nonlinear multidimensional least-squares fitting
Project description
These packages facilitate least-squares fitting of noisy data by
multi-dimensional, nonlinear functions of arbitrarily many
parameters. The central package is :mod:`lsqfit` which provides
the fitting capability. :mod:`lsqfit` 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:`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.
These packages use 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. The central package is :mod:`lsqfit` which provides
the fitting capability. :mod:`lsqfit` 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:`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.
These packages use the Gnu Scientific Library (GSL) to do the
fitting, numpy for efficient array arithmetic, and cython to
compile efficient core routines and interface code.
