pygsti.objectivefns.objectivefns

pygsti.objectivefns.objectivefns#

Defines objective-function objects

Classes

CachedObjectiveFunction(objective_function)

Holds various values of an objective function at a particular point.

Chi2Function(mdc_store[, regularization, ...])

Model-based chi-squared function: N(p-f)^2 / p

ChiAlphaFunction(mdc_store[, ...])

Model-based chi-alpha function: N[x + 1/(alpha * x^alpha) - (1 + 1/alpha)] where x := p/f.

CustomWeightedChi2Function(mdc_store[, ...])

Model-based custom-weighted chi-squared function: cw^2 (p-f)^2

DeltaLogLFunction(mdc_store[, ...])

Model-based delta log-likelihood function: N*f*log(f/p).

EvaluatedModelDatasetCircuitsStore(...)

Additionally holds quantities at a specific model-parameter-space point.

FreqWeightedChi2Function(mdc_store[, ...])

Model-based frequency-weighted chi-squared function: N(p-f)^2 / f

LogLWildcardFunction(logl_objective_fn, ...)

A wildcard-budget bolt-on to an existing objective function.

LpNormToPowerP(mdc_store[, regularization, ...])

Model-based loss function: |p-f|^power.

MDCObjectiveFunction(raw_objfn, mdc_store[, ...])

An objective function whose probabilities and counts are given by a Model and DataSet, respectively.

MaxLogLFunction(mdc_store[, regularization, ...])

Model-based maximum-model log-likelihood function: N*f*log(f)

ModelDatasetCircuitsStore(model, dataset[, ...])

Contains all the information that we'd like to persist when performing (multiple) evaluations of the same circuits using the same model and data set.

ObjectiveFunction()

So far, this is just a base class for organizational purposes

ObjectiveFunctionBuilder(cls_to_build[, ...])

A factory class for building objective functions.

PoissonPicDeltaLogLFunction(mdc_store[, ...])

Model-based poisson-picture delta log-likelihood function: N*f*log(f/p) - N*(f-p).

RawAbsPower(power[, regularization, ...])

The function |p-f|^power.

RawChi2Function([regularization, ...])

The function N(p-f)^2 / p

RawChiAlphaFunction([regularization, ...])

The function N[x + 1/(alpha * x^alpha) - (1 + 1/alpha)] where x := p/f.

RawCustomWeightedChi2Function([...])

The function custom_weight^2 (p-f)^2, with custom weights that default to 1.

RawDeltaLogLFunction([regularization, ...])

The function N*f*log(f/p).

RawFreqWeightedChi2Function([...])

The function N(p-f)^2 / f

RawMaxLogLFunction([regularization, ...])

The function N*f*log(f) (note this doesn't depend on the probability!).

RawObjectiveFunction([regularization, ...])

An objective function that acts on probabilities and counts directly.

RawPoissonPicDeltaLogLFunction([...])

The function N*f*log(f/p) - N*(f-p).

RawTVDFunction([regularization, ...])

The function 0.5 * |p-f|.

TVDFunction(mdc_store[, regularization, ...])

Model-based TVD function: 0.5 * w * |p-f|, where w is a vector of weights.

TermWeighted(raw_objfn, mdc_store[, ...])

Represents an objective whose term function takes the form

TimeDependentChi2Function(mdc_store[, ...])

Chi-squared function that can handle time-dependent circuits and data.

TimeDependentMDCObjectiveFunction(mdc_store)

A time-dependent model-based objective function

TimeDependentPoissonPicLogLFunction(mdc_store)

Poisson-picture delta log-likelihood function that can handle time-dependent circuits and data.

TimeIndependentMDCObjectiveFunction(...[, ...])

A time-independent model-based (MDCObjectiveFunction-derived) objective function.