pygsti.optimize.simplerlm.OptimizerResult

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pygsti.optimize.simplerlm.OptimizerResult#

class OptimizerResult(objective_func, opt_x, opt_f=None, opt_jtj=None, opt_unpenalized_f=None, chi2_k_distributed_qty=None, optimizer_specific_qtys=None)#

Bases: object

The result from an optimization.

Parameters:

  • objective_func (ObjectiveFunction) – The objective function that was optimized.

  • opt_x (numpy.ndarray) – The optimal argument (x) value. Often a vector of parameters.

  • opt_f (numpy.ndarray) – the optimal objective function (f) value. Often this is the least-squares vector of objective function values.

  • opt_jtj (numpy.ndarray, optional) – the optimal dot(transpose(J),J) value, where J is the Jacobian matrix. This may be useful for computing approximate error bars.

  • opt_unpenalized_f (numpy.ndarray, optional) – the optimal objective function (f) value with any penalty terms removed.

  • chi2_k_distributed_qty (float, optional) – a value that is supposed to be chi2_k distributed.

  • optimizer_specific_qtys (dict, optional) – a dictionary of additional optimization parameters.

Methods

__init__(objective_func, opt_x[, opt_f, ...])

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