Firsh Push at 20241207

claculate_output_data.py

@@ -0,0 +1,85 @@
+import csv
+import numpy as np
+
+judge = input("是否需要移動? (Y/N)")
+
+if judge == 'y' or judge == 'Y':
+    times = int(input("輸入要移動幾天: "))
+
+    for i in range(times):
+        date = input("輸入被移動的日期: ")
+        dateroot = "../Model_training_result/save_the_train_result(2024-" + date + ")/train_result.csv"
+        quantity_data = int(input("輸入要取出的資料筆數: "))
+
+        next_date = input("移動到哪一天? ")
+
+        with open(dateroot, "r", newline = '') as csvFile:
+            data = csv.reader(csvFile)
+            data = list(data)
+
+            with open("../Model_training_result/save_the_train_result(2024-" + next_date + ")/train_result.csv", "a+", newline = '') as csvFile1:
+                writer = csv.writer(csvFile1)
+                for i in range((quantity_data * 2 + 1) * -1 + 1, 0, 1):
+                    writer.writerow(data[i])
+                print("Data has been moved finish\n")
+
+
+
+date = input("輸入計算的日期: ")
+with open("../Model_training_result/save_the_train_result(2024-" + date + ")/train_result.csv", newline = '') as csvfile:
+    rows = csv.reader(csvfile)
+
+    row = list(rows)
+
+    calcalate_loss = 0
+    calculate_precision = 0
+    calculate_recall = 0
+    calculate_accuracy = 0
+    calculate_f = 0
+    calculate_auc = 0
+
+    list_loss = []
+    list_precision = []
+    list_recall = []
+    list_accuracy = []
+    list_f = []
+    list_auc = []
+    
+    for i in range(-1, -10, -2):
+        calcalate_loss += float(row[i][2])
+        list_loss.append(float(row[i][2]))
+
+        precision = str(row[i][3]).split("%")
+        calculate_precision += float(precision[0])
+        list_precision.append(float(precision[0]))
+        
+
+        recall = str(row[i][4]).split("%")
+        calculate_recall += float(recall[0])
+        list_recall.append(float(recall[0]))
+
+        accuracy = str(row[i][5]).split("%")
+        calculate_accuracy += float(accuracy[0])
+        list_accuracy.append(float(accuracy[0]))
+
+        f = str(row[i][6]).split("%")
+        calculate_f += float(f[0])
+        list_f.append(float(f[0]))
+
+        auc = str(row[i][7]).split("%")
+        calculate_auc += float(auc[0])
+        list_auc.append(float(auc[0]))
+
+calculate_list = [calcalate_loss, calculate_precision, calculate_recall, calculate_accuracy, calculate_f, calculate_auc]
+average = []
+for i in range(len(calculate_list)):
+    average.append((calculate_list[i] / 5))
+
+std_list = [list_precision, list_recall, list_accuracy, list_f, list_auc]
+standard = []
+standard.append(np.std(list_loss))
+for i in range(len(std_list)):
+    standard.append((np.std(std_list[i]) / 100))
+
+for i in range(len(average)):
+    print("{:.2f}±{:.3f}".format(average[i], standard[i]))