code: def msis(
      target: np.ndarray,
      lower_quantile: np.ndarray,
      upper_quantile: np.ndarray,
      seasonal_error: float,
      alpha: float,
  ) -> float:
      r"""
      .. math::
  
          msis = mean(U - L + 2/alpha * (L-Y) * I[Y<L] + 2/alpha * (Y-U) * I[Y>U]) / seasonal\_error
  
      See [SSA20]_ for more details.
      """  # noqa: E501
  
      numerator = np.mean(
          upper_quantile
          - lower_quantile
          + 2.0
          / alpha
          * (lower_quantile - target)
          * (target < lower_quantile)
          + 2.0
          / alpha
          * (target - upper_quantile)
          * (target > upper_quantile)
      )
  
      return numerator / seasonal_error
  
file_path: gluonts/src/gluonts/evaluation/metrics.py
imports: from typing import Optional
  import numpy
  from gluonts.time_feature import get_seasonality
label_desc: Use image node_id 9 for calling a global function with example usage: msis(target, lower_quantile, upper_quantile, seasonal_error, alpha) and returns: unknown