mirror of
https://github.com/p2p-ld/nwb-linkml.git
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100 lines
3.4 KiB
Python
100 lines
3.4 KiB
Python
import pdb
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import h5py
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import numpy as np
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import pytest
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from nwb_linkml.io.hdf5 import HDF5IO, truncate_file
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@pytest.mark.skip()
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@pytest.mark.parametrize("dset", ["aibs.nwb", "aibs_ecephys.nwb"])
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def test_hdf_read(data_dir, dset):
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NWBFILE = data_dir / dset
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io = HDF5IO(path=NWBFILE)
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# the test for now is just whether we can read it lol
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model = io.read()
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def test_truncate_file(tmp_output_dir):
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source = tmp_output_dir / "truncate_source.hdf5"
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# create a dang ol hdf5 file with a big dataset and some softlinks and make sure
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# we truncate the dataset and preserve softlink
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h5f = h5py.File(str(source), "w")
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data_group = h5f.create_group("data")
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dataset_contig = h5f.create_dataset(
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"/data/dataset_contig",
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data=np.zeros((1000, 30, 40), dtype=np.float64),
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compression="gzip",
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compression_opts=9,
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)
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dataset_chunked = h5f.create_dataset(
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"/data/dataset_chunked",
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data=np.zeros((1000, 40, 50), dtype=np.float64),
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compression="gzip",
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compression_opts=9,
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chunks=True,
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)
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dataset_contig.attrs["reference_other"] = dataset_chunked.ref
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dataset_chunked.attrs["reference_other"] = dataset_contig.ref
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dataset_contig.attrs["anattr"] = 1
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link_group = h5f.create_group("link/child")
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link_group.attrs["reference_contig"] = dataset_contig.ref
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link_group.attrs["reference_chunked"] = dataset_chunked.ref
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h5f.flush()
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h5f.close()
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source_size = source.stat().st_size
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# do it without providing target to check that we make filename correctly
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n = 10
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target_output = truncate_file(source, n=n)
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assert target_output == source.parent / (source.stem + "_truncated.hdf5")
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# check that we actually made it smaller
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target_size = target_output.stat().st_size
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# empirically, the source dataset is ~125KB and truncated is ~17KB
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assert target_size < source_size / 5
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# then check that we have what's expected in the file
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target_h5f = h5py.File(target_output, "r")
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# truncation happened
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assert target_h5f["data"]["dataset_contig"].shape == (n, 30, 40)
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assert target_h5f["data"]["dataset_chunked"].shape == (n, 40, 50)
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# references still work
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# can't directly assess object identity equality with "is"
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# so this tests if the referenced dereference and that they dereference to the right place
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assert (
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target_h5f[target_h5f["data"]["dataset_contig"].attrs["reference_other"]].name
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== target_h5f["data"]["dataset_chunked"].name
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)
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assert (
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target_h5f[target_h5f["data"]["dataset_chunked"].attrs["reference_other"]].name
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== target_h5f["data"]["dataset_contig"].name
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)
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assert (
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target_h5f[target_h5f["link"]["child"].attrs["reference_contig"]].name
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== target_h5f["data"]["dataset_contig"].name
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)
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assert (
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target_h5f[target_h5f["link"]["child"].attrs["reference_chunked"]].name
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== target_h5f["data"]["dataset_chunked"].name
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)
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assert target_h5f["data"]["dataset_contig"].attrs["anattr"] == 1
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@pytest.mark.skip()
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def test_flatten_hdf():
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from nwb_linkml.maps.hdf5 import flatten_hdf
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path = "/Users/jonny/Dropbox/lab/p2p_ld/data/nwb/sub-738651046_ses-760693773.nwb"
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import h5py
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h5f = h5py.File(path)
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flat = flatten_hdf(h5f)
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assert not any(["specifications" in v.path for v in flat.values()])
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pdb.set_trace()
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raise NotImplementedError("Just a stub for local testing for now, finish me!")
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