BEP032 tools

This repository collects tools supporting the BEP032 proposal. It originally emerged under the name AnDO (Animal Data Organization) and gathers a set of tools facilitating the usage of the proposed structure. For the documentation of BIDS itself, see https://bids-specification.readthedocs.io. The proposal is open to any type of feedback from the community and we are welcoming all types of constructive comments.

The provided tools integrating with BEP032 are :

BEP032Validator script to check if your dataset follows the current BEP032 rules
BEP032Generator script to create a BEP032 compatible folder structure without metadata files for a given set of subjects and sessions. These files need to be listed in an input CSV file.
BEP032Templater script to generate a BEP032 compatible folder structure including dummy files to be extended manually, e.g. using Excel or a text editor
BEP032Viewer script to display your dataset directory in a convenient way. (deprecated)

The official documentation is hosted on ReadTheDocs.

Installation

Dependencies

BEP032Validator requires:

Python (>= 3.7)
Pip3

User installation

To include all packages required for the BEP032 tools download the repository from https://github.com/INT-NIT/BEP032tools and run the following in the unpacked version of the repository

>  pip install BEP032tools[tools]

By installing BEP032Validator the following scripts will be installed:

General usage for the BEP032Validator script

usage: BEP032Validator.py [-h] [-v] path

positional arguments:
  path           Path to your folder

optional arguments:  -h, --help     show this help message and exit
  -v, --verbose  increase output verbosity

Specific usage

The validator can be directly used from the command line interface (CLI)

> BEP032Validator -v tests/dataset001/Landing

or from within Python

> from bep032tools.validator import BEP032Validator
> BEP032Validator.is_valid('tests/dataset001/Landing')

General usage for the Generator script

The generator can be used to create a BEP032 compatible folder structure (without metadata files) based on a list of sessions and subject. This list of sessions and subject has to be provided in form of a CSV file:

usage: BEP032Generator.py [-h] pathToCsv pathToDir

positional arguments:
  pathToCsv   Path to your folder
  pathToDir   Path to your csv file

optional arguments:
  -h, --help  show this help message and exit

The generator can be directly used from the command line interface (CLI)

> BEP032Generator data.csv data/

General usage for the Templater script

usage: BEP032Temlater.py [-h] pathToCsv pathToDir

positional arguments:
  pathToCsv   Path to your folder
  pathToDir   Path to your csv file

optional arguments:
  -h, --help  show this help message and exit

The templater can be directly used from the command line interface (CLI)

> BEP032Templater data.csv data/

How to create a BEP032 structure including custom metadata

There are two options to add custom metadata (files) to a BEP032 structure

1) Generation of the structure including dummy metadata files using the BEP032Templator and manual entry of the metadata in those files. 2) Programmatic extension of the BEP032Generator. For this you need to create a Python class that inherits from bep032tools.generator.BE032Generator and implements the missing metadata methods:

generate_metadata_file_sessions
generate_metadata_file_tasks
generate_metadata_file_dataset_description
generate_metadata_file_participants
generate_metadata_file_probes
generate_metadata_file_probes
generate_metadata_file_channels
generate_metadata_file_contacts
generate_metadata_file_scans

These methods should fetch the corresponding metadata information from your project specific location and create the corresponding CSV or JSON file using the generator.utils.save_json and generator.utils.save_tsv functions correspondingly. When all missing methods are implemented generator.BEP032Generator.generate_struct() will not only create the corresponding folder structure, but also all metadata files with the metadata provided.

Installation issues

In some cases pandas might not be properly installed via pip. In this case we recommend installing pandas via conda.

Development

We welcome new contributors of all experience levels.

Important links

Official source code repo: https://github.com/INT-NIT/BEP032tools
(In planning) Download releases: https://pypi.org/project/BEP032tools/
Issue tracker:https://github.com/INT-NIT/BEP032tools/issues

Contributing

To contribute to the development of BEP032tools, please open an issue or pull request or directly comment in the BEP032 proposal.

INT-NIT / BEP032tools

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