class_docstr: Dictionary-based wrapper of :py:class:`monai.apps.pathology.transforms.ExtractHEStains`.
  Class to extract a target stain from an image, using stain deconvolution.
  
  Args:
      keys: keys of the corresponding items to be transformed.
          See also: :py:class:`monai.transforms.compose.MapTransform`
      tli: transmitted light intensity. Defaults to 240.
      alpha: tolerance in percentile for the pseudo-min (alpha percentile)
          and pseudo-max (100 - alpha percentile). Defaults to 1.
      beta: absorbance threshold for transparent pixels. Defaults to 0.15
      max_cref: reference maximum stain concentrations for Hematoxylin & Eosin (H&E).
          Defaults to (1.9705, 1.0308).
      allow_missing_keys: don't raise exception if key is missing.
code: def __call__(
      self, data: Mapping[Hashable, np.ndarray]
  ) -> dict[Hashable, np.ndarray]:
      d = dict(data)
      for key in self.key_iterator(d):
          d[key] = self.extractor(d[key])
      return d
  
file_path: MONAI/monai/apps/pathology/transforms/stain/dictionary.py
imports: from __future__ import annotations
  from collections.abc import Hashable, Mapping
  import numpy
  from monai.config import KeysCollection
  from monai.transforms.transform import MapTransform
  from .array import ExtractHEStains, NormalizeHEStains
label_desc: Use image node_id 2 for calling the ExtractHEStainsd obj's underlying member method code with example usage: obj.__call__(data) and returns: d