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[![DOI](https://zenodo.org/badge/76566234.svg)](https://zenodo.org/badge/latestdoi/76566234) [![Build Status](https://travis-ci.org/vicbonj/pydtfe.svg?branch=master)](https://travis-ci.org/vicbonj/pydtfe) [![Code Health](https://landscape.io/github/vicbonj/density/master/landscape.svg?style=flat)](https://landscape.io/github/vicbonj/density/master)
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# density maps 2d and density cubes 3d
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Author: Victor Bonjean
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Mail: victor.bonjean@obspm.fr



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A code to perform very easily and quickly density maps in 2d or in density cubes in 3d with a distribution of points in inputs, using the Delaunay Tesselation Field Estimator (PhD thesis: Schaap, W. E. (2007). DTFE: the Delaunay Tessellation Field Estimator s.n.), and scipy (http://www.scipy.org/).
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- use "git clone https://git.ias.u-psud.fr/ByoPiC/pydtfe.git"
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- in scripts/, run the notebooks with the command "jupyter-notebook Density_map_*d.ipynb" in 2 or 3d
- test the examples and create your own maps or cubes with your own distributions of points !
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For 3d cube visualisation, you can use the "mayavi" library in python (http://docs.enthought.com/mayavi/mayavi/)
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--- In terms of compatibility, it's better to have the environment Anaconda (https://anaconda.org) installed on your computer, either 2.7 or 3.6. Otherwise, there is a requirements.txt ---