{"repo":"scikit-tda/kepler-mapper","free":true,"listed":false,"github":"https://github.com/scikit-tda/kepler-mapper","clone":"git clone https://github.com/scikit-tda/kepler-mapper.git","description":"Kepler Mapper: A flexible Python implementation of the Mapper algorithm.","language":"Python","stars":653,"topics":["data-visualization","mapper-algorithm","topological-data-analysis","tda","python","visualization","kepler-mapper","hacktoberfest"],"license":"MIT","category":"analytics","readme_excerpt":"KeplerMapper Nature uses as little as possible of anything. - Johannes Kepler This is a Python implementation of the TDA Mapper algorithm for visualization of high-dimensional data. For complete documentation, see https://kepler-mapper.scikit-tda.org. KeplerMapper employs approaches based on the Mapper algorithm (Singh et al.) as first described in the paper \"Topological Methods for the Analysis of High Dimensional Data Sets and 3D Object Recognition\". KeplerMapper can make use of Scikit-Learn API compatible cluster and scaling algorithms. Install Dependencies KeplerMapper requires: - Python ( = 3.6) - NumPy - Scikit-learn Using the plotly visualizations requires a few extra libraries: - igraph - Plotly - Ipywidgets Additionally, running some of the examples requires: - matplotlib - umap-learn Installation Install KeplerMapper with pip: To install from source: Usage KeplerMapper adopts the scikit-learn API as much as possible, so it should feel very familiar to anyone who has used these libraries. Python code Disclaimer Standard MIT disclaimer applies, see DISCLAIMER.md for full text. Development status is Alpha. How to cite To credit KeplerMapper in your work: https://kepler-mapper.scikit-tda.org/en/latest/#citations","default_branch":null,"files":null,"tree":[],"storefront":"/r/scikit-tda","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/scikit-tda/kepler-mapper/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}