code: def auto_response(
      gtab,
      data,
      roi_center=None,
      roi_radius=10,
      fa_thr=0.7,
      fa_callable=None,
      return_number_of_voxels=None,
  ):
      """Automatic estimation of ssst response function using FA.
  
      Parameters
      ----------
      gtab : GradientTable
      data : ndarray
          diffusion data
      roi_center : array-like, (3,)
          Center of ROI in data. If center is None, it is assumed that it is
          the center of the volume with shape `data.shape[:3]`.
      roi_radius : int
          radius of cubic ROI
      fa_thr : float
          FA threshold
      fa_callable : callable
          A callable that defines an operation that compares FA with the fa_thr.
          The operator should have two positional arguments
          (e.g., `fa_operator(FA, fa_thr)`) and it should return a bool array.
      return_number_of_voxels : bool
          If True, returns the number of voxels used for estimating the response
          function
  
      Returns
      -------
      response : tuple, (2,)
          (`evals`, `S0`)
      ratio : float
          The ratio between smallest versus largest eigenvalue of the response.
  
      Notes
      -----
      In CSD there is an important pre-processing step: the estimation of the
      fiber response function. In order to do this, we look for voxels with very
      anisotropic configurations. We get this information from
      csdeconv.mask_for_response_ssst(), which returns a mask of selected voxels
      (more details are available in the description of the function).
  
      With the mask, we compute the response function by using
      csdeconv.response_from_mask_ssst(), which returns the `response` and the
      `ratio` (more details are available in the description of the function).
      """
      msg = """Parameter `roi_radius` is now called `roi_radii` and can be an
      array-like (3,). Parameters `fa_callable` and `return_number_of_voxels`
      are not used anymore."""
      warnings.warn(msg, UserWarning)
      return auto_response_ssst(
          gtab, data, roi_center, roi_radius, fa_thr
      )
  
imports: import warnings
  import numpy
  import numbers
  from scipy.integrate import quad
  from scipy.special import lpn, gamma
  import scipy.linalg
  import scipy.linalg.lapack
  from dipy.data import small_sphere, get_sphere, default_sphere
  from dipy.core.geometry import cart2sphere
  from dipy.core.ndindex import ndindex
  from dipy.sims.voxel import single_tensor
  from dipy.reconst.multi_voxel import multi_voxel_fit
  from dipy.reconst.dti import TensorModel, fractional_anisotropy
  from dipy.reconst.shm import sph_harm_ind_list, real_sh_descoteaux_from_index, sph_harm_lookup, lazy_index, SphHarmFit, real_sh_descoteaux, sh_to_rh, forward_sdeconv_mat, SphHarmModel
  from dipy.reconst.utils import _roi_in_volume, _mask_from_roi
  from dipy.direction.peaks import peaks_from_model
  from dipy.core.geometry import vec2vec_rotmat
  from dipy.utils.deprecator import deprecate_with_version, deprecated_params
label_desc: Use image node_id 1 for calling a global function with example usage: auto_response(gtab, data, roi_center, roi_radius, fa_thr, fa_callable, return_number_of_voxels) and returns: auto_response_ssst