python 绘制 Caffe 的trainloss testloss testaccuracy 曲线

############################################################"""在终端中输入python C:\MYCaffe\caffe-master\tools\extra\parse_log.py D:\CaffeInfo\D_TrainVal\train_outputbak.log  D:\CaffeInfo\D_TrainVal得到train_outputbak.log.testtrain_outputbak.log.train"""############################################################

#!/usr/bin/python# -*- coding: UTF-8 -*-import numpy as npimport matplotlib.pyplot as plt  #from urlgrabber.grabber import _file_object_testfrom cProfile import label############################################################"""在终端中输入python C:\MYCaffe\caffe-master\tools\extra\parse_log.py D:\CaffeInfo\D_TrainVal\train_outputbak.log  D:\CaffeInfo\D_TrainVal得到train_outputbak.log.testtrain_outputbak.log.train"""############################################################def size_text_file (file_object):    str_file_object = str(file_object)    s1 = "open file '/"    s2 = "', mode"    a=0    b=0    i=0    for ch in str_file_object:        if str_file_object[i : i+len(s1) - 1] == s1[0:-1] :            a = i+len(s1) - 1        elif str_file_object[i : i+len(s2) - 1] == s2[0:-1] :             b=i        i = i + 1            #close the object    file_object.close()    print("path2text_file/name2text_file: " + str_file_object[a:b] + "\n")    #open the object    file_object = open(str_file_object[a:b])                 count_rows = 0    count_cols = 0    line = file_object.readline()    for ch in line:        if ch == ',' or ch == '\r' :            count_cols = count_cols+1        while line:        line = file_object.readline()        count_rows = count_rows + 1        #close the object    file_object.close()    return [ count_rows, count_cols ] ############################################################def data_text_file(file_object):    str_file_object = str(file_object)    s1 = "open file '/"    s2 = "', mode"    a=0    b=0    i=0    for ch in str_file_object:        if str_file_object[i : i+len(s1) - 1] == s1[0:-1] :            a = i+len(s1) - 1        elif str_file_object[i : i+len(s2) - 1] == s2[0:-1] :             b=i        i = i + 1                    [ count_rows, count_cols ] = size_text_file (file_object)    file_object.close()        print("path2text_file/name2text_file: " + str_file_object[a:b] + "\n")        file_object = open(str_file_object[a:b])        line = file_object.readline()    k=0     p=-1    i=0      j=0    data = np.zeros( ( count_rows - 1, count_cols ) )      while line:         line = file_object.readline()            for ch in line:            if ch == ',' or ch == '\r' :                data[i][j] =float ( line[p+1:k] )                p=k                j=j+1            k=k+1                i=i+1        k=0        p=-1        j=0         file_object.close()       return data########################################################################################################################file_train_log = open("D:\CaffeInfo\\D_TrainVal\\train_outputbak.log.train")      file_train_log_data = data_text_file( file_train_log )print(file_train_log_data)############################################################file_test_log = open( "D:\\CaffeInfo\\D_TrainVal\\train_outputbak.log.test" )file_test_log_data = data_text_file( file_test_log )############################################################print '\nplot the train loss and test accuracy\n'    _,ax1 = plt.subplots()    ax2 = ax1.twinx()          ax1.plot(file_train_log_data[0:, 0], file_train_log_data[0:, 3], 'k', label = 'train loss')ax1.plot(file_test_log_data[0:, 0], file_test_log_data[0:, 4], 'g', label = 'test loss')    ax2.plot(file_test_log_data[0:, 0], file_test_log_data[0:, 3], 'r', label = 'test accuracy')             ax1.set_xlabel('iteration')    ax1.set_ylabel('loss')   ax2.set_ylabel('accuracy')  handles1, labels1 = ax1.get_legend_handles_labels()handles2, labels2 = ax2.get_legend_handles_labels()ax1.legend(handles1[::-1], labels1[::-1], bbox_to_anchor=(0.74,0.11)) #left right, up downax2.legend(handles2[::-1], labels2[::-1], bbox_to_anchor=(0.6,0.8))plt.show()