numpy.linalg.inv # linalg.inv(a) [source] # Compute the inverse of a matrix. Given a square matrix a, return the matrix ainv satisfying a @ ainv = ainv @ a = eye(a.shape[0]). Parameters: a(…, …

Compute the (Moore-Penrose) pseudo-inverse of a matrix. Calculate the generalized inverse of a matrix using its singular-value decomposition (SVD) and including all large singular values.

numpy.matrix.I # property property matrix.I # Returns the (multiplicative) inverse of invertible self. Parameters: None Returns: retmatrix object If self is non-singular, ret is such that ret * self == …

SciPy contains functions not found in numpy.linalg, such as functions related to LU decomposition and the Schur decomposition, multiple ways of calculating the pseudoinverse, and matrix …

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 …

numpy.matrix.transpose # method matrix.transpose(*axes) # Returns a view of the array with axes transposed. Refer to numpy.transpose for full documentation. Parameters: axesNone, …

Return the lower or upper Cholesky decomposition, L * L.H or U.H * U, of the square matrix a, where L is lower-triangular, U is upper-triangular, and .H is the conjugate transpose operator …

This function computes the inverse of the one-dimensional n -point discrete Fourier transform computed by fft. In other words, ifft(fft(a)) == a to within numerical accuracy.

numpy.invert(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature]) = <ufunc 'invert'> # Compute bit-wise inversion, or bit-wise NOT, …

Jun 22, 2021 · numpy.linalg.inv ¶ linalg.inv(a) [source] ¶ Compute the (multiplicative) inverse of a matrix. Given a square matrix a, return the matrix ainv satisfying dot(a, ainv) = dot(ainv, a) = …