# Use numpy to print the product of a matrix by a random vector. # # Uses xpress.Dot to on a matrix and a vector. Note that the NumPy dot operator # works perfectly fine here. # # (C) 1983-2025 Fair Isaac Corporation import numpy as np import xpress as xp p = xp.problem() x = [p.addVariable() for i in range(5)] p.addConstraint(xp.Sum(x) >= 2) p.setObjective(xp.Sum(x[i]**2 for i in range(5))) p.optimize() A = np.array(range(30)).reshape(6, 5) # A is a 6x5 matrix. sol = np.array(p.getSolution()) # Suppose it's a vector of size 5. columns = A*sol # Not a matrix-vector product! v = xp.Dot(A, sol) # This is a matrix-vector product A*sol. print(v)