Metadata-Version: 2.1
Name: kmapper
Version: 1.2.0
Summary: Python implementation of Mapper algorithm for Topological Data Analysis.
Home-page: http://kepler-mapper.scikit-tda.org
Author: HJ van Veen, Nathaniel Saul
Author-email: info@mlwave.com, nat@saulgill.com
License: MIT
Description: [![PyPI version](https://badge.fury.io/py/kmapper.svg)](https://badge.fury.io/py/kmapper)
        [![Build Status](https://travis-ci.org/MLWave/kepler-mapper.svg?branch=master)](https://travis-ci.org/MLWave/kepler-mapper)
        [![Codecov](https://codecov.io/gh/mlwave/kepler-mapper/branch/master/graph/badge.svg)](https://codecov.io/gh/mlwave/kepler-mapper)
        [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1054444.svg)](https://doi.org/10.5281/zenodo.1054444)
        
        
        # KeplerMapper <img align="right" width="40" height="40" src="http://i.imgur.com/axOG6GJ.jpg">
        
        > 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](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 (>= 2.7 or >= 3.3)
          - NumPy
          - Scikit-learn
        
        Using the plotly visualizations requires a few extra libraries:
        
          - Python-Igraph
          - Plotly 
          - Ipywidgets
        
        Additionally, running some of the examples requires:
        
          - matplotlib
          - umap-learn
        
        
        ### Installation
        
        Install KeplerMapper with pip:
        
        ```
        pip install kmapper
        ```
        
        To install from source:
        ```
        git clone https://github.com/MLWave/kepler-mapper
        cd kepler-mapper
        pip install -e .
        ```
        
        ## 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
        ```python
        # Import the class
        import kmapper as km
        
        # Some sample data
        from sklearn import datasets
        data, labels = datasets.make_circles(n_samples=5000, noise=0.03, factor=0.3)
        
        # Initialize
        mapper = km.KeplerMapper(verbose=1)
        
        # Fit to and transform the data
        projected_data = mapper.fit_transform(data, projection=[0,1]) # X-Y axis
        
        # Create dictionary called 'graph' with nodes, edges and meta-information
        graph = mapper.map(projected_data, data, nr_cubes=10)
        
        # Visualize it
        mapper.visualize(graph, path_html="make_circles_keplermapper_output.html",
                         title="make_circles(n_samples=5000, noise=0.03, factor=0.3)")
        ```
        
        ## Disclaimer
        
        Standard MIT disclaimer applies, see `DISCLAIMER.md` for full text. Development status is Alpha.
        
        ## Cite
        
        Nathaniel Saul, & Hendrik Jacob van Veen. (2017, November 17). MLWave/kepler-mapper: 186f (Version 1.0.1). Zenodo. http://doi.org/10.5281/zenodo.1054444
        
        
Keywords: mapper,topology data analysis,algebraic topology,unsupervised learning
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Healthcare Industry
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=2.7,!=3.1,!=3.2,!=3.3
Description-Content-Type: text/markdown
Provides-Extra: testing
Provides-Extra: docs
