code: def _inflate_response(response, gtab, n, delta):
      """Used to inflate the response for the `multiplier_matrix` in the
      `MultiShellDeconvModel`.
      Parameters
      ----------
      response : MultiShellResponse object
      gtab : GradientTable
      n : int ``>= 0``
          The degree of the harmonic.
      delta : Delta generated from `_basic_delta`
      """
      if any((n % 2) != 0) or (n.max() // 2) >= response.sh_order:
          raise ValueError("Response and n do not match")
  
      iso = response.iso
      n_idx = np.empty(len(n) + iso, dtype=int)
      n_idx[:iso] = np.arange(0, iso)
      n_idx[iso:] = n // 2 + iso
      diff = abs(response.shells[:, None] - gtab.bvals)
      b_idx = np.argmin(diff, axis=0)
      kernel = response.response / delta
  
      return kernel[np.ix_(b_idx, n_idx)]
  
imports: from packaging.version import Version
  import numbers
  import warnings
  import numpy
  from dipy.core import geometry
  from dipy.core.gradients import GradientTable, gradient_table, unique_bvals_tolerance, get_bval_indices
  from dipy.data import default_sphere
  from dipy.reconst import shm
  from dipy.reconst.csdeconv import response_from_mask_ssst
  from dipy.reconst.dti import TensorModel, fractional_anisotropy, mean_diffusivity
  from dipy.reconst.multi_voxel import multi_voxel_fit
  from dipy.reconst.utils import _roi_in_volume, _mask_from_roi
  from dipy.sims.voxel import single_tensor
  from dipy.utils.optpkg import optional_package
label_desc: Use image node_id 2 for calling a global function with example usage: _inflate_response(response, gtab, n, delta) and returns: kernel