def test_duplicate_constraints(self):
eq = (self.x == 2)
le = (self.x <= 2)
obj = 0
def test(self):
objective, constraints = self.canonicalize()
sym_data = SymData(objective, constraints, SOLVERS[s.ECOS])
return (len(sym_data.constr_map[s.EQ]),
len(sym_data.constr_map[s.LEQ]))
Problem.register_solve("test", test)
p = Problem(Minimize(obj), [eq, eq, le, le])
result = p.solve(method="test")
self.assertEqual(result, (1, 1))
# Internal constraints.
X = Semidef(2)
obj = sum_entries(X + X)
p = Problem(Minimize(obj))
result = p.solve(method="test")
self.assertEqual(result, (0, 1))
# Duplicates from non-linear constraints.
exp = norm(self.x, 2)
prob = Problem(Minimize(0), [exp <= 1, exp <= 2])
result = prob.solve(method="test")
self.assertEqual(result, (0, 4))
def test_duplicate_constraints(self):
eq = (self.x == 2)
le = (self.x <= 2)
obj = 0
def test(self):
objective, constr_map = self.canonicalize()
print len(constr_map[s.SOC])
dims = self._format_for_solver(constr_map, s.ECOS)
return (len(constr_map[s.EQ]), len(constr_map[s.LEQ]))
Problem.register_solve("test", test)
p = Problem(Minimize(obj), [eq, eq, le, le])
result = p.solve(method="test")
self.assertEqual(result, (1, 1))
# Internal constraints.
z = hstack(self.x, self.x)
obj = sum_entries(z[:, 0] + z[:, 1])
p = Problem(Minimize(obj))
result = p.solve(method="test")
self.assertEqual(result, (2, 0))
# Duplicates from non-linear constraints.
exp = norm(self.x, 2)
prob = Problem(Minimize(0), [exp <= 1, exp <= 2])
result = prob.solve(method="test")
self.assertEqual(result, (0, 4))
def test_duplicate_constraints(self):
eq = (self.x == 2)
le = (self.x <= 2)
obj = 0
def test(self):
objective, constr_map = self.canonicalize()
self._presolve(objective, constr_map)
print len(constr_map[s.SOC])
dims = self._format_for_solver(constr_map, s.ECOS)
return (len(constr_map[s.EQ]),len(constr_map[s.LEQ]))
Problem.register_solve("test", test)
p = Problem(Minimize(obj),[eq,eq,le,le])
result = p.solve(method="test")
self.assertEqual(result, (1, 1))
# Internal constraints.
X = Semidef(2)
obj = sum_entries(X + X)
p = Problem(Minimize(obj))
result = p.solve(method="test")
self.assertEqual(result, (1, 1))
# Duplicates from non-linear constraints.
exp = norm(self.x, 2)
prob = Problem(Minimize(0), [exp <= 1, exp <= 2])
result = prob.solve(method="test")
self.assertEqual(result, (0, 4))
def test_duplicate_constraints(self):
eq = (self.x == 2)
le = (self.x <= 2)
obj = 0
def test(self):
objective, constraints = self.canonicalize()
sym_data = SymData(objective, constraints, SOLVERS[s.CVXOPT])
return (len(sym_data.constr_map[s.EQ]),
len(sym_data.constr_map[s.LEQ]))
Problem.register_solve("test", test)
p = Problem(Minimize(obj),[eq,eq,le,le])
result = p.solve(method="test")
self.assertEqual(result, (1, 1))
# Internal constraints.
X = Semidef(2)
obj = sum_entries(X + X)
p = Problem(Minimize(obj))
result = p.solve(method="test")
self.assertEqual(result, (0, 1))
# Duplicates from non-linear constraints.
exp = norm(self.x, 2)
prob = Problem(Minimize(0), [exp <= 1, exp <= 2])
result = prob.solve(method="test")
self.assertEqual(result, (0, 4))
def test_duplicate_constraints(self):
eq = (self.x == 2)
le = (self.x <= 2)
obj = 0
def test(self):
objective,constr_map,dims = self.canonicalize()
return (len(constr_map[s.EQ]),len(constr_map[s.INEQ]))
Problem.register_solve("test", test)
p = Problem(Minimize(obj),[eq,eq,le,le])
result = p.solve(method="test")
self.assertEqual(result, (1,1))
def test_duplicate_constraints(self):
eq = (self.x == 2)
le = (self.x <= 2)
obj = 0
def test(self):
objective, constr_map, dims = self.canonicalize()
return (len(constr_map[s.EQ]), len(constr_map[s.INEQ]))
Problem.register_solve("test", test)
p = Problem(Minimize(obj), [eq, eq, le, le])
result = p.solve(method="test")
self.assertEqual(result, (1, 1))
def test_register_solve(self):
Problem.register_solve("test",lambda self: 1)
p = Problem(Minimize(1))
result = p.solve(method="test")
self.assertEqual(result, 1)
def test(self, a, b=2):
return (a,b)
Problem.register_solve("test", test)
p = Problem(Minimize(0))
result = p.solve(1,b=3,method="test")
self.assertEqual(result, (1,3))
result = p.solve(1,method="test")
self.assertEqual(result, (1,2))
result = p.solve(1,method="test",b=4)
self.assertEqual(result, (1,4))
def test_register_solve(self):
Problem.register_solve("test",lambda self: 1)
p = Problem(Minimize(1))
result = p.solve(method="test")
self.assertEqual(result, 1)
def test(self, a, b=2):
return (a,b)
Problem.register_solve("test", test)
p = Problem(Minimize(0))
result = p.solve(1,b=3,method="test")
self.assertEqual(result, (1,3))
result = p.solve(1,method="test")
self.assertEqual(result, (1,2))
result = p.solve(1,method="test",b=4)
self.assertEqual(result, (1,4))
def test_duplicate_constraints(self):
eq = (self.x == 2)
le = (self.x <= 2)
obj = 0
def test(self):
objective,constr_map,dims,solver = self.canonicalize(s.ECOS)
return (len(constr_map[s.EQ]),len(constr_map[s.LEQ]))
Problem.register_solve("test", test)
p = Problem(Minimize(obj),[eq,eq,le,le])
result = p.solve(method="test")
self.assertEqual(result, (1,1))
# Internal constraints.
z = hstack(self.x, self.x)
obj = sum_entries(z[:,0] + z[:,1])
p = Problem(Minimize(obj))
result = p.solve(method="test")
self.assertEqual(result, (2,0))
def test_duplicate_constraints(self):
eq = (self.x == 2)
le = (self.x <= 2)
obj = 0
def test(self):
objective, constr_map, dims, solver = self.canonicalize(s.ECOS)
return (len(constr_map[s.EQ]), len(constr_map[s.LEQ]))
Problem.register_solve("test", test)
p = Problem(Minimize(obj), [eq, eq, le, le])
result = p.solve(method="test")
self.assertEqual(result, (1, 1))
# Internal constraints.
z = hstack(self.x, self.x)
obj = sum_entries(z[:, 0] + z[:, 1])
p = Problem(Minimize(obj))
result = p.solve(method="test")
self.assertEqual(result, (2, 0))
