class_docstr: Base class for all anomaly scorers
docstr: Checks if the series is stochastic (number of samples is higher than one).
docstr_tok: ["Checks","if","the","series","is","stochastic","(","number","of","samples","is","higher","than","one",")","."]
code: def _assert_stochastic(self, series: TimeSeries, name_series: str):
      "Checks if the series is stochastic (number of samples is higher than one)."
  
      raise_if_not(
          series.is_stochastic,
          f"Scorer {self.__str__()} is expecting `{name_series}` to be a stochastic timeseries"
          + f" (number of samples must be higher than 1, found: {series.n_samples}).",
      )
  
imports: from abc import ABC, abstractmethod
  from typing import Any, Sequence, Union
  import numpy
  from darts import TimeSeries
  from darts.ad.utils import _assert_same_length, _assert_timeseries, _intersect, _sanity_check_two_series, _to_list, eval_accuracy_from_scores, show_anomalies_from_scores
  from darts.logging import get_logger, raise_if_not
label_desc: Use image node_id 5 for calling the AnomalyScorer obj's underlying member method code with example usage: obj._assert_stochastic(series, name_series) without return types