matplotlib 画曲线图2

秒速五厘米 2022-03-29 14:50 228阅读 0赞

import matplotlib.pyplot as plt
    
    import numpy as np
    def get_file(acc_list,loss_list,filename):
        f1 = open(filename, 'r')
        for line in f1.readlines():
            # print(line)
            line = line.strip('\n')
            str_list = line.split(':')
    
            loss = float(str_list[-2].split(',')[0])
            acc = float(str_list[-1])
            acc_list.append(acc)
    
            loss_list.append(loss)
    
    
    baseline_acc=[]
    baseline_loss=[]
    dgc_acc=[]
    dgc_loss=[]
    ip_acc=[]
    ip_loss=[]
    rand_4_dgc_acc=[]
    rand_4_dgc_loss=[]
    
    
    # 获取acc,loss数据
    get_file(baseline_acc,baseline_loss,'train_baseline_resnet50.txt')
    get_file(dgc_acc,dgc_loss,'train_dgc_resnet50.txt')
    get_file(ip_acc,ip_loss,'train_ip_resnet50.txt')
    get_file(rand_4_dgc_acc,rand_4_dgc_loss,'train_rand_4_dgc_resnet50.txt')
    
    
    plt.figure()
    # 横坐标轴
    x = [i for i in range(0,88)]
    # 在绘制时设置lable, 逗号是必须的
    # l1, = plt.plot(x, baseline_loss[0:88], label = 'line', color = 'b', linewidth = 1.0, linestyle = '-')
    # l2, = plt.plot(x, dgc_loss[2:90], label = 'line', color = 'g', linewidth = 1.0, linestyle = '-')
    # l3, = plt.plot(x, ip_loss[2:90], label = 'line', color = 'r', linewidth = 1.0, linestyle = '-')
    # l4, = plt.plot(x, rand_4_dgc_loss[2:90], label = 'line', color = 'c', linewidth = 1.0, linestyle = '-')
    
    l1, = plt.plot(x, baseline_acc[0:88], label = 'line', color = 'b', linewidth = 1.0, linestyle = '-')
    l2, = plt.plot(x, dgc_acc[2:90], label = 'line', color = 'g', linewidth = 1.0, linestyle = '-')
    l3, = plt.plot(x, ip_acc[2:90], label = 'line', color = 'r', linewidth = 1.0, linestyle = '-')
    l4, = plt.plot(x, rand_4_dgc_acc[2:90], label = 'line', color = 'c', linewidth = 1.0, linestyle = '-')
    
    # 设置坐标轴的lable
    plt.xlabel('epoch')
    # plt.ylabel('loss')
    plt.ylabel('accuracy')
    # 设置legend
    plt.legend(handles = [l1, l2, l3,l4], labels = ['baseline', 'dgc','ip','rand_4_dgc'], loc = 'best')
    plt.grid()
    # plt.show()
    # plt.savefig('loss.jpg')
    plt.savefig('accuracy.jpg')

![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L1RIX05VTQ_size_16_color_FFFFFF_t_70]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L1RIX05VTQ_size_16_color_FFFFFF_t_70]: /images/20220329/b55129e715a1489eb3a98691405bdbc2.png