code: def __init__(self, points: tp.Iterable[tp.ArrayLike]) -> None:
      iterp = iter(points)
      self.sample_mins = np.array(next(iterp), copy=False)
      self.sample_maxs = self.sample_mins
      for point in iterp:
          self.sample_mins = np.minimum(self.sample_mins, point)
          self.sample_maxs = np.maximum(self.sample_maxs, point)
      self.epsilon = min(
          [x for x in self.sample_mins]
          + [1 - s for s in self.sample_maxs]
          + [1e-15]
      )
      assert (
          self.epsilon > 0.0
      ), f"Non-positive epsilon={self.epsilon} from mins {self.sample_mins} and maxs {self.sample_maxs}"
  
imports: import numpy
  from numpy.random import RandomState
  import nevergrad.common.typing
  from nevergrad.common.decorators import Registry
label_desc: Use image node_id 1 to create a new Rescaler object  with example: obj = Rescaler(points)