import pdb import h5py import pytest from pathlib import Path import numpy as np from ..fixtures import tmp_output_dir, data_dir from nwb_linkml.io.hdf5 import HDF5IO from nwb_linkml.io.hdf5 import truncate_file @pytest.mark.skip() @pytest.mark.parametrize('dset', ['aibs.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.io.hdf5 import HDF5IO 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!')