Firsh Push at 20241207

draw_tools/draw.py

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+from matplotlib import pyplot as plt
+import seaborn as sns
+import datetime
+import matplotlib.figure as figure
+import matplotlib.backends.backend_agg as agg
+from Load_process.file_processing import Process_File
+
+def plot_history(history_value, file_name, model_name):
+    File = Process_File()
+
+    plt.figure(figsize=(16,4))
+    plt.subplot(1,2,1)
+    plt.plot(history_value.history['accuracy'])
+    plt.plot(history_value.history['val_accuracy'])
+    plt.ylabel('Accuracy')
+    plt.xlabel('epoch')
+    plt.legend(['Train','Validation'], loc='upper left')
+    plt.title('Model Accuracy')
+
+    plt.subplot(1,2,2)
+    plt.plot(history_value.history['loss'])
+    plt.plot(history_value.history['val_loss'])
+    plt.ylabel('loss')
+    plt.xlabel('epoch')
+    plt.legend(['Train','Validation'], loc='upper left')
+    plt.title('Model Loss')
+
+    model_dir = '../Result/save_the_train_image( ' + str(datetime.date.today()) + " )"
+    File.JudgeRoot_MakeDir(model_dir)
+    modelfiles = File.Make_Save_Root(str(model_name) + " " + str(file_name) + ".png", model_dir)
+    plt.savefig(modelfiles)
+    plt.close("all")      # 關閉圖表
+
+def draw_heatmap(matrix, model_name, index): # 二分類以上混淆矩陣做法
+    File = Process_File()
+
+    # 创建热图
+    fig = figure.Figure(figsize=(6, 4))
+    canvas = agg.FigureCanvasAgg(fig)
+    Ax = fig.add_subplot(111)
+    sns.heatmap(matrix, square = True, annot = True, fmt = 'd', linecolor = 'white', cmap = "Purples", ax = Ax)#画热力图，cmap表示设定的颜色集
+
+    model_dir = '../Result/model_matrix_image ( ' + str(datetime.date.today()) + " )"
+    File.JudgeRoot_MakeDir(model_dir)
+    modelfiles = File.Make_Save_Root(str(model_name) + "-" + str(index) + ".png", model_dir)
+
+    # confusion.figure.savefig(modelfiles)
+    # 设置图像参数
+    Ax.set_title(str(model_name) + " confusion matrix")
+    Ax.set_xlabel("X-Predict label of the model")
+    Ax.set_ylabel("Y-True label of the model")
+
+    # 保存图像到文件中
+    canvas.print_figure(modelfiles)
+
+def Confusion_Matrix_of_Two_Classification(Model_Name, Matrix, index):
+    File = Process_File()
+
+    fx = sns.heatmap(Matrix, annot=True, cmap='turbo')
+
+    # labels the title and x, y axis of plot
+    fx.set_title('Plotting Confusion Matrix using Seaborn\n\n')
+    fx.set_xlabel('answer Values ')
+    fx.set_ylabel('Predicted Values')
+
+    # labels the boxes
+    fx.xaxis.set_ticklabels(['False','True'])
+    fx.yaxis.set_ticklabels(['False','True'])
+
+    model_dir = '../Result/model_matrix_image ( ' + str(datetime.date.today()) + " )"
+    File.JudgeRoot_MakeDir(model_dir)
+    modelfiles = File.Make_Save_Root(str(Model_Name) + "-" + str(index) + ".png", model_dir)
+
+    plt.savefig(modelfiles)
+    plt.close("all")      # 關閉圖表
+
+    pass