RunningTrainsPlot

Name	RunningTrainsPlot JSON
Version	1.0.7 JSON
	download
home_page	https://github.com/yourusername/RunningTrainsPlot
Summary	铁路列车运行数据可视化工具
upload_time	2025-09-14 12:34:59
maintainer	None
docs_url	None
author	Shen-Zeyu,Guan-Chengze,Zheng-Haoyu,He-Zelin,Wu-Yuqian
requires_python	>=3.6
license	None
keywords	railway train visualization plot diagram flow
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # RunningTrainsPlot

为研究人员与工程技术人员提供的可扩展、可交互的铁路可视化工具。

> **注意**: 本项目之前名为"RailwayTrainsVisualization"，现已更名为"RunningTrainsPlot"以提供更简洁的名称。如果您之前使用的是旧版本，请使用新名称重新安装。

## 功能特点

- **列流图 (Column Flow Chart)**：铁路线路流量可视化
- **速度曲线 (Speed Curve)**：列车速度-距离/时间曲线可视化
- **循环运行图 (Cyclic Diagram)**：列车循环运行图可视化
- **股道占用图 (Track Occupation)**：列车股道占用可视化
- **客流OD图 (Passenger Flow OD Chart)**：站点间客流可视化
- **工具函数**：数据加载、预处理和可视化工具

## 安装与更新

### 初次安装

```bash
pip install RunningTrainsPlot
```

### 更新到最新版本

```bash
pip install --upgrade RunningTrainsPlot
```

> 注意：只有在发布新版本后才需要使用--upgrade选项更新。可以通过`from RunningTrainsPlot import __version__; print(__version__)`检查当前版本。

### 验证安装

安装完成后可运行以下简单测试验证功能：

```python
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime, timedelta

# 检查版本
from RunningTrainsPlot import __version__
print(f"当前版本: {__version__}")

# 导入所有模块
from RunningTrainsPlot import passenger_flow, column_flow, speed_curve
from RunningTrainsPlot import cyclic_diagram, track_occupation

# 测试股道占用图
base_time = datetime(2023, 1, 1, 8, 0)
data = pd.DataFrame({
    'train_id': ['G201', 'D101', 'K105'],
    'track': ['1股道', '2股道', '3股道'],
    'arrival_time': [
        base_time,
        base_time + timedelta(hours=1),
        base_time + timedelta(hours=2)
    ],
    'departure_time': [
        base_time + timedelta(hours=0.5),
        base_time + timedelta(hours=2),
        base_time + timedelta(hours=3)
    ]
})

# 创建股道占用图
fig, ax = track_occupation.plot_track_occupation(
    data,
    title='股道占用图测试',
    figsize=(10, 6)
)
plt.show()
```

## 使用指南

### 列流图

```python
from RunningTrainsPlot import column_flow

# 加载数据
stations, flows = column_flow.load_flow_data("stations.csv", "flows.csv")

# 绘制图表
column_flow.plot_column_flow(stations, flows)
```

### 速度曲线

```python
from RunningTrainsPlot import speed_curve

# 加载数据
data = speed_curve.load_speed_data("speed_data.csv")

# 绘制速度-距离曲线
speed_curve.plot_speed_curve(data, x_col='distance', y_col='speed')

# 绘制速度-时间曲线
speed_curve.plot_speed_curve(data, x_col='time', y_col='speed')

# 同时绘制两种曲线
speed_curve.plot_speed_distance_time(data)
```

### 循环运行图

```python
from RunningTrainsPlot import cyclic_diagram

# 加载数据
data = cyclic_diagram.load_data("cycle_data.csv")

# 绘制图表
cyclic_diagram.plot_cyclic_diagram(data)
```

### 股道占用图

```python
from RunningTrainsPlot import track_occupation

# 加载数据
data = track_occupation.load_track_data("track_data.csv")

# 绘制股道占用图
track_occupation.plot_track_occupation(data)
```

### 客流OD图表

```python
from RunningTrainsPlot import passenger_flow

# 加载数据
data = passenger_flow.load_data("passenger_data.csv")

# 绘制图表
passenger_flow.plot_passenger_flow(data)
```

## 数据工具

```python
from RunningTrainsPlot import utils

# 加载数据
data = utils.load_data("data.csv")

# 预处理数据
processed_data = utils.preprocess_data(data)
```

## 版本历史

- **1.0.0** - 初始版本，从RailwayTrainsVisualization更名而来
- **1.0.1** - 新增原生循环运行图(cyclic_diagram)实现，不再依赖外部包

## 作者

- ZeyuShen <sc22zs2@leeds.ac.uk>

## 许可证

MIT

            

