zachetienne/nrpytutorial 开源项目中文解读：技术栈、适用场景与上手建议

项目介绍

zachetienne/nrpytutorial 是一个托管在 GitHub 上的开源项目，主要使用 Jupyter Notebook 编写，采用 BSD 2-Clause "Simplified" License 许可证，目前获得 104 个 Star、44 次 Fork。

仓库全名: zachetienne/nrpytutorial

README 摘要

NRPy+, SENRv2, and the NRPy+ Jupyter Tutorial This repository houses The newest version of NRPy+: Python-Based Code Generation for Numerical Relativity... and Beyond, The second version of SENR, the Simple, Efficient Numerical Relativity code (see the "Colliding Black Holes" Start-to-Finish tutorial notebook), and The NRPy+ Jupyter Tutorial: An Introduction to Python-Based Code Generation for Numerical Relativity…

完整内容见 GitHub 原始 README 或本页。

常见问题

nrpytutorial 用什么语言开发？

主要使用 Jupyter Notebook 编写，采用 BSD 2-Clause "Simplified" License 许可证，目前有 104 个 Star。

nrpytutorial 可以免费商用吗？

如何获取 nrpytutorial 的源码？

可以直接克隆仓库：git clone https://github.com/zachetienne/nrpytutorial.git，默认分支为 master；安装与运行步骤见仓库 README。

nrpytutorial 最近还在维护吗？

仓库最近一次更新为 6月9日，当前有 7 个未关闭 Issue；Star 数为 104，可作为社区活跃度的参考。

关于

NRPy+, BlackHoles@Home, SENRv2, and the NRPy+ Jupyter Tutorial: Python-Based Code Generation for Numerical Relativity... and Beyond!

adm automatic bssn code codegen general generation hyperbolic jupyter-notebook nrpy numerical pdes python reference-metric relativity sympy tutorial

BSD 2-Clause "Simplified" License
104 Stars
44 Forks
14 Watching

描述取自 GitHub 官方 API，中文内容由 GitRead 中文社区编辑团队整理。

简要分析

热度分

206

价值分

活跃状态

活跃

GitHub

语言占比

Jinja

Jupyter Notebook

Makefile

Python

Shell

TeX

贡献者

NRPy+, SENRv2, and the NRPy+ Jupyter Tutorial

This repository houses

The newest version of NRPy+: Python-Based Code Generation for Numerical Relativity… and Beyond,
The second version of SENR, the Simple, Efficient Numerical Relativity code (see the “Colliding Black Holes” Start-to-Finish tutorial notebook), and
The NRPy+ Jupyter Tutorial: An Introduction to Python-Based Code Generation for Numerical Relativity… and Beyond!

To explore the NRPy+ tutorial without downloading, check out the NRPy+ tutorial mybinder.

If you would like to explore the NRPy+ tutorial on your local computer, you’ll need to install Python, Jupyter, Sympy, and Matplotlib. Once they are installed, you may find this useful

In certain circumstances, developers may wish to execute one of these Jupyter notebooks from the command line. For example, when the notebook constructs an Einstein Toolkit thorn. In such a case, the following command should be useful:

jupyter nbconvert --to notebook --inplace --execute --ExecutePreprocessor.timeout=-1 [Jupyter notebook file]

Alternatively one can simply use the script:

./run_Jupyter_notebook.sh [Jupyter notebook file]

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