feat: add function for making sample signals of session_df

Handle_emg_data.py

@@ -495,26 +495,29 @@ class DL_data_handler:
         
     def get_emg_list(self, subject_nr, session_nr) -> list:
         list_of_emgs = []
-        for emg_nr in range(8):
+        df, _ = self.csv_handler.get_data(subject_nr, 'left', session_nr, 1)
-            df, _ = self.csv_handler.get_data(subject_nr, 'left', session_nr, emg_nr+1)
         list_of_emgs.append(df)
+        for emg_nr in range(7):
+            df, _ = self.csv_handler.get_data(subject_nr, 'left', session_nr, emg_nr+2)
+            list_of_emgs.append(DataFrame(df[get_emg_str(emg_nr+2)]))
         for emg_nr in range(8):
             df, _ = self.csv_handler.get_data(subject_nr, 'right', session_nr, emg_nr+1)
-            list_of_emgs.append(df)
+            list_of_emgs.append(DataFrame(df[get_emg_str(emg_nr+1)]))
-        return list_of_emgs
+        return list_of_emgs     # list of emg data where first element also has timestamp column
 
     def make_subj_sample(self, list_of_emgs):
-        starting_point:DataFrame = list_of_emgs[0].rename(columns={'emg1':'emg'})
+        # starting_point:DataFrame = list_of_emgs[0].rename(columns={'emg1':'emg'})
         tot_session_df_list = []
-        for i in range(2, 9):
+        for i in range(8):
-            emg_str = get_emg_str(i)
+            #emg_str = get_emg_str(i)
-            df = list_of_emgs[i-1].rename(columns={emg_str: 'emg'})
+            df = list_of_emgs[i]  # .rename(columns={emg_str: 'emg'})
             tot_session_df_list.append(df)
         for i in range(1, 9):
-            emg_str = get_emg_str(i)
+            emg_str_old = get_emg_str(i)
-            df = list_of_emgs[7+i].rename(columns={emg_str: 'emg'})
+            emg_str_new = get_emg_str(8+i)
+            df:DataFrame = list_of_emgs[7+i].rename(columns={emg_str_old: emg_str_new})
             tot_session_df_list.append(df)
-        tot_session_df = starting_point.append(tot_session_df_list, ignore_index=True, sort=True)
+        tot_session_df = pd.concat(tot_session_df_list, axis=1)
 
         return tot_session_df
     
@@ -523,14 +526,22 @@ class DL_data_handler:
             subj_samples = []
             for session_nr in range(4):
                 list_of_emg = self.get_emg_list(subject_nr+1, session_nr+1)
-                tot_session_df, samplerate = self.make_subj_sample(list_of_emg)
+                tot_session_df = self.make_subj_sample(list_of_emg)
-                samples = np.array_split(tot_session_df, split_nr)
+                samples = np.array_split(tot_session_df.to_numpy(), split_nr)
                 for array in samples:
-                    df = DataFrame(array)
+                    df = DataFrame(array).rename(columns={0:'timestamp'})
-                    samplerate = get_samplerate(df)
+                    df_finished, samplerate = self.reshape_session_df_to_signal(df)
-                    subj_samples.append([df, samplerate])
+                    subj_samples.append([df_finished, samplerate])
             
-            self.samples_per_subject[subject_nr] = subj_samples
+            self.samples_per_subject[subject_nr+1] = subj_samples
+    
+    def reshape_session_df_to_signal(self, df:DataFrame):
+        main_df = df[['timestamp', 1]].rename(columns={1: 'emg'})
+        for i in range(2, 17):
+            adding_df = df[['timestamp', i]].rename(columns={i: 'emg'})
+            main_df = pd.concat([main_df, adding_df], ignore_index=True)
+        samplerate = get_samplerate(main_df)
+        return main_df, samplerate
 
 
 # HELP FUNCTIONS: ------------------------------------------------------------------------: 
@@ -541,7 +552,8 @@ def get_emg_str(emg_nr):
 
 # Help: gets the min/max of a df
 def get_min_max_timestamp(df:DataFrame):
-    min = int(np.floor(df['timestamp'].min()))
+    #min = int(np.floor(df['timestamp'].min()))
+    min = df['timestamp'].min()
     max = df['timestamp'].max()
     return min, max
 

Present_data.py

@@ -100,6 +100,14 @@ def plot_all_emg_mfcc(data_list:list, label_list:list):
 
     plt.show() 
 
+def pretty(dict, indent=0):
+   for key, value in dict.items():
+      print('\t' * indent + str(key))
+      if isinstance(value, dict):
+         pretty(value, indent+1)
+      else:
+         print('\t' * (indent+1) + str(value))
+
 # DATA FUNCTIONS: --------------------------------------------------------------: 
 
 # The CSV_handler takes in data_type, but only for visuals. 
@@ -213,13 +221,15 @@ def main():
 
     csv_handler = CSV_handler()
     csv_handler.load_data('soft')
-    #print(csv_handler.get_data(1, 'left', 1, 1))
     dl_data_handler = DL_data_handler(csv_handler)
-    #dl_data_handler.store_samples(10)
+    dl_data_handler.store_samples(10)
-    #print(dl_data_handler.samples_per_subject)
+    dict = dl_data_handler.samples_per_subject
-    emg_list = dl_data_handler.get_emg_list(1, 1)
+    
-    df = dl_data_handler.make_subj_sample(emg_list)
+    test_session_df = dict.get(1)[0]
-    print(df.head)
+    print(test_session_df)
+    df, _ = dl_data_handler.reshape_session_df_to_signal(test_session_df)
+    print(df[:50])
+    
     
 
 main()