code: def generate_momentum_flattened(d, massmatrix):
      """like normal distribution, but make momenta distributed like a single gaussian.
      **this is the one being used**"""
      momentum = np.random.multivariate_normal(
          np.zeros(d), np.dot(massmatrix, np.eye(d))
      )
      norm = (momentum**2).sum() ** 0.5
      assert norm > 0
      momentum *= norm ** (1 / d) / norm
      return momentum
  
imports: import numpy
  import matplotlib.pyplot
  import scipy.special
  import scipy.stats
label_desc: Use image node_id 10 for calling a global function with example usage: generate_momentum_flattened(d, massmatrix) and returns: momentum