Simplex

class astropy.modeling.optimizers.Simplex

Bases: astropy.modeling.optimizers.Optimization

Neald-Mead (downhill simplex) algorithm.

This algorithm [1] only uses function values, not derivatives. Uses scipy.optimize.fmin.

References

1

Nelder, J.A. and Mead, R. (1965), “A simplex method for function minimization”, The Computer Journal, 7, pp. 308-313

Attributes Summary

supported_constraints

Methods Summary

__call__(self, objfunc, initval, fargs, **kwargs)

Run the solver.

Attributes Documentation

supported_constraints = ['bounds', 'fixed', 'tied']

Methods Documentation

__call__(self, objfunc, initval, fargs, **kwargs)

Run the solver.

Parameters

objfunccallable

objection function

initvaliterable

initial guess for the parameter values

fargstuple

other arguments to be passed to the statistic function

kwargsdict

other keyword arguments to be passed to the solver