Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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68 lines
2.4 KiB
68 lines
2.4 KiB
4 years ago
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import numpy as np
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import sample_path as sp
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import node
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class DynamicGraph():
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def __init__(self, sample_path):
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self.sample_path = sample_path
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self.graph = {}
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self.states_number = 0
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def initialize_graph(self, trajectory):
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for(node_id,state) in enumerate(trajectory.get_states()):
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n = node.Node(state, node_id)
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self.graph[state] = {"Arcs":{}, "Time":0.0, "Node":n}
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self.states_number += 1
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def build_graph_from_first_traj(self, trajectory):
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self.initialize_graph(trajectory)
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matrix_traj = trajectory.get_trajectory_as_matrix()
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for indx in range(len(matrix_traj) - 1):
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self.add_transaction(matrix_traj, indx)
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def add_transaction(self, matrix_traj, indx):
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current_state = matrix_traj[indx][1]
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next_state = matrix_traj[indx + 1][1]
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self.graph[current_state]["Time"] += matrix_traj[indx + 1][0] - matrix_traj[indx][0]
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next_node = self.graph[next_state]["Node"]
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if next_node not in self.graph[current_state]["Arcs"].keys():
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self.graph[current_state]["Arcs"][next_node] = 1
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else:
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self.graph[current_state]["Arcs"][next_node] += 1
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def append_new_trajectory(self, trajectory):
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matrix_traj = trajectory.get_trajectory_as_matrix()
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for indx in range(len(matrix_traj) - 1):
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current_state = matrix_traj[indx][1]
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next_state = matrix_traj[indx + 1][1]
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if current_state not in self.graph.keys():
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current_node = node.Node(current_state, self.states_number)
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self.graph[current_state] = {"Arcs":{}, "Time":0.0, "Node":current_node}
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self.states_number += 1
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if next_state not in self.graph.keys():
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next_node = node.Node(next_state, self.states_number)
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self.graph[next_state] = {"Arcs":{}, "Time":0.0, "Node":next_node}
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self.states_number += 1
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self.add_transaction(matrix_traj, indx)
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def build_graph(self):
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for indx, trajectory in enumerate(self.sample_path.trajectories):
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if indx == 0:
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self.build_graph_from_first_traj(trajectory)
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else:
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self.append_new_trajectory(trajectory)
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######Veloci Tests#######
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s1 = sp.SamplePath()
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s1.build_trajectories()
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print(s1.get_number_trajectories())
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g1 = DynamicGraph(s1)
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g1.build_graph()
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print(g1.graph)
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print(g1.states_number)
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