autocorr / nestfit

Bayesian spectral decomposition and model fitting using Nested Sampling

nestfit

Welcome to the NestFit source code repository. NestFit is a Bayesian framework for fitting spectral line data containing multiple velocity components. The official documentation and installation instructions may be found at https://nestfit.readthedocs.io as well as in the included docs/ directory.

If you make use of NestFit or a derivative in an academic work, please cite the forth-coming publication (Svoboda in prep.) or this Zenodo DOI:

@software{brian_svoboda_2021_4470028,
author       = {Brian Svoboda},
title        = {autocorr/nestfit: Initial public release},
month        = jan,
year         = 2021,
publisher    = {Zenodo},
version      = {v0.2},
doi          = {10.5281/zenodo.4470028},
url          = {https://doi.org/10.5281/zenodo.4470028}
}

License

This software is licensed under the MIT license. A copy is supplied in the LICENSE file.

This software makes use of the ammonia model code found in pyspeckit by Adam Ginsburg & Jordan Mirocha and contributors. The Python implementation in pyspeckit was originally based on the IDL program nh3fit by Erik Rosolowsky, described in Rosolowsky et al. (2008).

The implementation of the fast exponential function is taken from the LIME radiative transfer code developed by Christian Brinch and the LIME development team. These modified files (fastexp.h, fastexp.c) are licensed under the GNU GPL v3.

nestfit's Issues

Improve details on installation

I am trying to install the package, however, it is not well documented what needs to be modified. I guess that this is the suggested method:

python setup.py install --user

However, this must be modified in the setup.py file

MNEST_DIR = Path('/users/bsvoboda/code/MultiNest')

maybe use the LD_LIBRARY_PATH variable.

Also, if I need to use the icc compiler instead of gcc, then this command line could be used:

LDSHARED="icc -shared" CC=icc python setup.py install --user

also, I think that -openmp should be removed from setup.py in the case of using icc

How do you setup the code for a new dataset? What is the shortcut?

How to add a new cold-ammonia model?

I want to add the cold-ammonia model. The implementation of the model is simply

    dT0 = 41.18 # Energy difference between (2,2) and (1,1) in K
    trot = tkin * (1 + (tkin/dT0)*np.log(1 + 0.6*np.exp(-15.7/tkin)))**-1
    return ammonia(xarr, trot=trot, **kwargs)

I guess a new function AmmoniaRunner_cold() should be created, which looks almost the same as AmmoniaRunner_cold(). Anything else?

UltraNest support

Would you be interested to add support for https://johannesbuchner.github.io/UltraNest/ ?
The interface should be very similar to pymultinest.

UltraNest is a very reliable tuning-parameter-free algorithm. I have published some examples where the UltraNest algorithm is unbiased while pymultinest gives a different answer. UltraNest is a pure-python package and very easy to install with pip or conda.

UltraNest also supports resuming from disk and MPI parallelisation, if that is useful to you.