edge_pydb

Python-based database for the Extragalactic Database for Galaxy Evolution (EDGE). This package requires Python 3.

The EDGE database has several components (see index_csv.md and index_hdf.txt for details):

Zero-dimensional CSV tables (one value per galaxy), found in dat_glob.
One-dimensional CSV tables (e.g. radial profiles or spectra), found in dat_prof and dat_spec.
Downsampled 2D or 3D images, saved as HDF5 binary tables in the img_ directories, or as large HDF5 files in a user-specified area.

Installation

Required packages are:

Also needed for building the database (but not for general use) are:

Install the package directly from PyPI (https://pypi.org/project/edge-pydb/) using

pip install --user edge_pydb

or, if you prefer to keep the latest source code handy, by cloning this Github repository and running

pip install --user .

in the directory containing setup.py.

The --user flag ensures the package is not installed in your system-wide Python directories, which you may not have write access to. The package tries to save and update a configuration file _config.json, which provides the paths to all the database tables, so installation in your user area is recommended. Alternatively, you may save the configuration file in a different location using (e.g.):

import edge_pydb.util as edgeutil
edgeutil.save_config('/path/to/config.json')

You will then need to load this file whenever you start the package:

edgeutil.load_config('/path/to/config.json')

To uninstall you may use

pip uninstall edge_pydb

but note that the _config.json will not be removed, so to fully uninstall you will need to delete the edge_pydb directory manually using (e.g.):

rm -r ~/Library/Python/3.9/lib/python/site-packages/edge_pydb/

Merging in large data sets

The Github package only contains data for a single galaxy (NGC 4047), for demonstration and testing purposes. Larger data files can be downloaded from Zenodo:

HDF5 Files for CARMA EDGE

It is recommended that you unpack additional files into a single directory that is easily accessible on your file system, and not embedded within your Python libraries (site-packages area). Here is the suggested way to incorporate these into your runtime environment.

Leave the git directory in which this README is located. (This ensures that the package runs from your site-packages area and not the current directory.) Open an iPython shell and type:

import edge_pydb.util as edgeutil
edgeutil.listfiles(values=True)

This should show only the Github data installed in site-packages. Now suppose the additional data files are in a folder called pybase. Then type:

edgeutil.add_from_dir('/path/to/pybase/', max_depth=0, copy=False)

to add the additional files to your environment. This only needs to be done once after package installation, unless you add new files to pybase. Here the max_depth=0 parameter prevents files in subdirectories from being added. Use the listfiles command above to verify that the expected tables are available.

Basic Usage

from edge_pydb import EdgeTable
EdgeTable('list')

makes a listing of the available files.

ctrpos = EdgeTable('edge_coflux_smo7.csv')

loads a CSV file. ctrpos can now be treated like an astropy table, for example ctrpos.info() will summarize the contents and ctrpos.pprint() will print some of the data.

ctrpos = EdgeTable('edge_coflux_smo7.csv', cols=['Name', 'coRactr_smo7', 'coDectr_smo7'])

loads the three specified columns only from the CSV file.

leda = EdgeTable('edge_leda.csv', cols=['Name', 'ledaD25', 'ledaPA', 'ledaIncl'])
ctrpos.join(leda)

will merge a sub-table from edge_leda.csv into ctrpos. We must select the Name column from both tables for the join to work.

comom = EdgeTable('NGC4047.2d_smo7.hdf5', path='comom_smo')

loads an HDF5 file. The path must be given, otherwise a listing of available paths is provided.

A demo_notebk folder and various subfolders provide examples of accessing and plotting database values in a Jupyter notebook.

HDF5 File Contents

Detailed listings of the HDF5 files are provided in index_hdf.txt at the top level. Note that while each HDF5 file can bundle several tables or "paths," only one path can be read into EdgeTable at a time.

[label].pipe3d.hdf5: These are CALIFA data products from Pipe3D. As described in Sanchez et al. (2016a), there are five collections of images, bundled as ELINES, SFH, SSP, flux_elines, and indices. These are also the names of the five paths in the HDF5 file. Pixels are sampled from the original astrometric grid of CALIFA DR3, so these tables should not be joined with tables in the other HDF5 files. Additional columns in the ELINES and flux_elines tables provide calculated star formation rates, Hα extinctions, metallicities, and BPT classifications.
[label].2d_smo7.hdf5: These contain the CARMA CO moment maps and the matched resolution CALIFA data, and are thus likely to be the key files for your analysis. All are at a resolution of 7 arcsec (FWHM Gaussian beam), with astrometric grid defined by the CARMA images. CO moment maps were generated using three different methods (str, dil, smo), with each method being a separate table (path) within the HDF5 file. The straight (str) moment maps are generated without masking and have very poor signal-to-noise. To reject noise, the dilated (dil) moment maps use a dilated mask that starts at a high significance contour (3.5σ or greater in two consecutive channels) and expands to a surrounding 2σ contour. The smoothed (smo) moment maps use a mask that is obtained by smoothing the cube spatially (to 14") before constructing a dilated mask. For most purposes the dilated masks produce the best results. For the CALIFA data, which are found in separate tables named ELINES_sm etc., a separate run of Pipe3D has been performed on the smoothed CALIFA data, after matching to the 7" CARMA resolution.
[label].cocube_smo7.hdf5: These contain the CARMA CO data cubes and mask cubes, at a resolution of 7 arcsec (FWHM Gaussian beam). These tables have the same astrometric grid as those in [label].2d_smo7.hdf5 and can be joined with those tables (but note values in the 2D table will be replicated along the velocity axis).

Available datasets will expand over time, but current values for [label] include edge_carma (which uses a square sampling grid spaced by 3", sufficient for Nyquist sampling the CARMA beam), edge_carma_hex (which uses a hexagonal sampling grid and is still experimental) and edge_carma_allpix (all pixel values saved, resulting in much longer tables).

References

For more information about the CALIFA Data Release 3:

Sanchez et al. (2016b), "CALIFA, the Calar Alto Legacy Integral Field Area survey. IV. Third public data release."

For more information about EDGE:

Bolatto et al. (2017), "The EDGE-CALIFA Survey: Interferometric Observations of 126 Galaxies with CARMA."

If you use this package in a publication please also cite: