code: def primitive_norm(l, alpha):
      r"""Compute the normalization constant for a primitive Gaussian function.
  
      A Gaussian function centred at the position :math:`r = (x, y, z)` is defined as
  
      .. math::
  
          G = x^{l_x} y^{l_y} z^{l_z} e^{-\alpha r^2},
  
      where :math:`l = (l_x, l_y, l_z)` defines the angular momentum quantum number and :math:`\alpha`
      is the Gaussian function exponent. The normalization constant for this function is computed as
  
      .. math::
  
          N(l, \alpha) = (\frac{2\alpha}{\pi})^{3/4} \frac{(4 \alpha)^{(l_x + l_y + l_z)/2}}
          {(2l_x-1)!! (2l_y-1)!! (2l_z-1)!!)^{1/2}}.
  
      Args:
          l (tuple[int]): angular momentum quantum number of the basis function
          alpha (array[float]): exponent of the primitive Gaussian function
  
      Returns:
          array[float]: normalization coefficient
  
      **Example**
  
      >>> l = (0, 0, 0)
      >>> alpha = np.array([3.425250914])
      >>> n = primitive_norm(l, alpha)
      >>> print(n)
      array([1.79444183])
      """
      lx, ly, lz = l
  
      n = (
          (2 * alpha / np.pi) ** 0.75
          * (4 * alpha) ** (sum(l) / 2)
          / qml.math.sqrt(
              _fac2(2 * lx - 1) * _fac2(2 * ly - 1) * _fac2(2 * lz - 1)
          )
      )
      return n
  
imports: import itertools
  import numpy
  from scipy.special import factorial2
  import pennylane
label_desc: Use image node_id 1 for calling a global function with example usage: primitive_norm(l, alpha) and returns: n