def test__sort_leaderboard_no_rank():
rank = None
metrics = METRICS
score = {k: range(5) for k in metrics.keys()}
score['pipeline'] = range(5)
score = pd.DataFrame(score)
expected_return = score.iloc[::-1].reset_index(drop=True)
expected_return['rank'] = range(1, 6)
returned = benchmark._sort_leaderboard(score, rank, metrics)
assert len(returned.columns) == len(expected_return.columns)
assert sorted(returned.columns) == sorted(expected_return.columns)
pd.testing.assert_frame_equal(returned, expected_return[returned.columns])
def test__sort_leaderboard_rank_does_not_exist():
rank = 'does not exist'
metrics = {'f1': METRICS['f1']}
score = pd.DataFrame({
'pipeline': range(5),
'f1': range(5),
})
expected_return = pd.DataFrame({
'pipeline': range(5)[::-1],
'rank': range(1, 6),
'f1': range(5)[::-1],
})
returned = benchmark._sort_leaderboard(score, rank, metrics)
pd.testing.assert_frame_equal(returned, expected_return)
def test__sort_leaderboard_rank():
rank = 'f1'
metrics = METRICS
score = pd.DataFrame({
'pipeline': range(5),
'f1': range(5),
})
expected_return = pd.DataFrame({
'pipeline': range(5)[::-1],
'rank': range(1, 6),
'f1': range(5)[::-1],
})
returned = benchmark._sort_leaderboard(score, rank, metrics)
pd.testing.assert_frame_equal(returned, expected_return)