对于下面这种内容的log.log文件,如何跳过有ESSteps的行,而只读取剩下行中的Rewards和Total Steps数据,并以Total Steps数据为横坐标、Rewards数据为纵坐标画图:[32m[05-14 13:23:20 MainThread @train.py:373][0m Total Steps: 1299956 Reward: 98.06129722973967 [32m[05-14 13:23:21 MainThread @train.py:373][0m Total Steps: 1299984 Reward: 45.173203134342316 [32m[05-14 13:23:22 MainThread @train.py:373][0m Total Steps: 1300015 Reward: 78.54178229069575 [32m[05-14 13:23:22 MainThread @train.py:380][0m Evaluation over: 1 episodes, Reward: 112.39893016163798 Steps: 34 [32m[05-14 13:23:37 MainThread @train.py:427][0m ESSteps: 1951 Reward: 119.89624252947024 step: 33.425 sigma:0.004996741129169055
时间: 2023-11-27 20:52:55 浏览: 32
可以使用Python的re模块来匹配log.log文件中的每一行,然后跳过包含ESSteps的行,取出剩下行中的Total Steps和Reward数据。代码如下:
```python
import re
import matplotlib.pyplot as plt
steps = []
rewards = []
with open('log.log', 'r') as f:
for line in f:
if "ESSteps" in line:
continue
match = re.search(r'Total Steps: (\d+) Reward: ([\d\.]+)', line)
if match:
steps.append(int(match.group(1)))
rewards.append(float(match.group(2)))
plt.plot(steps, rewards)
plt.xlabel('Total Steps')
plt.ylabel('Rewards')
plt.show()
```
这段代码会读取log.log文件中的每一行,如果包含ESSteps则跳过,否则使用正则表达式匹配出Total Steps和Reward数据,并将它们分别添加到steps和rewards列表中。最后,使用matplotlib库画出横坐标为Total Steps、纵坐标为Rewards的图形。
相关问题
对于下面这种内容的log.log文件,如何跳过有ESSteps的行,而只读取剩下行中的Rewards和Total Steps数据:[32m[05-14 13:23:20 MainThread @train.py:373][0m Total Steps: 1299956 Reward: 98.06129722973967 [32m[05-14 13:23:21 MainThread @train.py:373][0m Total Steps: 1299984 Reward: 45.173203134342316 [32m[05-14 13:23:22 MainThread @train.py:373][0m Total Steps: 1300015 Reward: 78.54178229069575 [32m[05-14 13:23:22 MainThread @train.py:380][0m Evaluation over: 1 episodes, Reward: 112.39893016163798 Steps: 34 [32m[05-14 13:23:37 MainThread @train.py:427][0m ESSteps: 1951 Reward: 119.89624252947024 step: 33.425 sigma:0.004996741129169055
你可以使用Python中的正则表达式来匹配所需的行。以下是一个示例代码,可以读取log.log文件中除了包含"ESSteps"的行以外的所有行,然后提取其中的Rewards和Total Steps数据:
```python
import re
with open('log.log', 'r') as f:
for line in f:
if "ESSteps" in line:
continue
match = re.search(r'Total Steps:\s+(\d+)\s+Reward:\s+([\d.]+)', line)
if match:
steps = int(match.group(1))
reward = float(match.group(2))
print(f"Steps: {steps}, Reward: {reward}")
```
解释一下代码:
首先打开log.log文件并逐行读取。如果当前行包含"ESSteps",则跳过该行。否则,使用正则表达式匹配该行中的Total Steps和Reward数据。正则表达式中的\s表示空白字符,+表示一个或多个,\d表示数字,而()表示捕获组。match.group(1)捕获Total Steps数据,match.group(2)捕获Reward数据。最后将数据打印出来。
对于如下这种内容的log.log文件,如何从第9964行开始每跳过30行提取接下来10000行的reward数据:[32m[05-13 17:20:36 MainThread @train.py:373][0m Total Steps: 122 Reward: 10.252438767788885
可以使用Python的文件读取和处理操作,具体步骤如下:
1. 打开文件并跳过前9963行:
```python
with open('log.log') as f:
for i in range(9963):
next(f)
```
2. 每隔30行读取一次,并提取接下来的10000行数据:
```python
rewards = []
for i in range(333):
for j in range(10000):
line = next(f)
reward = line.split()[-1]
rewards.append(float(reward))
# 跳过接下来的29行
for k in range(29):
next(f)
```
3. 最终得到的rewards列表即为所需的reward数据。完整代码如下:
```python
with open('log.log') as f:
for i in range(9963):
next(f)
rewards = []
for i in range(333):
for j in range(10000):
line = next(f)
reward = line.split()[-1]
rewards.append(float(reward))
for k in range(29):
next(f)
```