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)
