Modules for storing and operating on astronomical source spectral energy distributions.
.. image:: https://github.com/bd-j/sedpy/workflows/Tests/badge.svg :target: https://github.com/bd-j/sedpy/actions?query=workflow%3ATests
.. image:: https://readthedocs.org/projects/sedpy/badge/?version=latest :target: https://sedpy.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status
sedpy
is pip installable:
.. code-block:: shell
python -m pip install astro-sedpy
Or you can install the latest version from github:
.. code-block:: shell
git clone https://github.com/bd-j/sedpy
cd sedpy
pip install .
Then in python, e.g.,
.. code-block:: python
from sedpy import observate
# get magnitude from a spectrum:
filt = observate.Filter("sdss_r0")
mag = filt.ab_mag(angstroms, f_lambda_cgs)
# or get several magnitudes at once
filterlist = observate.load_filters(["galex_NUV", "sdss_r0"])
mags = observate.getSED(angstroms, f_lambda_cgs, filterlist=filters)
For the filters available by default see the filter_list
.
For adding transmission curves, see these docs
.
.. _filter_list: sedpy/data/filters/README.md .. _docs: docs/transmissions.rst
This code can be referenced as:
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.4582723.svg :target: https://doi.org/10.5281/zenodo.4582723
observate
has methods for generating synthetic photometry through any filters,
and classes for dealing with filters generally. There is some functionality for spectra
(vaccum to air conversions).
With a huge debt to Mike Blanton's kcorrect <https://github.com/blanton144/kcorrect>
_ code .
attenuation
contains simple dust attenuation methods.
smoothing
methods for smoothing well-sampled spectra.
extinction
(Deprecated) classes for a detailed modeling of extinction curves,
following the Fitzpatrick & Massa parameterizations.
See dust_extinction <https://dust-extinction.readthedocs.io/en/stable/>
_ instead.