<div>
<img
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src="https://raw.githubusercontent.com/TGSAI/mdio.github.io/gh-pages/assets/images/mdio.png"
alt="MDIO"
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[][install_pip]
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[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
[black]: https://github.com/psf/black
[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"_** 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].
- 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.
- Import seismic interpretation, horizon, data. **FUTURE**
- Optimized chunking logic for various seismic types. **FUTURE**
- Wind Resource Assessment
- Numerical weather prediction models with arbitrary metadata. **FUTURE**
- Optimized chunking logic for time-series analysis and mapping. **FUTURE**
- [Xarray][xarray] interface. **FUTURE**
The features marked as **FUTURE** will be open-sourced at a later date.
# 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: `segyio`\
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/). Current maintainer is
[Altay Sansal](https://github.com/tasansal) with the support of
many more great colleagues.
This project template is based on [@cjolowicz]'s [Hypermodern Python Cookiecutter]
template.
[@cjolowicz]: https://github.com/cjolowicz
[pypi]: https://pypi.org/
[conda-forge]: https://conda-forge.org/
[hypermodern python cookiecutter]: https://github.com/cjolowicz/cookiecutter-hypermodern-python
[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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