Metadata-Version: 2.1
Name: multidimio
Version: 0.2.8
Summary: Cloud-native, scalable, and user-friendly multi dimensional energy data!
Home-page: https://mdio.dev
License: Apache-2.0
Keywords: mdio,multidimio,seismic,wind,data
Author: TGS
Author-email: sys-opensource@tgs.com
Maintainer: Altay Sansal
Maintainer-email: altay.sansal@tgs.com
Requires-Python: >=3.8,<3.11
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Provides-Extra: cloud
Provides-Extra: distributed
Provides-Extra: lossy
Requires-Dist: adlfs (>=2022.7.0,<2023.0.0) ; extra == "cloud"
Requires-Dist: bokeh (>=2.4.3,<3.0.0) ; extra == "distributed"
Requires-Dist: click (>=8.1.3,<9.0.0)
Requires-Dist: click-params (>=0.3.0,<0.4.0)
Requires-Dist: dask (>=2022.11.0)
Requires-Dist: distributed (>=2022.11.0) ; extra == "distributed"
Requires-Dist: gcsfs (>=2022.7.0,<2023.0.0) ; extra == "cloud"
Requires-Dist: numba (>=0.55.2,<1.0.0)
Requires-Dist: psutil (>=5.9.1,<6.0.0)
Requires-Dist: s3fs (>=2022.7.0,<2023.0.0) ; extra == "cloud"
Requires-Dist: segyio (>=1.9.3,<2.0.0)
Requires-Dist: tqdm (>=4.64.0,<5.0.0)
Requires-Dist: zarr (>=2.12.0,<3.0.0)
Requires-Dist: zfpy (>=1.0.0,<2.0.0) ; extra == "lossy"
Project-URL: Changelog, https://github.com/TGSAI/mdio-python/releases
Project-URL: Documentation, https://mdio-python.readthedocs.io
Project-URL: Repository, https://github.com/TGSAI/mdio-python
Description-Content-Type: text/markdown

<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>

[![PyPI](https://img.shields.io/pypi/v/multidimio.svg)][install_pip]
[![Conda](https://img.shields.io/conda/vn/conda-forge/multidimio)][install_conda]
[![Python Version](https://img.shields.io/pypi/pyversions/multidimio)][python version]
[![Status](https://img.shields.io/pypi/status/multidimio.svg)][status]
[![License](https://img.shields.io/pypi/l/multidimio)][license]

[![Tests](https://github.com/TGSAI/mdio-python/workflows/Tests/badge.svg)][tests]
[![Codecov](https://codecov.io/gh/TGSAI/mdio-python/branch/main/graph/badge.svg)][codecov]
[![Read the documentation at https://mdio-python.readthedocs.io/](https://img.shields.io/readthedocs/mdio-python/latest.svg?label=Read%20the%20Docs)][read the docs]

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)][pre-commit]
[![Black](https://img.shields.io/badge/code%20style-black-000000.svg)][black]

[![PyPI Downloads](https://static.pepy.tech/personalized-badge/multidimio?period=total&units=international_system&left_color=grey&right_color=blue&left_text=PyPI%20downloads)][pypi_]
[![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/multidimio?label=Conda%20downloads&style=flat)][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
[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.

# 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][install]
in the documentation.

# Using MDIO

Please see the [Command-line Reference][usage] for details.

For Python API please see the [API Reference][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][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/). Original authors
and current maintainers are [Altay Sansal](https://github.com/tasansal) and
[Sri Kainkaryam](https://github.com/srib); 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 -->

[license]: https://github.com/TGSAI/mdio-python/blob/main/LICENSE
[contributor guide]: https://github.com/TGSAI/mdio-python/blob/main/CONTRIBUTING.md
[usage]: https://mdio-python.readthedocs.io/en/latest/usage.html
[reference]: https://mdio-python.readthedocs.io/en/latest/reference.html
[install]: https://mdio-python.readthedocs.io/en/latest/installation.html

