https://github.com/CRC183-summer-school/school_2021

This is the repository for the CRC 183 summer school "Machine Learning in Condensed Matter Physics".
https://github.com/CRC183-summer-school/school_2021

Last synced: 27 days ago
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This is the repository for the CRC 183 summer school "Machine Learning in Condensed Matter Physics".

• Host: GitHub
• URL: https://github.com/CRC183-summer-school/school_2021
• Owner: CRC183-summer-school
• License: mit
• Created: 2021-06-18T07:45:31.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2021-07-18T09:47:40.000Z (almost 3 years ago)
• Last Synced: 2024-04-17T21:18:47.497Z (2 months ago)
• Language: Jupyter Notebook
• Size: 4.1 MB
• Stars: 28
• Watchers: 4
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# CRC 183 summer school "Machine Learning in Condensed Matter Physics"

This is the repository for the CRC 183 summer school ["Machine Learning in Condensed Matter Physics"](https://www.crc183.uni-koeln.de/summer-school-machine-learning/).

## Running the notebooks on remote servers

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/CRC183-summer-school/school_2021/)

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/markusschmitt/crc183_summer_school_2021/HEAD)

The badges above take you to servers of google colab or mybinder.org, where you can run the tutorial notebooks remotely.

## Installing required packages

In the hands-on sessions we will use [JAX](https://github.com/google/jax) and the [Netket](https://www.netket.org/) library. Installing NetKet is relatively straightforward and it will automatically install JAX as a dependency. 

For this Tutorial, **if you are running it locally on your machine**, we recommend that you create a clean virtual environment and install NetKet within: 

```bash

python3 -m venv netket

source netket/bin/activate

pip install --pre netket

```

If you are wondering why we use the flag ```--pre``` it is because today we will be working on a pre (beta) release of version 3.0. 

**If you are on Google Colab**, run the following command in the first cell in order to install the required packages:

```bash

!pip install --pre -U netket

```

For the second session you will also have to clone this repository to the Colab directory:

```bash

!git clone https://github.com/CRC183-summer-school/school_2021.git

```

### Set up Python environment using `conda` for Jupyter notebooks

If you have [anaconda](https://www.anaconda.com/products/individual) installed, you can set up an environment with all required packages as follows:

1. Install Jupyter notebook and the `nb_conda_kernels` package in the base environment

```

    conda install -c conda-forge notebook

    conda install -c conda-forge nb_conda_kernels

```

2. Create a new environment

```

    conda create --name  python=3.8 pip ipykernel ipywidgets matplotlib

```

3. Activate the new environment

```

    conda activate 

```

4. Install Netket (and thereby the dependencies JAX and Flax)

```

    pip install --pre netket

```

5. Leave the new environment

```

    conda deactivate

```

Now you can open Jupyter notebook from the command line (with your `base` environment active) by entering

```

    jupyter notebook

```

In the notebook you should be able to choose a kernel named `Python [conda env:]`. When running this kernel, the libraries you just installed should be known.

Source: How to set up jupyter notebook to work with anaconda environments: https://towardsdatascience.com/how-to-set-up-anaconda-and-jupyter-notebook-the-right-way-de3b7623ea4a