From 2787949a835462575bab84ee8146870c282333f4 Mon Sep 17 00:00:00 2001 From: aptx1231 <35984903+aptx1231@users.noreply.github.com> Date: Tue, 23 Nov 2021 23:51:10 +0800 Subject: [PATCH] update readme and contribution v1.0 (#216) * update readme and contribution * update readme and contribution --- contribution_list.md | 11 +++++++++-- readme.md | 32 ++++++++++++++++++++++++++++---- readme_zh.md | 32 ++++++++++++++++++++++++++++---- 3 files changed, 65 insertions(+), 10 deletions(-) diff --git a/contribution_list.md b/contribution_list.md index 1d891821..f4a80cfb 100644 --- a/contribution_list.md +++ b/contribution_list.md @@ -2,6 +2,8 @@ The model reproduction work in the library has been assisted by several developers. The specific contribution list is shown below. +For a list of all models reproduced in LibCity, see [Docs](https://bigscity-libcity-docs.readthedocs.io/en/latest/user_guide/model.html), where you can see the abbreviation of the model and the corresponding papers and citations. + | Task | Model | Contributor | | ------ | ------------------------------------------------------------ | ------ | |Time Series Prediction|HA|[XBR-1111](https://github.com/XBR-1111), [aptx1231](https://github.com/aptx1231)| @@ -43,14 +45,16 @@ The model reproduction work in the library has been assisted by several develope | | GTS | [aptx1231](https://github.com/aptx1231), [buaacjw](https://github.com/buaacjw), [t123yh](https://github.com/t123yh), [h9tyf](https://github.com/h9tyf) | | | GMAN | [huangjiawei128](https://github.com/huangjiawei128), [fry412](https://github.com/fry412) | | | ATDM | [zhangjiahui-buaa](https://github.com/zhangjiahui-buaa) | -| | HGCN | [XBR-1111](https://github.com/XBR-1111), [Matty-blu](https://github.com/Matty-blu), [nan0054](https://github.com/nan0054) | +| | HGCN | [XBR-1111](https://github.com/XBR-1111), [Matty-blu](https://github.com/Matty-blu), [nan0054](https://github.com/nan0054), [PotassiumWings](https://github.com/PotassiumWings) | | | STAGGCN | [a-l-r](https://github.com/a-l-r1), [aptx1231](https://github.com/aptx1231) | -| | DKFN | [a-l-r](https://github.com/a-l-r1), [aptx1231](https://github.com/aptx1231) | +| | DKFN | [a-l-r](https://github.com/a-l-r1), [aptx1231](https://github.com/aptx1231), [NickHan-cs](https://github.com/NickHan-cs) | | | STTN | [NickHan-cs](https://github.com/NickHan-cs) | |On-Demand Service Prediction|CCRNN|[aptx1231](https://github.com/aptx1231)| | |STG2Seq|[aptx1231](https://github.com/aptx1231), [Stevezzy](https://github.com/Stevezzy)| ||DMVSTNet|[l782993610](https://github.com/l782993610), [WANDY666](https://github.com/WANDY666)| |OD Matrix Prediction|GEML|[l782993610](https://github.com/l782993610)| +||CSTN|[l782993610](https://github.com/l782993610)| +|Traffic Accidents Prediction|GSNet|[excelsior399](https://github.com/excelsior399)| | Trajectory Next-Location Prediction | FPMC | [WenMellors](https://github.com/WenMellors) | | | RNN-1 | [WenMellors](https://github.com/WenMellors) | | | STRNN | [BugMakerzzz](https://github.com/BugMakerzzz), [xcw-1010](https://github.com/xcw-1010), [WenMellors](https://github.com/WenMellors) | @@ -62,9 +66,12 @@ The model reproduction work in the library has been assisted by several develope ||LSTPM|[ssdrywz](https://github.com/ssdrywz), [Jerry18231174](https://github.com/Jerry18231174), [WenMellors](https://github.com/WenMellors)| ||GeoSAN|[Reinhard-Tichy](https://github.com/Reinhard-Tichy)| ||HSTLSTM|[Creddittale](https://github.com/Creddittale), [WenMellors](https://github.com/WenMellors)| +|Estimated Time of Arrival|DeepTTE|[NickHan-cs](https://github.com/NickHan-cs)| |Map Matching|STMatching|[XBR-1111](https://github.com/XBR-1111)| ||IVMM|[excelsior399](https://github.com/excelsior399)| +||HMMM|[XBR-1111](https://github.com/XBR-1111)| |Road Network Representation Learning|ChebConv|[aptx1231](https://github.com/aptx1231)| +||LINE|[l782993610](https://github.com/l782993610)| diff --git a/readme.md b/readme.md index 56cfd910..88c7fabb 100644 --- a/readme.md +++ b/readme.md @@ -10,13 +10,14 @@ LibCity is