def test_merge_factors():
z = pd.DataFrame(
[
[1, 1, 1, 0, 0, 0, 1, 0, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 0, 0, 1, 0],
[0, 0, 0, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 1, 0, 1, 1, 1, 0],
],
index=[f"sample {i}" for i in range(11)],
columns=[f"LF{i}" for i in range(9)],
dtype=float,
) # expect 0,1,2 to be merged, and 3,7 to be merged
z_merged = utils.merge_factors(z, metric="euclidean", plot_dendro=False)
assert z_merged.shape[1] == 6
assert "0_1_2" in z_merged.columns
assert "3_7" in z_merged.columns
def test_merge_factors_with_custom_linkage():
z = pd.DataFrame(
[
[1, 1, 1, 0, 0, 0, 1, 0, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 0, 1, 1, 1, 0],
[1, 1, 1, 1, 1, 0, 0, 1, 0],
[0, 0, 0, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 1, 0, 0, 1, 1, 0],
[0, 0, 0, 1, 0, 1, 1, 1, 0],
],
index=[f"sample {i}" for i in range(11)],
columns=[f"LF{i}" for i in range(9)],
dtype=float,
) # expect 0,1,2 to be merged, and 3,7 to be merged
l = cluster.hierarchy.linkage(spatial.distance.pdist(z.T, "minkowski"),
"average")
z_merged = utils.merge_factors(z, l=l, plot_dendro=False)
assert z_merged.shape[1] == 6
assert "0_1_2" in z_merged.columns
assert "3_7" in z_merged.columns