def load_bn_from_file(self, file_name):
"""
Load a bayesian network to show.
Initially, the bn can be loaded by itself, but vertex positions must be loaded independently.
"""
try:
# load bayesian network
self.disc_bn = DiscreteBayesianNetworkExt()
self.disc_bn.load(file_name)
### Load Vertex locations
json_data = dic_from_json_file(file_name)
# Vertex locations
if "vertex_loc" in json_data.keys():
self.dict_to_gpoints(json_data["vertex_loc"])
else:
vl = ugraphic.create_vertex_locations(self.disc_bn)
self.dict_to_gpoints(vl)
except Exception:
ugraphic.show_warning(self.window,
"Error loading the Bayesian Network",
Exception)
return
self._draw_mode_edit()
def set_mode(self, mode):
"""
Select Edit or Run mode.
"""
self.mode = mode
if self.mode == Mode.edit_edge or self.mode == Mode.edit_vertex:
self.bedit.set_active(True)
self.toolbar_edit.set_visible(True)
self.toolbar_evidence.set_visible(False)
if self.mode == Mode.edit_vertex:
self.bvertex.set_active(True)
elif self.mode == Mode.run:
self.brun.set_active(True)
# Validate BN
for v in self.disc_bn.get_vertices():
# Validate cycles
try:
self.disc_bn.toporder()
except Exception:
ugraphic.show_warning(self.window,
"The Bayesian Network contains cycles.")
return
# Validate that the BN has all the cpts
ok = self.disc_bn.validate_cprob(v)
if not ok:
ugraphic.show_warning(self.window,
v + " is not valid.",
"please, check the probability table.")
self.bedit.set_active(True)
return
# compute marginals
self.marginals = self.disc_bn.compute_marginals(self.evidences)
self.toolbar_edit.set_visible(False)
self.toolbar_evidence.set_visible(True)
self.bclear_evidence.set_visible_horizontal(True)
print "aqui pasa"
self.selected_vertex = None
self.selected_edge = None
self.draw_graph()
def set_mode(self, mode):
"""
Select Edit or Run mode.
"""
self.mode = mode
if self.mode == Mode.edit_edge or self.mode == Mode.edit_vertex:
self.bedit.set_active(True)
self.toolbar_edit.set_visible(True)
self.toolbar_evidence.set_visible(False)
if self.mode == Mode.edit_vertex:
self.bvertex.set_active(True)
elif self.mode == Mode.run:
self.brun.set_active(True)
# Validate BN
for v in self.disc_bn.get_vertices():
# Validate cycles
try:
self.disc_bn.toporder()
except Exception:
ugraphic.show_warning(
self.window, "The Bayesian Network contains cycles.")
return
# Validate that the BN has all the cpts
ok = self.disc_bn.validate_cprob(v)
if not ok:
ugraphic.show_warning(
self.window, v + " is not valid.",
"please, check the probability table.")
self.bedit.set_active(True)
return
# compute marginals
self.marginals = self.disc_bn.compute_marginals(self.evidences)
self.toolbar_edit.set_visible(False)
self.toolbar_evidence.set_visible(True)
self.bclear_evidence.set_visible_horizontal(True)
print "aqui pasa"
self.selected_vertex = None
self.selected_edge = None
self.draw_graph()
def load_bn_from_file(self, file_name):
"""
Load a bayesian network to show.
Initially, the bn can be loaded by itself, but vertex positions must be loaded independently.
"""
try:
# load bayesian network
self.disc_bn = DiscreteBayesianNetworkExt()
self.disc_bn.load(file_name)
### Load Vertex locations
json_data = dic_from_json_file(file_name)
# Vertex locations
if "vertex_loc" in json_data.keys():
self.dict_to_gpoints(json_data["vertex_loc"])
else:
vl = ugraphic.create_vertex_locations(self.disc_bn)
self.dict_to_gpoints(vl)
except Exception:
ugraphic.show_warning(self.window, "Error loading the Bayesian Network", Exception)
return
self._draw_mode_edit()