Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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50 lines
1.8 KiB
50 lines
1.8 KiB
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class Structure:
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"""
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Contiene tutte il informazioni sulla struttura della rete (connessione dei nodi, valori assumibili dalle variabili)
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:structure_frame: il dataframe contenente le connessioni dei nodi della rete
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:variables_frame: il data_frame contenente i valori assumibili dalle variabili e si suppone il corretto ordinamento
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rispetto alle colonne del dataset
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"""
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def __init__(self, structure, variables):
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self.structure_frame = structure
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self.variables_frame = variables
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self.name_label = variables.columns.values[0]
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self.value_label = variables.columns.values[1]
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def list_of_edges(self):
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#edges_list = []
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#for indx, row in self.structure_frame.iterrows():
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#row_tuple = (row[0], row[1])
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#edges_list.append(row_tuple)
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records = self.structure_frame.to_records(index=False)
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edges_list = list(records)
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return edges_list
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def list_of_nodes_labels(self):
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return self.variables_frame[self.name_label].values.tolist()
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def list_of_nodes_indexes(self):
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nodes_indexes = []
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for indx in self.list_of_nodes_labels():
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nodes_indexes.append(indx)
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return nodes_indexes
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def get_node_id(self, node_indx):
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return self.variables_frame[self.name_label][node_indx]
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def get_node_indx(self, node_id):
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return list(self.variables_frame[self.name_label]).index(node_id)
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def get_states_number(self, node):
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return self.variables_frame[self.value_label][self.get_node_indx(node)]
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def get_states_number_by_indx(self, node_indx):
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#print(self.value_label)
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return self.variables_frame[self.value_label][node_indx]
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def __repr__(self):
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return "Variables:\n" + str(self.variables_frame) + "\nEdges: \n" + str(self.structure_frame)
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