import pdb import h5py import networkx as nx import numpy as np import pytest from nwb_linkml.io.hdf5 import HDF5IO, filter_dependency_graph, hdf_dependency_graph, truncate_file @pytest.mark.skip() @pytest.mark.parametrize("dset", ["aibs.nwb", "aibs_ecephys.nwb"]) def test_hdf_read(data_dir, dset): NWBFILE = data_dir / dset io = HDF5IO(path=NWBFILE) # the test for now is just whether we can read it lol model = io.read() def test_truncate_file(tmp_output_dir): source = tmp_output_dir / "truncate_source.hdf5" # create a dang ol hdf5 file with a big dataset and some softlinks and make sure # we truncate the dataset and preserve softlink h5f = h5py.File(str(source), "w") data_group = h5f.create_group("data") dataset_contig = h5f.create_dataset( "/data/dataset_contig", data=np.zeros((1000, 30, 40), dtype=np.float64), compression="gzip", compression_opts=9, ) dataset_chunked = h5f.create_dataset( "/data/dataset_chunked", data=np.zeros((1000, 40, 50), dtype=np.float64), compression="gzip", compression_opts=9, chunks=True, ) dataset_contig.attrs["reference_other"] = dataset_chunked.ref dataset_chunked.attrs["reference_other"] = dataset_contig.ref dataset_contig.attrs["anattr"] = 1 link_group = h5f.create_group("link/child") link_group.attrs["reference_contig"] = dataset_contig.ref link_group.attrs["reference_chunked"] = dataset_chunked.ref h5f.flush() h5f.close() source_size = source.stat().st_size # do it without providing target to check that we make filename correctly n = 10 target_output = truncate_file(source, n=n) assert target_output == source.parent / (source.stem + "_truncated.hdf5") # check that we actually made it smaller target_size = target_output.stat().st_size # empirically, the source dataset is ~125KB and truncated is ~17KB assert target_size < source_size / 5 # then check that we have what's expected in the file target_h5f = h5py.File(target_output, "r") # truncation happened assert target_h5f["data"]["dataset_contig"].shape == (n, 30, 40) assert target_h5f["data"]["dataset_chunked"].shape == (n, 40, 50) # references still work # can't directly assess object identity equality with "is" # so this tests if the referenced dereference and that they dereference to the right place assert ( target_h5f[target_h5f["data"]["dataset_contig"].attrs["reference_other"]].name == target_h5f["data"]["dataset_chunked"].name ) assert ( target_h5f[target_h5f["data"]["dataset_chunked"].attrs["reference_other"]].name == target_h5f["data"]["dataset_contig"].name ) assert ( target_h5f[target_h5f["link"]["child"].attrs["reference_contig"]].name == target_h5f["data"]["dataset_contig"].name ) assert ( target_h5f[target_h5f["link"]["child"].attrs["reference_chunked"]].name == target_h5f["data"]["dataset_chunked"].name ) assert target_h5f["data"]["dataset_contig"].attrs["anattr"] == 1 @pytest.mark.skip() def test_flatten_hdf(): from nwb_linkml.maps.hdf5 import flatten_hdf path = "/Users/jonny/Dropbox/lab/p2p_ld/data/nwb/sub-738651046_ses-760693773.nwb" import h5py h5f = h5py.File(path) flat = flatten_hdf(h5f) assert not any(["specifications" in v.path for v in flat.values()]) pdb.set_trace() raise NotImplementedError("Just a stub for local testing for now, finish me!") @pytest.mark.dev def test_dependency_graph(nwb_file, tmp_output_dir): """ dependency graph is correctly constructed from an HDF5 file """ graph = hdf_dependency_graph(nwb_file) A_unfiltered = nx.nx_agraph.to_agraph(graph) A_unfiltered.draw(tmp_output_dir / "test_nwb_unfiltered.png", prog="dot") graph = filter_dependency_graph(graph) A_filtered = nx.nx_agraph.to_agraph(graph) A_filtered.draw(tmp_output_dir / "test_nwb_filtered.png", prog="dot") pass @pytest.mark.skip def test_dependencies_hardlink(nwb_file): """ Test that hardlinks are resolved (eg. from /processing/ecephys/LFP/ElectricalSeries/electrodes to /acquisition/ElectricalSeries/electrodes Args: nwb_file: Returns: """ pass