一段metric指标的可视化代码

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  """
    可视化结果
    """
    import matplotlib.pyplot as plt
    f=open('/home/yanhua/Desktop/ncc-600_0.0004.txt','r')
    data=f.read().splitlines()
    f.close()
    test=data[1::2]
    testdsc=[]
    for i in range(len(test)):
        testdsc.append(float(test[i][-8:]))
        #testdsc.append(float(test[i][13:21]))
    # f2 = open('/home/yanhua/Desktop/mse-600_0.0004.txt', 'r')
    # data2 = f2.read().splitlines()
    # f2.close()
    # test2 = data2[1::2]
    # testdsc2 = []
    # for i in range(len(test2)):
    #     testdsc2.append(float(test2[i][-8:]))
    #     #testdsc2.append(float(test2[i][13:21]))
    # f3 = open('/home/yanhua/Desktop/gcc-600_0.0004.txt', 'r')
    # data3 = f3.read().splitlines()
    # f3.close()
    # test3 = data3[1::2]
    # testdsc3 = []
    # for i in range(len(test3)):
    #     testdsc3.append(float(test3[i][-8:]))
    #      #testdsc3.append(float(test3[i][13:21]))
    train=data[0::2]
    traindsc=[]
    for i in range(len(train)):
        traindsc.append(float(train[i][-8:]))
        #traindsc.append(float(train[i][14:22]))
    x = [i for i in range(len(testdsc))]
    figure = plt.figure(figsize=(20, 8), dpi=80)#figsize-指定figure的宽和高,dpi-指定绘图对象的分辨率
    plt.plot(x, testdsc, label='ncc_DSC')      #x-索引，testdsc-按索引具有的值,label-线条的标签
    plt.plot(x, traindsc, label='train_loss')
    # plt.plot(x,testdsc2,label='mse_DSC')
    # plt.plot(x, testdsc3, label='gcc_DSC')
    plt.xlabel("iterations", fontsize=15)       #fontsize-设置标签字体大小
    plt.ylabel("DSC", fontsize=15)
    plt.legend()
    plt.grid()
    plt.show()

文件的数据如下图所示

执行此段代码后，如会有如下所示效果