def test_calc_route_distances(shared_datadir, add_cli_arguments):
arguments = [
f"--files {shared_datadir / 'finder_output_example.hdf5'}",
"--model ted",
f"--output {shared_datadir/ 'temp_out.hdf5'}",
]
add_cli_arguments(" ".join(arguments))
calc_route_dist_main()
assert os.path.exists(str(shared_datadir / "temp_out.hdf5"))
data = pd.read_hdf(str(shared_datadir / "temp_out.hdf5"), "table")
assert "distances_time" in data.columns
assert "cluster_time" not in data.columns
assert "cluster_labels" not in data.columns
dist_mat = data.iloc[0].distance_matrix
assert len(dist_mat) == 3
assert pytest.approx(dist_mat[0][1], abs=1e-2) == 4.0596
assert pytest.approx(dist_mat[0][2], abs=1e-2) == 4.7446
assert pytest.approx(dist_mat[2][1], abs=1e-2) == 1.3149
dist_mat = data.iloc[1].distance_matrix
assert len(dist_mat) == 2
assert pytest.approx(dist_mat[0][1], abs=1e-2) == 4.0596
assert data.iloc[2].distance_matrix == [[0.0]]
def test_calc_route_only_clustering(shared_datadir, add_cli_arguments):
temp_file = str(shared_datadir / "temp_out.hdf5")
arguments = [
f"--files {shared_datadir / 'finder_output_example.hdf5'}",
"--model ted",
f"--output {temp_file}",
]
add_cli_arguments(" ".join(arguments))
calc_route_dist_main()
# Read in the created file and remove distances_time column
data = pd.read_hdf(temp_file, "table")
data = data[["trees", "distance_matrix"]]
data.to_hdf(temp_file, "table")
arguments = [
f"--files {temp_file}",
"--model ted",
f"--output {shared_datadir / 'temp_out2.hdf5'}",
"--nclusters 0",
"--only_clustering",
]
add_cli_arguments(" ".join(arguments))
calc_route_dist_main()
data = pd.read_hdf(str(shared_datadir / "temp_out2.hdf5"), "table")
assert "distances_time" not in data.columns
assert "cluster_time" in data.columns
assert "cluster_labels" in data.columns
assert data.iloc[0].cluster_labels == [1, 0, 0]
assert data.iloc[1].cluster_labels == []
assert data.iloc[2].cluster_labels == []
def test_calc_route_distances_with_lstm(shared_datadir, add_cli_arguments):
arguments = [
f"--files {shared_datadir / 'finder_output_example.hdf5'}",
f"--model {shared_datadir / 'dummy_model.ckpt'}",
f"--output {shared_datadir/ 'temp_out.hdf5'}",
]
add_cli_arguments(" ".join(arguments))
calc_route_dist_main()
assert os.path.exists(str(shared_datadir / "temp_out.hdf5"))
def test_calc_route_clustering(shared_datadir, add_cli_arguments):
arguments = [
f"--files {shared_datadir / 'finder_output_example.hdf5'}",
"--model ted",
f"--output {shared_datadir/ 'temp_out.hdf5'}",
"--nclusters 0",
]
add_cli_arguments(" ".join(arguments))
calc_route_dist_main()
data = pd.read_hdf(str(shared_datadir / "temp_out.hdf5"), "table")
assert "distances_time" in data.columns
assert "cluster_time" in data.columns
assert "cluster_labels" in data.columns
assert data.iloc[0].cluster_labels == [1, 0, 0]
assert data.iloc[1].cluster_labels == []
assert data.iloc[2].cluster_labels == []
def wrapper():
add_cli_arguments(" ".join(arguments))
calc_route_dist_main()