d953b47ada9e984ba5a7a8a53be7ffba5cb22f17,framework/Optimizers/RavenSampled.py,RavenSampled,localFinalizeActualSampling,#RavenSampled#Any#Any#Any#,236

Before Change

    // trim down opt point to the useful parts
    // TODO making a new dict might be costly, maybe worth just passing whole point?
    //// testing suggests no big deal on smaller problem
    rlz = dict((var, full[var]) for var in (list(self.toBeSampled.keys()) + [self._objectiveVar] + list(self.dependentSample.keys())))
    // the sign of the objective function is flipped in case we do maximization
    // so get the correct-signed value into the realization
    if self._minMax == "max":
      rlz[self._objectiveVar] *= -1

After Change

      _, rlz = self._targetEvaluation.realization(matchDict={"prefix": prefix}, asDataSet=False)
    else:
      // NOTE if here, then rlz is actually a xr.Dataset, NOT a dictionary!!
      _, rlz = self._targetEvaluation.realization(matchDict={"batchId": self.batchId}, asDataSet=True,options={"returnAllMatch":True})
    // _, full = self._targetEvaluation.realization(matchDict={"prefix": prefix}, asDataSet=False)
    if self._targetEvaluation.isEmpty:
      self.raiseAnError(RuntimeError, f"Expected to find entry with prefix "{prefix}" in TargetEvaluation "{self._targetEvaluation.name}", but it is empty!")
    _, full = self._targetEvaluation.realization(matchDict={"prefix": prefix})

Instances