OptimizerMixin¶
-
class
pyhf.optimize.mixins.
OptimizerMixin
(**kwargs)[source]¶ Bases:
object
Mixin Class to build optimizers.
Attributes
-
maxiter
¶
-
verbose
¶
Methods
-
__init__
(**kwargs)[source]¶ Create an optimizer.
- Parameters
maxiter (int) – maximum number of iterations. Default is 100000.
verbose (int) – verbose output level during minimization. Default is off (0).
-
minimize
(objective, data, pdf, init_pars, par_bounds, fixed_vals=None, return_fitted_val=False, return_result_obj=False, do_grad=None, do_stitch=False, **kwargs)[source]¶ Find parameters that minimize the objective.
- Parameters
objective (func) – objective function
data (list) – observed data
pdf (Model) – The statistical model adhering to the schema model.json
init_pars (list) – initial parameters
par_bounds (list) – parameter boundaries
fixed_vals (list) – fixed parameter values
return_fitted_val (bool) – return bestfit value of the objective
return_result_obj (bool) – return
scipy.optimize.OptimizeResult
do_grad (bool) – enable autodifferentiation mode. Default depends on backend (
pyhf.tensorlib.default_do_grad
).do_stitch (bool) – enable splicing/stitching fixed parameter.
kwargs – other options to pass through to underlying minimizer
- Returns
parameters (tensor): fitted parameters
minimum (float): if
return_fitted_val
flagged, return minimized objective valueresult (
scipy.optimize.OptimizeResult
): ifreturn_result_obj
flagged
- Return type
Fitted parameters or tuple of results
-