import os import time as tm import network_graph as ng import sample_path as sp import amalgamated_cims as acims class ParametersEstimator: def __init__(self, sample_path, net_graph): self.sample_path = sample_path self.net_graph = net_graph self.fancy_indexing_structure = self.net_graph.build_fancy_indexing_structure(1) self.amalgamated_cims_struct = None def init_amalgamated_cims_struct(self): self.amalgamated_cims_struct = acims.AmalgamatedCims(self.net_graph.get_states_number_of_all_nodes_sorted(), self.net_graph.get_nodes(), self.net_graph.get_ordered_by_indx_parents_values_for_all_nodes()) def parameters_estimation(self): print("Starting computing") t0 = tm.time() for indx, trajectory in enumerate(self.sample_path.trajectories): self.parameters_estimation_single_trajectory(trajectory.get_trajectory()) #print("Finished Trajectory number", indx) t1 = tm.time() - t0 print("Elapsed Time ", t1) def parameters_estimation_single_trajectory(self, trajectory): row_length = trajectory.shape[1] for indx, row in enumerate(trajectory): if trajectory[indx][1] == -1: break if trajectory[indx + 1][1] != -1: transition = self.find_transition(trajectory[indx], trajectory[indx + 1], row_length) which_node = transition[0] # print(which_node) which_matrix = self.which_matrix_to_update(row, transition[0]) which_element = transition[1] self.amalgamated_cims_struct.update_state_transition_for_matrix(which_node, which_matrix, which_element) #changed_node = which_node time = self.compute_time_delta(trajectory[indx], trajectory[indx + 1]) which_element = transition[1][0] self.amalgamated_cims_struct.update_state_residence_time_for_matrix(which_node, which_matrix, which_element, time) for node_indx in range(0, 3): if node_indx != transition[0]: # print(node) which_node = node_indx which_matrix = self.which_matrix_to_update(row, node_indx) which_element = row[node_indx + 1] self.amalgamated_cims_struct.update_state_residence_time_for_matrix( which_node, which_matrix, which_element, time) def find_transition(self, current_row, next_row, row_length): for indx in range(1, row_length): if current_row[indx] != next_row[indx]: return [indx - 1, (current_row[indx], next_row[indx])] def compute_time_delta(self, current_row, next_row): return next_row[0] - current_row[0] def which_matrix_to_update(self, current_row, node_indx): # produce strutture {'X':1, 'Y':2} dove X e Y sono i parent di node_id return current_row[self.fancy_indexing_structure[node_indx]] # Simple Test # os.getcwd() os.chdir('..') path = os.getcwd() + '/data' s1 = sp.SamplePath(path) s1.build_trajectories() s1.build_structure() g1 = ng.NetworkGraph(s1.structure) g1.init_graph() pe = ParametersEstimator(s1, g1) pe.init_amalgamated_cims_struct() print(pe.amalgamated_cims_struct.get_set_of_cims(0).get_cims_number()) print(pe.amalgamated_cims_struct.get_set_of_cims(1).get_cims_number()) print(pe.amalgamated_cims_struct.get_set_of_cims(2).get_cims_number()) #pe.parameters_estimation_single_trajectory(pe.sample_path.trajectories[0].get_trajectory()) pe.parameters_estimation() for matrix in pe.amalgamated_cims_struct.get_set_of_cims(1).actual_cims: print(matrix.state_residence_times) print(matrix.state_transition_matrix) matrix.compute_cim_coefficients() print(matrix.cim)