There are lots of ways of installing
asimov, and the best way of getting access to it depends both on your local setup, and on whether you have access to IGWN computing resources.
asimov was initially designed for use in analysing gravitational wave detector data, and so some of the information in this manual will be aimed directly at users from that background.
The simplest method for installing
asimov is to use the latest released version from
pypi, the python package index.
We always recommend installing in a virtual environment.
To create a new virtual environment you can run
$ mkdir environment
$ python -m venv environment
You can then “activate” the environment by running
$ source environment/bin/activate
You’ll need to run this activation step each time you open a new terminal when you want to use
You can then install asimov using
It is also possible to install asimov in a conda environment from conda forge.
You can do this by ensuring that your conda environment is activated, and then running
$ conda install -c conda-forge ligo-asimov
Installation from source
If you want to run unreleased code you can do this by installing directly from the asimov git repository.
The quickest way to do this is to run
$ pip install git+https://git.ligo.org/asimov/asimov.git
You should use the package with care if installing from source; while the master branch should represent stable code, it may contain new or undocumented features, or behave unexpectedly.
Installation for development
If you want to develop code in the
asimov repository then it can be helpful to install in development mode.
First clone a copy of the
asimov repository, for example by running
$ git clone https://git.ligo.org/asimov/asimov.git
Then you can install this repository into your current virtual environment by running
$ cd asimov
$ pip install -e .
Using an IGWN Environment
If you have access to IGWN compute facilities, such as the LIGO Data Grid, then you can use an IGWN environment to run asimov.
Asimov is pre-installed in both testing and deployed environments, so you should be able to access it on the cluster simply by activating one of these environments.
$ conda activate igwn-py39