def launch_analysis():
engine = Engine(animals.values.astype(float),
num_states=64,
cctypes=['categorical'] * len(animals.values[0]),
distargs=[{
'k': 2
}] * len(animals.values[0]),
rng=gu.gen_rng(7))
engine.transition(N=900)
with open('resources/animals/animals.engine', 'w') as f:
engine.to_pickle(f)
engine = Engine.from_pickle(open('resources/animals/animals.engine', 'r'))
D = engine.dependence_probability_pairwise()
pu.plot_clustermap(D)
def create_engine(dist, noise, num_samples, num_states, timestamp):
T = simulate_dataset(dist, noise, num_samples)
print 'Creating engine (%s %1.2f) ...' % (dist, noise)
engine = Engine(T, cctypes=['normal','normal'], num_states=num_states)
engine.to_pickle(file(filename_engine(dist, noise, timestamp), 'w'))