Skip to main content

PyPI Conda Python Version Status License

Tests Codecov Read the documentation at https://mdio-python.readthedocs.io/

pre-commit Ruff

PyPI Downloads Conda Downloads

🎉 MDIO v1 is out. Ingestion and export for SEG-Y is fully functional with templates! However, there may still be minor issues. Please report any issues you encounter.

🚧👷🏻 We are actively working on updating the documentation and adding missing features to v1 release. Please check back later for more updates!

"MDIO" is a library to work with large multidimensional energy datasets. The primary motivation behind MDIO is to represent multidimensional time series data in a format that makes it easier to use in resource assessment, machine learning, and data processing workflows.

See the documentation for more information.

This is not an official TGS product.

Features

Shared Features

  • Abstractions for common energy data types (see below).
  • Cloud native chunked storage based on Zarr and fsspec.
  • Standardized models for lossy and lossless data compression using Blosc and ZFP.
  • Distributed reads and writes using Dask.
  • Powerful command-line-interface (CLI) based on Click

Domain Specific Features

  • Oil & Gas Data
    • Import and export 2D - 5D seismic data types stored in SEG-Y.
    • Optimized chunking logic for various seismic types using MDIO templates.
    • Native Xarray data model and interface wrapper.
    • Import seismic interpretation, horizon, data. FUTURE

Installing MDIO

Simplest way to install MDIO via pip from PyPI:

$ pip install multidimio

or install MDIO via conda from conda-forge:

$ conda install -c conda-forge multidimio

Extras must be installed separately on Conda environments.

For details, please see the installation instructions in the documentation.

Using MDIO

Please see the Command-line Usage for details.

For Python API please see the API Reference for details.

Requirements

Minimal

Chunked storage and parallelization: zarr, dask, numba, and psutil.
SEG-Y Parsing: TGSAI/segy
CLI and Progress Bars: click, click-params, and tqdm.

Optional

Distributed computing [distributed]: distributed and bokeh.
Cloud Object Store I/O [cloud]: s3fs, gcsfs, and adlfs.
Lossy Compression [lossy]: zfpy

Contributing to MDIO

Contributions are very welcome. To learn more, see the Contributor Guide.

Licensing

Distributed under the terms of the Apache 2.0 license, MDIO is free and open source software.

Issues

If you encounter any problems, please file an issue along with a detailed description.

Credits

This project was established at TGS. The current maintainer is Brian Michell with the support of many more great colleagues.

Download files

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

Source Distribution

multidimio-1.2.1.tar.gz (94.9 kB view details)

Uploaded Source

Built Distribution

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

multidimio-1.2.1-py3-none-any.whl (136.5 kB view details)

Uploaded Python 3

File details

Details for the file multidimio-1.2.1.tar.gz.

File metadata

  • Download URL: multidimio-1.2.1.tar.gz
  • Upload date:
  • Size: 94.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for multidimio-1.2.1.tar.gz
Algorithm Hash digest
SHA256 06441b8c1ea4a26ab53bb07b43c94a69a84e767f63872c60e7274522356a62c9
MD5 b2dac7c6ff1e4aa1eda044ef931049c3
BLAKE2b-256 c65fabf0508d6e8b79e70cb38f014b623456d8bf1842f845ee596fcd70bb1bbf

See more details on using hashes here.

File details

Details for the file multidimio-1.2.1-py3-none-any.whl.

File metadata

  • Download URL: multidimio-1.2.1-py3-none-any.whl
  • Upload date:
  • Size: 136.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for multidimio-1.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 ef79f8e5732cd42d290d4097c1dd90d69bf86a7bbd9b46d9b7c80cdd23cae78a
MD5 c92b8611984b0f6ee4d385672fe5d715
BLAKE2b-256 713ea4613e2efa8ed3309d4014f5f9d5dd3e0c0a3e6b9d7f77599ce0485f70cd

See more details on using hashes here.

Supported by

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