def __init__(self, time_series, absolute_threshold_value_upper=None,<EOL>absolute_threshold_value_lower=None, baseline_time_series=None):
super(AbsoluteThreshold, self).__init__(self.__class__.__name__, time_series, baseline_time_series)<EOL>self.absolute_threshold_value_upper = absolute_threshold_value_upper<EOL>self.absolute_threshold_value_lower = absolute_threshold_value_lower<EOL>if not self.absolute_threshold_value_lower and not self.absolute_threshold_value_upper:<EOL><INDENT>raise exceptions.RequiredParametersNotPassed('<STR_LIT>'<EOL>'<STR_LIT>'<EOL>'<STR_LIT>')<EOL><DEDENT>
Initialize algorithm, check all required args are present

:param time_series: The current time series dict to run anomaly detection on
:param absolute_threshold_value_upper: Time series values above this are considered anomalies
:param absolute_threshold_value_lower: Time series values below this are considered anomalies
:param baseline_time_series: A no-op for now
:return: