code: def _compute_subject_basis(corr_mat):
      """From correlation matrix between shared response and subject data,
      Finds subject's basis
  
      Parameters
      ----------
  
      corr_mat: array, shape=[n_component, n_voxels]
      or shape=[n_components, n_supervoxels]
          correlation matrix between shared response and subject data or
           subject reduced data
          element k, v is given by S.T.dot(X_i) where S is the shared response
           and X_i the data of subject i.
  
      Returns
      -------
  
      basis: array, shape=[n_components, n_voxels]
      or shape=[n_components, n_supervoxels]
          basis of subject or reduced_basis of subject
      """
      # The perturbation is only here to be
      # consistent with current implementation
      # of DetSRM.
      perturbation = np.zeros(corr_mat.shape)
      np.fill_diagonal(perturbation, 0.001)
      U, _, V = scipy.linalg.svd(
          corr_mat + perturbation, full_matrices=False
      )
      return U.dot(V)
  
imports: import hashlib
  import logging
  import os
  import numpy
  import scipy
  from joblib import Parallel, delayed
  from brainiak.funcalign.srm import DetSRM
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.exceptions import NotFittedError
  import uuid
label_desc: Use image node_id 28 for calling a global function with example usage: _compute_subject_basis(corr_mat) and returns: U