lisacattools

Python module for interacting with example LISA catalogs

1 - Getting Started

These instructions will get you a copy of the project up and running on your local machine, either for development and testing purposes or as an installed package. For more information, see the documentation at https://lisa-analysis-center.github.io/lisacattools.

1.1 - Prerequisites

You will need python3 to run this program.

1.2 - Installing by cloning the repository

First, we need to clone the repository

git clone https://github.com/tlittenberg/lisacattools.git

1.2.1 - For users

To install the package for non-root users:

make user

To install the package on the root system:

make

1.2.2 - For developers

Create a virtualenv

make prepare-dev
source ..venv

Install the sotfware and the external libraries for development purpose

make install-dev

1.3 - Installing by pip

pip install lisacattools

2 - Development (only if the repository has be cloned)

2.1 - Writing the code

Install the software by PIP (developers version)

Then, develop your code and commit

git commit

The tests and code style formatter will be run automatically. To ignore the checks, do

git commit --no-verify

2.2 - Running the tests

make test

2.3 - Testing on python 3.8,3.9,3.10

Install all required prerequisite dependencies:

sudo apt-get update; sudo apt-get install make build-essential libssl-dev zlib1g-dev \
libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm \
libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev

Download and execute installation script: 

curl https://pyenv.run | bash

Add the following entries into your ~/.bashrc file:

# pyenv
export PATH="$HOME/.pyenv/bin:$PATH"
eval "$(pyenv init --path)"
eval "$(pyenv virtualenv-init -)"

Restart your shell:

exec $SHELL

Validate installation:

pyenv --version

Once the dependencies are installed, test on python 3.8, 3.8 and 3.10 :

make tox

3 - Running the tutorial

Once the software is installed, data must be downloaded for the tutorial. The data are downloaded from a google drive and are large files -- ~10GB in total -- and will be installed in tutorial/data. Datasets include a catalog of simulated MBH detections with parameters updated on a weekly cadence, and two UCB catalogs, using 3 and 6 months of simulated LISA data.

make data

Then install jupyter and run the tutorial

make demo

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

• James I. Thorpe, Tyson B. Littenberg - Initial work
• Jean-Christophe Malapert

License

This project is licensed under the Apache 2.0 License - see the LICENSE file for details