Merging traje but keep type of columns

main_package/classes/conditional_intensity_matrix.py

@@ -15,6 +15,7 @@ class ConditionalIntensityMatrix:
 
     def update_state_residence_time_for_state(self, state, time):
         #print("Time updating In state", state, time)
+        #print(state)
         self.state_residence_times[state] = self.state_residence_times[state] + time
 
     def compute_cim_coefficients(self):

main_package/classes/json_importer.py

@@ -96,8 +96,8 @@ class JsonImporter(AbstractImporter):
         for col_name in columns_header:
             if col_name == 'Time':
                 sample_frame[col_name + 'Delta'] = sample_frame[col_name].diff()
-            else:
+            #else:
-                sample_frame[col_name + 'Delta'] = (sample_frame[col_name].diff().bfill() != 0).astype(int)
+                #sample_frame[col_name + 'Delta'] = (sample_frame[col_name].diff().bfill() != 0).astype(int)
         #sample_frame['Delta'] = sample_frame['Time'].diff()
         #print(sample_frame)
 
@@ -134,9 +134,10 @@ class JsonImporter(AbstractImporter):
          """
         for indx in range(len(self.df_samples_list)):
             self.df_samples_list[indx] = self.df_samples_list[indx].iloc[0:0]
+        self.concatenated_samples = self.concatenated_samples.iloc[0:0]
 
 
-ij = JsonImporter("../data")
+"""ij = JsonImporter("../data")
 ij.import_data()
 #print(ij.df_samples_list[7])
 print(ij.df_structure)
@@ -144,4 +145,4 @@ print(ij.df_variables)
 #print((ij.build_list_of_samples_array(0)[1].size))
 #ij.compute_row_delta_sigle_samples_frame(ij.df_samples_list[0])
 ij.compute_row_delta_in_all_samples_frames()
-print(ij.concatenated_samples.to_numpy())
+print(ij.concatenated_samples.to_numpy())"""

main_package/classes/parameters_estimator.py

@@ -1,6 +1,7 @@
 import os
 import time as tm
 from line_profiler import LineProfiler
+import numpy as np
 
 import network_graph as ng
 import sample_path as sp
@@ -30,12 +31,18 @@ class ParametersEstimator:
         #print("Elapsed Time ", t1)
 
     def parameters_estimation_single_trajectory(self, trajectory):
+        tr_len = trajectory.shape[0]
+        row_length = trajectory.shape[1]
+        print(tr_len)
+        print(row_length)
         t0 = tm.time()
         for indx, row in enumerate(trajectory):
-            if trajectory[indx][1] == -1:
+           """ #if int(trajectory[indx][1]) == -1:
+                #break
+            if indx == tr_len - 2:
                 break
             if trajectory[indx + 1][1] != -1:
-                transition = self.find_transition(trajectory[indx], trajectory[indx + 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])
@@ -43,7 +50,9 @@ class ParametersEstimator:
                 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])
+            if int(trajectory[indx][0]) == 0:
+                time = trajectory[indx + 1][0]
+            #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)
@@ -53,20 +62,19 @@ class ParametersEstimator:
                     # print(node)
                     which_node = node_indx
                     which_matrix = self.which_matrix_to_update(row, node_indx)
-                    which_element = row[node_indx + 1]
+                    which_element = int(row[node_indx + 1])
                     # print("State res time element " + str(which_element) + node)
                     # print("State res time matrix indx" + str(which_matrix))
                     self.amalgamated_cims_struct.update_state_residence_time_for_matrix(which_node, which_matrix,
                                                                                         which_element, time)
         t1 = tm.time() - t0
-        print("Elapsed Time ", t1)
+        print("Elapsed Time ", t1)"""
 
-    def find_transition(self, current_row, next_row):
+    def find_transition(self, current_row, next_row, row_length):
-        for indx in range(1, len(current_row)):
+        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]
 
@@ -97,7 +105,7 @@ 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())
 lp = LineProfiler()
 lp_wrapper = lp(pe.parameters_estimation_single_trajectory)
-lp_wrapper(pe.sample_path.trajectories[0].get_trajectory())
+lp_wrapper(pe.sample_path.trajectories.get_trajectory())
 lp.print_stats()
 #pe.parameters_estimation()
 """for matrix in pe.amalgamated_cims_struct.get_set_of_cims(1).actual_cims:

main_package/classes/sample_path.py

@@ -21,14 +21,16 @@ class SamplePath:
     def __init__(self, files_path):
         print()
         self.importer = imp.JsonImporter(files_path)
-        self.trajectories = []
+        self.trajectories = None
         self.structure = None
 
     def build_trajectories(self):
         self.importer.import_data()
-        for traj_data_frame in self.importer.df_samples_list:
+        self.importer.compute_row_delta_in_all_samples_frames()
-            trajectory = tr.Trajectory(self.importer.build_list_of_samples_array(traj_data_frame))
+        #self.trajectories = self.importer.concatenated_samples.to_numpy()
-            self.trajectories.append(trajectory)
+        #for traj_data_frame in self.importer.df_samples_list:
+        self.trajectories = tr.Trajectory(self.importer.build_list_of_samples_array(self.importer.concatenated_samples))
+            #self.trajectories.append(trajectory)
         self.importer.clear_data_frames()
 
     def build_structure(self):
@@ -38,4 +40,11 @@ class SamplePath:
         return len(self.trajectories)
 
 
+"""os.getcwd()
+os.chdir('..')
+path = os.getcwd() + '/data'
 
+s1 = SamplePath(path)
+s1.build_trajectories()
+s1.build_structure()
+print(s1.trajectories.get_trajectory())"""