def get_solution_edges(self, prefix="x"):
""" Get the nonzero edge tuples from the LP solution """
varnames = self.get_solution_varnames(prefix=prefix)
return [
mip_utils.get_edge_from_varname(varname) for varname in varnames
]
def get_edges(self, prefix="x"):
""" Get the edges of the problem graph """
varnames = [name for name in self.get_varnames() if prefix in name]
return [
mip_utils.get_edge_from_varname(varname) for varname in varnames
]
def set_mincut_graph(self):
""" Build a graph structure for mincut """
values = self.get_varvals()
names = self.get_varnames()
edges = [mip_utils.get_edge_from_varname(name) for name in names]
self.initialise_mincut_graph()
self._mincut_graph = constraints.set_mincut_graph(
self._mincut_graph, edges, values)
def set_mincut_constraint(self, vertex_a, vertex_b):
""" Build a mincut constraint for a given pair of vertices """
variables = constraints.get_mincut_variables(self._mincut_graph,
vertex_a, vertex_b,
self.variable_dict,
self._is_symmetric)
if variables is None:
return None
varnames = [variable.name for variable in variables]
edges = [
mip_utils.get_edge_from_varname(varname) for varname in varnames
]
uniques = np.unique(edges)
if variables is not None:
self._funcs["add_mincut"](self.problem, variables,
self.variable_dict)
