(data, max_percent_anomalies)
return max_outliers
Calculates the max_outliers for an input data set

      data : pandas DataFrame
        the input data set
      max_percent_anomalies : float
        the input maximum number of anomalies per percent of data set values
Calculates the max_outliers for an input data set
Calculates the max_outliers for an input data set
def _get_max_outliers(data, max_percent_anomalies):
    """
    Calculates the max_outliers for an input data set

      data : pandas DataFrame
        the input data set
      max_percent_anomalies : float
        the input maximum number of anomalies per percent of data set values
    """
    max_outliers = int(np.trunc(data.size * max_percent_anomalies))
    assert max_outliers, 'With longterm=True, AnomalyDetection splits the data into 2 week periods by default. You have {0} observations in a period, which is too few. Set a higher piecewise_median_period_weeks.'.format(
        data.size)
    return max_outliers
def _get_max_outliers ( data , max_percent_anomalies ) : max_outliers = int ( np . trunc ( data . size * max_percent_anomalies ) ) assert max_outliers , 'With longterm=True, AnomalyDetection splits the data into 2 week periods by default. You have {0} observations in a period, which is too few. Set a higher piecewise_median_period_weeks.' . format ( data . size ) return max_outliers