从日志读取关键数据，按照相关日期进行数据分析

分析靠近后向挡墙的距离

import os
import re
import sys
import matplotlib.pyplot as plt
from datetime import datetime

def process_distance_data(file_path):
    distances = []
    timestamps = []
    try:
        with open(file_path, 'r', encoding='utf-8', errors='ignore') as file:
            for line in file:
                match = re.search(r'\[(\d{4}-\d{2}-\d{2}),(\d{2}:\d{2}:\d{2}\.\d{3})\]-距离后向挡墙距离([\d.]+) 完整度:([\d.]+)', line)
                if match:
                    date_str = match.group(1)
                    time_str = match.group(2)
                    timestamp_str = f"{date_str},{time_str}"
                    timestamp = datetime.strptime(timestamp_str, '%Y-%m-%d,%H:%M:%S.%f')
                    distance_str = match.group(3)
                    distance = float(distance_str) if distance_str != "340282346638528859811704183484516925440" else 80
                    if distance <= 80:
                        distances.append(distance)
                        timestamps.append(timestamp)
    except FileNotFoundError:
        print(f"Error: File '{file_path}' not found.")
    except Exception as e:
        print(f"Error: {e}")
    return distances, timestamps

def visualize_distances(distances, timestamps):
    plt.scatter(timestamps, distances, color='red', label='Data Points')  # 红色点
    plt.plot(timestamps, distances, color='blue', label='Line Plot')  # 蓝色折线
    plt.title('Distance from Rear Wall')
    plt.xlabel('Timestamp')
    plt.ylabel('Distance')
    plt.xticks(rotation=45)
    plt.legend()  # 添加图例
    plt.tight_layout()
    plt.show()

def export_distances_to_txt(distances, output_file):
    with open(output_file, 'w') as file:
        for distance in distances:
            file.write(f"{distance}\n")
    print(f"Distances exported to {output_file}")

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print("Usage: python script.py ")
        sys.exit(1)

    file_path = sys.argv[1]
    output_file = "distances.txt"
    if os.path.exists(file_path):
        distances, timestamps = process_distance_data(file_path)
        visualize_distances(distances, timestamps)
        # No need to export to txt file since you didn't provide the export_distances_to_txt function
    else:
        print("File not found.")

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60