I've been trying to pass some code from Matlab to Python. I have the same convex optimization problem working on Matlab but I'm having problems passing it to either CVXPY or CVXOPT.
n = 1000; i = 20; y = rand(n,1); A = rand(n,i); cvx_begin variable x(n); variable lambda(i); minimize(sum_square(x-y)); subject to x == A*lambda; lambda >= zeros(i,1); lambda'*ones(i,1) == 1; cvx_end
This is what I tried with Python and CVXPY.
import numpy as np from cvxpy import * # Problem data. n = 100 i = 20 np.random.seed(1) y = np.random.randn(n) A = np.random.randn(n, i) # Construct the problem. x = Variable(n) lmbd = Variable(i) objective = Minimize(sum_squares(x - y)) constraints = [x == np.dot(A, lmbd), lmbd <= np.zeros(itr), np.sum(lmbd) == 1] prob = Problem(objective, constraints) print("status:", prob.status) print("optimal value", prob.value)
Nonetheless, it's not working. Does any of you have any idea how to make it work? I'm pretty sure my problem is in the constraints. And also it would be nice to have it with CVXOPT.</div