Source code for toqito.matrix_props.is_positive_semidefinite

"""Is matrix a positive semidefinite matrix."""
import numpy as np

from toqito.matrix_props import is_hermitian


[docs] def is_positive_semidefinite(mat: np.ndarray, rtol: float = 1e-05, atol: float = 1e-08) -> bool: r""" Check if matrix is positive semidefinite (PSD) [WikPSD]_. Examples ========== Consider the following matrix .. math:: A = \begin{pmatrix} 1 & -1 \\ -1 & 1 \end{pmatrix} our function indicates that this is indeed a positive semidefinite matrix. >>> from toqito.matrix_props import is_positive_semidefinite >>> import numpy as np >>> A = np.array([[1, -1], [-1, 1]]) >>> is_positive_semidefinite(A) True Alternatively, the following example matrix :math:`B` defined as .. math:: B = \begin{pmatrix} -1 & -1 \\ -1 & -1 \end{pmatrix} is not positive semidefinite. >>> from toqito.matrix_props import is_positive_semidefinite >>> import numpy as np >>> B = np.array([[-1, -1], [-1, -1]]) >>> is_positive_semidefinite(B) False References ========== .. [WikPSD] Wikipedia: Definiteness of a matrix. https://en.wikipedia.org/wiki/Definiteness_of_a_matrix :param mat: Matrix to check. :param rtol: The relative tolerance parameter (default 1e-05). :param atol: The absolute tolerance parameter (default 1e-08). :return: Return :code:`True` if matrix is PSD, and :code:`False` otherwise. """ if not is_hermitian(mat, rtol, atol): return False evals, _ = np.linalg.eigh(mat) return all(x >= -abs(atol) for x in evals)