class_docstr: Extract data from a SurfaceImage, averaging over atlas regions.
  
  Parameters
  ----------
  labels_img : SurfaceImage object
      Region definitions, as one image of labels.
  
  label_names : :obj:`list` of :obj:`str`, default=None
      Full labels corresponding to the labels image.
  
  Attributes
  ----------
  labels_data_ : :obj:`numpy.ndarray`
  
  labels_ : :obj:`numpy.ndarray`
  
  label_names_ : :obj:`numpy.ndarray`
class_docstr_tok: ["Extract","data","from","a","SurfaceImage",",","averaging","over","atlas","regions",".","Parameters","--","--","--","--","--","labels_img",":","SurfaceImage","object","Region","definitions",",","as","one","image","of","labels",".","label_names",":",":","obj",":","`","list","`","of",":","obj",":","`","str","`",",","default=None","Full","labels","corresponding","to","the","labels","image",".","Attributes","--","--","--","--","--","labels_data_",":",":","obj",":","`","numpy.ndarray","`","labels_",":",":","obj",":","`","numpy.ndarray","`","label_names_",":",":","obj",":","`","numpy.ndarray","`"]
docstr: Prepare and perform signal extraction from regions.
  
  Parameters
  ----------
  img : SurfaceImage object
      Mesh and data for both hemispheres.
  
  y : None
      This parameter is unused. It is solely included for scikit-learn
      compatibility.
  
  Returns
  -------
  numpy.ndarray
      Signal for each element.
      shape: (img data shape, total number of vertices)
docstr_tok: ["Prepare","and","perform","signal","extraction","from","regions",".","Parameters","--","--","--","--","--","img",":","SurfaceImage","object","Mesh","and","data","for","both","hemispheres",".","y",":","None","This","parameter","is","unused",".","It","is","solely","included","for","scikit-learn","compatibility",".","Returns","--","--","--","-","numpy.ndarray","Signal","for","each","element",".","shape",":","(","img","data","shape",",","total","number","of","vertices",")"]
code: def fit_transform(
      self, img: SurfaceImage, y: Any = None
  ) -> np.ndarray:
      """Prepare and perform signal extraction from regions.
  
      Parameters
      ----------
      img : SurfaceImage object
          Mesh and data for both hemispheres.
  
      y : None
          This parameter is unused. It is solely included for scikit-learn
          compatibility.
  
      Returns
      -------
      numpy.ndarray
          Signal for each element.
          shape: (img data shape, total number of vertices)
      """
      del y
      return self.fit(img).transform(img)
  
imports: from __future__ import annotations
  from typing import Any
  import numpy
  import pandas
  from joblib import Memory
  from sklearn.base import BaseEstimator, TransformerMixin
  from nilearn import signal
  from nilearn._utils.cache_mixin import CacheMixin, cache
  from nilearn._utils.class_inspect import get_params
  from nilearn.experimental.surface._surface_image import PolyMesh, SurfaceImage
label_desc: Use image node_id 4 for calling the SurfaceLabelsMasker obj's underlying member method code with example usage: obj.fit_transform(img, y) and returns: self