Metadata-Version: 2.4
Name: astro-fitted
Version: 2.0.0
Summary: Fitting astrophysical transients with relativistic accretion disc models.
Home-page: https://github.com/fittingtransientswithdiscs/FitTeD
Author: Andrew Mummery
Author-email: amummery@ias.edu
License: BSD-3-Clause
Project-URL: Documentation, https://fittingtransientswithdiscs.github.io/FitTeD/
Project-URL: Source, https://github.com/fittingtransientswithdiscs/FitTeD
Project-URL: Changelog, https://github.com/fittingtransientswithdiscs/FitTeD/blob/main/CHANGELOG.md
Project-URL: Paper, https://ui.adsabs.harvard.edu/abs/2025MNRAS.544.2225M/abstract
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: emcee
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: pandas
Requires-Dist: astropy
Requires-Dist: matplotlib
Requires-Dist: importlib_resources
Requires-Dist: corner
Requires-Dist: h5py
Requires-Dist: tqdm
Requires-Dist: numba
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: license-file
Dynamic: project-url
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# README #

Hey. 

Thanks for using FitTeD. 

The paper describing this package is here: https://ui.adsabs.harvard.edu/abs/2025MNRAS.544.2225M/abstract
Please cite if you make use of this code in your research.

### Setup ###

To get this all up and running, you will need to run the following:

* Pull into its own folder
* Within the folder, run "python3 -m pip install -e ."

That is the whole installation. FitTeD is pure Python: there is no compiler,
no build step, and the same install works on Linux, macOS and Windows.

* The -e flag is optional. It makes the package editable in place; a plain
  "python3 -m pip install ." works identically.

To run the below examples you will need to also have manyTDE installed (Andy and Sjoert's database of optical/UV TDE light curves). 

* This is only necessary if you want to get TDE data sets by IAU name, rather than loading your own data. 
* manyTDE can be found here: https://github.com/sjoertvv/manyTDE
* Again just run “ python3 -m pip install -e . ” in the manyTDE directory to set up. 

### Running the code ###

There are 3 example scripts in the fitted/examples directory which run through how this all works. 

Running 
> data_loading.py 

Will set up a FitTeD Data_Set class for the tidal disruption event AT2019dsg and do some processing (see code/paper for details).

Running 
> fitting_models.py

will show you how to generate FitTeD models, and fit them to data in various ways. 

Switch the variables `yes_i_want_to_run_a_chain` and `yes_i_want_to_find_a_best_fit` to True if you want to do a proper analysis, although running the chain will take ~ 5 hours with current settings (on my laptop). 

If you do run the chain, then 
> analysis.py

shows you some science results you can get from the fit. 

Happy TDE-ing. 

Cheers,
Andy*, Ed, and Adam

P.S., any comments/questions, drop me a line. 

* amummery@ias.edu
