def _load_and_merge_mps(mp_list, store, label_merger, metadata_merger, merge_tasks):
mp_list = [mp.load_dataframes(store=store) for mp in mp_list]
mp = MetaPartition.merge_metapartitions(
mp_list, label_merger=label_merger, metadata_merger=metadata_merger
)
mp = mp.concat_dataframes()
for task in merge_tasks:
mp = mp.merge_dataframes(**task)
return mp
def test_merge_metapartitions():
df = pd.DataFrame({"P": [1, 1], "L": [1, 2], "TARGET": [1, 2]})
df_2 = pd.DataFrame({"P": [1], "info": "a"})
mp = MetaPartition(label="cluster_1", data={"core": df, "helper": df_2})
df_3 = pd.DataFrame({"P": [1, 1], "L": [1, 2], "PRED": [0.1, 0.2]})
mp2 = MetaPartition(label="cluster_1", data={"predictions": df_3})
merged_mp = MetaPartition.merge_metapartitions(metapartitions=[mp, mp2])
df = pd.DataFrame({
"P": [1, 1],
"L": [1, 2],
"TARGET": [1, 2],
"info": ["a", "a"],
"PRED": [0.1, 0.2],
})
assert merged_mp.label == "cluster_1"
assert len(merged_mp.data) == 3