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