Library for differentiable generation of synthetic skies for LSST DESC
Project description
lsstdesc-diffsky is a python library based on JAX for producing mock catalogs tailored to LSST DESC science requirements.
Installation
The latest release of lsstdesc-diffsky is available for installation with pip or conda-forge:
$ conda install -c conda-forge lsstdesc-diffsky
To install lsstdesc-diffsky into your environment from the source code:
$ cd /path/to/root/lsstdesc-diffsky $ pip install .
Conda environment
For a typical development environment in conda:
$ conda create -c conda-forge -n diffstuff python=3.9 numpy jax pytest ipython jupyter matplotlib scipy h5py diffmah diffstar dsps diffsky lsstdesc-diffsky
Documentation
Online documentation for lsstdesc-diffsky is available at lsstdesc-diffsky.readthedocs.io
Testing
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
Available Catalogs
A prototype catalalog is available at NERSC and is called skysim_v3.1.0
Working at NERSC
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.
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