GCRCatalogs is a Python package that serves as a repository of various galaxy catalogs and sky catalogs for the LSST Dark Energy Science Collaboration (DESC). It provides a unified user interface to access all catalogs by using the Generic Catalog Reader (GCR) base class.

This package is also used by the DESCQA validation framework, and the concept and description of this reader interface can be found in the DESCQA paper and also the GCR repo.

The instructions below are intended for DESC members. If you are using public DESC data sets with GCRCatalogs, please follow the instructions on the DESC Data Portal: data.lsstdesc.org.

Below is a list of most-used catalogs. To find a complete, most up-to-date list of all available catalogs, run the following code:

import GCRCatalogs

# List all catalogs that are recommended for general consumption
GCRCatalogs.get_available_catalog_names()

# List all catalogs, including those may not be intended for general consumption
GCRCatalogs.get_available_catalog_names(include_default_only=False)

# List all catalogs whose names contain the word "object"
GCRCatalogs.get_available_catalog_names(include_default_only=False, name_contains="object")

# List all catalogs whose names start with the word "buzzard"
GCRCatalogs.get_available_catalog_names(include_default_only=False, name_startswith="buzzard")

(Note: remove False in the above line to only see recommended catalogs.)

Each catalog is specified by a YAML config file, which can be found here.

You can also find an overview and more detailed description of all the data products of DESC Data Challenge 2 at the "DC2 Data Product Overview" Confluence page (DESC member only).

by Andrew Hearin, Eve Kovacs, Patricia Larsen, Esteban Rangel, Katrin Heitmann et al.

• roman_rubin_v1.1.3_elais: This catalog is a variant of roman_rubin_v1.1.2_elais that uses an improved tuning of the SED model parameters. The resulting luminosity distributions are in better agreement with the validation data (COSMOS 2020 and DESCQA tests).

• roman_rubin_v1.1.2_elais: This catalog was produced for the joint roman-desc image simulations using differentiable, forward modeling techniques. Predictions for the galaxy SEDs are based on their star-formation hsitories. Sky area covers the ELAIS field and is ~110 sq. deg.

• roman_rubin_v1.1.1_elais: DEPRECATED. This catalog was produced for the joint roman-desc image simulations using differentiable, forward modeling techniques. This catalog is deprecated as it contains a serious bug resulting in satellite galaxies that are too bright.

by Andrew Hearin, Danila Korytov, Eve Kovacs, Esteban Rangel, Patricia Larsen, Joe Hollowed, Andrew Benson, Katrin Heitmann et al.

• skysim5000_v1.2: latest SkySim5000 catalog, with bug fixes for ellipticity and concentration values; tidal torque fields added, full sky area (~5000 sq. deg.)
  • skysim5000_v1.2_image: same but only covers the image simulation sky area (~400 sq. deg.)
  • skysim5000_v1.2_small: same but only covers a small sky area (~50 sq. deg.) for testing purposes
  • skysim5000_v1.1.2: preliminary version of new SkySim5000 catalog, full sky area (~5000 sq. deg.) (0<z<1)
  • skysim5000_v1.1.1: previous SkySim5000 catalog, full sky area (~5000 sq. deg.)
  • skysim5000_v1.1.1_image: same but only covers the image simulation sky area (~400 sq. deg.)
  • skysim5000_v1.1.1_small: same but only covers a small sky area (~50 sq. deg.) for testing purposes
  • skysim5000_v1.1.1_parquet: same but using parquet files as the underlying format for better performance; no native quantities
  • skysim5000_v1.1.1_redmapper_v0.8.5: Redmapper catalog (v0.8.5) for skysim5000_v1.1.1 (provided by Eli Rykoff).
  • skysim5000_v1.1.1_redmagic_v0.8.5_highdens: Redmagic catalog (v0.8.5) for skysim5000_v1.1.1 for the high density sample (provided by Eli Rykoff).
  • skysim5000_v1.1.1_redmagic_v0.8.5_highlum: Redmagic catalog (v0.8.5) for skysim5000_v1.1.1 for the high luminosity sample (provided by Eli Rykoff).

by Andrew Benson, Andrew Hearin, Katrin Heitmann, Danila Korytov, Eve Kovacs, Patricia Larsen et al.

