Fix Excel File Bug - Save Total Excel Results

src/result/analyseExcel.py

+import os
+import openpyxl
+
+
+def swap_excel_cols(folder_path):
+    # Iteriere durch alle Excel-Dateien im Ordner
+    for filename in os.listdir(folder_path):
+        if filename.endswith(".xlsx"):
+            file_path = os.path.join(folder_path, filename)
+            swap_file_cols(file_path)
+
+
+def swap_file_cols(file_path):
+    # Lade das Workbook
+    wb = openpyxl.load_workbook(file_path)
+
+    # Wähle das erste Blatt aus
+    ws = wb.worksheets[0]
+
+    # Definiert die Zeilen, in denen die Spalten getauscht werden sollen
+    rows = [19, 42, 65, 88, 111, 134, 140]
+
+    # Tausche die Spalten in jeder Zeile
+    for row in rows:
+        col_d = ws.cell(row=row + 1, column=4).value
+        col_e = ws.cell(row=row + 1, column=5).value
+        ws.cell(row=row + 1, column=4).value = col_e
+        ws.cell(row=row + 1, column=5).value = col_d
+
+    # Speichere das Workbook
+    wb.save(file_path)
+
+
+def read_metrics(path):
+    # Save unique values of opt and act in a dictionary
+    unique_opt = dict()
+    unique_act = dict()
+    final_matrix_loss = dict()
+    final_matrix_accuracy = dict()
+    final_matrix_recall_oos = dict()
+    final_matrix_recall_not_oos = dict()
+    final_matrix_duration = dict()
+
+    for file in os.listdir(path):
+        if file.endswith(".xlsx"):
+            filename = os.path.join(path, file)
+            wb = openpyxl.load_workbook(filename)
+            sheet = wb.active
+
+            # Split file name and get opt, act2, and act_128
+            opt, act2, act_128 = file.split("_")[0], file.split("_")[1], file.split("_")[2]
+
+            # Combine act2 and act_128
+            act = act2 + " " + act_128
+
+            # Get metrics
+            loss = sheet["B141"].value
+            accuracy = sheet["C141"].value
+            recall_oos = sheet["D141"].value
+            recall_not_oos = sheet["E141"].value
+            duration = sheet["F141"].value
+            duration, _ = duration.split(".")
+
+            # Add opt and act to the final matrix
+            if opt not in unique_opt:
+                count_opt = len(unique_opt) + 2
+                unique_opt[opt] = count_opt
+
+            if act not in unique_act:
+                count_act = len(unique_act) + 2
+                unique_act[act] = count_act
+
+            # Write accuracy to the final matrix
+            final_matrix_loss[opt + act] = loss
+            final_matrix_accuracy[opt + act] = accuracy
+            final_matrix_recall_oos[opt + act] = recall_oos
+            final_matrix_recall_not_oos[opt + act] = recall_not_oos
+            final_matrix_duration[opt + act] = duration
+
+    create_metriken_matrix(unique_opt, unique_act,
+                           final_matrix_loss, final_matrix_accuracy, final_matrix_recall_oos,
+                           final_matrix_recall_not_oos, final_matrix_duration)
+
+
+def create_metriken_matrix(
+        unique_opt, unique_act, final_matrix_loss, final_matrix_accuracy,
+        final_matrix_recall_oos, final_matrix_recall_not_oos, final_matrix_duration):
+    # Create a new Excel workbook and write the final matrix
+    wb = openpyxl.Workbook()
+    sheet = wb.active
+    sheet = write_matrix_in_excel(sheet, unique_opt, unique_act, final_matrix_loss, 0)
+    sheet = write_matrix_in_excel(sheet, unique_opt, unique_act, final_matrix_accuracy, 6)
+    sheet = write_matrix_in_excel(sheet, unique_opt, unique_act, final_matrix_recall_oos, 12)
+    sheet = write_matrix_in_excel(sheet, unique_opt, unique_act, final_matrix_recall_not_oos, 18)
+    sheet = write_matrix_in_excel(sheet, unique_opt, unique_act, final_matrix_duration, 24)
+    wb.save("evaluation_oos_erkennung.xlsx")
+
+
+def write_matrix_in_excel(sheet, unique_opt, unique_act, final_matrix, c):
+
+    sheet.cell(row=1, column=c+1, value="2")
+    sheet.cell(row=1, column=c+2, value="128")
+
+    # Write opt names
+    count_opt = 3
+    for opt_key in sorted(unique_opt.keys()):
+        sheet.cell(row=1, column=c+count_opt, value=opt_key)
+        count_opt += 1
+
+    # Write act names
+    count_act = 2
+    for act_key in sorted(unique_act.keys()):
+        act_2, act128 = act_key.split(" ")
+        sheet.cell(row=count_act, column=c+1, value=act_2)
+        sheet.cell(row=count_act, column=c+2, value=act128)
+        count_act += 1
+
+    count_opt = 3
+    # Write accuracy values
+    for opt_key in sorted(unique_opt.keys()):
+        count_act = 2
+        for act_key in sorted(unique_act.keys()):
+            if opt_key + act_key in final_matrix:
+                sheet.cell(row=count_act, column=c+count_opt, value=final_matrix[opt_key + act_key])
+            count_act += 1
+        count_opt += 1
+    return sheet
+
+
+# Call the function with the folder path
+# swap_excel_cols("/Users/dwillers/Programmierung/Master/Okan-Server/Results Kopie/5050")
+# swap_file_cols("/Users/dwillers/Programmierung/Master/Okan-Server/Results Kopie/5050/Ftrl_softmax_softmax_03_02_23__03_19.xlsx")
+# read_metrics("/Users/dwillers/Programmierung/Master/Okan-Server/Results Kopie/5050")

src/result/createExcelFile.py

@@ -73,8 +73,8 @@ def create_excel_result(worksheet, r, callback, config, config_knn, evaluate_met
     worksheet.cell(row=r, column=1).value = config_knn.excluded_folder.name
     worksheet.cell(row=r, column=2).value = evaluate_metrics[0]
     worksheet.cell(row=r, column=3).value = evaluate_metrics[1]
-    worksheet.cell(row=r, column=4).value = evaluate_metrics[2]
-    worksheet.cell(row=r, column=5).value = evaluate_metrics[3]
+    worksheet.cell(row=r, column=4).value = evaluate_metrics[3]
+    worksheet.cell(row=r, column=5).value = evaluate_metrics[2]
     r = r + 4
     return worksheet, r
 
@@ -98,8 +98,8 @@ def average_evaluate_cross_validation(worksheet, r, model_evaluate_metrics, trai
     worksheet.cell(row=r, column=1).value = len(training_duration_models)
     worksheet.cell(row=r, column=2).value = total_information[0]
     worksheet.cell(row=r, column=3).value = total_information[1]
-    worksheet.cell(row=r, column=4).value = total_information[2]
-    worksheet.cell(row=r, column=5).value = total_information[3]
+    worksheet.cell(row=r, column=4).value = total_information[3]
+    worksheet.cell(row=r, column=5).value = total_information[2]
     # Durchschnittswert wieder in Datetime-Objekt umwandeln
     average_datetime = format(total_information[4])
     worksheet.cell(row=r, column=6).value = average_datetime