a unified, comprehensive, and extensible library, which provides rese LibCity currently supports the following tasks: -* Time Series Prediction * Traffic State Prediction * Traffic Flow Prediction * Traffic Speed Prediction * On-Demand Service Prediction - * OD Matrix Prediction + * Origin-destination Matrix Prediction + * Traffic Accidents Prediction * Trajectory Next-Location Prediction +* Estimated Time of Arrival * Map Matching * Road Network Representation Learning @@ -24,7 +25,7 @@ LibCity currently supports the following tasks: * **Unified**: LibCity builds a systematic pipeline to implement, use and evaluate traffic prediction models in a unified platform. We design basic spatial-temporal data storage, unified model instantiation interfaces, and standardized evaluation procedure. -* **Comprehensive**: 54 models covering 8 traffic prediction tasks have been reproduced to form a comprehensive model warehouse. Meanwhile, LibCity collects 32 commonly used datasets of different sources and implements a series of commonly used evaluation metrics and strategies for performance evaluation. +* **Comprehensive**: 60 models covering 9 traffic prediction tasks have been reproduced to form a comprehensive model warehouse. Meanwhile, LibCity collects 35 commonly used datasets of different sources and implements a series of commonly used evaluation metrics and strategies for performance evaluation. * **Extensible**: LibCity enables a modular design of different components, allowing users to flexibly insert customized components into the library. Therefore, new researchers can easily develop new models with the support of LibCity. @@ -67,13 +68,36 @@ This script will run the GRU model on the METR_LA dataset for traffic state pred More details is represented in [Docs](https://bigscity-libcity-docs.readthedocs.io/en/latest/get_started/quick_start.html). +## Reproduced Model List + +For a list of all models reproduced in LibCity, see [Docs](https://bigscity-libcity-docs.readthedocs.io/en/latest/user_guide/model.html), where you can see the abbreviation of the model and the corresponding papers and citations. + +## Tutorial + +In order to facilitate users to use LibCity, we provide users with some tutorials: + +- We gave lectures on both ACM SIGSPATIAL 2021 Main Track and Local Track. For related lecture videos and Slides, please see our [HomePage](https://libcity.ai/#/tutorial) (Chinese and English). +- We provide entry-level tutorials (in Chinese and English) in the documentation. + - [Install and quick start](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/install_quick_start.html) & [安装和快速上手](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/install_quick_start.html) + - [Run an existing model in LibCity](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/run_model.html) & [运行LibCity中已复现的模型](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/run_model.html) + - [Add a new model to LibCity](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/add_model.html) & [在LibCity中添加新模型](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/add_model.html) + - [Tuning the model with automatic tool](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/hyper_tune.html) & [使用自动化工具调参](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/hyper_tune.html) + - [Visualize Atomic Files](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/data_visualization.html) & [原子文件可视化](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/data_visualization.html) +- In order to facilitate the use of domestic users in China, we provide an introductory tutorial (in Chinese) on Zhihu. + - [LibCity：一个统一、全面、可扩展的交通预测算法库](https://zhuanlan.zhihu.com/p/401186930) + - [LibCity入门教程（1）——安装与快速上手](https://zhuanlan.zhihu.com/p/400814990) + - [LibCity入门教程（2）——运行LibCity中已复现的模型](https://zhuanlan.zhihu.com/p/400819354) + - [LibCity入门教程（3）——在LibCity中添加新模型](https://zhuanlan.zhihu.com/p/400821482) + - [LibCity入门教程（4）—— 自动化调参工具](https://zhuanlan.zhihu.com/p/401190615) + - [北航BIGSCity课题组提出LibCity工具库：城市时空预测深度学习开源平台](https://zhuanlan.zhihu.com/p/436191860) + ## Contribution