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https://github.com/alexandrehiroyuki/datatome

Data analysis and filtering using time series for embedded devices (IoT). All in a single C++ library, Data Tome. Focus on the developer's experience and performance. It is the successor to the MovingAveragePlus library.
https://github.com/alexandrehiroyuki/datatome

algorithms analysis arduino arduino-library cpp data-processing data-structures filters moving-average pio platformio platformio-library standard-deviation variance

Last synced: about 15 hours ago
JSON representation

Host: GitHub
URL: https://github.com/alexandrehiroyuki/datatome
Owner: AlexandreHiroyuki
License: mit
Created: 2023-12-23T02:46:16.000Z (9 months ago)
Default Branch: main
Last Pushed: 2024-08-20T02:07:47.000Z (about 1 month ago)
Last Synced: 2024-09-21T06:33:33.577Z (4 days ago)
Topics: algorithms, analysis, arduino, arduino-library, cpp, data-processing, data-structures, filters, moving-average, pio, platformio, platformio-library, standard-deviation, variance
Language: C++
Homepage: https://alexandrehiroyuki.github.io/DataTomeDocs/
Size: 211 KB
Stars: 6
Watchers: 1
Forks: 0
Open Issues: 7
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE

Awesome Lists containing this project

README

        # Data Tome

[![Latest Release](https://img.shields.io/github/v/release/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome/releases)

[![PlatformIO Registry](https://badges.registry.platformio.org/packages/alexandrehiroyuki/library/DataTome.svg)](https://registry.platformio.org/libraries/alexandrehiroyuki/DataTome)

[![Latest Release Date](https://img.shields.io/github/release-date/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome/releases)

[![Last Commit Date](https://img.shields.io/github/last-commit/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome/commits/master)

[![GitHub Stars](https://img.shields.io/github/stars/AlexandreHiroyuki/DataTome?style=flat&color=yellow)](https://github.com/AlexandreHiroyuki/DataTome/stargazers)

[![Contributors](https://img.shields.io/github/contributors-anon/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome/graphs/contributors)

[![Top Language](https://img.shields.io/github/languages/top/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome)







## Description

Data Tome is a C++ library for data analysis and data filtering on embedded devices (IoT). Focus on the developer's experience and performance.

- Simple Moving Average (SMA). 

- Exponential Moving Average (EMA).

- Cumulative Average (CA).

- Simple Moving Median (implemented on DataTomeAnalysis).

- Variance, Standard Deviation, and more.

## Getting Started

- This library is listed in the official [Arduino Library Manager](https://www.arduino.cc/reference/en/libraries/datatome/).

- _**—Recommended Platform—**_ Use the [PlatformIO Registry](https://registry.platformio.org/libraries/alexandrehiroyuki/DataTome) to install the library!

- You can see the source code at the [GitHub Repository](https://github.com/AlexandreHiroyuki/DataTome).

- To avoid duplicating data for smaller samples of the same data, _[check the Partials feature](https://alexandrehiroyuki.github.io/DataTomeDocs/docs/category/partials)_!

## Documentation

This library calculates statistical functions using a time-series sample implemented with a circular array that improves the performance.

- Online Docs: _[Click here to see the full documentation](https://alexandrehiroyuki.github.io/DataTomeDocs/)_

- Docs GitHub Repository: _[The documentation is coded with docusaurus, and you can visit the repository](https://github.com/AlexandreHiroyuki/DataTomeDocs)_

## Contributing

[Read here how to contribute](https://github.com/AlexandreHiroyuki/DataTome/blob/master/CONTRIBUTING.md).

It describes how to report issues, code conventions, testing, and how to publish a package on the PlatformIO Registry.

## Developed by

**Alexandre Hiroyuki** – [GitHub](https://github.com/AlexandreHiroyuki) – [LinkedIn](https://www.linkedin.com/in/alexandre-hiroyuki-yamauchi/)