class_docstr: Sampler used for prediction.
  
  Always selects the last time point for splitting i.e. the forecast point
  for the time series.
class_docstr_tok: ["Sampler","used","for","prediction",".","Always","selects","the","last","time","point","for","splitting","i.e",".","the","forecast","point","for","the","time","series","."]
code: def __call__(self, ts: np.ndarray) -> np.ndarray:
      a, b = self._get_bounds(ts)
      assert self.allow_empty_interval or a <= b
      return np.array([b]) if a <= b else np.array([], dtype=int)
  
imports: from typing import Tuple
  import numpy
  from gluonts.dataset.stat import ScaleHistogram
  from gluonts.pydantic import BaseModel
label_desc: Use image node_id 1 for calling the PredictionSplitSampler obj's underlying member method code with example usage: obj.__call__(ts) and returns: unknown