code: def cti_design_matrix(gtab1, gtab2):
      r"""Construct B design matrix for CTI.
  
      Parameters
      ----------
      gtab1: dipy.core.gradients.GradientTable
          A GradientTable class instance for first DDE diffusion epoch
      gtab2: dipy.core.gradients.GradientTable
          A GradientTable class instance for second DDE diffusion epoch
  
      Returns
      -------
      B: array(N, 43)
      Design matrix or B matrix for the CTI model assuming multiple
      Gaussian Components
  
      """
      b1 = gtab1.bvals
      b2 = gtab2.bvals
      n1 = gtab1.bvecs
      n2 = gtab2.bvecs
      B = np.zeros((len(b1), 43))
  
      B[:, 0] = -b1 * (n1[:, 0] ** 2) - b2 * (n2[:, 0] ** 2)
      B[:, 1] = (
          -2 * b1 * n1[:, 0] * n1[:, 1] - 2 * b2 * n2[:, 0] * n2[:, 1]
      )
      B[:, 2] = -b1 * n1[:, 1] ** 2 - b2 * n2[:, 1] ** 2
      B[:, 3] = (
          -2 * b1 * n1[:, 0] * n1[:, 2] - 2 * b2 * n2[:, 0] * n2[:, 2]
      )
      B[:, 4] = (
          -2 * b1 * n1[:, 1] * n1[:, 2] - 2 * b2 * n2[:, 1] * n2[:, 2]
      )
      B[:, 5] = -b1 * n1[:, 2] ** 2 - b2 * n2[:, 2] ** 2
      B[:, 6] = (b1 * b1 * n1[:, 0] ** 4 + b2 * b2 * n2[:, 0] ** 4) / 6
      B[:, 7] = (b1 * b1 * n1[:, 1] ** 4 + b2 * b2 * n2[:, 1] ** 4) / 6
      B[:, 8] = (b1 * b1 * n1[:, 2] ** 4 + b2 * b2 * n2[:, 2] ** 4) / 6
      B[:, 9] = (
          2 * b1 * b1 * n1[:, 0] ** 3 * n1[:, 1]
          + 2 * b2 * b2 * n2[:, 0] ** 3 * n2[:, 1]
      ) / 3
      B[:, 10] = (
          2 * b1 * b1 * n1[:, 0] ** 3 * n1[:, 2]
          + 2 * b2 * b2 * n2[:, 0] ** 3 * n2[:, 2]
      ) / 3
      B[:, 11] = (
          2 * b1 * b1 * n1[:, 1] ** 3 * n1[:, 0]
          + 2 * b2 * b2 * n2[:, 1] ** 3 * n2[:, 0]
      ) / 3
      B[:, 12] = (
          2 * b1 * b1 * n1[:, 1] ** 3 * n1[:, 2]
          + 2 * b2 * b2 * n2[:, 1] ** 3 * n2[:, 2]
      ) / 3
      B[:, 13] = (
          2 * b1 * b1 * n1[:, 2] ** 3 * n1[:, 0]
          + 2 * b2 * b2 * n2[:, 2] ** 3 * n2[:, 0]
      ) / 3
      B[:, 14] = (
          2 * b1 * b1 * n1[:, 2] ** 3 * n1[:, 1]
          + 2 * b2 * b2 * n2[:, 2] ** 3 * n2[:, 1]
      ) / 3
      B[:, 15] = (
          b1 * b1 * n1[:, 0] ** 2 * n1[:, 1] ** 2
          + b2 * b2 * n2[:, 0] ** 2 * n2[:, 1] ** 2
      )
      B[:, 16] = (
          b1 * b1 * n1[:, 0] ** 2 * n1[:, 2] ** 2
          + b2 * b2 * n2[:, 0] ** 2 * n2[:, 2] ** 2
      )
      B[:, 17] = (
          b1 * b1 * n1[:, 1] ** 2 * n1[:, 2] ** 2
          + b2 * b2 * n2[:, 1] ** 2 * n2[:, 2] ** 2
      )
      B[:, 18] = (
          2 * b1 * b1 * n1[:, 0] ** 2 * n1[:, 1] * n1[:, 2]
          + 2 * b2 * b2 * n2[:, 0] ** 2 * n2[:, 1] * n2[:, 2]
      )
      B[:, 19] = (
          2 * b1 * b1 * n1[:, 1] ** 2 * n1[:, 0] * n1[:, 2]
          + 2 * b2 * b2 * n2[:, 1] ** 2 * n2[:, 0] * n2[:, 2]
      )
      B[:, 20] = (
          2 * b1 * b1 * n1[:, 2] ** 2 * n1[:, 0] * n1[:, 1]
