examples/opf/clients/nyctaxi/nyctaxi_anomaly.py
def _setRandomEncoderResolution(minResolution=0.001):
  """
  Given model params, figure out the correct resolution for the
  RandomDistributed encoder. Modifies params in place.
  """
  encoder = (
    model_params.MODEL_PARAMS["modelParams"]["sensorParams"]["encoders"]["value"]
  )

  if encoder["type"] == "RandomDistributedScalarEncoder":
    rangePadding = abs(_INPUT_MAX - _INPUT_MIN) * 0.2
    minValue = _INPUT_MIN - rangePadding
    maxValue = _INPUT_MAX + rangePadding
    resolution = max(minResolution,
                     (maxValue - minValue) / encoder.pop("numBuckets")
                    )
    encoder["resolution"] = resolution
def _setRandomEncoderResolution(minResolution=0.001):
  """
  Given model params, figure out the correct resolution for the
  RandomDistributed encoder. Modifies params in place.
  """
  encoder = (
    model_params.MODEL_PARAMS["modelParams"]["sensorParams"]["encoders"]["value"]
  )

  if encoder["type"] == "RandomDistributedScalarEncoder":
    rangePadding = abs(_INPUT_MAX - _INPUT_MIN) * 0.2
    minValue = _INPUT_MIN - rangePadding
    maxValue = _INPUT_MAX + rangePadding
    resolution = max(minResolution,
                     (maxValue - minValue) / encoder.pop("numBuckets")
                    )
    encoder["resolution"] = resolution
Given model params, figure out the correct resolution for the
  RandomDistributed encoder. Modifies params in place.