feat: add new class DL_data_handler and make sample func

Handle_emg_data.py

@@ -458,6 +458,32 @@ class CSV_handler:
         else
 '''
 
+class DL_data_handler:
+
+    def __init__(self) -> None:
+        pass
+
+    def make_subj_sample(tot_emgs_list):
+        starting_point:DataFrame = tot_emgs_list[0].rename(columns={'emg1':'emg'})
+        print(starting_point)
+
+        result:DataFrame = None
+
+        left_nr_remaining = len(tot_emgs_list) - 1
+        for i in range(left_nr_remaining):
+            i += 1
+            emg_str = get_emg_str(i)
+            tot_emgs_list[i].rename(columns={emg_str: 'emg'}, inplace=True)
+            result = starting_point.append(tot_emgs_list[i])
+        return result
+    
+    def get_emg_list(csv_handler:CSV_handler, subject_nr, session_nr, split) -> list:
+
+        
+        return None
+
+
+
 # HELP FUNCTIONS: ------------------------------------------------------------------------: 
 
 # Help: gets the str from emg nr

Present_data.py

@@ -8,8 +8,10 @@ from matplotlib import cm
 import matplotlib.ticker as ticker
 
 # Global variables for MFCC
-mfcc_stepsize = 0.5
-mfcc_windowsize = 2
+mfcc_stepsize = 0.5     # Seconds
+mfcc_windowsize = 2     # Seconds
+nr_coefficients = 13    # Number of coefficients
+nr_mel_filters = 40     # Number of mel-filter-bins 
 
 
 # PLOT FUNCTIONS --------------------------------------------------------------: 
@@ -139,10 +141,10 @@ def denoice_dataset(handler:Handler.CSV_handler, subject_nr, which_arm, round, e
 
 # Slightly modified mfcc with inputs like below.
 # Returns N (x_values from original df) and mfcc_y_values 
-def mfcc_custom(df:DataFrame, samplesize, windowsize, stepsize):
+def mfcc_custom(df:DataFrame, samplesize, windowsize, stepsize, nr_coefficients, nr_mel_filters):
     N = get_xory_from_df('x', df)
     y = get_xory_from_df('y', df)
-    return N, base.mfcc(y, samplesize, windowsize, stepsize)
+    return N, base.mfcc(y, samplesize, windowsize, stepsize, nr_coefficients, nr_mel_filters)
 
 
 # CASE FUNTIONS ----------------------------------------------------------------: 
@@ -232,9 +234,10 @@ def main():
 
     csv_handler = CSV_handler()
     load_data(csv_handler, 'soft')
-    #mfcc_3_plots_1_1_2(csv_handler)
-    #mfcc_3_plots_3_3_4(csv_handler)
-    mfcc_all_emg_plots(csv_handler)
+    df, samplerate = get_data(csv_handler, 1, 'left', 1, 1)
+    mfcc_data = mfcc_custom(df, samplerate, mfcc_windowsize, mfcc_stepsize)
+
+    print(np.array(mfcc_data).shape)
     
 
 main()