Installation
If you're familiar with Python, you
can install PTArcade with pip
or conda
, the Python package manager.
If not, we recommend using a docker
or singularity
virtual environment.
With conda (recommended)¶
PTArcade is now available on conda-forge! you can install PTArcade using conda by typing in a terminal (1)
- See here for conda installation info.
- If you want to install PTArcade in a new environment, run
This will install PTArcade and all the required dependencies in a conda environment named ptarcade
. PTArcade will download and cache the following PTA datasets at runtime:
NANOGrav 12.5-year, NANOGrav 15-year, and IPTA DR2.
With pip¶
PTArcade is also published as a PyPI package and can be installed with
pip
, ideally by using a virtual environment. Open up a terminal
and install PTArcade with:
- We suggest to install PTArcade in a virtual environment. You can do so by running
This will automatically install compatible versions of all Python dependencies and, as for the conda installation, download the following PTA datasets at runtime: NANOGrav 12.5-year, NANOGrav 15-year, and IPTA DR2.
Non-Python Dependencies
If you choose to install from PyPI, you'll need to get the non-Python dependencies yourself.
libstempo
needs tempo2. You can install it by typing in a terminal-
sckit-sparse
needs suitesparse. You can install it by typing in a terminal -
mpi4py
needs an MPI implementation. You can install it by typing in a terminal
With docker¶
The official Docker image is a great way to get up and running in a few minutes, as it comes with all dependencies pre-installed. Open up a terminal and pull the image with:
With singularity¶
A singularity environment with all the necessary dependencies already installed can be downloaded by typing
This will create a Singularity image and save it asptarcade.sif
in the current working directory.
On Apple silicon¶
If you're using a Mac with Apple silicon, there are some dependencies of PTArcade that are not available for your architecture.
We recommend using conda
and specifying osx-64
as your platform so that the dependencies can be installed.
If you have a recent version of conda
(>=23.10.0), you can use the following to set up your environment: