Skip to main content

A JSON schema-based framework for mapping and structuring experimental data

Project description

TokaMap

TokaMap is a JSON schema-based framework for mapping and structuring experimental data. It provides a standardized way to define how experimental measurements, calculations, and data transformations should be organized and validated.

The Python package contains the following components:

  • tokamap: A module that provides details about the install, such as the schemas directory
  • tokamap.validator: The validation module for ensuring data consistency and correctness

And the following CLI tools:

  • tokamap: Command-line interface for querying details about the install, such as the schemas directory
  • tokamap-validator: Command-line interface for validating TokaMap mappings

Overview

TokaMap defines a set of JSON schemas that allow researchers and engineers to:

  • Map experimental data using structured configuration files
  • Define data sources with standardized parameters and arguments
  • Create expressions and calculations from mapped data
  • Partition and group data based on experimental attributes
  • Validate mappings to ensure data consistency and correctness

Installation

From PyPI

pip install tokamap

From Source

git clone https://github.com/ukaea/tokamap.git
pip install .

TokaMap CLI

Finding the schemas directory:

tokamap --schemas-dir

Checking the installed version:

tokamap --version

TokaMap library

Finding the schemas directory:

from tokamap import schemas_dir

print(schemas_dir())

Checking the installed version:

from tokamap import __version__

print(__version__)

Validation

TokaMap includes a Python validator tool to ensure your mapping files conform to the schemas.

Usage

Validate a TokaMap mapping directory:

tokamap-validator /path/to/mapping/directory

For verbose output:

tokamap-validator -v /path/to/mapping/directory

The validator will:

  1. Check that the configuration file (mappings.cfg.json) exists and is valid
  2. Validate the top-level globals file
  3. Validate each mapping group's globals and mappings files

Validator Requirements

  • Python >= 3.13
  • jsonschema >= 4.25.0

Architecture

The TokaMap system consists of three main schema components:

1. Configuration Schema (mappings.cfg.schema.json)

Defines the top-level configuration structure including:

  • Metadata: Experiment information, author, and version
  • Partitions: Data partitioning rules with selectors (max_below, min_above, exact, closest)
  • Groups: Array of group identifiers

2. Globals Schema (globals.schema.json)

Defines global configuration settings, particularly data source configurations with their associated arguments.

3. Mappings Schema (mappings.schema.json)

Defines the structure for mapping experimental data with five main mapping types:

  • DIMENSION: Maps dimensional probe data
  • VALUE: Maps static values (numbers, strings, arrays, objects)
  • DATA_SOURCE: Maps external data sources with configurable arguments, offsets, scaling, and slicing
  • EXPR: Maps mathematical expressions with parameters
  • CUSTOM: Maps custom functions from external libraries

For more information see the docs.

Contributing

TokaMap is developed to support experimental data mapping workflows. The schemas are designed to be extensible while maintaining validation integrity.

License

See the main project LICENSE file for license information.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tokamap-0.3.2.tar.gz (65.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tokamap-0.3.2-py3-none-any.whl (10.1 kB view details)

Uploaded Python 3

File details

Details for the file tokamap-0.3.2.tar.gz.

File metadata

  • Download URL: tokamap-0.3.2.tar.gz
  • Upload date:
  • Size: 65.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for tokamap-0.3.2.tar.gz
Algorithm Hash digest
SHA256 aa4956c40a391b71711d27ae0588867802fafde94c9cfd0360299f36d2401bff
MD5 7715ee279126a69649021b767e373aab
BLAKE2b-256 8a82fc10d4562368df94e4bf308d510ffb9cd5484c87a59be7dfe0c8d3eeaa5a

See more details on using hashes here.

Provenance

The following attestation bundles were made for tokamap-0.3.2.tar.gz:

Publisher: publish-to-pypi.yml on ukaea/tokamap

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file tokamap-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: tokamap-0.3.2-py3-none-any.whl
  • Upload date:
  • Size: 10.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for tokamap-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 cc3edbaf42cc452fbbc7412a198a09d2c8195ec241ff26d28c86e527427b49f1
MD5 77b1f701b70deddd065cb3b6a9797afa
BLAKE2b-256 46b2e45ce6bd76f0dcffce110394a39bb122bf311ecfadc049e350c671fbd77c

See more details on using hashes here.

Provenance

The following attestation bundles were made for tokamap-0.3.2-py3-none-any.whl:

Publisher: publish-to-pypi.yml on ukaea/tokamap

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page