Cluster Reconstruction of Observables Workbench: CROW
The LSST-DESC Cluster Reconstruction of Observables Workbench (CROW) code is a DESC tool consisting of a Python library for predicting galaxy cluster observabless.
Crow can be installed with pip or conda.
For a pip installation, run:
pip install lsstdesc-crowFor a conda installation, run:
conda install -c conda-forge lsstdesc-crowAfter, to use is in your code, just do
import crowCrow requires Python version 3.11 or later.
Crow has the following dependencies:
This code has been released by DESC, although it is still under active development. You are welcome to re-use the code, which is open source and available under terms consistent with our LICENSE (BSD 3-Clause).
Example usage can be found in the notebooks folder.
DESC Projects: External contributors and DESC members wishing to use Crow for DESC projects should consult with the DESC Clusters analysis working group (CL WG) conveners, ideally before the work has started, but definitely before any publication or posting of the work to the arXiv.
Non-DESC Projects by DESC members: If you are in the DESC community, but planning to use Crow in a non-DESC project, it would be good practice to contact the CL WG co-conveners and/or the Crow Team leads as well (see Contact section). A desired outcome would be for your non-DESC project concept and progress to be presented to the working group, so working group members can help co-identify tools and/or ongoing development that might mutually benefit your non-DESC project and ongoing DESC projects.
External Projects by Non-DESC members: If you are not from the DESC community, you are also welcome to contact Crow Team leads to introduce your project and share feedback.
You are welcome to contribute to the code. To do so, please make sure
you use isort and black on your code and assure you provide unit tests.
If you have comments, questions, or feedback, please contact the current leads of the LSST DESC Crow Team: Michel Aguena (m-aguena, aguena@inaf.it) and Eduardo Barroso (eduardojsbarroso, barroso@lapp.in2p3.fr)