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import pysmile

 

# Tutorial6 creates a dynamic Bayesian network (DBN),

# performs the inference, then saves the model to disk.

 

class Tutorial6:

    def __init__(self):

        print("Starting Tutorial6...")

        net = pysmile.Network()

        loc = self.create_cpt_node(net,

              "Location", "Location",

              ["Pittsburgh", "Sahara"],

              160, 360)

        rain = self.create_cpt_node(net, 

               "Rain", "Rain", 

               ["true", "false"],

               380, 240)

        umb = self.create_cpt_node(net,

              "Umbrella", "Umbrella",

              ["true", "false"],

              300, 100)

        

        net.set_node_temporal_type(rain, pysmile.NodeTemporalType.PLATE)

        net.set_node_temporal_type(umb, pysmile.NodeTemporalType.PLATE)

 

        net.add_arc(loc, rain)

        net.add_temporal_arc(rain, rain, 1)

        net.add_arc(rain, umb)

 

        rain_def = [

            0.7,  # P(Rain=true |Location=Pittsburgh)

            0.3,  # P(Rain=false|Location=Pittsburgh)

            0.01, # P(Rain=true |Location=Sahara)

            0.99  # P(Rain=false|Location=Sahara)

        ]

 

        net.set_node_definition(rain, rain_def)

 

        rain_def_temporal = [

            0.7,   # P(Rain=true |Location=Pittsburgh,Rain[t-1]=true)

            0.3,   # P(Rain=false|Location=Pittsburgh,Rain[t-1]=true)

            0.3,   # P(Rain=true |Location=Pittsburgh,Rain[t-1]=false)

            0.7,   # P(Rain=false|Location=Pittsburgh,Rain[t-1]=false)

            0.001, # P(Rain=true |Location=Sahara,Rain[t-1]=true)

            0.999, # P(Rain=false|Location=Sahara,Rain[t-1]=true)

            0.01,  # P(Rain=true |Location=Sahara,Rain[t-1]=false)

            0.99   # P(Rain=false|Location=Sahara,Rain[t-1]=false)

        ]

        net.set_node_temporal_definition(rain, 1, rain_def_temporal)

 

        umb_def = [

            0.9, # P(Umbrella=true |Rain=true)

            0.1, # P(Umbrella=false|Rain=true)

            0.2, # P(Umbrella=true |Rain=false)

            0.8  # P(Umbrella=false|Rain=false)

        ]

        net.set_node_definition(umb, umb_def)

 

        net.set_slice_count(5)

 

        print("Performing update without evidence.")

        self.update_and_show_temporal_results(net)

 

        print("Setting Umbrella[t=1], to true and Umbrella[t=3] to false.")

        net.set_temporal_evidence(umb, 1, 0)

        net.set_temporal_evidence(umb, 3, 1)

        self.update_and_show_temporal_results(net)

 

        net.write_file("tutorial6.xdsl")

        print("Tutorial6 complete: Network written to tutorial6.xsdl")

 

 

    def update_and_show_temporal_results(self, net):

        net.update_beliefs()

        slice_count = net.get_slice_count()

        for h in net.get_all_nodes():

            if net.get_node_temporal_type(h) == pysmile.NodeTemporalType.PLATE:

                outcome_count = net.get_outcome_count(h)

                print("Temporal beliefs for " + net.get_node_id(h) + ":")

                v = net.get_node_value(h)

                for slice_idx in range(0, slice_count):

                    s = "\tt=" + str(slice_idx) + ":"

                    for i in range(0, outcome_count):

                        s = s + " " + str(v[slice_idx * outcome_count + i])

                    print(s)

        print("")

 

 

    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