Merge pull request #535 from alan-turing-institute/tutorial-setup

Post-workshop improved tutorial setup instructions

Author: radka-j

docs/getting-started/installation.md

@@ -1,21 +1,14 @@
 # Installation instructions
 
-`AutoEmulate` is a Python package that can be installed in a number of ways. In this section we will describe the main ways to install the package.
+`AutoEmulate` is a Python package that can be installed in a number of ways.
+In this section we will describe the main ways to install the package.
+For new users, we recommend installing the package from PyPI.
+For users who want to contribute to the package, we recommend using Poetry to install the package from the source code.
 
 ## Prerequisites
 
 **Python Version:** `AutoEmulate` requires Python `>=3.10` and `<3.13`.
 
-## Install from GitHub
-
-This is the easiest way to install `AutoEmulate`.
-
-Currently, because we are in active development, it's recommended to install the development version from GitHub:
-
-```bash
-pip install git+https://github.com/alan-turing-institute/autoemulate.git
-```
-
 ## Install from PyPI
 
 To get the latest release from PyPI:
@@ -59,5 +52,70 @@ poetry env activate
 Then activate the virtual environment using the command displayed by the previous command. This will be something like:
 
 ```bash
-    source /Users/yourName/Library/Caches/pypoetry/virtualenvs/autoemulate-l4vGdsmY-py3.11/bin/activate
-```
+source /Users/yourName/Library/Caches/pypoetry/virtualenvs/autoemulate-l4vGdsmY-py3.11/bin/activate
+```
+
+## Interactive tutorials
+
+You can run the Quickstart demo and other interactive tutorials fron the documentation locally.
+The examples are all Jupyter notebooks and can be run in your favoured method, such as JupyterLab, Jupyter Notebook, or VS Code.
+
+<details>
+<summary>
+These steps will guide you in the simplest way to set up a virtual environment, install the package from PyPI and run the notebooks with JupyterLab.
+</summary>
+
+1. Clone the AutoEmulate repository:
+
+   ```bash
+   git clone https://github.com/alan-turing-institute/autoemulate
+   ```
+2. Navigate into the directory:
+
+   ```bash
+   cd autoemulate
+   ```
+3. Set up a virtual environment called `autoemulate`:
+
+   ```bash
+   python -m venv autoemulate
+   ```
+4. Activate the virtual environment:
+   - On Windows:
+
+     ```bash
+     autoemulate\Scripts\activate
+     ```
+
+   - On macOS/Linux:
+
+     ```bash
+     source autoemulate/bin/activate
+     ```
+5. Install the package from PyPI:
+
+   ```bash
+   pip install autoemulate
+   ```
+6. Install JupyterLab:
+
+   ```bash
+   pip install jupyterlab
+   ```
+7. Create a Jupyter kernel for the virtual environment:
+
+   ```bash
+   python -m ipykernel install --user --name autoemulate --display-name "Python (autoemulate)"
+   ```
+
+   This command registers the virtual environment as a Jupyter kernel named `Python (autoemulate)`, which you can select in JupyterLab.
+8. Launch JupyterLab:
+
+   ```bash
+   jupyter lab
+   ```
+9. Open the `docs/getting-started/quickstart.ipynb` notebook in JupyterLab.
+10. Set the kernel to use the `Python (autoemulate)` kernel you created earlier. You can do this by clicking on the kernel name in the top right corner of the JupyterLab interface and selecting `Python (autoemulate)` from the dropdown menu.
+11. Find other interactive tutorials in the `docs/tutorials` directory, which you can open and run in JupyterLab.
+
+</details>

docs/tutorials/index.md

@@ -1,3 +1,5 @@
 # Tutorials
 
 These are more in-depth workflows which cover all aspects of `AutoEmulate`, from comprehensive overviews of the features to strategies for minimising computation time with larger datasets or when using hyperparameter optimisation.
+
+These tutorials are all Jupyter notebooks which can be [run in a local interactive session](../getting-started/installation.md#interactive-tutorials).