• cosmoDC2_v1.1.4_image: latest cosmoDC2 catalog (used for Run 2.1+)
• cosmoDC2_v1.1.4_small: 17 contiguous healpixels of cosmoDC2_v1.1.4_image for testing purposes
• cosmoDC2_v1.1.4_redmapper_v0.8.1: Redmapper catalog (v0.8.1) for cosmoDC2_v1.1.4_image (provided by Eli Rykoff).
• cosmoDC2_v1.1.4_redmagic_v0.8.1_highdens: Redmagic catalog (v0.8.1) for cosmoDC2_v1.1.4_image for the high density sample (provided by Eli Rykoff).
• cosmoDC2_v1.1.4_redmagic_v0.8.1_highlum: Redmagic catalog (v0.8.1) for cosmoDC2_v1.1.4_image for the high luminosity sample (provided by Eli Rykoff).
• cosmoDC2_v1.1.4_wazp_v1.0_truez: WaZP catalog (v1.0) for cosmoDC2_v1.1.4 using true redshifts (provided by Michel Aguena).
• cosmoDC2_v1.1.4_wazp_v1.0_flexzboost_v1: WaZP catalog (v1.0) for cosmoDC2_v1.1.4_image_with_photozs_flexzboost_v1 using FlexZBoost redshifts (provided by Michel Aguena).
• cosmoDC2_v1.1.4_image_with_photozs_v1 and cosmoDC2_v1.1.4_small_with_photozs_v1: containing photo-z for cosmoDC2 v1.1.4 (provided by Sam Schmidt)
• cosmoDC2_v1.1.4_image_with_photoz_calib and cosmoDC2_v1.1.4_small_with_photoz_calib: containing columns that identify DESI-like QSOs, LRGs, ELGs, or a magnitude limited sample in cosmoDC2 v1.1.4 (provided by Chris Morrison)

by Andrew Benson, Andrew Hearin, Katrin Heitmann, Danila Korytov, Eve Kovacs, Patricia Larsen et al.

• protoDC2: full catalog
• protoDC2_test: same as protoDC2 but this one skips time-consuming md5 check
• proto-dc2_vX.X_test.yaml: some other versions of the protoDC2 catalog

by Joe DeRose, Risa Wechsler, Eli Rykoff et al.

• buzzard: full catalog, DES Y3 area
• buzzard_test: same as buzzard but a small subset for testing purpose / faster access
• buzzard_high-res: higher resolution, smaller sky area
• buzzard_v2.0.0_x: different realizations of the version of the buzzard catalog documented in arXiv:1901.02401.

by LSST DESC, compiled by the DC2 Team

• dc2_truth_run3.1i_agn_auxiliary_info: Useful derived information for AGN.
• dc2_truth_run3.1i_agn_truth_summary: AGN truth summary table.
• dc2_truth_run3.1i_agn_variability_truth: AGN variable truth information
• dc2_truth_run3.1i_lensed_agn_truth_summary: Truth summary table for lensed AGN.
• dc2_truth_run3.1i_lensed_agn_variability_truth: Variable truth information for lensed AGN.
• dc2_truth_run3.1i_lensed_host_truth_summary: Truth summary table for lensed host galaxies.
• dc2_truth_run3.1i_lensed_sne_truth_summary: Truth summary table for lensed SNe.
• dc2_truth_run3.1i_lensed_sn_variability_truth: Variable truth information for lensed SNe.

