pydftools
A pure-python port of the dftools R package.
This package attempts to imitate the dftools package (repo: https://github.com/obreschkow/dftools ) quite closely, while being as Pythonic as possible. Do note that 2D+ models are not yet implemented in this Python port, and neither are non-parametric models. Hopefully they will be along soon.
From dftool’s description:
This package can find the most likely P parameters of a D-dimensional distribution function (DF) generating N objects, where each object is specified by D observables with measurement uncertainties. For instance, if the objects are galaxies, it can fit a MF (P=1), a mass-size distribution (P=2) or the mass-spin-morphology distribution (P=3). Unlike most common fitting approaches, this method accurately accounts for measurement is uncertainties and complex selection functions. A full description of the algorithm can be found in Obreschkow et al. (2017).
In short, clean out Eddington bias from your fits:
Free software: MIT license
Documentation: https://pydftools.readthedocs.io.
Features
Simple and fast parameter fitting for generative distribution functions
Several examples (with astronomical applications in mind)
Several plotting routines so that you can go from nothing to a plot in minutes
A mockdata() function which can produce data to fit.
Support for arbitrary 1D models, several kinds of selection functions, jackknife and bootstrap resampling, Gaussian error estimation and more.
Credits
This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.
History
0.1.0 (2017-10-25)
First release on PyPI.
All basic examples working as expected
TravisCI, Readthedocs set up.
Does not have multi-dimension support, or non-parametric support.
1 maintainer
Metadata
1 maintainer
Release files for pydftools 0.1.0
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Total release size: 655.4 kB
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