code: def test_GGM2(verbose=0):
      shape = 1
      scale = 1
      mean = 0
      var = 1
      G = GGM(shape, scale, mean, var)
      sx = 1000
      x = -2.5 + nr.randn(sx)
      G.estimate(x)
      if verbose:
          G.parameters()
      b = np.absolute(G.mixt) < 0.1
      assert b
  
file_path: nipy/nipy/algorithms/clustering/tests/test_ggm.py
imports: import numpy
  import numpy.random
  import scipy.stats
  from ..ggmixture import GGGM, GGM, Gamma
label_desc: Use image node_id 2 for calling a global function with example usage: test_GGM2(verbose) without return types