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Read problem data into matrix and vectors Description Obtain coefficient matrix, objective coefficients, and constraints' right-hand sides for a given problem. Further explanation of this example:
'Xpress Python Reference Manual'
Source Files By clicking on a file name, a preview is opened at the bottom of this page.
example_getmatrix.py # Example to show how to retrieve the coefficient matrix from a # problem. # # (C) Fair Isaac Corp., 1983-2024 import xpress as xp import scipy.sparse p = xp.problem() p.read('prob1.lp') # Obtain matrix representation of the coefficient matrix for problem. # Restrict to one million coefficients. coef, ind, beg = [], [], [] p.getrows(beg, ind, coef, 1000000, 0, p.attributes.rows - 1) # The function getrows() provides a richer output by filling up ind # not with numerical indices but with the Python objects # (i.e. Xpress variables) corresponding to the variable # indices. Convert them to numerical indices using the getIndex() # function. ind_n = [p.getIndex(v) for v in ind] # Create a Compressed Sparse Row (CSR) format matrix using the data # from getrows plus the numerical indices. A = scipy.sparse.csr_matrix((coef, ind_n, 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) b, c = [], [] p.getobj(c, 0, p.attributes.cols - 1) p.getrhs(b, 0, p.attributes.rows - 1) print(b) print(c) | |||||||||||

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