class_docstr: inverse-Gaussian ??? used by NIG
      
code: def simulate(self, l, m, nrepl):
      N = np.random.randn(nrepl, 1)
      Y = N**2
      X = (
          m
          + (0.5 * m * m / l) * Y
          - (0.5 * m / l) * np.sqrt(4 * m * l * Y + m * m * (Y**2))
      )
      U = np.random.rand(nrepl, 1)
  
      ind = U > m / (X + m)
      X[ind] = m * m / X[ind]
      return X.ravel()
  
imports: import numpy
  import matplotlib.pyplot
label_desc: Use image node_id 2 for calling the IG obj's underlying member method code with example usage: obj.simulate(l, m, nrepl) and returns: X