def test_violation(self):
I = [[0, -1, 0], [-1, 1, 1], [0, 1, -1]]
P = Probability([2, 2], [2, 2])
objective = define_objective_with_I(I, P)
sdpRelaxation = MoroderHierarchy([flatten(P.parties[0]), flatten(P.parties[1])], verbose=0, normalized=False)
sdpRelaxation.get_relaxation(1, objective=objective, substitutions=P.substitutions)
Problem = convert_to_picos(sdpRelaxation, duplicate_moment_matrix=True)
X = Problem.get_variable("X")
Y = Problem.get_variable("Y")
Z = Problem.add_variable("Z", (sdpRelaxation.block_struct[0], sdpRelaxation.block_struct[0]))
Problem.add_constraint(Y.partial_transpose() >> 0)
Problem.add_constraint(Z.partial_transpose() >> 0)
Problem.add_constraint(X - Y + Z == 0)
Problem.add_constraint(Z[0, 0] == 1)
solution = Problem.solve(verbose=0)
self.assertTrue(abs(solution["obj"] - 0.139) < 10e-3)
"""
from ncpol2sdpa import generate_variables, SdpRelaxation, convert_to_picos
# Number of Hermitian variables
n_vars = 2
# Level of relaxation
level = 2
# Get Hermitian variables
X = generate_variables(n_vars, hermitian=True)
# Define the objective function
obj = X[0] * X[1] + X[1] * X[0]
# Inequality constraints
inequalities = [-X[1]**2 + X[1] + 0.5]
# Equality constraints
equalities = []
equalities.append(X[0]**2 - X[0])
# Obtain SDP relaxation
sdpRelaxation = SdpRelaxation(X)
sdpRelaxation.get_relaxation(level,
objective=obj,
inequalities=inequalities,
equalities=equalities)
P = convert_to_picos(sdpRelaxation)
P.solve()
@author: Peter Wittek
"""
from ncpol2sdpa import generate_variables, SdpRelaxation, convert_to_picos
# Number of Hermitian variables
n_vars = 2
# Level of relaxation
level = 2
# Get Hermitian variables
X = generate_variables(n_vars, hermitian=True)
# Define the objective function
obj = X[0] * X[1] + X[1] * X[0]
# Inequality constraints
inequalities = [-X[1] ** 2 + X[1] + 0.5]
# Equality constraints
equalities = []
equalities.append(X[0] ** 2 - X[0])
# Obtain SDP relaxation
sdpRelaxation = SdpRelaxation(X)
sdpRelaxation.get_relaxation(level, objective=obj,
inequalities=inequalities,
equalities=equalities)
P = convert_to_picos(sdpRelaxation)
P.solve()
