Simplify Python guide

HPC_Python_Guide.md

@@ -23,78 +23,27 @@ sxm2sh
 a100sh
 ```
 
-## II. First time virtualenv setup
+## II. Setup Virtualenv
+1. Get to a CPU or GPU node on the cluster (see [Section I](#i-preliminaries)).
 
-1. Navigate to your project folder.
+2. Navigate to your project folder.
 
-2. Load modules for Python by entering:
-   ```
-   module load python3/3.9.14
-   module load numpy/1.23.3-python-3.9.14-openblas-0.3.21
-   module load scipy/1.9.1-python-3.9.14
-   module load matplotlib/3.6.0-numpy-1.23.3-python-3.9.14
-   module load cuda/11.6
-   ```
-   We load `numpy`, `scipy`, and `matplotlib` as modules, because the HPC team have made optimized versions for the HPC cluster.
-   
-   > __NOTE:__ This guide uses Python 3.9 and CUDA 11.6 but other versions are available.
-
-3. Create a virtualenv by running:
-   ```
-   virtualenv <VENV_NAME>
-   ```
-
-4. Activate the virtualenv by running:
-    ```
-    source <VENV_NAME>/bin/activate
-    ```
-
-You should now be able to install packages with pip install <PACKAGE> as normal.
-
-> __Troubleshooting:__ If pip doesn't work, you may need to manually install it with:
+3. Download `scripts/init.sh` and place it in your project folder. This **only** needs to be done the first time.
+   > **Tip:** You can do this by calling
+   > ```bash
+   > wget https://lab.compute.dtu.dk/patmjen/hcp_tutorials/-/raw/main/scripts/init.sh
    > ```
-> easy_install pip
-> ```
-
-## III. Virtualenv activation
-
-> __NOTE:__ These steps must be done every time. Also if you change from a login node to a GPU node (e.g. by calling `sxm2sh`)
+   > in the terminal.
 
-1. Navigate to your project folder.
-
-2. Load modules for Python by entering:
+4. Call 
    ```
-   module load python3/3.9.14
-   module load numpy/1.23.3-python-3.9.14-openblas-0.3.21
-   module load scipy/1.9.1-python-3.9.14
-   module load matplotlib/3.6.0-numpy-1.23.3-python-3.9.14
-   module load cuda/11.6
+   source init.sh
    ```
-   We load  `numpy` and `scipy` as modules, since the HPC team have made optimized versions for the HPC cluster.
+   This will setup and activate your virtualenv. You must **do this every time** you log in or change node (e.g. by calling `sxm2sh`)!
+   > **Tip:** You can configure the Python version, CUDA version, and name and location of the virtualenv by changing the variables at the top of `init.sh`.
 
-3. Activate the virtualenv by running:
-   ```
-   source <VENV_NAME>/bin/activate
-   ```
-
-> __Pro tip:__ To make life easy, put these commands in a bash script called `init.sh`:
-> ```
-> #!/bin/bash
-> module load python3/3.9.14
-> module load numpy/1.23.3-python-3.9.14-openblas-0.3.21
-> module load scipy/1.9.1-python-3.9.14
-> module load matplotlib/3.6.0-numpy-1.23.3-python-3.9.14
-> module load cuda/11.6
->
-> source <VENV_NAME>/bin/activate
-> ```
-> 
-> which you can then run by entering:
-> ```
-> source init.sh
-> ```
-> 
-> and this will prepare everything
+5. Your are done! You can now install packages with `pip install <PACKAGE>` and run python3 code with `python`.
+   > __Troubleshooting:__ If pip doesn't work, you may need to manually install it with: `easy_install pip`
 
 ## IV. Jupyter notebooks on ThinLinc
 
@@ -108,7 +57,7 @@ You should now be able to install packages with pip install <PACKAGE> as normal.
    a100sh -X
    ```
 
-3. Navigate to your project folder, load modules, and activate the virtualenv. Same steps as in section III.
+3. Navigate to your project folder and activate the virtualenv. Same steps as in [section II](#ii-setup-virtualenv).
 
 4. Install Jupyter with:
    ```
@@ -135,7 +84,7 @@ You should now be able to install packages with pip install <PACKAGE> as normal.
 
 1. Open a terminal on the cluster, either through ThinLinc or ssh.
 
-2. Call `sxm2sh` or `linuxsh`, as described in section I, so you are not on a login node.
+2. Call `sxm2sh` or `linuxsh`, as described in [section I](#i-preliminaries), so you are not on a login node.
 
 3. Start a tmux session by running:
    ```
@@ -153,7 +102,7 @@ You should now be able to install packages with pip install <PACKAGE> as normal.
    echo $HOSTNAME
    ```
 
-5. Navigate to your project folder, load modules, and activate the virtualenv. Same steps as in section III.
+5. Navigate to your project folder, and activate the virtualenv. Same steps as in [section II](#ii-setup-virtualenv).
 
 6. Start a Jupyter lab or Jupyter notebook server by entering one of the following:
    ```