Simplex¶
-
class
astropy.modeling.optimizers.
Simplex
[source]¶ 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
Methods Summary
__call__
(objfunc, initval, fargs, **kwargs)Run the solver.
Attributes Documentation
-
supported_constraints
= ['bounds', 'fixed', 'tied']¶
Methods Documentation
-
__call__
(objfunc, initval, fargs, **kwargs)[source]¶ Run the solver.
- Parameters
- objfunc
python:callable()
objection function
- initvalpython:iterable
initial guess for the parameter values
- fargs
python:tuple
other arguments to be passed to the statistic function
- kwargs
python:dict
other keyword arguments to be passed to the solver
- objfunc