code: def _kt_maximum_converge(ang, dt, md, kt):
      """Helper function that computes the inverse of the directional kurtosis
      of a voxel along a given direction in polar coordinates
  
      Parameters
      ----------
      ang : array (2,)
          array containing the two polar angles
      dt : array (6,)
          elements of the diffusion tensor of the voxel.
      md : float
          mean diffusivity of the voxel
      kt : array (15,)
          elements of the kurtosis tensor of the voxel.
  
      Returns
      -------
      neg_kt : float
          The inverse value of the apparent kurtosis for the given direction.
  
      Notes
      -----
      This function is used to refine the kurtosis maximum estimate
  
      See Also
      --------
      dipy.reconst.dki.kurtosis_maximum
  
      """
      n = np.array([sphere2cart(1, ang[0], ang[1])])
      return -1.0 * directional_kurtosis(dt, md, kt, n)
  
imports: import numpy
  import warnings
  import scipy.optimize
  import dipy.core.sphere
  from dipy.reconst.multi_voxel import multi_voxel_fit
  from dipy.reconst.dti import TensorFit, mean_diffusivity, from_lower_triangular, lower_triangular, decompose_tensor, MIN_POSITIVE_SIGNAL, nlls_fit_tensor, restore_fit_tensor
  from dipy.reconst.utils import dki_design_matrix
  from dipy.reconst.recspeed import local_maxima
  from dipy.reconst.base import ReconstModel
  from dipy.core.ndindex import ndindex
  from dipy.core.geometry import sphere2cart, cart2sphere, perpendicular_directions
  from dipy.core.optimize import PositiveDefiniteLeastSquares
  from dipy.data import get_sphere, get_fnames, load_sdp_constraints
  from dipy.reconst.vec_val_sum import vec_val_vect
  from dipy.core.gradients import check_multi_b
label_desc: Use image node_id 15 for calling a global function with example usage: _kt_maximum_converge(ang, dt, md, kt) and returns: unknown