Complex-valued matrix with real eigenvalues (but complex-valued eigenvectors); note that a.conj().T == a, i.e., a is Hermitian. >>> a = np . array ([[ 1 , 1 j ], [ - 1 j , 1 ]]) >>> eigenvalues , …

numpy.diag# numpy. diag (v, k = 0) [source] # Extract a diagonal or construct a diagonal array. See the more detailed documentation for numpy.diagonal if you use this function to extract a …

If a is 2-D, then a 1-D array containing the diagonal and of the same type as a is returned unless a is a matrix, in which case a 1-D array rather than a (2-D) matrix is returned in order to maintain …

numpy.matrix.diagonal# method. matrix. diagonal (offset = 0, axis1 = 0, axis2 = 1) # Return specified diagonals. In NumPy 1.9 the returned array is a read-only view instead of a copy as …

Returns specified diagonals of a matrix (or a stack of matrices) x. This function is Array API compatible, contrary to numpy.diagonal , the matrix is assumed to be defined by the last two …

Return the eigenvalues and eigenvectors of a complex Hermitian (conjugate symmetric) or a real symmetric matrix. Returns two objects, a 1-D array containing the eigenvalues of a , and a 2-D …

numpy.ndarray.diagonal#. method. ndarray. diagonal (offset = 0, axis1 = 0, axis2 = 1) # Return specified diagonals. In NumPy 1.9 the returned array is a read-only view instead of a copy as …

Returns the sum along the specified diagonals of a matrix (or a stack of matrices) x.

numpy.matrix# class numpy. matrix (data, dtype = None, copy = True) [source] # Returns a matrix from an array-like object, or from a string of data. A matrix is a specialized 2-D array that …

>>> # wide matrices >>> a = np. zeros ((3, 5), int) >>> np. fill_diagonal (a, 4, wrap = True) >>> a array([[4, 0, 0, 0, 0], [0, 4, 0, 0, 0], [0, 0, 4, 0, 0]]) The anti-diagonal can be filled by reversing …