          + 2 * b2 * b2 * n2[:, 2] ** 2 * n2[:, 0] * n2[:, 1]
      )
      B[:, 21] = b1 * n1[:, 0] ** 2 * b2 * n2[:, 0] ** 2
      B[:, 22] = b1 * n1[:, 1] ** 2 * b2 * n2[:, 1] ** 2
      B[:, 23] = b1 * n1[:, 2] ** 2 * b2 * n2[:, 2] ** 2
      B[:, 24] = (
          b1 * n1[:, 1] ** 2 * b2 * n2[:, 2] ** 2
          + b1 * n1[:, 2] ** 2 * b2 * n2[:, 1] ** 2
      )
      B[:, 25] = (
          b1 * n1[:, 0] ** 2 * b2 * n2[:, 2] ** 2
          + b1 * n1[:, 2] ** 2 * b2 * n2[:, 0] ** 2
      )
      B[:, 26] = (
          b1 * n1[:, 0] ** 2 * b2 * n2[:, 1] ** 2
          + b1 * n1[:, 1] ** 2 * b2 * n2[:, 0] ** 2
      )
      B[:, 27] = 2 * (
          b1 * n1[:, 0] ** 2 * b2 * n2[:, 1] * n2[:, 2]
          + b1 * n1[:, 1] * n1[:, 2] * b2 * n2[:, 0] ** 2
      )
      B[:, 28] = 2 * (
          b1 * n1[:, 0] ** 2 * b2 * n2[:, 0] * n2[:, 2]
          + b1 * n1[:, 0] * n1[:, 2] * b2 * n2[:, 0] ** 2
      )
      B[:, 29] = 2 * (
          b1 * n1[:, 0] ** 2 * b2 * n2[:, 0] * n2[:, 1]
          + b1 * n1[:, 0] * n1[:, 1] * b2 * n2[:, 0] ** 2
      )
      B[:, 30] = 2 * (
          b1 * n1[:, 1] ** 2 * b2 * n2[:, 1] * n2[:, 2]
          + b1 * n1[:, 1] * n1[:, 2] * b2 * n2[:, 1] ** 2
      )
      B[:, 31] = 2 * (
          b1 * n1[:, 1] ** 2 * b2 * n2[:, 0] * n2[:, 2]
          + b1 * n1[:, 0] * n1[:, 2] * b2 * n2[:, 1] ** 2
      )
      B[:, 32] = 2 * (
          b1 * n1[:, 1] ** 2 * b2 * n2[:, 1] * n2[:, 0]
          + b1 * n1[:, 1] * n1[:, 0] * b2 * n2[:, 1] ** 2
      )
      B[:, 33] = 2 * (
          b1 * n1[:, 2] ** 2 * b2 * n2[:, 2] * n2[:, 1]
          + b1 * n1[:, 2] * n1[:, 1] * b2 * n2[:, 2] ** 2
      )
      B[:, 34] = 2 * (
          b1 * n1[:, 2] ** 2 * b2 * n2[:, 2] * n2[:, 0]
          + b1 * n1[:, 2] * n1[:, 0] * b2 * n2[:, 2] ** 2
      )
      B[:, 35] = 2 * (
          b1 * n1[:, 2] ** 2 * b2 * n2[:, 0] * n2[:, 1]
          + b1 * n1[:, 0] * n1[:, 1] * b2 * n2[:, 2] ** 2
      )
      B[:, 36] = 4 * (
          b1 * n1[:, 1] * n1[:, 2] * b2 * n2[:, 1] * n2[:, 2]
      )
      B[:, 37] = 4 * (
          b1 * n1[:, 0] * n1[:, 2] * b2 * n2[:, 0] * n2[:, 2]
      )
      B[:, 38] = 4 * (
          b1 * n1[:, 0] * n1[:, 1] * b2 * n2[:, 0] * n2[:, 1]
      )
      B[:, 39] = 4 * (
          b1 * n1[:, 0] * n1[:, 2] * b2 * n2[:, 1] * n2[:, 2]
          + b1 * n1[:, 1] * n1[:, 2] * b2 * n2[:, 0] * n2[:, 2]
      )
      B[:, 40] = 4 * (
          b1 * n1[:, 0] * n1[:, 1] * b2 * n2[:, 0] * n2[:, 2]
          + b1 * n1[:, 0] * n1[:, 2] * b2 * n2[:, 0] * n2[:, 1]
      )
      B[:, 41] = 4 * (
          b1 * n1[:, 0] * n1[:, 1] * b2 * n2[:, 1] * n2[:, 2]
          + b1 * n1[:, 1] * n1[:, 2] * b2 * n2[:, 0] * n2[:, 1]
      )
      B[:, 42] = -np.ones(len(b1))
  
      return B
  
imports: import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: cti_design_matrix(gtab1, gtab2) and returns: B