code: def _check_isc_input(iscs, pairwise=False):
      """Checks ISC inputs for statistical tests
  
      Input ISCs should be n_subjects (leave-one-out approach) or
      n_pairs (pairwise approach) by n_voxels or n_ROIs array or a 1D
      array (or list) of ISC values for a single voxel or ROI. This
      function is only intended to be used internally by other
      functions in this module (e.g., bootstrap_isc, permutation_isc).
  
      Parameters
      ----------
      iscs : ndarray or list
          ISC values
  
      Returns
      -------
      iscs : ndarray
          Array of ISC values
  
      n_subjects : int
          Number of subjects
  
      n_voxels : int
          Number of voxels (or ROIs)
      """
  
      # Standardize structure of input data
      if type(iscs) == list:
          iscs = np.array(iscs)[:, np.newaxis]
  
      elif isinstance(iscs, np.ndarray):
          if iscs.ndim == 1:
              iscs = iscs[:, np.newaxis]
  
      # Check if incoming pairwise matrix is vectorized triangle
      if pairwise:
          try:
              test_square = squareform(iscs[:, 0], force="tomatrix")
              n_subjects = test_square.shape[0]
          except ValueError:
              raise ValueError(
                  "For pairwise input, ISCs must be the "
                  "vectorized triangle of a square matrix."
              )
      elif not pairwise:
          n_subjects = iscs.shape[0]
  
      # Infer subjects, voxels and print for user to check
      n_voxels = iscs.shape[1]
      logger.info(
          "Assuming {0} subjects with and {1} "
          "voxel(s) or ROI(s) in bootstrap ISC test.".format(
              n_subjects, n_voxels
          )
      )
  
      return iscs, n_subjects, n_voxels
  
imports: import numpy
  import logging
  from scipy.spatial.distance import squareform
  from itertools import combinations, permutations, product
  from brainiak.fcma.util import compute_correlation
  from brainiak.utils.utils import array_correlation, phase_randomize, p_from_null, _check_timeseries_input
label_desc: Use image node_id 3 for calling a global function with example usage: _check_isc_input(iscs, pairwise) and returns: iscs,  n_subjects,  n_voxels