Skip to main content

Cluster Reconstruction of Observables Workbench

Project description

CROW

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. The code documentation can be found at https://lsstdesc.org/crow/.

Table of contents

  1. Installing CROW
  2. Using CROW
  3. Contributing to CROW
  4. Contact

Installing Crow

Crow can be installed with pip or conda.

For a pip installation, run:

pip install lsstdesc-crow

For a conda installation, run:

conda install -c conda-forge lsstdesc-crow

After, to use is in your code, just do

import crow

Requirements

Crow requires Python version 3.11 or later.

Dependencies

Crow has the following dependencies:

Optional Dependencies

  • NumCosmo — required only for the NumCosmoIntegrator. If not installed, all other functionality remains available. NumCosmo is only available via conda, not pip:
  conda install -c conda-forge numcosmo

Using Crow

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.

Contributing to Crow

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.

Updating Public Documentation on lsstdesc.org

This is easy! Once you have merged all approved changes into main, you will want to update the public documentation. Just go to the publish-docs branch (git checkout publish-docs) and run the ./publish_docs script.

Contact

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)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

lsstdesc_crow-1.0.9.tar.gz (41.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

lsstdesc_crow-1.0.9-py3-none-any.whl (36.2 kB view details)

Uploaded Python 3

File details

Details for the file lsstdesc_crow-1.0.9.tar.gz.

File metadata

  • Download URL: lsstdesc_crow-1.0.9.tar.gz
  • Upload date:
  • Size: 41.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for lsstdesc_crow-1.0.9.tar.gz
Algorithm Hash digest
SHA256 c5ae390e0056101000fdbe09a1073f18c1f13ff2efbeb356ec8e0414167b9395
MD5 b603bcc98790ba7ca0a9d9ff1f29e07e
BLAKE2b-256 9eeb5c38cf89f27c2c8131234fdbd8744d42c3b124e8b7b4829372c9c2b1489d

See more details on using hashes here.

Provenance

The following attestation bundles were made for lsstdesc_crow-1.0.9.tar.gz:

Publisher: publish.yml on LSSTDESC/crow

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file lsstdesc_crow-1.0.9-py3-none-any.whl.

File metadata

  • Download URL: lsstdesc_crow-1.0.9-py3-none-any.whl
  • Upload date:
  • Size: 36.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for lsstdesc_crow-1.0.9-py3-none-any.whl
Algorithm Hash digest
SHA256 a91191099ac2b4e862473d1d1a09116d32afea05a13f1ab4a67d65291e1a65e6
MD5 08d2ceec3f62b2d96ec882aca1a08d25
BLAKE2b-256 b28966b120710a7ca717afbbf98a1e1e49dbd37ce032a84145cccda0a7aa3709

See more details on using hashes here.

Provenance

The following attestation bundles were made for lsstdesc_crow-1.0.9-py3-none-any.whl:

Publisher: publish.yml on LSSTDESC/crow

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page