Complete Major changes in project structure

main_package/classes/dynamic_graph.py

@@ -0,0 +1,68 @@
+import numpy as np
+import sample_path as sp
+import node
+
+
+class DynamicGraph():
+
+    def __init__(self, sample_path):
+        self.sample_path = sample_path
+        self.graph = {}
+        self.states_number = 0
+
+    def initialize_graph(self, trajectory):
+        for(node_id,state) in enumerate(trajectory.get_states()):
+            n = node.Node(state, node_id)
+            self.graph[state] = {"Arcs":{}, "Time":0.0, "Node":n}
+            self.states_number += 1
+
+    
+    def build_graph_from_first_traj(self, trajectory):
+        self.initialize_graph(trajectory)
+        matrix_traj = trajectory.get_trajectory_as_matrix()
+        for indx in range(len(matrix_traj) - 1):
+            self.add_transaction(matrix_traj, indx)
+
+    def add_transaction(self, matrix_traj, indx):
+        current_state = matrix_traj[indx][1]
+        next_state = matrix_traj[indx + 1][1]
+        self.graph[current_state]["Time"] += matrix_traj[indx + 1][0] - matrix_traj[indx][0]
+        next_node = self.graph[next_state]["Node"]
+        if next_node not in self.graph[current_state]["Arcs"].keys():
+            self.graph[current_state]["Arcs"][next_node] = 1
+        else:
+            self.graph[current_state]["Arcs"][next_node] += 1
+    
+    def append_new_trajectory(self, trajectory):
+        matrix_traj = trajectory.get_trajectory_as_matrix()
+        for indx in range(len(matrix_traj) - 1):
+            current_state = matrix_traj[indx][1]
+            next_state = matrix_traj[indx + 1][1]
+            if current_state not in self.graph.keys():
+                current_node = node.Node(current_state, self.states_number)
+                self.graph[current_state] = {"Arcs":{}, "Time":0.0, "Node":current_node}
+                self.states_number += 1
+            if next_state not in self.graph.keys():
+                next_node = node.Node(next_state, self.states_number)
+                self.graph[next_state] = {"Arcs":{}, "Time":0.0, "Node":next_node}
+                self.states_number += 1
+            self.add_transaction(matrix_traj, indx)
+
+    def build_graph(self):
+        for indx, trajectory in enumerate(self.sample_path.trajectories):
+            if indx == 0:
+                self.build_graph_from_first_traj(trajectory)
+            else:
+                self.append_new_trajectory(trajectory)
+
+
+######Veloci Tests#######
+
+s1 = sp.SamplePath()
+s1.build_trajectories()
+print(s1.get_number_trajectories())
+
+g1 = DynamicGraph(s1)
+g1.build_graph()
+print(g1.graph)
+print(g1.states_number)

main_package/classes/importer.py

@@ -33,8 +33,8 @@ class Importer():
         for file in read_files:
             my_df = pd.read_csv(file) #TODO:Aggiungere try-catch controllo correttezza dei tipi di dato presenti nel dataset e.g. i tipi di dato della seconda colonna devono essere float
             self.df_list.append(my_df)
+        
 
-    
     def merge_value_columns(self, df):
         """ Effettua il merging di tutte le colonne che contengono i valori delle variabili in un unica colonna chiamata State.
 
@@ -45,6 +45,15 @@ class Importer():
         """
         df['State'] = df[df.columns[2:]].apply(lambda row: ''.join(row.values.astype(str)), axis=1)
 
+    def drop_unneccessary_columns(self, df):
+        cols = df.columns.values[2:-1]
+        print(cols)
+        df.drop(cols, axis=1, inplace=True)
+
+    def drop_unneccessary_columns_in_all_frames(self):
+        for data_frame in self.df_list:
+            self.drop_unneccessary_columns(data_frame)
+
     def merge_value_columns_in_all_frames(self):
         for data_frame in self.df_list:
             self.merge_value_columns(data_frame)
@@ -55,30 +64,9 @@ class Importer():
     def clear_data_frames(self):
         for data_frame in self.df_list:
             data_frame = data_frame.iloc[0:0]
-    
-
-    
-    
-
-
-
-
-    """def build_trajectories(self):
-        for data_frame in self.df_list:
-            self.merge_value_columns(data_frame)
-            trajectory = data_frame[['Time','State']].to_numpy()
-            self.trajectories.append(trajectory)
-            #Clear the data_frame
-            data_frame = data_frame.iloc[0:0]"""
-
-
 
 
 
-#imp = Importer("../data")
-#imp.import_data_from_csv()
-#imp.build_trajectories()
-#print(imp.trajectories[0])
 
 
 

main_package/classes/node.py

@@ -0,0 +1,21 @@
+
+
+class Node():
+
+    def __init__(self, state_id, node_id=-1):
+        self.state_id = state_id
+        self.node_id = node_id
+
+    def __key(self):
+        return (self.state_id)
+
+    def __hash__(self):
+        return hash(self.__key())
+
+    def __eq__(self, other):
+        if isinstance(other, Node):
+            return self.__key() == other.__key()
+        return NotImplemented
+
+    def __repr__(self):
+        return "<%s, %d>"% (self.state_id, self.node_id)

main_package/classes/sample_path.py

@@ -1,12 +1,13 @@
 import pandas as pd
 import numpy as np
+import os
 import importer as imp
 import trajectory as tr
 
 
 class SamplePath():
 
-    def __init__(self, files_path):
+    def __init__(self, files_path=os.getcwd() + "/main_package/data"):
         self.importer = imp.Importer(files_path)
         self.trajectories = []
 
@@ -14,6 +15,7 @@ class SamplePath():
     def build_trajectories(self):
         self.importer.import_data_from_csv()
         self.importer.merge_value_columns_in_all_frames()
+        self.importer.drop_unneccessary_columns_in_all_frames()
         for data_frame in self.importer.get_data_frames():
             trajectory = tr.Trajectory(data_frame)
             self.trajectories.append(trajectory)
@@ -26,9 +28,9 @@ class SamplePath():
 
 ######Veloci Tests#######
 
-s1 = SamplePath("../data")
+s1 = SamplePath()
 s1.build_trajectories()
 print(s1.get_number_trajectories())
-print(type(s1.trajectories[0].get_trajectory()[0][1]))
+#print(s1.trajectories[0].get_trajectory())
 
 

main_package/classes/trajectory.py

@@ -1,16 +1,17 @@
 import pandas as pd
 import numpy as np
-import importer
 
 
 class Trajectory():
 
     def __init__(self, data_frame):
-        self.actual_trajectory = self.build_trajectory(data_frame)
-
-    
-    def build_trajectory(self, data_frame):
-        return data_frame[['Time','State']].to_numpy()
-
+        self.actual_trajectory = data_frame
+        
     def get_trajectory(self):
         return self.actual_trajectory
+    
+    def get_trajectory_as_matrix(self):
+        return self.actual_trajectory[['Time','State']].to_numpy()
+
+    def get_states(self):
+        return self.actual_trajectory['State'].unique()