PYPHOT – A tool for computing photometry from spectra

PYPHOT – A tool for computing photometry from spectra#

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This is a set of tools to compute synthetic photometry in a simple way, suitable for integration in larger projects.

Important

New major release (v2.0.0) which introduces new features and breaking changes.

See What’s new.

The inputs are response functions for the desired photometric passbands, and stellar spectra.

Filters are represented individually by a Filter object. Collections of filters are handled with a Library. We provide an internal library that contains a signitificant amount of common filters. Note that we use the word “filter” in a generic sense: in many cases it corresponds in fact to a total throughput, that includes the actual filter transmission, the transmission of the optics, the wavelength-dependent efficiency of the detector, and (for ground-based photometric systems) the transmission of the atmosphere.

Each filter is minimally defined by a wavelength, a throughput, and a detector type that may be either energy or photon (default). Many properties such as central or pivot wavelengths are computed internally.

Units are provided for the wavelengths of the filters, zero points in multiple units are also accessible (AB, Vega magnitude, Jy, erg/s/cm2/AA). The default detector is assumed to be a photon-counting device, but energy-sensitive detectors are also handled for the computations.

Note

Pyphot handles units from Astropy Units (as default), Pint, and EzUnits (ezunits). You can switch between them using the pyphot.config.set_units_backend() function.

import pyphot.config
pyphot.config.set_units_backend('astropy')
pyphot.config.set_units_backend('pint')
pyphot.config.set_units_backend('ezunits')

Package main content#

This package is mostly organized around 2 main classes:

  • Filter that handles filter definitions and manipulations.

  • Library that handles a collection of filters in a few formats.

Additionally, and for convenience

Documentation Contents#

Installation#

Pyphot is available on PyPI and can be installed using any common package manager.

  • Using pip: (Use the –user option if you don’t have permissions to install libraries)

https://img.shields.io/pypi/v/pyphot.svg 
pip install git+https://github.com/mfouesneau/pyphot

  • Manually from latest source on GitHub:

git clone https://github.com/mfouesneau/pyphot
cd pyphot
python setup.py intall

Internal Vega reference#

As mentioned in the above, sometimes a spectrum of reference of Vega is necessary.

By default, we use the synthetic spectrum alpha_lyr_stis_003 provided by Bohlin 2007, a common reference througout many photometric suites.

The interface to the Vega template is given through the pyphot.vega.Vega class.

Since v.1.7.0, additional flavors and description of the internal Vega reference can be found on the Details on the internal Vega reference spectra page.

To use a specific Vega flavor for the photometric calculations in Pyphot, you can set the vega keyword parameter when creating a passband or use the set_vega_flavor method to update it. For example, to use the alpha_lyr_stis_011 flavor when creating a passband filter, you can do the following:

from pyphot.astropy import UnitFilter, Unit as u

# Create a passband using the Vega flavor
pb = UnitFilter(
    [4000, 5000, 6000] * u.AA,
    [0.1, 0.8, 0.1],
    name="Example Passband",
    dtype="photon"
    vega="stis_011"  # Specify the Vega flavor,
)

Or alternatively, you can set/reset the Vega flavor after:

from pyphot import svo

pb = svo.get_pyphot_filter("GALEX/GALEX.FUV")
# Set the Vega flavor to use
pb.set_vega_flavor("stis_011")

Internal Sun reference#

We also provide observed and theoretical references for the solar spectrum following Colina, Bohlin, & Castelli 1996.

The observed solar spectrum comes from CALSPEC sun_reference_stis_001.fits which provides the ultraviolet to near-infrared absolute flux distribution of the Sun covering the 0.12-2.5 μm wavelength range. The solar reference spectrum combines absolute flux measurements from satellites and from the ground with a model spectrum for the near-infrared.

The theoretical spectrum comes from the Kurucz’93 atlas: sun_kurucz93.fitsftp://ftp.stsci.edu/cdbs/grid/k93models/standards/sun_kurucz93.fits The theoretical spectrum is scaled to match the observed spectrum from 1.5 - 2.5 microns, and then it is used where the observed spectrum ends. The theoretical model of the Sun uses the following parameters when the Sun is at 1 au:

Solar Parameters#

log_Z

T_eff

log_g

V_{Johnson}

+0.0

5777

+4.44

-26.75

The interface to the Sun templates is given through the pyphot.sun.Sun class.

Contributors#

Author: Morgan Fouesneau (@mfouesneau)

Direct contributions to the code base:

How to contribute#

This project is open source and new contributions and contributors are very welcome!

Please open a new issue or new pull request for bugs, feedback, or new features you would like to see. If there is an issue you would like to work on, please leave a comment, and we will be happy to assist.

Please have a look at our code of conduct.

Citation#

If you use this software in your work, please cite it using the following:

@software{fouesneau2025pyphot,
author       = {Fouesneau, Morgan},
title        = {pyphot},
month        = jan,
year         = 2025,
publisher    = {Zenodo},
version      = {pyphot\_v2.0.0},
doi          = {10.5281/zenodo.14712174},
url          = {https://doi.org/10.5281/zenodo.14712174},
}

Indices and tables#

Contents