NASA SBIR Phase I & II - Open Source Parallel Image Analysis and Machine Learning Pipeline

This repository archives the prototype ELM software developed in NASA SBIR Phase I and II from 2016 to January 2018. Current versions of this code are available at EarthML.pyviz.org; the code here is primarily of historical interest.

Using the Code

To use this code:

Install:

Create the development environment:

conda env create

Activate the environment:

source activate elm-env

(older versions of the code may have elm in place of elm-env above. The environment name was changed to avoid conflict with elm package on anaconda.org. The elm-env is uploaded to the nasasbir org on anaconda.org.)

Install the source:

python setup.py develop

Clone the elm-data repo using Git LFS so that more tests can be run:

brew install git-lfs # or apt-get, yum, etc
git lfs install
git clone https://github.com/ContinuumIO/elm-data
git remote add origin https://github.com/ContinuumIO/elm-data

Add the following to your .bashrc or environment, changing the paths depending on where you have cloned elm-data:

export DASK_EXECUTOR=SERIAL
export ELM_EXAMPLE_DATA_PATH=/Users/psteinberg/Documents/elm-data

Read more docs

cd docs
source activate elm-env
pip install recommonmark sphinx sphinx_rtd_theme numpydoc
make html

Then view the resulting files in docs/build in your browser's file:// protocol.