def _getClassifierInputRecord(self, inputRecord):
    """
    inputRecord - dict containing the input to the sensor

    Return a 'ClassifierInput' object, which contains the mapped
    bucket index for input Record
    """
    absoluteValue = None
    bucketIdx = None

    if self._predictedFieldName is not None and self._classifierInputEncoder is not None:
      absoluteValue = inputRecord[self._predictedFieldName]
      bucketIdx = self._classifierInputEncoder.getBucketIndices(absoluteValue)[0]

    return ClassifierInput(dataRow=absoluteValue,
                           bucketIndex=bucketIdx)
def _getClassifierInputRecord(self, inputRecord):
    """
    inputRecord - dict containing the input to the sensor

    Return a 'ClassifierInput' object, which contains the mapped
    bucket index for input Record
    """
    absoluteValue = None
    bucketIdx = None

    if self._predictedFieldName is not None and self._classifierInputEncoder is not None:
      absoluteValue = inputRecord[self._predictedFieldName]
      bucketIdx = self._classifierInputEncoder.getBucketIndices(absoluteValue)[0]

    return ClassifierInput(dataRow=absoluteValue,
                           bucketIndex=bucketIdx)
def _getClassifierInputRecord ( self , inputRecord ) : absoluteValue = None bucketIdx = None if self . _predictedFieldName is not None and self . _classifierInputEncoder is not None : absoluteValue = inputRecord [ self . _predictedFieldName ] bucketIdx = self . _classifierInputEncoder . getBucketIndices ( absoluteValue ) [ 0 ] return ClassifierInput ( dataRow = absoluteValue , bucketIndex = bucketIdx )
inputRecord - dict containing the input to the sensor

    Return a 'ClassifierInput' object, which contains the mapped
    bucket index for input Record
inputRecord - dict containing the input to the sensor