class_docstr: Abstract class for "continuous time" samplers, which, given a lower bound
  and upper bound, sample "points" (events) in continuous time from a
  specified interval.
class_docstr_tok: ["Abstract","class","for","``","continuous","time","''","samplers",",","which",",","given","a","lower","bound","and","upper","bound",",","sample","``","points","''","(","events",")","in","continuous","time","from","a","specified","interval","."]
code: def _get_bounds(self, interval_length: float) -> Tuple[float, float]:
      return (
          self.min_past,
          interval_length - self.min_future,
      )
  
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 ContinuousTimePointSampler obj's underlying member method code with example usage: obj._get_bounds(interval_length) and returns: self,  unknown