Metadata-Version: 2.1
Name: findthegap
Version: 0.0.3
Summary: Tools for finding gaps and valleys in data distribution with a twice-differentiable density estimator with finite support.
Home-page: https://github.com/contardog/findthegap
Author: Gabriella Contardo
Author-email: gcontardo@flatironinstitute.org
License: UNKNOWN
Project-URL: Bug Tracker, https://github.com/contardog/findthegap
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

## FindTheGap

This package provides tools for geometric data analysis, targeted at finding gaps and valleys in data distribution. It provides a (twice-differentiable) density estimator (Quartic Kernel Density Estimator) relying on pytorch for auto-differentaition, and methods to estimate critical points in the density as well as various statistics to identify and trace `gaps' and valleys in the distribution. See https://github.com/contardog/findthegap for demo and usecase notebook in the folder 'examples'.

This package can be installed through pip (https://pypi.org/project/findthegap/):

```
pip install findthegap 
```


Dependencies:
* numpy >= 1.19.5

* torch >= 1.10.1

* scipy >= 1.5.4


Notebook requirements:
galpy, sklearn, astropy, matplotlib



Authors: Gabriella Contardo (CCA at Simons Foundation), David W. Hogg(CCA/NYU/MPIA)

