import os

from line_profiler import LineProfiler

import numba as nb
import numpy as np
import network_graph as ng
import sample_path as sp
import sets_of_cims_container as acims


class ParametersEstimator:

    def __init__(self, sample_path, net_graph):
        self.sample_path = sample_path
        self.net_graph = net_graph
        self.sets_of_cims_struct = None

    def init_sets_cims_container(self):
        self.sets_of_cims_struct = acims.SetsOfCimsContainer(self.net_graph.get_nodes(),
                                                             self.net_graph.get_states_number_of_all_nodes_sorted(),
                                                    self.net_graph.get_ordered_by_indx_parents_values_for_all_nodes())


    def compute_parameters(self):
        #print(self.net_graph.get_nodes())
        #print(self.amalgamated_cims_struct.sets_of_cims)
        #enumerate(zip(self.net_graph.get_nodes(), self.amalgamated_cims_struct.sets_of_cims))
        for indx, aggr in enumerate(zip(self.net_graph.get_nodes(), self.sets_of_cims_struct.sets_of_cims)):
            #print(self.net_graph.time_filtering[indx])
            #print(self.net_graph.time_scalar_indexing_strucure[indx])
            self.compute_state_res_time_for_node(self.net_graph.get_node_indx(aggr[0]), self.sample_path.trajectories.times,
                                                 self.sample_path.trajectories.trajectory,
                                                 self.net_graph.time_filtering[indx],
                                                 self.net_graph.time_scalar_indexing_strucure[indx],
                                                 aggr[1].state_residence_times)
            #print(self.net_graph.transition_filtering[indx])
            #print(self.net_graph.transition_scalar_indexing_structure[indx])
            self.compute_state_transitions_for_a_node(self.net_graph.get_node_indx(aggr[0]),
                                                      self.sample_path.trajectories.complete_trajectory,
                                                      self.net_graph.transition_filtering[indx],
                                                      self.net_graph.transition_scalar_indexing_structure[indx],
                                                      aggr[1].transition_matrices)
            aggr[1].build_cims(aggr[1].state_residence_times, aggr[1].transition_matrices)

    def compute_parameters_for_node(self, node_id):
        pos_index = self.net_graph.graph_struct.get_positional_node_indx(node_id)
        node_indx = self.net_graph.get_node_indx(node_id)
        #print("Nodes", self.net_graph.get_nodes())
        self.compute_state_res_time_for_node(node_indx, self.sample_path.trajectories.times,
                                             self.sample_path.trajectories.trajectory,
                                             self.net_graph.time_filtering[pos_index],
                                             self.net_graph.time_scalar_indexing_strucure[pos_index],
                                             self.sets_of_cims_struct.sets_of_cims[pos_index].state_residence_times)
        # print(self.net_graph.transition_filtering[indx])
        # print(self.net_graph.transition_scalar_indexing_structure[indx])
        self.compute_state_transitions_for_a_node(node_indx,
                                                  self.sample_path.trajectories.complete_trajectory,
                                                  self.net_graph.transition_filtering[pos_index],
                                                  self.net_graph.transition_scalar_indexing_structure[pos_index],
                                                  self.sets_of_cims_struct.sets_of_cims[pos_index].transition_matrices)
        self.sets_of_cims_struct.sets_of_cims[pos_index].build_cims(
            self.sets_of_cims_struct.sets_of_cims[pos_index].state_residence_times,
            self.sets_of_cims_struct.sets_of_cims[pos_index].transition_matrices)


    def compute_state_res_time_for_node(self, node_indx, times, trajectory, cols_filter, scalar_indexes_struct, T):
        #print(times.size)
        #print(trajectory)
        #print(cols_filter)
        #print(scalar_indexes_struct)
        #print(T)
        T[:] = np.bincount(np.sum(trajectory[:, cols_filter] * scalar_indexes_struct / scalar_indexes_struct[0], axis=1)
                           .astype(np.int), \
                           times,
                           minlength=scalar_indexes_struct[-1]).reshape(-1, T.shape[1])
        #print("Done This NODE", T)

    def compute_state_residence_time_for_all_nodes(self):
        for node_indx, set_of_cims in enumerate(self.amalgamated_cims_struct.sets_of_cims):
            self.compute_state_res_time_for_node(node_indx, self.sample_path.trajectories[0].get_times(),
                self.sample_path.trajectories[0].get_trajectory(), self.columns_filtering_structure[node_indx],
                    self.scalar_indexes_converter[node_indx], set_of_cims.state_residence_times)


    def compute_state_transitions_for_a_node(self, node_indx, trajectory, cols_filter, scalar_indexing, M):
        #print(node_indx)
        #print(trajectory)
        #print(cols_filter)
        #print(scalar_indexing)
        #print(M)
        diag_indices = np.array([x * M.shape[1] + x % M.shape[1] for x in range(M.shape[0] * M.shape[1])],
                                dtype=np.int64)
        trj_tmp = trajectory[trajectory[:, int(trajectory.shape[1] / 2) + node_indx].astype(np.int) >= 0]
        #print(trj_tmp)
        #print("Summing", np.sum(trj_tmp[:, cols_filter] * scalar_indexing / scalar_indexing[0], axis=1).astype(np.int))
        #print(M.shape[1])
        #print(M.shape[2])

        M[:] = np.bincount(np.sum(trj_tmp[:, cols_filter] * scalar_indexing / scalar_indexing[0], axis=1).astype(np.int),
                           minlength=scalar_indexing[-1]).reshape(-1, M.shape[1], M.shape[2])
        M_raveled = M.ravel()
        M_raveled[diag_indices] = 0
        #print(M_raveled)
        M_raveled[diag_indices] = np.sum(M, axis=2).ravel()
        #print(M_raveled)

        #print(M)

    def compute_state_transitions_for_all_nodes(self):
        for node_indx, set_of_cims in enumerate(self.amalgamated_cims_struct.sets_of_cims):
            self.compute_state_transitions_for_a_node(node_indx, self.sample_path.trajectories[0].get_complete_trajectory(),
                 self.transition_filtering[node_indx],
                    self.transition_scalar_index_converter[node_indx], set_of_cims.transition_matrices)