• dc2_object_run2.2i_dr6: static object catalog for Run 2.2i DR6 (WFD and DDF visits; a small sky region in the upper right corner of the footprint was excluded in the current version (v1))
• dc2_object_run2.2i_dr6_with_addons: same as dc2_object_run2.2i_dr6 but with all available add-on catalogs (currently including metacal and truth-match; photo-z add-on not yet available. Use dc2_object_run2.2i_dr6a_with_photoz for a preview of photo-z.)
• dc2_redmapper_run2.2i_dr6_wfd_v0.8.1: Redmapper catalog (v0.8.1) for dc2_object_run2.2i_dr6 (provided by Eli Rykoff).
• dc2_redmagic_run2.2i_dr6_wfd_v0.8.1_highdens: Redmagic catalog (v0.8.1) for dc2_object_run2.2i_dr for the high density sample (provided by Eli Rykoff).
• dc2_redmagic_run2.2i_dr6_wfd_v0.8.1_highlum: Redmagic catalog (v0.8.1) for dc2_object_run2.2i_dr for the high luminosity sample (provided by Eli Rykoff).

• dc2_object_run2.2i_dr2_wfd: static object catalog for Run2.2i DR2 (WFD visits)
• dc2_object_run2.2i_dr2_wfd_with_addons: same as dc2_object_run2.2i_dr2_wfd but with all available add-on catalogs (currently including only truth-match; metacal, photo-z not yet available)

Note: DR3 processing is not fully completed; a few tracts are missing. Here dr3a is a preview of DR3.

• dc2_object_run2.2i_dr3a: static object catalog for Run 2.2i DR3 (preview)
• dc2_object_run2.2i_dr3a_with_metacal: dc2_object_run2.2i_dr3a + metacal (preview; missing more tracts)
• dc2_object_run2.2i_dr3a_with_photoz: dc2_object_run2.2i_dr3a + photo-z (preview)

• dc2_run2.2i_truth_merged_summary: combined truth summary table (galaxies, stars, SNe); partitioned by tract.
• dc2_run2.2i_truth_galaxy_summary: galaxy truth summary table, partitioned by healpixel, like cosmoDC2.
• dc2_run2.2i_truth_sn_summary: SN truth summary table.
• dc2_run2.2i_truth_sn_variability: SN variability truth information.
• dc2_run2.2i_truth_star_summary: star truth summary table.
• dc2_run2.2i_truth_star_variability: star variability truth information.

• dc2_object_run1.2i: static object catalog for Run 1.2i (with only DPDD columns and native columns needed for the DPDD columns)
• dc2_object_run1.2i_with_photoz: same as dc2_object_run1.2i but with photo-z's (columns that start with photoz_). Photo-z provided by Sam Schmidt.
• dc2_object_run1.2i_all_columns: static object catalog for Run 1.2i (with DPDD and all native columns, slower to access)
• dc2_object_run1.2i_tract4850, dc2_object_run1.2i_tract5063: same as dc2_object_run1.2i_all_columns but only has one tract for testing purpose / faster access
• dc2_object_run1.2p: static object catalog for Run 1.2p (with only DPDD columns and native columns needed for the DPDD columns)
• dc2_object_run1.2p_all_columns: static object catalog for Run 1.2p (with DPDD and all native columns, slower to access)
• dc2_object_run1.2p_tract4850: same as dc2_object_run1.2p_all_columns but only has one tract (4850)for testing purpose / faster access

• dc2_truth_run1.2_static: truth catalog for Run 1.2 (static objects only, corresponds to proto-dc2_v3.0)
• dc2_truth_run1.2_variable_lightcurve: light curves of variable objects in the truth catalog for Run 1.2
• dc2_truth_run1.2_variable_summary: summary table of variable objects in the truth catalog for Run 1.2

• dc2_dia_source_run1.2p_test: DIASource Table catalog for a test DIA processing of Tract+Paptch 4849+6,6 for Run 1.2p (with only DPDD columns and native columns needed for the DPDD columns).

• dc2_forced_source_run1.2p: Forced Source Table catalog for Run 1.2p (with only DPDD columns and native columns needed for the DPDD columns). This is the forced-position photometry based on the positions in the Object Table.

