Umami calculates landscape metrics
Project description
Umami
Umami calculates topographic metrics for use in assessing model-data fit.
It is presently under construction.
There will eventually be a binder link here to some notebooks that provide introductory examples.
Getting Help
Use the Issues Page to ask questions and get help. Please search open and closed issues to identify if a question has already been asked. We welcome all questions.
Contributing
User contributions are welcome pull requests on a development branch. Umami strives for a meaningful 100% code coverage, adherence to PEP8, low lint levels using Flake8, and Black style. Many of these standards are enforced by continuous integration tests and the development team will help you bring contributions into compliance. Please see the Development Practices page for more information.
Installation instructions
WARNING: conda and pip distributions are not presently active Before installing umami you will need a python distribution. We recommend that you use the Anaconda python distribution. Unless you have a specific reason to want Python 2.7 we strongly suggest that you install Python 3.7 (or the current 3.* version provided by Anaconda).
To install the release version of umami (this is probably what you want) we support conda and pip package management.
Using conda
Open a terminal and execute the following:
conda config --add channels conda-forge
conda install umami
Using pip
Open a terminal and execute the following:
pip install umami
From source code
To install the umami source code version of umami we recommend creating a conda environment for umami.
git clone https://github.com/TerrainBento/umami.git
cd umami
conda env create -f environment-dev.yml
conda activate umami-dev
python setup.py install
A note to developers
If you plan to develop with umami, please fork umami, clone the forked repository, and replace python setup.py install
with python setup.py develop
. We recommend developing new features on a development branch.
How to cite
This repository will be submitted to JOSS.
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