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)
def test_GGM1(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) b = np.absolute(G.mean+2.5)<0.5 if verbose: #G.parameters() print x.max() assert(b)