pygsti.extras.drift.trmodel.maxlikelihood

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pygsti.extras.drift.trmodel.maxlikelihood#

maxlikelihood(trmodel, ds, minp=0.0001, maxp=0.999999, bounds=None, returnoptout=False, optoptions=None, verbosity=1)#

Finds the maximum likelihood TimeResolvedModel given the data.

Parameters:

  • timeresolvedmodel (TimeResolvedModel) – The TimeResolvedModel that is used as the seed, and which defines the class of parameterized models to optimize over.

  • ds (DataSet) – A DataSet, containing time-series data.

  • minp (float, optional) – Value used to smooth the 0 and 1 probability boundaries for the likelihood function.

  • maxp (float, optional) – Value used to smooth the 0 and 1 probability boundaries for the likelihood function.

  • bounds (list or None, optional) – Bounds on the parameters, as specified in scipy.optimize.minimize

  • optout (bool, optional) – Wether to return the output of scipy.optimize.minimize

  • optoptions (dict, optional) – Optional arguments for scipy.optimize.minimize.

Returns:

The maximum loglikelihood model

Return type:

float

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