docstr: Given a model fit, predict the signal.
  
  Parameters
  ----------
  gtab : GradientTable class instance
         Gradient directions and bvalues
  
  S0 : float
      S0 value here is not necessary and will not be used to predict the
      signal. It has been added to conform to the structure of the
      predict method in multi_voxel which requires a keyword argument S0.
  
  Returns
  -------
  signal : array
      The signal values predicted for this model using its parameters.
code: def predict(self, gtab, S0=1.0):
      """Given a model fit, predict the signal.
  
      Parameters
      ----------
      gtab : GradientTable class instance
             Gradient directions and bvalues
  
      S0 : float
          S0 value here is not necessary and will not be used to predict the
          signal. It has been added to conform to the structure of the
          predict method in multi_voxel which requires a keyword argument S0.
  
      Returns
      -------
      signal : array
          The signal values predicted for this model using its parameters.
  
      """
      return ivim_prediction(self.model_params, gtab)
  
imports: import warnings
  import numpy
  from scipy.optimize import least_squares, differential_evolution
  from dipy.reconst.base import ReconstModel
  from dipy.reconst.multi_voxel import multi_voxel_fit
  from dipy.utils.optpkg import optional_package
label_desc: Use image node_id 8 for calling the IvimFit obj's underlying member method code with example usage: obj.predict(gtab, S0) and returns: ivim_prediction