The LibCity is mainly developed and maintained by Beihang Interest Group on SmartCity ([BIGSCITY](https://www.bigcity.ai/)). The core developers of this library are [@aptx1231](https://github.com/aptx1231) and [@WenMellors](https://github.com/WenMellors). Several co-developers have also participated in the reproduction of the model, the list of contributions of which is presented in the [reproduction contribution list](./contribution_list.md). -If you encounter a bug or have any suggestion, please contact us by [raising an issue](https://github.com/LibCity/Bigscity-LibCity/issues). +If you encounter a bug or have any suggestion, please contact us by [raising an issue](https://github.com/LibCity/Bigscity-LibCity/issues). You can also contact us by sending an email to bigscity@126.com. ## Cite diff --git a/readme_zh.md b/readme_zh.md index 9ed56d21..e508d27a 100644 --- a/readme_zh.md +++ b/readme_zh.md @@ -10,13 +10,14 @@ LibCity 是一个统一、全面、可扩展的代码库，为交通预测领域 LibCity 目前支持以下任务： -* 时间序列预测 * 交通状态预测 * 交通流量预测 * 交通速度预测 * 交通需求预测 - * OD矩阵预测 + * 起点-终点（OD）矩阵预测 + * 交通事故预测 * 轨迹下一跳预测 +* 到达时间预测 * 路网匹配 * 路网表征学习 @@ -24,7 +25,7 @@ LibCity 目前支持以下任务： * **统一性**：LibCity 构建了一个系统的流水线以在一个统一的平台上实现、使用和评估交通预测模型。 我们设计了统一的时空数据存储格式、统一的模型实例化接口和标准的模型评估程序。 -* **全面性**：复现覆盖 8 个交通预测任务的 54 个模型，形成了全面的模型库。 同时，LibCity 收集了 32 个不同来源的常用数据集，并实现了一系列常用的性能评估指标和策略。 +* **全面性**：复现覆盖 9 个交通预测任务的 60 个模型，形成了全面的模型库。 同时，LibCity 收集了 35 个不同来源的常用数据集，并实现了一系列常用的性能评估指标和策略。 * **可扩展性**：LibCity 实现了不同组件的模块化设计，允许用户灵活地加入自定义组件。 因此，新的研究人员可以在 LibCity 的支持下轻松开发新模型。 @@ -65,13 +66,36 @@ python run_model.py --task traffic_state_pred --model GRU --dataset METR_LA 更多细节请访问 [文档](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/get_started/quick_start.html) 。 +## Reproduced Model List + +LibCity 中所复现的全部模型列表见[文档](https://bigscity-libcity-docs.readthedocs.io/en/latest/user_guide/model.html)，在这里你可以看到模型的简称和对应的论文及引用文献。 + +## Tutorial + +为了方便用户使用 LibCity，我们为用户提供了一些入门教程： + +- 我们在 ACM SIGSPATIAL 2021 Main Track 以及 Local Track 上都进行了演讲，相关的演讲视频和Slide见我们的[主页](https://libcity.ai/#/tutorial)（中英文）。 +- 我们在文档中提供了入门级教程（中英文）。 + - [Install and quick start](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/install_quick_start.html) & [安装和快速上手](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/install_quick_start.html) + - [Run an existing model in LibCity](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/run_model.html) & [运行LibCity中已复现的模型](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/run_model.html) + - [Add a new model to LibCity](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/add_model.html) & [在LibCity中添加新模型](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/add_model.html) + - [Tuning the model with automatic tool](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/hyper_tune.html) & [使用自动化工具调参](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/hyper_tune.html) + - [Visualize Atomic Files](https://bigscity-libcity-docs.readthedocs.io/en/latest/tutorial/data_visualization.html) & [原子文件可视化](https://bigscity-libcity-docs.readthedocs.io/zh_CN/latest/tutorial/data_visualization.html) +- 为了便于国内用户使用，我们在知乎上提供了入门教程（中文）。 + - [LibCity：一个统一、全面、可扩展的交通预测算法库](https://zhuanlan.zhihu.com/p/401186930) + - [LibCity入门教程（1）——安装与快速上手](https://zhuanlan.zhihu.com/p/400814990) + - [LibCity入门教程（2）——运行LibCity中已复现的模型](https://zhuanlan.zhihu.com/p/400819354) + - [LibCity入门教程（3）——在LibCity中添加新模型](https://zhuanlan.zhihu.com/p/400821482) + - [LibCity入门教程（4）—— 自动化调参工具](https://zhuanlan.zhihu.com/p/401190615) + - [北航BIGSCity课题组提出LibCity工具库：城市时空预测深度学习开源平台](https://zhuanlan.zhihu.com/p/436191860) + ## Contribution LibCity 主要由北航智慧城市兴趣小组 ([BIGSCITY](https://www.bigcity.ai/)) 开发和维护。 该库的核心开发人员是 [@aptx1231](https://github.com/aptx1231) 和 [@WenMellors](https://github.com/WenMellors)。 若干共同开发者也参与了模型的复现，其贡献列表在 [贡献者列表](./contribution_list.md) 。 -如果您遇到错误或有任何建议，请通过以下方式与我们联系： [提交issue](https://github.com/LibCity/Bigscity-LibCity/issues)。 +如果您遇到错误或有任何建议，请通过 [提交issue](https://github.com/LibCity/Bigscity-LibCity/issues) 的方式与我们联系。您也可以通过发送邮件的方式联系我们，邮箱为bigscity@126.com。 ## Cite