代码解析：
根据caffe日志文档，字符切割读取需要的x，y轴点，利用pylab 绘制曲线图。
注意：切取字符串的时候可能会丢失精度，同时也有可能因为截取的字符串太短出错，所以必须根据自己的日志设置需要截取字符串的合适的长度
#!/usr/bin/python
# -*- coding: UTF-8 -*-
# 文件名：DrawPic.py
import os
import pylab as pl
# 函数名：draw_roc
# 参数说明：
# loss_flag:画loss或者loss_dis标记（1为loss）
# filepath:本地文件夹路径
# filename:本地文件名称
def draw_roc(loss_flag,filePath,fileName):
# 本地文件名称
myFile = filePath + fileName
# 绘图变量
fig = pl.figure()
# 读取文件
loss_file = open(myFile)
iter_file = open(myFile)
# x轴对象
x1 = []
# y轴对象
y1 = []
# 定位x轴元素出现的位置
iter_first = 'Iteration'
iter_last = ' / '
# 定位y轴元素出现的位置（两组y轴对象）
loss = '#0:'
loss_dif = '#1: loss_dif'
dic = {}
# 最小loss
try:
# 读取x轴点坐标
for line in iter_file:
try:
first = line.index(iter_first) + 10
last = line.index(iter_last)
x1.append(float(line[first:last]))
except:
pass
# 当loss_fig=1时，读取y轴点坐标
if loss_flag == 1:
for line in loss_file:
try:
loss_first_pos = line.index(loss) + 11
try:
temp = float(line[loss_first_pos:loss_first_pos + 7])
y1.append(temp)
print 'y1====', temp
# if float(line[loss_first_pos:loss_first_pos+7])>10:
# print line[loss_first_pos:loss_first_pos + 7]
except:
temp = float(line[loss_first_pos:loss_first_pos + 5])
y1.append(temp)
print 'y1====', temp
except:
pass
else:
# 当loss_fig！= 1时，读取y轴点坐标
for line in loss_file:
try:
loss_dif_first_pos = line.index(loss_dif) + 15
try:
temp = float(line[loss_dif_first_pos:loss_dif_first_pos + 8])
y1.append(temp)
except:
temp = float(line[loss_dif_first_pos:loss_dif_first_pos + 6])
y1.append(temp)
except:
pass
finally:
# 关闭文件资源
loss_file.close()
iter_file.close()
# 最小Los值
min_los = 1
# 最小迭代次数
min_los_iter = 0
# 去y轴最小对象
for temp in range(len(y1)):
# print'temp===', temp
test = min_los - y1[temp]
if test > 0:
min_los = y1[temp]
min_los_iter = x1[temp]
print'min_los===', min_los, '===min_los_iter===', min_los_iter
pl.plot(x1, y1, label='min_loss') # x1为x轴，y1为y轴
# pl.xticks(x1, rotation=0) # 绘制x轴坐标
pl.margins(0.08)
pl.title('Iteration|loss') # give plot a title
pl.xlabel('Iteration y_min=' + str(min_los) + ' x_min=' + str(
min_los_iter)) # make axis labels
pl.ylabel('loss') # y轴名字
pl.xlim(min(x1), x1[len(x1) - 1]) # set axis limits
pl.ylim(min(y1), max(y1))
pl.legend(loc='upper left') # upper left 标识线条
pl.show() # 显示图像
if loss_flag == 1:
# 保存loss图像，本地地址：filepath+'loss.jpg'
fig.savefig(filePath + 'loss.jpg')
else:
# 保存loss_dif图像，本地地址：filepath+'loss_dif.jpg'
fig.savefig(filePath + 'loss_dif.jpg')
if __name__ == '__main__':
# 函数名：draw_roc
# 参数说明：
# loss_flag:画loss或者loss_dis标记（1为loss）
# filepath:本地文件夹路径
# filename:本地文件名称
draw_roc(1,'C:\\work\\1221\\3\\','caffe.xiaoran-Vostro-3900.xiaoran.log.INFO.20171222-110151.31630')
draw_roc(2, 'C:\\work\\1221\\3\\', 'caffe.xiaoran-Vostro-3900.xiaoran.log.INFO.20171222-110151.31630')