pygsti.report.direct_logl_matrix

pygsti.report.direct_logl_matrix(sigma, dataset, directGateset, strs, minProbClip=1e-06, fidPairs=None)
Computes the Direct-X log-likelihood matrix, containing the values
of 2*( log(L)_upperbound - log(L) ) for a base gatestring sigma.

Similar to logl_matrix, except the probabilities used to compute LogL values come from using the “composite gate” of directGatesets[sigma], a GateSet assumed to contain some estimate of sigma stored under the gate label “GsigmaLbl”.

Parameters:
  • sigma (GateString or tuple of gate labels) – The gate sequence that is sandwiched between each prepStr and effectStr
  • dataset (DataSet) – The data used to specify frequencies and counts
  • directGateset (GateSet) – GateSet which contains an estimate of sigma stored under the gate label “GsigmaLbl”.
  • strs (2-tuple) – A (prepStrs,effectStrs) tuple usually generated by calling get_spam_strs(...)
  • minProbClip (float, optional) – defines the minimum probability clipping.
  • fidPairs (list, optional) – A list of (iRhoStr,iEStr) tuples specifying a subset of all the prepStr,effectStr pairs to include in the matrix. Other elements are set to NaN.
Returns:

Direct-X chi^2 values corresponding to gate sequences where gateString is sandwiched between the each (effectStr,prepStr) pair.

Return type:

numpy array of shape ( len(effectStrs), len(prepStrs) )