docstr: Calculates diffusion properties for a single voxel
  
  Parameters
  ----------
  model : object,
      AnalyticalModel
  data : 1d ndarray,
      fitted data
  sh_coef : 1d ndarray,
      forecast sh coefficients
  d_par : float,
      parallel diffusivity
  d_perp : float,
      perpendicular diffusivity
docstr_tok: ["Calculates","diffusion","properties","for","a","single","voxel","Parameters","--","--","--","--","--","model",":","object",",","AnalyticalModel","data",":","1d","ndarray",",","fitted","data","sh_coef",":","1d","ndarray",",","forecast","sh","coefficients","d_par",":","float",",","parallel","diffusivity","d_perp",":","float",",","perpendicular","diffusivity"]
code: def __init__(self, model, data, sh_coef, d_par, d_perp):
      """Calculates diffusion properties for a single voxel
  
      Parameters
      ----------
      model : object,
          AnalyticalModel
      data : 1d ndarray,
          fitted data
      sh_coef : 1d ndarray,
          forecast sh coefficients
      d_par : float,
          parallel diffusivity
      d_perp : float,
          perpendicular diffusivity
      """
      OdfFit.__init__(self, model, data)
      self.model = model
      self._sh_coef = sh_coef
      self.gtab = model.gtab
      self.sh_order = model.sh_order
      self.d_par = d_par
      self.d_perp = d_perp
  
      self.rho = None
  
imports: from warnings import warn
  import numpy
  from dipy.reconst.cache import Cache
  from dipy.reconst.multi_voxel import multi_voxel_fit
  from dipy.reconst.csdeconv import csdeconv
  from dipy.reconst.shm import real_sh_descoteaux_from_index
  from scipy.special import gamma, hyp1f1
  from dipy.core.geometry import cart2sphere
  from dipy.data import default_sphere
  from dipy.reconst.odf import OdfModel, OdfFit
  from scipy.optimize import leastsq
  from dipy.utils.optpkg import optional_package
label_desc: Use image node_id 1 to create a new ForecastFit object from inherited base classes: OdfFit with example: obj = ForecastFit(model, data, sh_coef, d_par, d_perp)