<< Click to Display Table of Contents >> Navigation:  Tutorials > Tutorial 1: Creating a Bayesian Network > Tutorial1.py

import pysmile

 

# Tutorial1 creates a simple network with three nodes,

# then writes its content as XDSL file to disk.

 

class Tutorial1:

    def __init__(self):

        net = pysmile.Network()

 

        e = self.create_cpt_node(net,

            "Economy", "State of the economy",

            ["Up","Flat","Down"], 

            160, 40)

        

        s = self.create_cpt_node(net,

            "Success", "Success of the venture",

            ["Success","Failure"], 

            60, 40)

        

        f = self.create_cpt_node(net,

            "Forecast", "Expert forecast",

            ["Good","Moderate","Poor"], 

            110, 140)

            

        net.add_arc(e, s)

        net.add_arc(s, f)

        

        # we can also use node identifiers when creating arcs  

        net.add_arc("Economy", "Forecast");

        

        economyDef = [

            0.2, # P(Economy=U)

            0.7, # P(Economy=F)

            0.1  # P(Economy=D)

        ]

        net.set_node_definition(e, economyDef)

        

        successDef = [

            0.3, # P(Success=S|Economy=U)

            0.7, # P(Success=F|Economy=U)

            0.2, # P(Success=S|Economy=F)

            0.8, # P(Success=F|Economy=F)

            0.1, # P(Success=S|Economy=D)

            0.9  # P(Success=F|Economy=D)

        ]

        net.set_node_definition(s, successDef)

        

        forecastDef = [

            0.70, # P(Forecast=G|Success=S,Economy=U)

            0.29, # P(Forecast=M|Success=S,Economy=U)

            0.01, # P(Forecast=P|Success=S,Economy=U)

        

            0.65, # P(Forecast=G|Success=S,Economy=F)

            0.30, # P(Forecast=M|Success=S,Economy=F)

            0.05, # P(Forecast=P|Success=S,Economy=F)

        

            0.60, # P(Forecast=G|Success=S,Economy=D)

            0.30, # P(Forecast=M|Success=S,Economy=D)

            0.10, # P(Forecast=P|Success=S,Economy=D)

        

            0.15,  # P(Forecast=G|Success=F,Economy=U)

            0.30, # P(Forecast=M|Success=F,Economy=U)

            0.55, # P(Forecast=P|Success=F,Economy=U)

        

            0.10, # P(Forecast=G|Success=F,Economy=F)

            0.30, # P(Forecast=M|Success=F,Economy=F)

            0.60, # P(Forecast=P|Success=F,Economy=F)

        

            0.05, # P(Forecast=G|Success=F,Economy=D)

            0.25, # P(Forecast=G|Success=F,Economy=D)

            0.70  # P(Forecast=G|Success=F,Economy=D)

        ]

        net.set_node_definition(f, forecastDef)

        

        net.write_file("tutorial1.xdsl")

        

        print("Tutorial1 complete: Network written to tutorial1.xdsl")

 

 

    def create_cpt_node(self, net, id, name, outcomes, x_pos, y_pos):

        handle = net.add_node(pysmile.NodeType.CPT, id)

        

        net.set_node_name(handle, name)

        net.set_node_position(handle, x_pos, y_pos, 85, 55)

        

        initial_outcome_count = net.get_outcome_count(handle)

        

        for i in range(0, initial_outcome_count):

            net.set_outcome_id(handle, i, outcomes[i])

        

        for i in range(initial_outcome_count, len(outcomes)):

            net.add_outcome(handle, outcomes[i])

            

        return handle