class_docstr: Class for fitting the Diffusion Kurtosis Model
docstr: Compute the maximum value of a single voxel kurtosis tensor
  
  Parameters
  ----------
  sphere : Sphere class instance, optional
      The sphere providing sample directions for the initial search of
      the maximum value of kurtosis.
  gtol : float, optional
      This input is to refine kurtosis maximum under the precision of the
      directions sampled on the sphere class instance. The gradient of
      the convergence procedure must be less than gtol before successful
      termination. If gtol is None, fiber direction is directly taken
      from the initial sampled directions of the given sphere object
  
  Returns
  -------
  max_value : float
      kurtosis tensor maximum value
docstr_tok: ["Compute","the","maximum","value","of","a","single","voxel","kurtosis","tensor","Parameters","--","--","--","--","--","sphere",":","Sphere","class","instance",",","optional","The","sphere","providing","sample","directions","for","the","initial","search","of","the","maximum","value","of","kurtosis",".","gtol",":","float",",","optional","This","input","is","to","refine","kurtosis","maximum","under","the","precision","of","the","directions","sampled","on","the","sphere","class","instance",".","The","gradient","of","the","convergence","procedure","must","be","less","than","gtol","before","successful","termination",".","If","gtol","is","None",",","fiber","direction","is","directly","taken","from","the","initial","sampled","directions","of","the","given","sphere","object","Returns","--","--","--","-","max_value",":","float","kurtosis","tensor","maximum","value"]
code: def kmax(self, sphere="repulsion100", gtol=1e-5, mask=None):
      r"""Compute the maximum value of a single voxel kurtosis tensor
  
      Parameters
      ----------
      sphere : Sphere class instance, optional
          The sphere providing sample directions for the initial search of
          the maximum value of kurtosis.
      gtol : float, optional
          This input is to refine kurtosis maximum under the precision of the
          directions sampled on the sphere class instance. The gradient of
          the convergence procedure must be less than gtol before successful
          termination. If gtol is None, fiber direction is directly taken
          from the initial sampled directions of the given sphere object
  
      Returns
      -------
      max_value : float
          kurtosis tensor maximum value
  
      """
      return kurtosis_maximum(self.model_params, sphere, gtol, mask)
  
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 7 for calling the DiffusionKurtosisFit obj's underlying member method code with example usage: obj.kmax(sphere, gtol, mask) and returns: kurtosis_maximum