DISCLAIMER: LANTERN is currently in alpha and the primary interface is subject to change
The official documentation with usage is available at:
https://lantern-gpl.readthedocs.io. Documentation covers
instructions for running lantern
on GPL data, including a
demonstration on an example dataset. On a typical desktop, examples
should run in under ten minutes.
lantern
requires only a standard computer with enough RAM to
support the in-memory operations. Runtime of model training on
large-scale GPL datasets (
This package is supported for macOS and Linux. The package has been tested on the following systems:
- macOS: Catalina (10.15)
- Linux: Ubuntu 18.04
lantern
depends primarily on pytorch
and gpytorch
, as well as
the components of the Python scientific stack:
pandas
numpy
Installation time for lantern
is typically less than one minute.
LANTERN
currently must be installed from this repository directly,
either through pip:
python -m pip install git+https://github.com/usnistgov/lantern.git
of by cloning this repository:
git clone https://github.com/usnistgov/lantern.git
cd lantern
python setup.py install
In either case, it is recommended to install inside a virtual environment.
Source code to reproduce the analysis of the LANTERN manuscript are available at github.com/usnistgov/lantern/tree/master/manuscript.
This project is covered under the NIST Software License