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README.md

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# Numerical Methods of Accelerator Physics
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# Material for this tutorial
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- The theoretical lecture can be found here
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- The tutorial in slide form is here
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MSc lecture at TU Darmstadt, etit, TEMF by Adrian Oeftiger in 2022/23.
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# Installation instructions
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Fourteenth part of a jupyter notebook lecture series, guest lecture held by Dr. Andrea Santamaria Garcia on 10.02.2023.
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## Get the repository with Git
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You will need to have Git previously installed in your computer.
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To check if you have it installed, open your terminal and type:
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Find the rendered HTML slides [here](https://aoeftiger.github.io/TUDa-NMAP-14/).
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---
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## Run online
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Run this notebook talk online, interactively on mybinder.org:
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/aoeftiger/TUDa-NMAP-14/v1.0)
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The `lecture.ipynb` notebook will work out-of-the-box.
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---
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## Run on TU Darmstadt jupyterhub
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If you have a TU ID, access the [local TU Darmstadt jupyterhub](https://tu-jupyter-i.ca.hrz.tu-darmstadt.de/) using your TU ID.
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``` bash
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git --version
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```
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A possible way to upload and run this lecture repository is the following:
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### Git installation in mac
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1. Open a terminal by clicking on the top right "New" -> "Terminal".
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``` bash
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brew update
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brew install git
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```
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2. A new tab opens with a terminal, click into the black area and enter (copy&pasting):
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### Git installation in linux
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#### Ubuntu/Debian
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``` bash
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wget https://github.com/aoeftiger/TUDa-NMAP-14/archive/refs/heads/main.zip
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unzip main.zip
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cd TUDa-NMAP-14-main
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sudo apt install git
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```
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3. You have downloaded, unzipped and entered the lecture repository. As a last step, install the dependencies:
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#### CentOS
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``` bash
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export TMPDIR="`pwd`"
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pip install -r requirements_noversions.txt --prefix="`pwd`"/requirements
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```
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Close the terminal tab and open the `lecture.ipynb` notebook inside the repository directory on the jupyterhub main page.
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sudo yum install git
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```
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---
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Once you have Git installed open your terminal, go to your desired directory, and type:
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``` bash
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git clone https://github.com/machine-learning-tutorial/bayesian-optimization.git
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cd bayesian-optimization
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```
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## Run locally
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## Get the repository with direct download
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Open your terminal, go to your desired directory, and type:
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``` bash
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wget https://github.com/machine-learning-tutorial/bayesian-optimization/archive/refs/heads/main.zip
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unzip main.zip
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cd bayesian-optimization
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```
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The notebook can of course also be run on your local computer using your own jupyter notebook server. Install such an environment e.g. via the extensive [Anaconda distribution](https://www.anaconda.com/products/distribution), the minimalistic [Miniconda distribution](https://docs.conda.io/en/main/miniconda.html) or the extremely fast [Mamba package manager](https://mamba.readthedocs.io/en/latest/). (The order indicates preference by simplicity in installation and usage.)
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## Install required libraries in a virtual environment
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You may find all required packages in the `requirements.txt` file.

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