code: def unique_float(data,
                   return_index=False,
                   return_inverse=False,
                   digits=None):
      
      data = np.asanyarray(data)
      as_int = float_to_int(data, digits)
      _junk, unique, inverse = np.unique(as_int,
                                         return_index=True,
                                         return_inverse=True)
  
      if (not return_index) and (not return_inverse):
          return data[unique]
  
      result = [data[unique]]
  
      if return_index:
          result.append(unique)
      if return_inverse:
          result.append(inverse)
      return tuple(result)
docs: Identical to the numpy.unique command, except evaluates floating point
      numbers, using a specified number of digits.
  
      If digits isn't specified, the library default TOL_MERGE will be used.