Utilities for nonlinear least-squares fits.
Project description
This package facilitates least-squares fitting of noisy data by
multi-dimensional, nonlinear functions of arbitrarily many
parameters. :mod:`lsqfit` provides the fitting capability;
it makes heavy use of package :mod:`gvar`, which provides tools for
the analysis of error propagation, and also for the creation of
complicated multi-dimensional gaussian distributions. (:mod:`gvar`
is distributed separately.) :mod:`lsqfit` supports Bayesian priors
for the fit parameters, with arbitrarily complicated multidimensional
Gaussian distributions. It uses automatic differentiation to compute
gradients, greatly simplifying the design of fit functions.
In addition to :mod:`gvar`, this package uses the Gnu Scientific
Library (GSL) to do the fitting, numpy for efficient array arithmetic,
and cython to compile efficient core routines and interface code.
multi-dimensional, nonlinear functions of arbitrarily many
parameters. :mod:`lsqfit` provides the fitting capability;
it makes heavy use of package :mod:`gvar`, which provides tools for
the analysis of error propagation, and also for the creation of
complicated multi-dimensional gaussian distributions. (:mod:`gvar`
is distributed separately.) :mod:`lsqfit` supports Bayesian priors
for the fit parameters, with arbitrarily complicated multidimensional
Gaussian distributions. It uses automatic differentiation to compute
gradients, greatly simplifying the design of fit functions.
In addition to :mod:`gvar`, this package uses the Gnu Scientific
Library (GSL) to do the fitting, numpy for efficient array arithmetic,
and cython to compile efficient core routines and interface code.
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