GNU Affero General Public License v3.0

项目介绍

DusKing1/PID-Evaluator 是一个托管在 GitHub 上的开源项目,主要使用 Jupyter Notebook 编写,采用 GNU Affero General Public License v3.0 许可证,目前获得 19 个 Star、5 次 Fork。

仓库全名
DusKing1/PID-Evaluator
开源许可证
GNU Affero General Public License v3.0
Star 数
19
Fork 数
5
未关闭 Issue
10

README 摘要

PID-Evaluator This is the kernel code of the online analyzer - Blackbox Mate Online, AKA BBM. You can check the BBM website here How to run those scripts? 1. Install Jupyter Notebook 2. Download this repo and install all the dependency packages 3. Run .ipynb files 4. Then just enjoy each cell! Optional: 1. Download and install Anaconda 2. Install jupyter notebook extension in VSCode 3. Then enjoy each cell in…

完整内容见 GitHub 原始 README 或本页 。

常见问题

PID-Evaluator 用什么语言开发?

主要使用 Jupyter Notebook 编写,采用 GNU Affero General Public License v3.0 许可证,目前有 19 个 Star。

PID-Evaluator 可以免费商用吗?

仓库标注的许可证为 GNU Affero General Public License v3.0,商用前请先阅读仓库 LICENSE 文件确认授权范围。

如何获取 PID-Evaluator 的源码?

可以直接克隆仓库:git clone https://github.com/DusKing1/PID-Evaluator.git;安装与运行步骤见仓库 README。

PID-Evaluator 最近还在维护吗?

仓库最近一次更新为 2022年10月9日,当前有 10 个未关闭 Issue;Star 数为 19,可作为社区活跃度的参考。

关于

GitHub 原始描述(英文)

Kernel code of the Blackbox Mate Online

描述取自 GitHub 官方 API,保持仓库作者书写的原文。

简要分析

热度分
48
价值分
14
活跃状态
活跃

README

PID-Evaluator

This is the kernel code of the online analyzer - Blackbox Mate Online, AKA BBM.

You can check the BBM website here

How to run those scripts?

  1. Install Jupyter Notebook
  2. Download this repo and install all the dependency packages
  3. Run .ipynb files
  4. Then just enjoy each cell!

Optional:

  1. Download and install Anaconda
  2. Install jupyter notebook extension in VSCode
  3. Then enjoy each cell in VSCode!

Dependencies

  • numpy
  • matplotlib
  • pandas
  • scipy
  • os

License

A-GPLv3.0

Credit

This tool/script is strongly inspired by PID-Analyzer and PIDtoolbox, so thanks goes to all those whom have contributed to PID-analyzer and PIDtoolbox.

Origins for this repo (Thanks!):

  • Plasmatree (for PID-Analyzer),
  • Brian White (for PIDtoolbox),
  • ColinNiu (for pyPIDtoolbox)

Big thanks to current and past contributors:

  • Chiang, Hugo (DusKing) - optimizing many details to make it scientific and usable
  • ColinNiu - for the surprising framework
  • Pawn, David (pdw) - for the massive testing job

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