pack5's Introduction

pack5

python utility script to bundle multiple npz files into one hdf5

Usage

This small script assumes that you have something like this:

$ ls tests/*{json,npy}
tests/data_000000.npy  tests/data_000007.npy  tests/pars000004.json
tests/data_000001.npy  tests/data_000008.npy  tests/pars000005.json
tests/data_000002.npy  tests/data_000009.npy  tests/pars000006.json
tests/data_000003.npy  tests/pars000000.json  tests/pars000007.json
tests/data_000004.npy  tests/pars000001.json  tests/pars000008.json
tests/data_000005.npy  tests/pars000002.json  tests/pars000009.json
tests/data_000006.npy  tests/pars000003.json

The json files go as metadata with the .npy files. As mentioned it's the goal of this small script to pack the .npy files into a hdf5 compliant format. This can be done in 2 ways:

by using a wildcard expression

$ python3 ./pack5.py --output cli.h5 --numpy-wc "./tests/data*.npy" --json-wc "./tests/pars*.json"

This will store are contents of the 10 .npy files inside cli.h5 and attach the contents of the respective pars*.json as attributes (for more details, see dataset attributes.

by providing a list of files

$ python3 ./pack5.py --output cli.h5 --numpy-list numpy.list --json-list json.list

which in turn contain the full paths.

The tool is written such that it can store only chunks of the data inside a series of hdf5 files:

$ python3 ./pack5.py --output cli.h5 --numpy-wc "./tests/data*.npy" --json-wc "./tests/pars*.json" --files-per-chunk 2
Wrote 5/5 .h5 files from 10 inputs

This has created 5 .h5 files with 2 npy/json datasets inside each.

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