OptMethod¶
-
class
sherpa.optmethods.
OptMethod
(name, optfunc)[source]¶ Bases:
sherpa.utils.NoNewAttributesAfterInit
Base class for the optimisers.
Parameters: - name (str) – The name of the optimiser.
- optfunc (function) – The function which optimises the model: its arguments are a function which evalutes the statistic given a list of parameter values, the starting parameters, minima, and maxima, followed by keyword arguments matching the configuration data.
Attributes Summary
default_config
The default settings for the optimiser. Methods Summary
fit
(statfunc, pars, parmins, parmaxes[, …])Run the optimiser. Attributes Documentation
-
default_config
¶ The default settings for the optimiser.
Methods Documentation
-
fit
(statfunc, pars, parmins, parmaxes, statargs=(), statkwargs={})[source]¶ Run the optimiser.
Parameters: - statfunc (function) – Given a list of parameter values as the first argument and,
as the remaining positional arguments,
statargs
andstatkwargs
as keyword arguments, return the statistic value. - pars (sequence) – The start position of the model parameter values.
- parmins (sequence) – The minimum allowed values for each model parameter. This
must match the length of
pars
. - parmaxes (sequence) – The maximum allowed values for each model parameter. This
must match the length of
pars
. - statargs (optional) – Additional positional arguments to send to
statfunc
. - statkwargs (optional) – Additional keyword arguments to send to
statfunc
.
Returns: newpars – The model parameters after the optimiser has run.
Return type: tuple
- statfunc (function) – Given a list of parameter values as the first argument and,
as the remaining positional arguments,