import numpy as np import conditional_intensity_matrix as cim class SetOfCims: """ Rappresenta la struttura che aggrega tutte le CIM per la variabile di label node_id :node_id: la label della varibile a cui fanno riferimento le CIM :ordered_parent_set: il set dei parent della variabile node_id ordinata secondo la property indx :value: il numero massimo di stati assumibili dalla variabile :actual_cims: le CIM della varibile """ def __init__(self, node_id, parents_states_number, node_states_number): self.node_id = node_id self.parents_states_number = parents_states_number self.node_states_number = node_states_number self.actual_cims = None self.build_actual_cims_structure() def build_actual_cims_structure(self): cims_number = 1 for state_number in self.parents_states_number: cims_number = cims_number * state_number self.actual_cims = np.empty(cims_number, dtype=cim.ConditionalIntensityMatrix) for indx, matrix in enumerate(self.actual_cims): self.actual_cims[indx] = cim.ConditionalIntensityMatrix(self.node_states_number) def update_state_transition(self, indexes, element_indx_tuple): matrix_indx = self.indexes_converter(indexes) self.actual_cims[matrix_indx].update_state_transition_count(element_indx_tuple) def update_state_residence_time(self, which_matrix, which_element, time): matrix_indx = self.indexes_converter(which_matrix) self.actual_cims[matrix_indx].update_state_residence_time_for_state(which_element, time) def get_cims_number(self): return len(self.actual_cims) def indexes_converter(self, indexes): # Si aspetta array del tipo [2,2] dove #print(type(indexes)) if indexes.size == 0: return 0 else: vector_index = 0 for indx, value in enumerate(indexes): vector_index = vector_index*self.parents_states_number[indx] + indexes[indx] return vector_index """ sofc = SetOfCims('W', [], 2) sofc.build_actual_cims_structure() print(sofc.actual_cims) print(sofc.indexes_converter([]))"""