hostphot 2.7.1

Global and local photometry of galaxies hosting supernovae or other transients

Global and local photometry of galaxies hosting supernovae or other transients

Read the full documentation at hostphot.readthedocs.io. It is recommended to read the Further Information section to understand how HostPhot works.

---

Conda environment

It is recommended to create an environment before installing HostPhot:

conda create -n hostphot pip
conda activate hostphot
pip install hostphot

Requirements

HostPhot has the following requirements:

numpy
pandas
matplotlib
python-dotenv
astropy
reproject
photutils
astroquery
extinction
sfdmap
pyvo
sep
ipywidgets (optional: for interactive aperture)
ipympl (optional: for interactive aperture)
ipython (optional: for interactive aperture)
pytest (optional: for testing the code)

Tests

To run the tests, go to the parent directory and run the following command:

pytest -v

Modules

Cutouts

This module allows you to download image cutouts from different surveys (e.g. PS1):

from hostphot.cutouts import download_images

name = 'SN2004eo'
host_ra, host_dec = 308.2092, 9.92755  # coords of host galaxy of SN2004eo
survey = 'PS1'
download_images(name, host_ra, host_dec, survey=survey)

Image Pre-processing

Coadds can be created and stars can be masked out of the images:

from hostphot.coadd import coadd_images

coadd_filters = 'riz'
coadd_images(name, filters=coadd_filters, survey=survey)  # creates a new fits file

from hostphot.image_masking import create_mask

# one can extract the mask parameters from the coadd
# this also creates new fits files
coadd_mask_params = create_mask(name, host_ra, host_dec,
                                filt=coadd_filters, survey=survey,
                                extract_params=True)  

for filt in 'grizy':
    create_mask(name, host_ra, host_dec, filt, survey=survey,
                common_params=coadd_mask_params)

If the user is not happy with the result of the masking, there are a few parameters that can be adjusted. For instance, threshold sets the threshold used by sep for detecting objects. Lowering it will allow the detection of fainter objects. sigma is the width of the gaussian used for convolving the image and masking the detected objects. If crossmatch is set to True, the detected objects are cross-matched with the Gaia catalog and only those in common are kept. This is useful for very nearby host galaxies (e.g. that of SN 2011fe) so the structures of the galaxy are not maked out, artificially lowering its flux.

Local Photometry

Local photometry can be obtained for multiple circular apertures:

import hostphot.local_photometry as lp

ap_radii = [3, 4]  # aperture radii in units of kpc
ra, dec =  308.22579, 9.92853 # coords of SN2004eo
z = 0.0157  # redshift

results = lp.multi_band_phot(name, ra, dec, z,
                             survey=survey, ap_radii=ap_radii, 
                             use_mask=True, correct_extinction=True,
                             save_plots=True)

If the results return NaN values, this means that the flux is below the detection limit for the given survey.

Global Photometry

Global photometry can be obtained in a similar way to local photometry, using common aperture:

import hostphot.global_photometry as gp

results = gp.multi_band_phot(name, host_ra, host_dec, 
                             survey=survey, ra=ra, dec=dec,
                             use_mask=True, correct_extinction=True,
                             common_aperture=True, coadd_filters='riz', 
                             save_plots=True)

By default, HostPhot corrects for Milky Way extinction using the recalibrated dust maps by Schlafly & Finkbeiner (2011) and the extinction law from Fitzpatrick (1999).

Surveys List

This is the list of surveys in HostPhot:

• DES
• PS1
• SDSS
• GALEX
• 2MASS
• WISE
• unWISE
• Legacy Survey
• Spitzer (SEIP)
• VISTA (VHS, VIDEO, VIKING)

Contributing

To contribute, either open an issue or send a pull request (prefered option). You can also contact me directly (check my profile: https://github.com/temuller).

Adding other surveys

If you wish a survey to be added to HostPhot, there are a couple of ways of doing it. 1) You can do a pull request, following the same structure as used for the surveys that are already implemented, or 2) open an issue asking for a survey to be added. Either way, there are a fews things needed to add a survey: where to download the images from (e.g., using astroquery), zero-points to convert the images's flux/counts values into magnitudes, the magnitude system (e.g. AB, Vega), the pixel scaling of the images (in units of arcsec/pixel), the filters transmission functions and any other piece of information necessary to properly estimate magnitudes, errors, etc. If you open an issue asking for a survey to be added, please include all this information. For more information, please check the Adding New Surveys section of the documentation.

Citing HostPhot

If you make use of HostPhot, please cite the following paper:

@article{Müller-Bravo2022, 
  author = {Tomás E. Müller-Bravo and Lluís Galbany},
  title = {HostPhot: global and local photometry of galaxies hosting supernovae or other transients},
  doi = {10.21105/joss.04508}, 
  url = {https://doi.org/10.21105/joss.04508}, 
  year = {2022}, 
  publisher = {The Open Journal}, 
  volume = {7}, 
  number = {76}, 
  pages = {4508},  
  journal = {Journal of Open Source Software} 
} 

What's new!

v2.7.1

• Adding SED plotting
• Fixed plotting angle of masked object v2.7.0
• MAJOR BUG: Convertion factor between different pixel scales fixed (it was previously inverted). This affects the common aperture photometry between different surveys!
• Moving font family to _constant.py file v2.6.2
• Prettier plots (now using aplpy), but also more informative!
• Scale of the apertures for the masks is now a parameter (r)
• Raise exception is now True by default when calculating photometry v2.6.1
• 2MASS cutouts improved (picking largest image) v2.6.0:
• HST (WFC3 only - pseudo-trial) included
• 2MASS cutouts fixed (it now downloads the image closest to the given coordinates) v2.5.1:
• Using sfdmap2 instead of sfdmap to avoid issues with numpy version (requires Python>=3.9) v2.5.0:
• Systematic error floor added to PS1 photometry
• Added missing uncertainties in the error budget of DES (~5 mmag)
• Flux/counts have been added to output photometry
• GALEX now downloads images with largest exposure time by default
• Fixed image realignment/orientation between different surveys when using common apertures (for masking and global photometry)
• Added option to output mask parameters, and also aperture parameters for global photometry
• Option added to set a distant threshold to identify the host galaxy in the image (by default use the nearest object)
• Slight change in the column names of the local photometry output file
• Offsets in SDSS zeropoints to place it in the AB system
• overwrite set to True by default when downloading image cutouts
• Other minor bugs fixed

v2.4.0:

• Fixed and improved GALEX cutouts
• Better galaxy identification
• Better output plots for masked images
• Option to return NaN or raise an exception when getting photometry

v2.3.2:

• Improved download of GALEX images (download even if they seem to be just background noise)

Acknowledgements

I thank Yuchen LIU for helping me adding Spitzer as part of AstroHackWeek 2022.