def uncropped_data_and_metadata():
full_data_file = os.path.join(TEST_DATA_DIR, "trimouse_eval.pickle")
metadata_file = full_data_file.replace("eval", "meta")
with open(full_data_file, "rb") as file:
data = pickle.load(file)
with open(metadata_file, "rb") as file:
metadata = pickle.load(file)
params = crossvalutils._set_up_evaluation(data)
data_unc, _ = crossvalutils._rebuild_uncropped_data(data, params)
meta_unc = crossvalutils._rebuild_uncropped_metadata(metadata, params["imnames"])
return data_unc, meta_unc
def test_get_n_best_paf_graphs(evaluation_data_and_metadata):
data, metadata = evaluation_data_and_metadata
params = crossvalutils._set_up_evaluation(data)
n_graphs = 5
paf_inds, dict_ = crossvalutils._get_n_best_paf_graphs(data,
metadata,
params["paf_graph"],
n_graphs=n_graphs)
assert len(paf_inds) == n_graphs
assert len(dict_) == len(params["paf_graph"])
assert len(paf_inds[0]) == 11
assert paf_inds[0] == BEST_GRAPH
assert len(paf_inds[-1]) == len(params["paf_graph"])
def test_get_n_best_paf_graphs_montblanc(
evaluation_data_and_metadata_montblanc):
data, metadata = evaluation_data_and_metadata_montblanc
params = crossvalutils._set_up_evaluation(data)
paf_inds, dict_ = crossvalutils._get_n_best_paf_graphs(
data,
metadata,
params["paf_graph"],
)
assert len(paf_inds) == 4
assert len(dict_) == len(params["paf_graph"])
assert [len(inds) for inds in paf_inds] == list(range(3, 7))
assert paf_inds[-1] == BEST_GRAPH_MONTBLANC
assert len(paf_inds[-1]) == len(params["paf_graph"])