def solve_via_data(self,
data,
warm_start,
verbose,
solver_opts,
solver_cache=None):
import ecos
cones = dims_to_solver_dict(data[ConicSolver.DIMS])
# Default verbose to false for BB wrapper.
if 'mi_verbose' in solver_opts:
mi_verbose = solver_opts['mi_verbose']
del solver_opts['mi_verbose']
else:
mi_verbose = verbose
solution = ecos.solve(data[s.C],
data[s.G],
data[s.H],
cones,
data[s.A],
data[s.B],
verbose=verbose,
mi_verbose=mi_verbose,
bool_vars_idx=data[s.BOOL_IDX],
int_vars_idx=data[s.INT_IDX],
**solver_opts)
return solution
def test_advanced2(self):
"""Test code from the advanced section of the tutorial.
"""
x = cvx.Variable()
prob = cvx.Problem(cvx.Minimize(cvx.square(x)), [x == 2])
# Get ECOS arguments.
data, chain, inverse = prob.get_problem_data(cvx.ECOS)
# Get ECOS_BB arguments.
data, chain, inverse = prob.get_problem_data(cvx.ECOS_BB)
# Get CVXOPT arguments.
if cvx.CVXOPT in cvx.installed_solvers():
data, chain, inverse = prob.get_problem_data(cvx.CVXOPT)
# Get SCS arguments.
data, chain, inverse = prob.get_problem_data(cvx.SCS)
import ecos
# Get ECOS arguments.
data, chain, inverse = prob.get_problem_data(cvx.ECOS)
# Call ECOS solver.
solution = ecos.solve(data["c"], data["G"], data["h"],
ecos_conif.dims_to_solver_dict(data["dims"]),
data["A"], data["b"])
# Unpack raw solver output.
prob.unpack_results(solution, chain, inverse)