code: def sticks_and_ball(
      gtab,
      d=0.0015,
      S0=1.0,
      angles=((0, 0), (90, 0)),
      fractions=(35, 35),
      snr=20,
  ):
      """Simulate the signal for a Sticks & Ball model.
  
      Parameters
      ----------
      gtab : GradientTable
          Signal measurement directions.
      d : float, optional
          Diffusivity value.
      S0 : float, optional
          Unweighted signal value.
      angles : array (K, 2) or (K, 3), optional
          List of K polar angles (in degrees) for the sticks or array of K
          sticks as unit vectors.
      fractions : array-like, optional
          Percentage of each stick.  Remainder to 100 specifies isotropic
          component.
      snr : float, optional
          Signal to noise ratio, assuming Rician noise.  If set to None, no
          noise is added.
  
      Returns
      -------
      S : (N,) ndarray
          Simulated signal.
      sticks : (M,3)
          Sticks in cartesian coordinates.
  
      References
      ----------
      .. [1] Behrens et al., "Probabilistic diffusion
             tractography with multiple fiber orientations:  what can we gain?",
             Neuroimage, 2007.
  
      """
      fractions = [f / 100.0 for f in fractions]
      f0 = 1 - np.sum(fractions)
      S = np.zeros(len(gtab.bvals))
  
      sticks = _check_directions(angles)
  
      for i, g in enumerate(gtab.bvecs[1:]):
          S[i + 1] = f0 * np.exp(-gtab.bvals[i + 1] * d) + np.sum(
              [
                  fractions[j]
                  * np.exp(-gtab.bvals[i + 1] * d * np.dot(s, g) ** 2)
                  for (j, s) in enumerate(sticks)
              ]
          )
  
          S[i + 1] = S0 * S[i + 1]
  
      S[gtab.b0s_mask] = S0
      S = add_noise(S, snr, S0)
  
      return S, sticks
  
imports: import numpy
  from numpy import dot
  from dipy.core.geometry import sphere2cart
  from dipy.core.geometry import vec2vec_rotmat
  from dipy.core.gradients import GradientTable
  from dipy.reconst.utils import dki_design_matrix
  from scipy.special import jn
label_desc: Use image node_id 6 for calling a global function with example usage: sticks_and_ball(gtab, d, S0, angles, fractions, snr) and returns: S,  sticks