class_docstr: Samples each point with the same fixed probability.
  
  Parameters
  ----------
  p
      Probability of selecting a time point
class_docstr_tok: ["Samples","each","point","with","the","same","fixed","probability",".","Parameters","--","--","--","--","--","p","Probability","of","selecting","a","time","point"]
code: def __call__(self, ts: np.ndarray) -> np.ndarray:
      a, b = self._get_bounds(ts)
  
      if a > b:
          return np.array([], dtype=int)
  
      window_size = b - a + 1
      (indices,) = np.where(
          np.random.random_sample(window_size) < self.p
      )
      return indices + a
  
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 UniformSplitSampler obj's underlying member method code with example usage: obj.__call__(ts) and returns: unknown, np