https://github.com/data-exp-lab/analysis_schema

Experimental declarative analysis schema for yt
https://github.com/data-exp-lab/analysis_schema

Last synced: about 1 year ago
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Experimental declarative analysis schema for yt

• Host: GitHub
• URL: https://github.com/data-exp-lab/analysis_schema
• Owner: data-exp-lab
• License: mit
• Created: 2019-04-20T19:29:59.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2024-11-19T21:57:00.000Z (over 1 year ago)
• Last Synced: 2024-11-19T22:44:16.173Z (over 1 year ago)
• Language: Python
• Homepage:
• Size: 780 KB
• Stars: 2
• Watchers: 4
• Forks: 2
• Open Issues: 9
• Metadata Files:
  • Readme: README.md
  • Changelog: HISTORY.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE

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README

          
# Analysis Schema

A declarative schema and workflow framework for analysis and visualization of physical systems.

The Analysis Schema creates a workflow system that processes a configuration file where users specify _what_ they would like the code to do, instead of _how_ to do it to complete analysis and visualization tasks. It supports high level analysis description that can be saved, shared, and reused in JSON document.

It consists of three pieces:

1. A structured schema that guides the workflow. See [`yt_analysis_schema.json`](yt_analysis_schema.json).

2. An engine that connects input from the configuration file to the underlying code.

3. The configuration file.

## Installation

TODO

## Example

Use a JSON file to describe a basic plot. The file has to reference the structured schema file, which is also called the analysis schema. The schema validates the workflow and ensures the correct data types are used.

Let's call this `example.json` and fill it out:

```JSON

{

    "$schema": "yt_analysis_schema.json",

    "Plot": [

        {

            "ProjectionPlot": {

                "Dataset": [

                    {

                        "Filename": "IsolatedGalaxy/galaxy0030/galaxy0030",

                        "DatasetName": "IG"

                    }

                ],

                "Axis": "y",

                "FieldNames": {

                    "field": "density",

                    "field_type": "gas"

                }

            }

        }

    ]

}

```

Once a configuration file is complete, the file can be submitted to the `analysis_schema` command line interface,

```

analysis_schema run-analysis example.json

```

After running that command, image files will be saved and their filenames will display at the command line.

Documentation is coming soon to: https://analysis-schema.readthedocs.io.

More examples can be seen with this virtual poster [describing Analysis Schema use cases](https://samwalkow.github.io/2021-scipy-poster-ScientificWorkflowDescription/) and in the examples folder above.

## Dependencies

Currently, the Analysis Schema is built from [yt](https://github.com/yt-project/yt), a python library for analyzing and visauliation volumetric data. It also uses [pydantic](https://github.com/pydantic/pydantic) to create the schema and validate workflow input.

[![yt-project](https://img.shields.io/static/v1?label="works%20with"&message="yt"&color="blueviolet")](https://yt-project.org)

The Analysis Schema requires Python 3.7+ and yt 4.0 in addition to other packages.

## License

* Free software: MIT license