Simplex¶
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class
astropy.modeling.optimizers.
Simplex
[source] [edit on github]¶ 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] (1, 2) 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__
(objfunc, initval, fargs, **kwargs)Run the solver. Attributes Documentation
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supported_constraints
= ['bounds', 'fixed', 'tied']¶
Methods Documentation
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__call__
(objfunc, initval, fargs, **kwargs)[source] [edit on github]¶ Run the solver.
Parameters: - objfunc : callable
objection function
- initval : iterable
initial guess for the parameter values
- fargs : tuple
other arguments to be passed to the statistic function
- kwargs : dict
other keyword arguments to be passed to the solver
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