docstr: Generate signals from this model class instance and given parameters.
  
  Parameters
  ----------
  params : numpy.ndarray
      Array of shape (..., 28) containing the model parameters. Element 0
      is the natural logarithm of the signal without diffusion-weighting,
      elements 1-6 are the diffusion tensor elements in Voigt notation,
      and elements 7-27 are the covariance tensor elements in Voigt
      notation.
  
  Returns
  -------
  S : numpy.ndarray
      Signals.
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code: def predict(self, params):
      """Generate signals from this model class instance and given parameters.
  
      Parameters
      ----------
      params : numpy.ndarray
          Array of shape (..., 28) containing the model parameters. Element 0
          is the natural logarithm of the signal without diffusion-weighting,
          elements 1-6 are the diffusion tensor elements in Voigt notation,
          and elements 7-27 are the covariance tensor elements in Voigt
          notation.
  
      Returns
      -------
      S : numpy.ndarray
          Signals.
      """
      S0 = np.exp(params[..., 0])
      D = params[..., 1:7, np.newaxis]
      C = params[..., 7::, np.newaxis]
      S = qti_signal(self.gtab, D, C, S0)
      return S
  
imports: from warnings import warn
  import numpy
  from dipy.reconst.base import ReconstModel
  from dipy.reconst.dti import auto_attr
  from dipy.utils.optpkg import optional_package
label_desc: Use image node_id 3 for calling the QtiModel obj's underlying member method code with example usage: obj.predict(params) and returns: S