restoreio Documentation

restoreio is a python package to Restore Incomplete Oceanographic datasets, with a specific focus on ocean surface velocity data. This package can also generate data ensemble and perform statistical analysis, which allows uncertainty qualification of such datasets.

GitHub

PyPI

Anaconda Cloud

Online Interface

Install

User Guide

API reference

Publications

Supported Platforms

Successful installation and tests performed on the following operating systems, architectures, and Python versions:

Platform	Arch	Python Version			Continuous Integration
		3.9	3.10	3.11
Linux	X86-64	✔	✔	✔
	AARCH-64	✔	✔	✔
macOS	X86-64	✔	✔	✔
	ARM-64	✔	✔	✔
Windows	X86-64	✔	✔	✔
	ARM-64	✔	✔	✔

Python wheels for restoreio for all supported platforms and versions in the above are available through PyPI and Anaconda Cloud. If you need restoreio on other platforms, architectures, and Python versions, raise an issue on GitHub and we build its Python Wheel for you.

Install

Install with pip from PyPI:

pip install restoreio

Install with conda from Anaconda Cloud:

conda install -c s-ameli -c conda-forge restoreio

For complete installation guide, see:

• Install
  • 1. Install from Wheels
  • 2. Install in Virtual Environment
  • 3. Troubleshooting
  • 4. Generate Documentation
  • 5. Test Package

User Guide

• User Guide
  • Getting Started
  • Input Data
  • Data Restoration Settings
  • Generating Ensemble
  • Output Data

API Reference

Check the list of functions, classes, and modules of restoreio with their usage, options, and examples.

• API Reference
  • Python Interface
  • Command Line Interface (CLI)

Examples

• Examples
  • Dataset
  • Reproducing Results

Online Web-Based Interface

Alongside restoreio python package, we also offer an online service as a web-based interface for this software. This platform is available at: https://restoreio.org.

This online gateway allows users to efficiently process both local and remote datasets. The computational tasks are executed on the server side, leveraging the parallel processing capabilities of a high-performance computing cluster. Moreover, the web-based interface seamlessly integrates an interactive globe map, empowering sophisticated visualization of the results within the online platform.

Technical Notes

How to Contribute

We welcome contributions via GitHub’s pull request. If you do not feel comfortable modifying the code, we also welcome feature requests and bug reports as GitHub issues.

Publications

For information on how to cite restoreio, publications, and software packages that used restoreio, see:

• Publications
  • How to Cite
  • Publications/Software Using restoreio

License

This project uses a BSD 3-clause license, in hopes that it will be accessible to most projects. If you require a different license, please raise an issue and we will consider a dual license.