def test_diag_prob(self):
"""Test a problem with diag.
"""
C = Variable(3, 3)
obj = Maximize(C[0, 2])
constraints = [
diag(C) == 1, C[0, 1] == 0.6, C[1, 2] == -0.3, C == semidefinite(3)
]
prob = Problem(obj, constraints)
result = prob.solve()
self.assertAlmostEqual(result, 0.583151)
def test_diag_prob(self):
"""Test a problem with diag.
"""
C = Variable(3, 3)
obj = Maximize(C[0, 2])
constraints = [diag(C) == 1,
C[0, 1] == 0.6,
C[1, 2] == -0.3,
C == semidefinite(3)]
prob = Problem(obj, constraints)
result = prob.solve()
self.assertAlmostEqual(result, 0.583151)
def test_sdp_problem(self):
# SDP in objective.
obj = Minimize(sum_entries(square(self.X - self.F)))
p = Problem(obj,[])
result = p.solve()
self.assertAlmostEqual(result, 1)
self.assertAlmostEqual(self.X.value[0,0], 1, places=3)
self.assertAlmostEqual(self.X.value[0,1], 0)
self.assertAlmostEqual(self.X.value[1,0], 0)
self.assertAlmostEqual(self.X.value[1,1], 0)
# SDP in constraint.
# ECHU: note to self, apparently this is a source of redundancy
obj = Minimize(sum_entries(square(self.Y - self.F)))
p = Problem(obj, [self.Y == semidefinite(2)])
result = p.solve()
self.assertAlmostEqual(result, 1)
self.assertAlmostEqual(self.Y.value[0,0], 1, places=4)
self.assertAlmostEqual(self.Y.value[0,1], 0)
self.assertAlmostEqual(self.Y.value[1,0], 0)
self.assertAlmostEqual(self.Y.value[1,1], 0)
# Index into semidef.
obj = Minimize(square(self.X[0,0] - 1) +
square(self.X[1,0] - 2) +
#square(self.X[0,1] - 3) +
square(self.X[1,1] - 4))
p = Problem(obj,[])
result = p.solve()
print self.X.value
self.assertAlmostEqual(result, 0)
self.assertAlmostEqual(self.X.value[0,0], 1, places=3)
self.assertAlmostEqual(self.X.value[0,1], 2, places=4)
self.assertAlmostEqual(self.X.value[1,0], 2, places=4)
self.assertAlmostEqual(self.X.value[1,1], 4, places=4)
def test_sdp_problem(self):
# SDP in objective.
obj = Minimize(sum_entries(square(self.X - self.F)))
p = Problem(obj, [])
result = p.solve()
self.assertAlmostEqual(result, 1)
self.assertAlmostEqual(self.X.value[0, 0], 1, places=3)
self.assertAlmostEqual(self.X.value[0, 1], 0)
self.assertAlmostEqual(self.X.value[1, 0], 0)
self.assertAlmostEqual(self.X.value[1, 1], 0)
# SDP in constraint.
# ECHU: note to self, apparently this is a source of redundancy
obj = Minimize(sum_entries(square(self.Y - self.F)))
p = Problem(obj, [self.Y == semidefinite(2)])
result = p.solve()
self.assertAlmostEqual(result, 1)
self.assertAlmostEqual(self.Y.value[0, 0], 1, places=4)
self.assertAlmostEqual(self.Y.value[0, 1], 0)
self.assertAlmostEqual(self.Y.value[1, 0], 0)
self.assertAlmostEqual(self.Y.value[1, 1], 0)
# Index into semidef.
obj = Minimize(
square(self.X[0, 0] - 1) + square(self.X[1, 0] - 2) +
#square(self.X[0,1] - 3) +
square(self.X[1, 1] - 4))
p = Problem(obj, [])
result = p.solve()
print self.X.value
self.assertAlmostEqual(result, 0)
self.assertAlmostEqual(self.X.value[0, 0], 1, places=3)
self.assertAlmostEqual(self.X.value[0, 1], 2, places=4)
self.assertAlmostEqual(self.X.value[1, 0], 2, places=4)
self.assertAlmostEqual(self.X.value[1, 1], 4, places=4)
def setUp(self):
self.X = semidefinite(2)
self.Y = Variable(2, 2)
self.F = matrix([[1, 0], [0, -1]], tc='d')
def setUp(self):
self.X = semidefinite(2)
self.Y = Variable(2,2)
self.F = matrix([[1,0],[0,-1]], tc='d')
