Old engine for Continuous Time Bayesian Networks. Superseded by reCTBN. 🐍
https://github.com/madlabunimib/PyCTBN
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36 lines
1.6 KiB
36 lines
1.6 KiB
import set_of_cims as socim
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import numpy as np
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class AmalgamatedCims:
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"""
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Aggrega un insieme di oggetti SetOfCims indicizzandoli a partire dal node_id della variabile:
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{X:SetofCimsX, Y:SetOfCimsY.......}
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"""
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# list_of_vars_orders contiene tutte le liste con i parent ordinati secondo il valore indx
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def __init__(self, states_number_per_node, list_of_keys, list_of_parents_states_number):
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self.sets_of_cims = []
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self.init_cims_structure(list_of_keys, states_number_per_node, list_of_parents_states_number)
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#self.states_per_variable = states_number
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def init_cims_structure(self, keys, states_number_per_node, list_of_parents_states_number):
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#print(keys)
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#print(list_of_parents_states_number)
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for indx, key in enumerate(keys):
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self.sets_of_cims.append(
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socim.SetOfCims(key, list_of_parents_states_number[indx], states_number_per_node[indx]))
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def get_set_of_cims(self, node_id):
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return self.sets_of_cims[node_id]
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def get_cims_of_node(self, node_indx, cim_indx):
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return self.sets_of_cims[node_indx].get_cim(cim_indx)
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def get_vars_order(self, node):
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return self.actual_cims[node][1]
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def update_state_transition_for_matrix(self, node, which_matrix, element_indx):
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self.sets_of_cims[node].update_state_transition(which_matrix, element_indx)
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def update_state_residence_time_for_matrix(self, which_node, which_matrix, which_element, time):
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self.sets_of_cims[which_node].update_state_residence_time(which_matrix, which_element, time)
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