lsstdesc-diffsky is a python library based on JAX for producing mock catalogs tailored to LSST DESC science requirements.
The latest release of lsstdesc-diffsky is available for installation with pip. It is important to use consistent versions of the Diff+ libraries, particularly diffmah, diffstar, and dsps. To do so, we recommend starting from a base environment of jax managed by conda-forge using /path/to/lsstdesc-diffsky/requirements.txt as follows:
$ conda create -c conda-forge -n diffsky_env python=3.9 --file=requirements.txt $ conda activate diffsky_env
Online documentation for lsstdesc-diffsky is available at lsstdesc-diffsky.readthedocs.io
To run the suite of unit tests:
$ cd /path/to/root/lsstdesc-diffsky $ pytest
To build html of test coverage:
$ pytest -v --cov --cov-report html $ open htmlcov/index.html
The mock catalalog generated for the Roman/Rubin 2023 image simulations is available at NERSC and is called roman_rubin_2023_v1.1.2.
If you want to use the desc-python environment at NERSC, you will need to add lsstdesc-diffsky and its dependencies yourself. The directions for cloning and adding packages to the environment can be found here. Once you have built the basic environment, you will need to activate it and install lsstdesc-diffsky and its dependencies. Note that the appropriate version of the diffsky codes can vary with the mock being used.
If you wish to use the code in a jupyter notebook, you will also need to install a python kernel as follows:
$ python -m ipykernel install --user --name=my_kernel_name
demo_load_catalog is a demo notebook showing how to load the catalog from a notebook running at NERSC and perform some basic operations.