src/nupic/swarming/dummy_model_runner.py
def _getMetrics(self):
    """ Protected function that can be overridden by subclasses. Its main purpose
    is to allow the the OPFDummyModelRunner to override this with deterministic
    values

    Returns: All the metrics being computed for this model
    """
    metric = None
    if self.metrics is not None:
      metric = self.metrics(self._currentRecordIndex+1)
    elif self.metricValue is not None:
      metric = self.metricValue
    else:
      raise RuntimeError('No metrics or metric value specified for dummy model')

    return {self._optimizeKeyPattern:metric}
def _getMetrics(self):
    """ Protected function that can be overridden by subclasses. Its main purpose
    is to allow the the OPFDummyModelRunner to override this with deterministic
    values

    Returns: All the metrics being computed for this model
    """
    metric = None
    if self.metrics is not None:
      metric = self.metrics(self._currentRecordIndex+1)
    elif self.metricValue is not None:
      metric = self.metricValue
    else:
      raise RuntimeError('No metrics or metric value specified for dummy model')

    return {self._optimizeKeyPattern:metric}
def _getMetrics ( self ) : metric = None if self . metrics is not None : metric = self . metrics ( self . _currentRecordIndex + 1 ) elif self . metricValue is not None : metric = self . metricValue else : raise RuntimeError ( 'No metrics or metric value specified for dummy model' ) return { self . _optimizeKeyPattern : metric }
Protected function that can be overridden by subclasses. Its main purpose
    is to allow the the OPFDummyModelRunner to override this with deterministic
    values

    Returns: All the metrics being computed for this model
Protected function that can be overridden by subclasses . Its main purpose is to allow the the OPFDummyModelRunner to override this with deterministic values