docs: def bounded_uniform(cls, lowest, highest, weight_interval=None):
          """
          Initialize with a uniform distribution between two values.
  
          If no ``weight_interval`` is passed, this weight distribution
          will just consist of ``[(lowest, 1), (highest, 1)]``. If specified,
          weights (still with uniform weight distribution) will be added every
          ``weight_interval``. Use this if you intend to modify the weights
          in any complex way after initialization.
  
          Args:
              lowest (float or int):
              highest (float or int):
              weight_interval (int):
  
          Returns:
              SoftFloat: A newly constructed instance.
          """
          if weight_interval is None:
              weights = [(lowest, 1), (highest, 1)]
          else:
              i = lowest
              weights = []
              while i < highest:
                  weights.append((i, 1))
                  i += weight_interval
              weights.append((highest, 1))
          return cls(weights)