• dc2_source_run1.2i: Source Table catalog for Run 1.2i (with only DPDD columns and native columns needed for the DPDD columns)

• dc2_eimages_run1.2i_visit-181898: one visit of e-images for Run 1.2i
• dc2_eimages_run1.2p_visit-181898: one visit of e-images for Run 1.2p

All catalogs available in GCRCatalogs are physically located at NERSC (most are mirrored at IN2P3-CC as well). At NERSC, you need to be in the lsst user group to access them. You can find instructions about getting a NERSC account and joining lsst group at this Confluence page (DESC members only).

It is recommended that you first install DESC-specific kernels for your NERSC jupyter environment (you only need to do this once). To do so, log in to cori.nersc.gov and run:

source /global/common/software/lsst/common/miniconda/kernels/setup.sh

Detailed instructions can also be found at this Confluence page (DESC members only).

Then, you can start a NERSC notebook server and open a notebook with the desc-python or desc-stack kernel. GCRCatalogs and necessary dependencies are already installed in these two kernels. You can check if it works simply by running:

import GCRCatalogs

If you don't have these DESC-specific kernels installed, you can modify sys.path at run time (not recommended). At the very first cell of your notebook, run:

import sys
sys.path.insert(0, '/global/common/software/lsst/common/miniconda/current/lib/python3.6/site-packages')

You can activate DESC Python environment by running the following line on NERSC (needs to be in bash or zsh):

source /global/common/software/lsst/common/miniconda/setup_current_python.sh

If you want to use GCRCatalogs in a Python script, you can either activate DESC Python environment before you run the script, or edit the hashbang line of the script to be:

#!/global/common/software/lsst/common/miniconda/current/envs/stack/bin/python

If you need to use a newer version of GCRCatalogs than the one installed in the DESC Python environment, here's what you need to do:

1. Clone this repo (on a NERSC machine):

   git clone git@github.com:LSSTDESC/gcr-catalogs.git

   (Note that if you want to use a PR, you need to clone the corresponding branch.)

2. Add the path to sys.path in your notebook.

   import sys
   sys.path.insert(0, '/path/to/cloned/gcr-catalogs')

   (Note that if you use sys.path for the DESC Python environment, you should add the line above right after you insert the DESC Python environment.)

If you are running DESCQA and want to use your cloned GCRCatalogs, you can add the path to -p option:

./run_master.sh -t <tests> -c <catalogs> -p /path/to/cloned/gcr-catalogs

See more instrcutions for DESCQA here.

GCRCatalogs is also pip-installable, in case you need to install, say the master branch of GCRCatalogs in your own Python environment (no, in most cases you don't need this):

pip install https://github.com/LSSTDESC/gcr-catalogs/archive/master.zip

Here's the very basic usage of GCRCatalogs. Scroll down to see the example notebooks and more advanced usages.

import GCRCatalogs

# see all available catalogs
print(GCRCatalogs.get_available_catalogs(names_only=True))

# load a catalog
catalog = GCRCatalogs.load_catalog('protoDC2')

# load a catalog with runtime custom options
# (one needs to check catalog configs to know the keywords)
catalog = GCRCatalogs.load_catalog('cosmoDC2_v1.1.4_image', config_overwrite={'healpix_pixels': [8786, 8787, 8788]})
catalog = GCRCatalogs.load_catalog('dc2_object_run2.2i_dr6', config_overwrite={'tracts': [3638, 3639, 3640])

# see all available quantities
print(sorted(catalog.list_all_quantities()))

# load quantities
data = catalog.get_quantities(['ra', 'dec'])

• You can find quantity definitions in GCRCatalogs/SCHEMA.md.

• See this notebook for a detailed tutorial on how to use GCRCatalogs.

• See this notebook for a example of using the composite catalog feature.

• See this notebook for an actual application (the Conditional Luminosity Function test) using GCR Catalogs. (Thanks to Joe DeRose for providing the CLF test example!)

• You can find more tutorial notebooks that use GCRCatalogs in LSSTDESC/DC2-analysis.

• See also the GCR documentation for the complete GCR API.