code: def _transform(
      data: np.ndarray,
      methods: Dict[str, PreProcessMethods],
      all_stats: Dict[str, Dict[str, float]],
      mapping: Dict[PreProcessMethods, Any],
  ) -> None:
      for str_idx, stats in all_stats.items():
          idx = int(str_idx)
          fn = mapping[methods[str_idx]]
          data[..., idx] = fn(data[..., idx], stats)
  
imports: import numpy
  from enum import Enum
  from typing import Any
  from typing import Dict
  from typing import List
  from typing import Optional
  from dataclasses import dataclass
  from cftool.misc import safe_execute
  from cftool.misc import shallow_copy_dict
  from cftool.array import normalize
  from cftool.array import normalize_from
  from cftool.array import recover_normalize_from
  from cftool.array import min_max_normalize
  from cftool.array import min_max_normalize_from
  from cftool.array import recover_min_max_normalize_from
  from cftool.array import quantile_normalize
  from cftool.array import quantile_normalize_from
  from cftool.array import recover_quantile_normalize_from
  from .file import FileParserBlock
  from .recognizer import RecognizerBlock
  from ....schema import DataBundle
  from ....schema import ColumnTypes
  from ....schema import INoInitDataBlock
label_desc: Use image node_id 2 for calling a global function with example usage: _transform(data, methods, all_stats, mapping) without return types