How to convert to elektronn3's expected hdf5 data set layout

neuro_data_zxy_to_neuro_data_cdhw.py

#!/usr/bin/env python3

# Example script to (in-place!) convert a data set from the standard layout
# expected by ELEKTRONN2 (z, x, y) to the new layout that elektronn3 uses
# (C, D, H, W).
# Remember to make a backup of your hdf5s before running this.
# The new data set format can still be read by ELEKTRONN2.

# This example assumes you want to convert the neuro_data_zxy example data set
# and execute the script in its directory.
# The lines for flipping the last axes is commented out because it is not
# relevant for our test data (this may be different with other data sets).

import h5py

fnames = [  # Explicit file names for clarity
    'barrier_int16_0.h5',
    'barrier_int16_1.h5',
    'barrier_int16_2.h5',
    'raw_0.h5',
    'raw_1.h5',
    'raw_2.h5',
]

## Uncomment to automatically find all hdf5 files in the CWD:
# fnames = [f for f in os.listdir() if f.endswith('.h5')]

for fname in fnames:
    with h5py.File(fname) as f:
        for k in f.keys():
            val = f[k].value.copy()
            print('Before:', f[k])
            if val.ndim == 3:
                val = val[None]  # Prepend single channel axis
            ## Uncomment the following line to flip the last two axes
            ## (...,x,y) -> (...,y,x) or in PyTorch notation: (...,W,H) -> (...,H,W)
            # val = val.swapaxes(-1, -2)
            del f[k]
            f.create_dataset(k, data=val, chunks=True)  # Compression could lead to issues
            print('After:', f[k])
            print('  Chunk size:', f[k].chunks)