Pakiet: python-bumps (0.7.11-2)

[ Pakiet źródłowy: python-bumps  ]

data fitting and Bayesian uncertainty modeling for inverse problems (Python 2)

Bumps is a set of routines for curve fitting and uncertainty analysis from a Bayesian perspective. In addition to traditional optimizers which search for the best minimum they can find in the search space, bumps provides uncertainty analysis which explores all viable minima and finds confidence intervals on the parameters based on uncertainty in the measured values. Bumps has been used for systems of up to 100 parameters with tight constraints on the parameters. Full uncertainty analysis requires hundreds of thousands of function evaluations, which is only feasible for cheap functions, systems with many processors, or lots of patience.

Bumps includes several traditional local optimizers such as Nelder-Mead simplex, BFGS and differential evolution. Bumps uncertainty analysis uses Markov chain Monte Carlo to explore the parameter space. Although it was created for curve fitting problems, Bumps can explore any probability density function, such as those defined by PyMC. In particular, the bumps uncertainty analysis works well with correlated parameters.

Bumps can be used as a library within your own applications, or as a framework for fitting, complete with a graphical user interface to manage your models.

This package installs the library for Python 2.

Inne pakiety związane z python-bumps

• dep: python

  Interaktywny, wysokopoziomowy język obiektowy (wersja Python2)

• dep: python-matplotlib (>= 1.0)

  System do rysowania wykresów oparty na Pythonie w stylu podobnym do Matlaba

• dep: python-numpy (>= 1.3.0)

  Szybkie dodawanie obiektów tablicy, moduł do języka Python

• dep: python-scipy (>= 0.7.0)

  scientific tools for Python

• dep: python-six

  Python 2 and 3 compatibility library (Python 2 interface)

• dep: python-typing

  Backport of the standard 3.5 library typing module

• rec: bumps-private-libs

  data fitting and Bayesian uncertainty modeling for inverse problems (libraries)

• rec: python-wxgtk3.0

  Python interface to the wxWidgets Cross-platform C++ GUI toolkit

• sug: python-bumps-doc

  data fitting and Bayesian uncertainty modeling for inverse problems (docs)

• sug: python-sklearn

  Python modules for machine learning and data mining - Python 2

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