def test_ilr(self):
np.random.seed(0)
table = pd.DataFrame([[1, 1, 2, 2], [1, 2, 2, 1], [2, 2, 1, 1]],
index=[1, 2, 3],
columns=['a', 'b', 'c', 'd'])
table = table.reindex(columns=np.random.permutation(table.columns))
ph = pd.Series([1, 2, 3], index=table.index)
tree = gradient_linkage(table, ph)
res_balances = ilr_transform(table, tree)
exp_balances = pd.DataFrame([[0.693147, -5.551115e-17, 2.775558e-17],
[0.000000, -4.901291e-01, -4.901291e-01],
[-0.693147, 5.551115e-17, -2.775558e-17]],
columns=['y0', 'y1', 'y2'],
index=[1, 2, 3])
pdt.assert_frame_equal(res_balances, exp_balances)
def test_ilr(self):
np.random.seed(0)
table = pd.DataFrame([[1, 1, 2, 2],
[1, 2, 2, 1],
[2, 2, 1, 1]],
index=[1, 2, 3],
columns=['a', 'b', 'c', 'd'])
table = table.reindex(columns=np.random.permutation(table.columns))
ph = pd.Series([1, 2, 3], index=table.index)
tree = gradient_linkage(table, ph)
res_balances = ilr_transform(table, tree)
exp_balances = pd.DataFrame(
[[0.693147, -5.551115e-17, 2.775558e-17],
[0.000000, -4.901291e-01, -4.901291e-01],
[-0.693147, 5.551115e-17, -2.775558e-17]],
columns=['y0', 'y1', 'y2'],
index=[1, 2, 3])
pdt.assert_frame_equal(res_balances, exp_balances)