scipy.optimize.nnls¶
- scipy.optimize.nnls(A, b)[source]¶
- Solve argmin_x || Ax - b ||_2 for x>=0. This is a wrapper for a FORTAN non-negative least squares solver. - Parameters: - A : ndarray - Matrix A as shown above. - b : ndarray - Right-hand side vector. - Returns: - x : ndarray - Solution vector. - rnorm : float - The residual, || Ax-b ||_2. - Notes - The FORTRAN code was published in the book below. The algorithm is an active set method. It solves the KKT (Karush-Kuhn-Tucker) conditions for the non-negative least squares problem. - References - Lawson C., Hanson R.J., (1987) Solving Least Squares Problems, SIAM 
