# 大规模地理时间序列的可视化方法 **Repository Path**: zkrain/GeoChron ## Basic Information - **Project Name**: 大规模地理时间序列的可视化方法 - **Description**: 大规模地理时间序列的可视化方法 - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2024-12-18 - **Last Updated**: 2024-12-18 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README ## Information(基本信息) ### Reference(文献) ```sh @article{DBLP:journals/tvcg/DengCSDTXWW24, author = {Zikun Deng and Shifu Chen and Tobias Schreck and Dazhen Deng and Tan Tang and Mingliang Xu and Di Weng and Yingcai Wu}, title = {Visualizing Large-Scale Spatial Time Series with GeoChron}, journal = {{IEEE} Trans. Vis. Comput. Graph.}, volume = {30}, number = {1}, pages = {1194--1204}, year = {2024}, url = {https://doi.org/10.1109/TVCG.2023.3327162}, doi = {10.1109/TVCG.2023.3327162} } ``` ### Presentation Video(展示视频) https://www.youtube.com/watch?v=DLJtBFaW6HY ## Environment(运行环境) Python 3.8.10 npm@9.8.0 Node.js v20.5.1 ## 1. Front-end Setup (前端配置) ### 1.1 Installation(安装) ```sh npm install ```  ### 1.2 Compile and Hot-Reload for Development(以开发状态运行) ```sh npm run dev ```  ## 2. Back-end Setup (后端配置) 将下述的 1_edges_tws.json 文件下载并拷贝到/py/server 目录下 链接: https://pan.baidu.com/s/1EIg4OMq5d42dMUrSxRVndw?pwd=ku5v 提取码: ku5v 在命令行运行 ```sh cd py/server/ python3 index.py ``` or ```sh cd py/server/ python index.py ```  ## 3. Usage(使用流程) 步骤 1:用户在前端确定关联-距离参数后(如下图右左键单击),后端输出日志如下图右