套件：python3-bumps（0.8.0-1）
data fitting and Bayesian uncertainty modeling for inverse problems (Python 3)
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 3.
其他與 python3-bumps 有關的套件
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- dep: python3
- interactive high-level object-oriented language (default python3 version)
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- dep: python3-matplotlib (>= 1.0)
- Python based plotting system in a style similar to Matlab (Python 3)
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- dep: python3-numpy (>= 1.3.0)
- Fast array facility to the Python 3 language
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- dep: python3-scipy (>= 0.7.0)
- scientific tools for Python 3
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- dep: python3-six
- Python 2 and 3 compatibility library (Python 3 interface)
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- rec: bumps-private-libs
- data fitting and Bayesian uncertainty modeling for inverse problems (libraries)
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- rec: python3-wxgtk4.0
- Python 3 interface to the wxWidgets Cross-platform C++ GUI toolkit
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- sug: python-bumps-doc
- data fitting and Bayesian uncertainty modeling for inverse problems (docs)
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- sug: python3-sklearn
- Python modules for machine learning and data mining - Python 3