Computational Physics, Linear Algebra, Python, Math, Matrix.
know how the sub-transformations are found. The singular value decomposition can be done with the linalg.svd() function from Numpy (note that np.linalg.eig(A) works only on square matrices and will give an error for A). A = np.array([[7, 2], [3, 4], [5, 3]]) U, D, V = np.linalg.svd(A) U