# Test osqp python module
import osqp
# import osqppurepy as osqp
import numpy as np
from scipy import sparse
import scipy as sp
# Unit Test
import unittest
class warm_start_tests(unittest.TestCase):
def setUp(self):
"""
Setup default options
"""
self.opts = {'verbose': False,
'adaptive_rho': False,
'eps_abs': 1e-08,
'eps_rel': 1e-08,
'polish': False,
'check_termination': 1}
def test_warm_start(self):
# Big problem
sp.random.seed(2)
self.n = 100
self.m = 200
self.A = sparse.random(self.m, self.n, density=0.9, format='csc')
self.l = -sp.rand(self.m) * 2.
self.u = sp.rand(self.m) * 2.
P = sparse.random(self.n, self.n, density=0.9)
self.P = sparse.triu(P.dot(P.T), format='csc')
self.q = sp.randn(self.n)
# Setup solver
self.model = osqp.OSQP()
self.model.setup(P=self.P, q=self.q, A=self.A, l=self.l, u=self.u,
**self.opts)
# Solve problem with OSQP
res = self.model.solve()
# Store optimal values
x_opt = res.x
y_opt = res.y
tot_iter = res.info.iter
# Warm start with zeros and check if number of iterations is the same
self.model.warm_start(x=np.zeros(self.n), y=np.zeros(self.m))
res = self.model.solve()
self.assertEqual(res.info.iter, tot_iter)
# Warm start with optimal values and check that number of iter < 10
self.model.warm_start(x=x_opt, y=y_opt)
res = self.model.solve()
self.assertLess(res.info.iter, 10)