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print(__version__)`\u68c0\u67e5\u5f53\u524d\u7248\u672c\u3002\r\n\r\n### \u9a8c\u8bc1\u5b89\u88c5\r\n\r\n\u5b89\u88c5\u5b8c\u6210\u540e\u53ef\u8fd0\u884c\u4ee5\u4e0b\u7b80\u5355\u6d4b\u8bd5\u9a8c\u8bc1\u529f\u80fd\uff1a\r\n\r\n```python\r\nimport pandas as pd\r\nimport matplotlib.pyplot as plt\r\nfrom datetime import datetime, timedelta\r\n\r\n# \u68c0\u67e5\u7248\u672c\r\nfrom RunningTrainsPlot import __version__\r\nprint(f\"\u5f53\u524d\u7248\u672c: {__version__}\")\r\n\r\n# \u5bfc\u5165\u6240\u6709\u6a21\u5757\r\nfrom RunningTrainsPlot import passenger_flow, column_flow, speed_curve\r\nfrom RunningTrainsPlot import cyclic_diagram, track_occupation\r\n\r\n# \u6d4b\u8bd5\u80a1\u9053\u5360\u7528\u56fe\r\nbase_time = datetime(2023, 1, 1, 8, 0)\r\ndata = pd.DataFrame({\r\n    'train_id': ['G201', 'D101', 'K105'],\r\n    'track': ['1\u80a1\u9053', '2\u80a1\u9053', '3\u80a1\u9053'],\r\n    'arrival_time': [\r\n        base_time,\r\n        base_time + timedelta(hours=1),\r\n        base_time + timedelta(hours=2)\r\n    ],\r\n    'departure_time': [\r\n        base_time + timedelta(hours=0.5),\r\n        base_time + timedelta(hours=2),\r\n        base_time + timedelta(hours=3)\r\n    ]\r\n})\r\n\r\n# \u521b\u5efa\u80a1\u9053\u5360\u7528\u56fe\r\nfig, ax = track_occupation.plot_track_occupation(\r\n    data,\r\n    title='\u80a1\u9053\u5360\u7528\u56fe\u6d4b\u8bd5',\r\n    figsize=(10, 6)\r\n)\r\nplt.show()\r\n```\r\n\r\n## \u4f7f\u7528\u6307\u5357\r\n\r\n### \u5217\u6d41\u56fe\r\n\r\n```python\r\nfrom RunningTrainsPlot import column_flow\r\n\r\n# \u52a0\u8f7d\u6570\u636e\r\nstations, flows = column_flow.load_flow_data(\"stations.csv\", \"flows.csv\")\r\n\r\n# \u7ed8\u5236\u56fe\u8868\r\ncolumn_flow.plot_column_flow(stations, flows)\r\n```\r\n\r\n### \u901f\u5ea6\u66f2\u7ebf\r\n\r\n```python\r\nfrom RunningTrainsPlot import speed_curve\r\n\r\n# \u52a0\u8f7d\u6570\u636e\r\ndata = speed_curve.load_speed_data(\"speed_data.csv\")\r\n\r\n# \u7ed8\u5236\u901f\u5ea6-\u8ddd\u79bb\u66f2\u7ebf\r\nspeed_curve.plot_speed_curve(data, x_col='distance', y_col='speed')\r\n\r\n# \u7ed8\u5236\u901f\u5ea6-\u65f6\u95f4\u66f2\u7ebf\r\nspeed_curve.plot_speed_curve(data, x_col='time', y_col='speed')\r\n\r\n# \u540c\u65f6\u7ed8\u5236\u4e24\u79cd\u66f2\u7ebf\r\nspeed_curve.plot_speed_distance_time(data)\r\n```\r\n\r\n### \u5faa\u73af\u8fd0\u884c\u56fe\r\n\r\n```python\r\nfrom RunningTrainsPlot import cyclic_diagram\r\n\r\n# \u52a0\u8f7d\u6570\u636e\r\ndata = cyclic_diagram.load_data(\"cycle_data.csv\")\r\n\r\n# \u7ed8\u5236\u56fe\u8868\r\ncyclic_diagram.plot_cyclic_diagram(data)\r\n```\r\n\r\n### \u80a1\u9053\u5360\u7528\u56fe\r\n\r\n```python\r\nfrom RunningTrainsPlot import track_occupation\r\n\r\n# \u52a0\u8f7d\u6570\u636e\r\ndata = track_occupation.load_track_data(\"track_data.csv\")\r\n\r\n# \u7ed8\u5236\u80a1\u9053\u5360\u7528\u56fe\r\ntrack_occupation.plot_track_occupation(data)\r\n```\r\n\r\n### \u5ba2\u6d41OD\u56fe\u8868\r\n\r\n```python\r\nfrom RunningTrainsPlot import passenger_flow\r\n\r\n# \u52a0\u8f7d\u6570\u636e\r\ndata = passenger_flow.load_data(\"passenger_data.csv\")\r\n\r\n# \u7ed8\u5236\u56fe\u8868\r\npassenger_flow.plot_passenger_flow(data)\r\n```\r\n\r\n## \u6570\u636e\u5de5\u5177\r\n\r\n```python\r\nfrom RunningTrainsPlot import utils\r\n\r\n# \u52a0\u8f7d\u6570\u636e\r\ndata = utils.load_data(\"data.csv\")\r\n\r\n# \u9884\u5904\u7406\u6570\u636e\r\nprocessed_data = utils.preprocess_data(data)\r\n```\r\n\r\n## \u7248\u672c\u5386\u53f2\r\n\r\n- **1.0.0** - \u521d\u59cb\u7248\u672c\uff0c\u4eceRailwayTrainsVisualization\u66f4\u540d\u800c\u6765\r\n- **1.0.1** - \u65b0\u589e\u539f\u751f\u5faa\u73af\u8fd0\u884c\u56fe(cyclic_diagram)\u5b9e\u73b0\uff0c\u4e0d\u518d\u4f9d\u8d56\u5916\u90e8\u5305\r\n\r\n## \u4f5c\u8005\r\n\r\n- ZeyuShen <sc22zs2@leeds.ac.uk>\r\n\r\n## \u8bb8\u53ef\u8bc1\r\n\r\nMIT\r\n",
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