Mapper Interactive is a web-based framework for interactive analysis and visualization of high-dimensional point cloud data built upon the Mapper algorithm. It is an open source software released under the MIT License.
The Mapper algorithm is a tool from topological data analysis first introduced by Gurjeet Singh, Facundo Mémoli and Gunnar Carlsson in 2007 (http://dx.doi.org/10.2312/SPBG/SPBG07/091-100).
git clone https://github.com/MapperInteractive/MapperInteractive.git (or git clone [email protected]:MapperInteractive/MapperInteractive.git)
cd MapperInteractive
python3 run.pyAfter running the above commands, you can run Mapper Interactive by visiting http://127.0.0.1:8080/ on the local machine (If possible, please use Chrome).
This software requires Kepler Mapper, scikit-learn, NetworkX and flask to run.
If you do not have these packages installed, please use the following command to intall them.
pip install scikit-learn
pip install networkx
pip install flask
pip install flask_assetsTo perform linear regression, please also make sure you have statsmodels installed.
pip install statsmodelsWhen loading a dataset into the interface, please make sure to put the data file to be loaded in the folder app/static/uploads/.
Please refer to a user-guide here for the command-line API.
This project is licensed under the MIT License - see the LICENSE file for details.
Pull requests are welcomed.
Mapper Interactive: A Scalable, Extendable, and Interactive Toolbox for the Visual Exploration of High-Dimensional Data.
Youjia Zhou, Nithin Chalapathi, Archit Rathore, Yaodong Zhao, Bei Wang.
IEEE Pacific Visualization (PacificVis), accepted, 2021.