = True)

Validate arguments and format inputs for toeplitz functions

c_or_cr : array_like or tuple of (array_like, array_like): The vector c, or a tuple of arrays (c, r). Whatever the actual shape of c, it will be converted to a 1-D array. If not supplied, r = conjugate(c) is assumed; in this case, if c[0] is real, the Toeplitz matrix is Hermitian. r[0] is ignored; the first row of the Toeplitz matrix is [c[0], r[1:]]. Whatever the actual shape of r, it will be converted to a 1-D array.
b : (M,) or (M, K) array_like: Right-hand side in T x = b.
check_finite : bool: Whether to check that the input matrices contain only finite numbers. Disabling may give a performance gain, but may result in problems (result entirely NaNs) if the inputs do contain infinities or NaNs.
keep_b_shape : bool: Whether to convert a (M,) dimensional b into a (M, 1) dimensional matrix.
enforce_square : bool, optional: If True (default), this verifies that the Toeplitz matrix is square.

r : array: 1d array corresponding to the first row of the Toeplitz matrix.
: c: array: 1d array corresponding to the first column of the Toeplitz matrix.
: b: array: (M,), (M, 1) or (M, K) dimensional array, post validation, corresponding to b.
: dtype: numpy datatype: dtype stores the datatype of r, c and b. If any of r, c or b are complex, dtype is np.complex128, otherwise, it is np.float.
: b_shape: tuple: Shape of b after passing it through _asarray_validated.