>>> import numpy as np
>>> import criticalnet as cnet
>>>
>>> im = cnet.data.sample('baboon')

>>> net0 = cnet.CriticalNet(image=im, ktimes=110, lap_mode='LOG')
>>> net0.compute(beta=10, extrema_dist=25, draw=True)

>>> import numpy as np
>>> from scipy.misc import face 
>>> from PIL import Image
>>> import criticalnet as cnet
>>>
>>> racc = Image.fromarray(face(), mode='RGB')
>>> im = np.array(racc.convert(mode='F'))
>>>
>>> net0 = cnet.CriticalNet(image=im, ktimes=110)
>>> net0.calc_sscale()
>>> net0.calc_lap('DOG')
>>> net0.calc_beta_levels()
>>> net0.calc_cnet(beta=8, extrema_dist=30)
>>> net0.draw()

>>> import networkx as nx
>>> G = net0.G
>>> nx.is_directed_acyclic_graph(G)