77 lines
2.8 KiB
Python
77 lines
2.8 KiB
Python
from matplotlib import pyplot as plt
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import seaborn as sns
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import datetime
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import matplotlib.figure as figure
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import matplotlib.backends.backend_agg as agg
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from Load_process.file_processing import Process_File
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def plot_history(Epochs, Losses, Accuracys, file_name, model_name):
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File = Process_File()
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plt.figure(figsize=(16,4))
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plt.subplot(1,2,1)
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plt.plot(range(1, Epochs + 1), Losses[0])
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plt.plot(range(1, Epochs + 1), Losses[1])
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plt.ylabel('Accuracy')
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plt.xlabel('epoch')
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plt.legend(['Train','Validation'], loc='upper left')
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plt.title('Model Accuracy')
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plt.subplot(1,2,2)
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plt.plot(range(1, Epochs + 1), Accuracys[0])
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plt.plot(range(1, Epochs + 1), Accuracys[1])
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plt.ylabel('loss')
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plt.xlabel('epoch')
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plt.legend(['Train','Validation'], loc='upper left')
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plt.title('Model Loss')
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model_dir = '../Result/save_the_train_image( ' + str(datetime.date.today()) + " )"
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File.JudgeRoot_MakeDir(model_dir)
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modelfiles = File.Make_Save_Root(str(model_name) + " " + str(file_name) + ".png", model_dir)
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plt.savefig(modelfiles)
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plt.close("all") # 關閉圖表
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def draw_heatmap(matrix, model_name, index): # 二分類以上混淆矩陣做法
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File = Process_File()
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# 创建热图
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fig = figure.Figure(figsize=(6, 4))
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canvas = agg.FigureCanvasAgg(fig)
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Ax = fig.add_subplot(111)
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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
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model_dir = '../Result/model_matrix_image ( ' + str(datetime.date.today()) + " )"
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File.JudgeRoot_MakeDir(model_dir)
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modelfiles = File.Make_Save_Root(str(model_name) + "-" + str(index) + ".png", model_dir)
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# confusion.figure.savefig(modelfiles)
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# 设置图像参数
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Ax.set_title(str(model_name) + " confusion matrix")
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Ax.set_xlabel("X-Predict label of the model")
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Ax.set_ylabel("Y-True label of the model")
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# 保存图像到文件中
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canvas.print_figure(modelfiles)
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def Confusion_Matrix_of_Two_Classification(Model_Name, Matrix, index):
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File = Process_File()
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fx = sns.heatmap(Matrix, annot=True, cmap='turbo')
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# labels the title and x, y axis of plot
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fx.set_title('Plotting Confusion Matrix using Seaborn\n\n')
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fx.set_xlabel('answer Values ')
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fx.set_ylabel('Predicted Values')
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# labels the boxes
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fx.xaxis.set_ticklabels(['False','True'])
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fx.yaxis.set_ticklabels(['False','True'])
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model_dir = '../Result/model_matrix_image ( ' + str(datetime.date.today()) + " )"
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File.JudgeRoot_MakeDir(model_dir)
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modelfiles = File.Make_Save_Root(str(Model_Name) + "-" + str(index) + ".png", model_dir)
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plt.savefig(modelfiles)
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plt.close("all") # 關閉圖表
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pass |