set_method
- sherpa.astro.ui.set_method(meth)
Set the optimization method.
The primary task of Sherpa is to fit a model M(p) to a set of observed data, where the vector p denotes the model parameters. An optimization method is one that is used to determine the vector of model parameter values, p0, for which the chosen fit statistic is minimized.
- Parameters
meth (str) – The name of the method (case is not important). The
list_methods
function returns the list of supported values.- Raises
sherpa.utils.err.ArgumentErr – If the
meth
argument is not recognized.
See also
get_method_name
Return the name of the current optimization method.
list_methods
List the supported optimization methods.
set_stat
Set the fit statistic.
Notes
The available methods include:
levmar
The Levenberg-Marquardt method is an interface to the MINPACK subroutine lmdif to find the local minimum of nonlinear least squares functions of several variables by a modification of the Levenberg-Marquardt algorithm 1.
moncar
The implementation of the moncar method is based on 2.
neldermead
The implementation of the Nelder Mead Simplex direct search is based on 3.
simplex
This is another name for
neldermead
.
References
- 1
J.J. More, “The Levenberg Marquardt algorithm: implementation and theory,” in Lecture Notes in Mathematics 630: Numerical Analysis, G.A. Watson (Ed.), Springer-Verlag: Berlin, 1978, pp.105-116.
- 2
Storn, R. and Price, K. “Differential Evolution: A Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces.” J. Global Optimization 11, 341-359, 1997.
- 3
Jeffrey C. Lagarias, James A. Reeds, Margaret H. Wright, Paul E. Wright “Convergence Properties of the Nelder-Mead Simplex Algorithm in Low Dimensions”, SIAM Journal on Optimization,Vol. 9, No. 1 (1998), pages 112-147.
Examples
>>> set_method('neldermead')