def test_pairwise_dependence_probability():
x = np.random.randn(30)
s1 = pd.Series(x)
s2 = pd.Series(x + 1.0)
s3 = pd.Series(np.random.rand(30))
df = pd.concat([s1, s2, s3], axis=1)
df.columns = ['c0', 'c1', 'c2']
engine = Engine(df, n_models=10, use_mp=False)
engine.init_models()
engine.run(5)
depprob = engine.pairwise_func('dependence_probability')
assert depprob.ix[0, 0] == 1.
assert depprob.ix[1, 1] == 1.
assert depprob.ix[2, 2] == 1.
assert depprob.ix[0, 1] == depprob.ix[1, 0]
assert depprob.ix[0, 2] == depprob.ix[2, 0]
assert depprob.ix[1, 2] == depprob.ix[2, 1]
def test_pairwise_dependence_probability():
x = np.random.randn(30)
s1 = pd.Series(x)
s2 = pd.Series(x + 1.0)
s3 = pd.Series(np.random.rand(30))
df = pd.concat([s1, s2, s3], axis=1)
df.columns = ['c0', 'c1', 'c2']
engine = Engine(df, n_models=10, use_mp=False)
engine.init_models()
engine.run(5)
depprob = engine.pairwise_func('dependence_probability')
assert depprob.ix[0, 0] == 1.
assert depprob.ix[1, 1] == 1.
assert depprob.ix[2, 2] == 1.
assert depprob.ix[0, 1] == depprob.ix[1, 0]
assert depprob.ix[0, 2] == depprob.ix[2, 0]
assert depprob.ix[1, 2] == depprob.ix[2, 1]
