| Name | multidimio JSON |
| Version |
1.0.9
JSON |
| download |
| home_page | None |
| Summary | Cloud-native, scalable, and user-friendly multi dimensional energy data! |
| upload_time | 2025-10-24 20:07:12 |
| maintainer | None |
| docs_url | None |
| author | Altay Sansal |
| requires_python | <3.14,>=3.11 |
| license | None |
| keywords |
mdio
multidimio
seismic
wind
data
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<div>
<img
class="logo"
src="https://raw.githubusercontent.com/TGSAI/mdio.github.io/gh-pages/assets/images/mdio.png"
alt="MDIO"
width=200
height=auto
style="margin-top:10px;margin-bottom:10px"
/>
</div>
[][install_pip]
[][install_conda]
[][python version]
[][status]
[][apache 2.0 license]
[][tests]
[][codecov]
[][read the docs]
[][pre-commit]
[][ruff]
[][pypi_]
[][conda-forge_]
[pypi_]: https://pypi.org/project/multidimio/
[conda-forge_]: https://anaconda.org/conda-forge/multidimio
[status]: https://pypi.org/project/multidimio/
[python version]: https://pypi.org/project/multidimio
[read the docs]: https://mdio-python.readthedocs.io/
[tests]: https://github.com/TGSAI/mdio-python/actions?workflow=Tests
[codecov]: https://app.codecov.io/gh/TGSAI/mdio-python
[pre-commit]: https://github.com/pre-commit/pre-commit
[ruff]: https://github.com/astral-sh/ruff
[install_pip]: https://mdio-python.readthedocs.io/en/latest/installation.html#using-pip-and-virtualenv
[install_conda]: https://mdio-python.readthedocs.io/en/latest/installation.html#using-conda
> 🎉 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][read the docs] 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][zarr] and [fsspec][fsspec].
- Standardized models for lossy and lossless data compression using [Blosc][blosc] and [ZFP][zfp].
- Distributed reads and writes using [Dask][dask].
- Powerful command-line-interface (CLI) based on [Click][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][xarray] data model and interface wrapper.
- Import seismic interpretation, horizon, data. **FUTURE**
# Installing MDIO
Simplest way to install _MDIO_ via [pip] from [PyPI]:
```shell
$ pip install multidimio
```
or install _MDIO_ via [conda] from [conda-forge]:
```shell
$ 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](https://www.tgs.com/). The current maintainer is [Altay Sansal](https://github.com/tasansal) with the support of
many more great colleagues.
[pypi]: https://pypi.org/
[conda-forge]: https://conda-forge.org/
[file an issue]: https://github.com/TGSAI/mdio-python/issues
[pip]: https://pip.pypa.io/
[conda]: https://docs.conda.io/
[dask]: https://www.dask.org/
[zarr]: https://zarr.dev/
[fsspec]: https://filesystem-spec.readthedocs.io/en/latest/
[s3fs]: https://s3fs.readthedocs.io/
[gcsfs]: https://gcsfs.readthedocs.io/
[adlfs]: https://github.com/fsspec/adlfs
[blosc]: https://www.blosc.org/
[zfp]: https://computing.llnl.gov/projects/zfp
[xarray]: https://xarray.dev/
[click]: https://palletsprojects.com/p/click/
<!-- github-only -->
[apache 2.0 license]: https://github.com/TGSAI/mdio-python/blob/main/LICENSE
[contributor guide]: https://github.com/TGSAI/mdio-python/blob/main/CONTRIBUTING.md
[command-line usage]: https://mdio-python.readthedocs.io/en/latest/usage.html
[api reference]: https://mdio-python.readthedocs.io/en/latest/reference.html
[installation instructions]: https://mdio-python.readthedocs.io/en/latest/installation.html
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Please\n> check back later for more updates!\n\n**_\"MDIO\"_** is a library to work with large multidimensional energy datasets.\nThe primary motivation behind **MDIO** is to represent multidimensional\ntime series data in a format that makes it easier to use in resource assessment,\nmachine learning, and data processing workflows.\n\nSee the [documentation][read the docs] for more information.\n\nThis is not an official TGS product.\n\n# Features\n\n**Shared Features**\n\n- Abstractions for common energy data types (see below).\n- Cloud native chunked storage based on [Zarr][zarr] and [fsspec][fsspec].\n- Standardized models for lossy and lossless data compression using [Blosc][blosc] and [ZFP][zfp].\n- Distributed reads and writes using [Dask][dask].\n- Powerful command-line-interface (CLI) based on [Click][click]\n\n**Domain Specific Features**\n\n- Oil & Gas Data\n - Import and export 2D - 5D seismic data types stored in SEG-Y.\n - Optimized chunking logic for various seismic types using MDIO templates.\n - Native [Xarray][xarray] data model and interface wrapper.\n - Import seismic interpretation, horizon, data. **FUTURE**\n\n# Installing MDIO\n\nSimplest way to install _MDIO_ via [pip] from [PyPI]:\n\n```shell\n$ pip install multidimio\n```\n\nor install _MDIO_ via [conda] from [conda-forge]:\n\n```shell\n$ conda install -c conda-forge multidimio\n```\n\n> Extras must be installed separately on `Conda` environments.\n\nFor details, please see the [installation instructions]\nin the documentation.\n\n# Using MDIO\n\nPlease see the [Command-line Usage] for details.\n\nFor Python API please see the [API Reference] for details.\n\n# Requirements\n\n## Minimal\n\nChunked storage and parallelization: `zarr`, `dask`, `numba`, and `psutil`.\\\nSEG-Y Parsing: `TGSAI/segy`\\\nCLI and Progress Bars: `click`, `click-params`, and `tqdm`.\n\n## Optional\n\nDistributed computing `[distributed]`: `distributed` and `bokeh`.\\\nCloud Object Store I/O `[cloud]`: `s3fs`, `gcsfs`, and `adlfs`.\\\nLossy Compression `[lossy]`: `zfpy`\n\n# Contributing to MDIO\n\nContributions are very welcome.\nTo learn more, see the [Contributor Guide].\n\n# Licensing\n\nDistributed under the terms of the [Apache 2.0 license],\n_MDIO_ is free and open source software.\n\n# Issues\n\nIf you encounter any problems,\nplease [file an issue] along with a detailed description.\n\n# Credits\n\nThis project was established at [TGS](https://www.tgs.com/). 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