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Merge pull request #5 from TGSAI/feature/docs
Documentation Improvements
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.flake8

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tests/*:S101
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src/mdio/segy/_standards_rev0.py:B950
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src/mdio/segy/ebcdic.py:B950
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src/mdio/commands/segy.py:D301

.pre-commit-config.yaml

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name: Check for added large files
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entry: check-added-large-files
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language: system
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args: ["--maxkb=1000"]
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- id: check-toml
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name: Check Toml
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entry: check-toml

README.md

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[pre-commit]: https://github.com/pre-commit/pre-commit
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[black]: https://github.com/psf/black
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**_"MDIO"_** is a library to work with large multi-dimensional energy datasets.
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The primary motivation behind **MDIO** is to represent multi-dimensional
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time series data in a format that makes it easier to use in resource assesment,
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**_"MDIO"_** is a library to work with large multidimensional energy datasets.
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The primary motivation behind **MDIO** is to represent multidimensional
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time series data in a format that makes it easier to use in resource assessment,
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machine learning, and data processing workflows.
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## Features
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# Features
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**Shared Features**
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- Oil & Gas Data
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- Import and export 2D - 5D seismic data types stored in SEG-Y.
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- Import seismic interpretation, horizon, data (experimental).
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- Optimized chunking logic for various seismic types.
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- Import seismic interpretation, horizon, data. **FUTURE**
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- Optimized chunking logic for various seismic types. **FUTURE**
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- Wind Resource Assessment
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- Numerical weather prediction models with arbitrary metadata.
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- Optimized chunking logic for time-series analysis and mapping.
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- [Xarray][xarray] interface.
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- Numerical weather prediction models with arbitrary metadata. **FUTURE**
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- Optimized chunking logic for time-series analysis and mappin. **FUTURE**
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- [Xarray][xarray] interface. **FUTURE**
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## Requirements
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The features marked as **FUTURE** will be open-sourced at a later date.
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- TODO
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## Installation
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# Installation
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You can install _MDIO_ via [pip] from [PyPI]:
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`distributed` installs [Dask][dask] for parallel, distributed processing.\
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`cloud` installs [fsspec][fsspec] backed I/O libraries for [AWS' S3][s3fs],
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[Google's GCS][gcsfs], and [Azure ABS][adlfs].\
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`lossy` will install the ZFPY library for lossy chunk compression.
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`lossy` will install the [ZFPY][zfp] library for lossy chunk compression.
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## Usage
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# Usage
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Please see the [Command-line Reference] for details.
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## Contributing
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For Python API please see the [API Reference] for details.
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# Requirements
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### Minimal
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Chunked storage and parallelization: `zarr`, `dask`, `numba`, and `psutil`.\
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SEG-Y Parsing: `segyio`\
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CLI and Progress Bars: `click`, `click-params`, and `tqdm`.
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### Optional
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Distributed computing `[distributed]`: `distributed` and `bokeh`.\
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Cloud Object Store I/O `[cloud]`: `s3fs`, `gcsfs`, and `adlfs`.\
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Lossy Compression `[lossy]`: `zfpy`
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# Contributing
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Contributions are very welcome.
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To learn more, see the [Contributor Guide].
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## License
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# License
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Distributed under the terms of the [Apache 2.0 license][license],
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_MDIO_ is free and open source software.
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## Issues
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# Issues
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If you encounter any problems,
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please [file an issue] along with a detailed description.
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## Credits
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# Credits
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This project was established at [TGS](https://www.tgs.com/). Original authors
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and current maintainers are [Altay Sansal](https://github.com/tasansal) and
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[Sri Kainkaryam](https://github.com/srib); with the support of many more great
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colleagues.
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This project was generated from [@cjolowicz]'s [Hypermodern Python Cookiecutter] template.
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This project template is based on [@cjolowicz]'s [Hypermodern Python Cookiecutter]
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template.
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[@cjolowicz]: https://github.com/cjolowicz
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[pypi]: https://pypi.org/
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[license]: https://github.com/TGSAI/mdio-python/blob/main/LICENSE
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[contributor guide]: https://github.com/TGSAI/mdio-python/blob/main/CONTRIBUTING.md
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[command-line reference]: https://mdio-python.readthedocs.io/en/latest/usage.html
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[api reference]: https://mdio-python.readthedocs.io/en/latest/reference.html

docs/conf.py

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"sphinx.ext.autodoc",
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"sphinx.ext.napoleon",
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"sphinx_click",
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"myst_parser",
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"sphinx_copybutton",
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"myst_nb",
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]
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autodoc_typehints = "description"
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autodoc_typehints_format = "short"
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autodoc_member_order = "groupwise"
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html_theme = "furo"
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autoclass_content = "both"
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html_theme = "furo"
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myst_heading_anchors = 2
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# sphinx-copybutton configurations
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copybutton_prompt_text = r">>> |\.\.\. |\$ |In \[\d*\]: | {2,5}\.\.\.: | {5,8}: "
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copybutton_prompt_is_regexp = True
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nb_execution_mode = "off"

docs/index.md

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hidden:
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maxdepth: 1
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---
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notebooks/quickstart
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usage
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reference
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contributing

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