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vivarium-models

Connecting Simularium prototypes together using Vivarium

Installation

Docker

First, install Docker (https://docs.docker.com/engine/install/). Using Docker, you can avoid building and installing the simulation engine dependencies.

If using a package manager, like homebrew for mac, use brew install --cask docker then open the Docker app in Applications/ and give it permissions.

Installation with pyenv + conda

To see all pyenv versions:

pyenv install list

To install a particular version of python (or conda):

pyenv install anaconda3-5.3.1

Install dependencies using pyenv + conda:

pyenv local anaconda3-5.3.1 # or whatever version you have installed
pyenv virtualenv vivarium-models
pyenv local vivarium-models
conda env update -f env.yml

Installation with conda alone

Install conda: https://docs.conda.io/en/latest/miniconda.html

Using conda, you can run

conda env create -f env.yml
conda activate vivarium-models

which will create and then activate a conda environment called vivarium-models with all the required dependencies (including ReaDDy) installed.

To update:

conda env update -f env.yml

Alternatively:

Stable Release: pip install vivarium_models (coming soon)
Development Head: pip install git+https://github.com/simularium/vivarium-models.git

ReaDDy models depend on ReaDDy, which requires conda. Install ReaDDy with conda install -c readdy/label/dev readdy after adding the conda-forge channel conda config --add channels conda-forge

Documentation

For full package documentation please visit simularium.github.io/vivarium_models.

Development

See CONTRIBUTING.md for information related to developing the code.

Commands You Need To Know

  1. black vivarium_models

    This will fix lint issues.

  2. make build

    This will run tox which will run all your tests as well as lint your code.

  3. make clean

    This will clean up various Python and build generated files so that you can ensure that you are working in a clean environment.

  4. make docs

    This will generate and launch a web browser to view the most up-to-date documentation for your Python package.