code: def best_float():
      """Floating point type with best precision
  
      This is nearly always np.longdouble, except on Windows, where np.longdouble
      is Intel80 storage, but with float64 precision for calculations.  In that
      case we return float64 on the basis it's the fastest and smallest at the
      highest precision.
  
      SPARC float128 also proved so slow that we prefer float64.
  
      Returns
      -------
      best_type : numpy type
          floating point type with highest precision
  
      Notes
      -----
      Needs to run without error for module import, because it is called in
      ``ok_floats`` below, and therefore in setting module global ``OK_FLOATS``.
      """
      try:
          long_info = type_info(np.longdouble)
      except FloatingError:
          return np.float64
      if (
          long_info["nmant"] > type_info(np.float64)["nmant"]
          and machine() != "sparc64"
      ):  # sparc has crazy-slow float128
          return np.longdouble
      return np.float64
  
imports: from __future__ import annotations
  import warnings
  from platform import machine, processor
  import numpy
  from .deprecated import deprecate_with_version
label_desc: Use image node_id 13 for calling a global function with example usage: best_float() and returns: np, np, np