Installation and Environment#

This page summarizes how to set up an environment for running GWIAS-HM.

Required packages#

Core dependencies from the repository README:

numpy
scipy
matplotlib
scikit-learn
pandas
gsl
lal
lalsimulation
astropy
numba
multiprocess
cogwheel

Optional but recommended#

torch
lightning
nflows
corner
jupyterlab

Suggested setup workflow#

Create and activate your environment manager of choice (for example Conda).
Install the required scientific stack listed above.
Install optional ML/notebook packages if you plan to run prior-learning workflows.
Verify that key imports succeed from the repository root.

Quick import check#

From the repository root, run:

python - <<'PY'
import numpy, scipy, pandas, matplotlib, astropy, numba, multiprocess
print("Core Python dependencies import successfully.")
PY

Notes#

Some workflows rely on LIGO-related libraries and data-access tooling.
Cluster workflows and large-scale runs may need additional site-specific configuration.
For documentation building requirements specifically, see docs/sphinx/requirements.txt.