# Example to show how to retrieve the coefficient matrix from a # problem. # # (C) 1983-2025 Fair Isaac Corporation import xpress as xp import scipy.sparse p = xp.problem() p.readProb('Data/prob1.lp') # Obtain matrix representation of the coefficient matrix for problem. beg, ind, coef = p.getRows(0, p.attributes.rows - 1) # Create a Compressed Sparse Row (CSR) format matrix using the data # from getRows. A = scipy.sparse.csr_matrix((coef, ind, beg)) # Convert the CSR matrix to a NumPy array of arrays, so that each row # is a (non-compressed) array. M = A.toarray() print(A) print(M) c = p.getObj(0, p.attributes.cols - 1) b = p.getRHS(0, p.attributes.rows - 1) print(b) print(c)