Repository URL to install this package:
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Version:
0.6.2.post5 ▾
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# Test osqp python module
import osqp
from osqp.tests.utils import load_high_accuracy, rel_tol, abs_tol, decimal_tol
# import osqppurepy as osqp
import numpy as np
from scipy import sparse
import scipy as sp
# Unit Test
import unittest
import numpy.testing as nptest
class unconstrained_tests(unittest.TestCase):
def setUp(self):
"""
Setup unconstrained quadratic problem
"""
# Unconstrained QP problem
sp.random.seed(4)
self.n = 30
self.m = 0
P = sparse.diags(np.random.rand(self.n)) + 0.2*sparse.eye(self.n)
self.P = P.tocsc()
self.q = np.random.randn(self.n)
self.A = sparse.csc_matrix((self.m, self.n))
self.l = np.array([])
self.u = np.array([])
self.opts = {'verbose': False,
'eps_abs': 1e-08,
'eps_rel': 1e-08,
'polish': False}
self.model = osqp.OSQP()
self.model.setup(P=self.P, q=self.q, A=self.A, l=self.l, u=self.u,
**self.opts)
def test_unconstrained_problem(self):
# Solve problem
res = self.model.solve()
# Assert close
x_sol, _, obj_sol = load_high_accuracy('test_unconstrained_problem')
# Assert close
nptest.assert_allclose(res.x, x_sol, rtol=rel_tol, atol=abs_tol)
nptest.assert_almost_equal(
res.info.obj_val, obj_sol, decimal=decimal_tol)