class_docstr: Affine transform a * x + b
  
  Parameters
  ----------
  a: float
  b: float
class_docstr_tok: ["Affine","transform","a","*","x","+","b","Parameters","--","--","--","--","--","a",":","float","b",":","float"]
code: def __init__(self, a: tp.BoundValue, b: tp.BoundValue) -> None:
      super().__init__()
      self.a = bound_to_array(a)
      self.b = bound_to_array(b)
      if not np.any(self.a):
          raise ValueError(
              '"a" parameter should be non-zero to prevent information loss.'
          )
      self.name = f"Af({a},{b})"
  
imports: import uuid
  import itertools
  import numpy
  from scipy import stats
  import nevergrad.common.typing
  from .None import utils
label_desc: Use image node_id 1 to create a new Affine object from inherited base classes: Transform with example: obj = Affine(a, b)