pygsti.tools.logl_max

pygsti.tools.logl_max(dataset, gatestring_list=None, countVecMx=None, poissonPicture=True, check=False)

The maximum log-likelihood possible for a DataSet. That is, the log-likelihood obtained by a maximal model that can fit perfectly the probability of each gate string.

Parameters:
  • dataset (DataSet) – the data set to use.
  • gatestring_list (list of (tuples or GateStrings), optional) – Each element specifies a gate string to include in the max-log-likelihood sum. Default value of None implies all the gate strings in dataset should be used.
  • countVecMx (numpy array, optional) – Two-dimensional numpy array whose rows correspond to the data set’s spam labels (i.e. dataset.get_spam_labels()). Each row is contains the dataset counts for that spam label for each gate string in gatestring_list. Use fill_count_vecs(...) to generate this quantity when it is useful elsewhere (e.g. for logl(...) calls).
  • poissonPicture (boolean, optional) – Whether the Poisson-picture maximum log-likelihood should be returned.
  • check (boolean, optional) – Whether additional check is performed which computes the max logl another way an compares to the faster method.
Returns:

Return type:

float