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 __init__(self, window, disc_bn=DiscreteBayesianNetworkExt()):
self.window = window
# Create graphic widgets
self.box_disc_bn, self.drawing_box, self.toolbar_edit, self.toolbar_evidence, self.bedit, self.brun, self.bvertex, \
self.bclear_evidence = ugraphic.create_widget(
res.TAB_DISC_BAYES_NET_GLADE,
[BOX_DISC_BN, DRAWING_BOX, TB_EDIT_BN, TB_EVIDENCE, RB_EDIT, RB_RUN, RB_VERTEX, RB_CLEAR_EVIDENCE], self)
super(BoxDiscreteBN, self).__init__(spacing=1)
self.pack_start(self.box_disc_bn, True, True, 0)
self.set_visible(True)
self.drawer = GraphDrawer()
self.drawing_box.pack_start(self.drawer.get_drawing_area(), True, True,
0)
self.mode = Mode.edit_vertex
# Temporal vertex for edge
self.vertex_1 = None
self.selected_vertex = None
self.selected_edge = None
self.marginals = None
self.evidences = {}
# Temporal arrow for mouse motion
self.tmp_arrow = None
# Graph
self.disc_bn = disc_bn
# Vertex locations to draw
self.vertex_locations = {}
self.clicked_point = None
self.button_pressed = False
# connect listeners
self.drawer.clicked_element_listener = self.clicked_element
self.drawer.clicked_clear_space_listener = self.clicked_clear_space
self.drawer.right_click_elem_listener = self.right_clicked_elem
self.drawer.double_clicked_element_listener = self.double_click_on_elem
# Graphical objects in the background
self.background_gobjs = []
def do_activate(self):
# Graph
vertices = ["A", "B", "C", "D"]
edges = [["A", "B"], ["C", "B"], ["D", "B"]]
states = {
"A": ["atrue", "afalse"],
"B": ["true", "false"],
"C": ["ctrue", "cfalse"],
"D": ["1", "2", "3"]
}
cpt_v = "D"
disc_bn = DiscreteBayesianNetworkExt()
disc_bn.set_vertices(vertices)
disc_bn.E = edges
# States
for s, iss in states.items():
for i in iss:
disc_bn.add_state(s, i)
gtable = gwidgets.GraphicCptTable(disc_bn, cpt_v)
# table = gwidgets.create_treeview_for_cpt(vertices, edges, states, cpt_v)
## Window
window = Gtk.Window(application=self, title="CPT for " + cpt_v)
window.set_default_size(250, 100)
window.set_border_width(10)
# the label we use to show the selection
label = Gtk.Label()
label.set_text("fads")
# a grid to attach the widgets
grid = Gtk.Grid()
grid.attach(gtable.view, 0, 0, 1, 1)
grid.attach(label, 0, 1, 1, 1)
# attach the grid to the window
window.add(grid)
window.show_all()
if window:
window.connect("destroy", Gtk.main_quit)
from gi.repository import Gtk, GObject
import random
from lib_sallybn.disc_bayes_net.DiscreteBayesianNetworkExt import DiscreteBayesianNetworkExt
from lib_sallybn.disc_bayes_net.BoxDiscreteBN import BoxDiscreteBN
# Create window
window = Gtk.Window()
window.set_size_request(800, 600)
## Discrete bn
disc_bn = DiscreteBayesianNetworkExt()
# Vertex and its states
disc_bn.add_vertex("A", states=["true1", "false1"])
disc_bn.add_vertex("C", states=["true", "false"])
disc_bn.add_vertex("B", states=["true", "false"])
# Edges
disc_bn.add_edge(["A", "B"])
disc_bn.add_edge(["C", "B"])
# CPTs
cprob_b = {
"['true1', 'true']": [.3, .7],
"['true1', 'false']": [.9, .1],
"['false1', 'true']": [.05, .95],
"['false1', 'false']": [.5, .5]
}
cprob_a = [.3, .7]
cprob_c = [.2, .8]