The dataset viewer is not available for this subset.
Exception: SplitsNotFoundError Message: The split names could not be parsed from the dataset config. Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 159, in compute compute_split_names_from_info_response( File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 131, in compute_split_names_from_info_response config_info_response = get_previous_step_or_raise(kind="config-info", dataset=dataset, config=config) File "/src/libs/libcommon/src/libcommon/simple_cache.py", line 567, in get_previous_step_or_raise raise CachedArtifactError( libcommon.simple_cache.CachedArtifactError: The previous step failed. During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 499, in get_dataset_config_info for split_generator in builder._split_generators( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 88, in _split_generators raise ValueError( ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 75, in compute_split_names_from_streaming_response for split in get_dataset_split_names( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 572, in get_dataset_split_names info = get_dataset_config_info( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 504, in get_dataset_config_info raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314,000 Galaxies
Dataset Schema
This schema describes the columns in the GZ DECaLS catalogues; gz_decals_auto_posteriors
, gz_decals_volunteers_1_and_2
, and gz_decals_volunteers_5
.
In all catalogues, galaxies are identified by their iauname
. Galaxies are unique within a catalogue. gz_decals_auto_posteriors
contains all galaxies with appropriate imaging and photometry in DECaLS DR5, while gz_decals_volunteers_1_and_2
, and gz_decals_volunteers_5
contain subsets classified by volunteers in the respective campaigns.
The columns reporting morphology measurements are named like {some-question}_{an-answer}
. For example, for the first question, both volunteer catalogues include the following:
Column | Description |
---|---|
smooth-or-featured_total | Total number of volunteers who answered the "Smooth of Featured" question |
smooth-or-featured_smooth | Count of volunteers who responded "Smooth" to the "Smooth or Featured" question |
smooth-or-featured_featured-or-disk | Count of volunteers who responded "Featured or Disk", similarly |
smooth-or-featured_artifact | Count of volunteers who responded "Artifact", similarly |
smooth-or-featured_smooth_fraction | Fraction of volunteers who responded "Smooth" to the "Smooth or Featured" question, out of all respondes (i.e. smooth count / total) |
smooth-or-featured_featured-or-disk_fraction | Fraction of volunteers who responded "Featured or Disk", similarly |
smooth-or-featured_artifact_fraction | Fraction of volunteers who responded "Artifact", similarly |
The questions and answers are slightly different for gz_decals_volunteers_1_and_2
than gz_decals_volunteers_5
. See the paper for more.
The volunteer catalogues include {question}_{answer}_debiased
columns which attempt to estimate what the vote fractions would be if the same galaxy were imaged at lower redshift. See the paper for more. Note that the debiased measurements are highly uncertain on an individual galaxy basis and therefore should be used with caution. Debiased estimates are only available for galaxies with 0.02<z<0.15, -21.5>M_r>-23, and at least 30 votes for the first question (`Smooth or Featured') after volunteer weighting.
The automated catalogue, gz_decals_auto_posteriors
, includes predictions for all galaxies and all questions even when that question may not be appropriate (e.g. number of spiral arms for a smooth elliptical). To assess relevance, we include {question}_proportion_volunteers_asked
columns showing the estimated fraction of volunteers that would have been asked each question (i.e. the product of the vote fractions for the preceding answers). We suggest a cut of {question}_proportion_volunteers_asked
> 0.5 as a starting point.
The automated catalogue does not include volunteer counts or totals (naturally).
Each catalogue includes a pair of columns to warn where galaxies may have been classified using an inappropriately large field-of-view (due to incorrect radii measurements in the NSA, on which the field-of-view is calculated). We suggest excluding galaxies (<1%) with such warnings.
Column | Description |
---|---|
wrong_size_statistic | Mean distance from center of all pixels above double the 20th percentile (i.e. probable source pixels) |
wrong_size_warning | True if wrong_size_statistic > 161.0, our suggested starting cut. Approximately the mean distance of all pixels from center |
For convenience, each catalogue includes the same set of basic astrophysical measurements copied from the NASA Sloan Atlas (NSA). Additional measurements can be added my crossmatching on iauname
with the NSA. See here for the NSA schema. If you use these columns, you should cite the NSA.
Column | Description |
---|---|
ra | Right ascension (degrees) |
dec | Declination (degrees) |
iauname | Unique identifier listed in NSA v1.0.1 |
petro_theta | "Azimuthally-averaged SDSS-style Petrosian radius (derived from r band" |
petro_th50 | "Azimuthally-averaged SDSS-style 50% light radius (r-band)" |
petro_th90 | "Azimuthally-averaged SDSS-style 50% light radius (r-band)" |
elpetro_absmag_r | "Absolute magnitude from elliptical Petrosian fluxes in rest-frame" in SDSS r |
sersic_nmgy_r | "Galactic-extinction corrected AB flux" in SDSS r |
redshift | "Heliocentric redshift" ("z" column in NSA) |
mag_r | 22.5 - 2.5 log10(sersic_nmgy_r). Not the same as the NSA mag column! |
@dataset{walmsley_mike_2020_4573248,
author = {Walmsley, Mike and
Lintott, Chris and
Tobias, Geron and
Kruk, Sandor J and
Krawczyk, Coleman and
Willett, Kyle and
Bamford, Steven and
Kelvin, Lee S and
Fortson, Lucy and
Gal, Yarin and
Keel, William and
Masters, Karen and
Mehta, Vihang and
Simmons, Brooke and
Smethurst, Rebecca J and
Smith, Lewis and
Baeten, Elisabeth M L and
Macmillan, Christine},
title = {{Galaxy Zoo DECaLS: Detailed Visual Morphology
Measurements from Volunteers and Deep Learning for
314,000 Galaxies}},
month = dec,
year = 2020,
publisher = {Zenodo},
version = {0.0.2},
doi = {10.5281/zenodo.4573248},
url = {https://doi.org/10.5281/zenodo.4573248}
}
- Downloads last month
- 58