Visualization of the Results Guide¶

Methods of Visualization¶

After running the study, there are two primary ways to visualize the results:

Saving Figures Automatically Use the -s option when executing the tool (see Options of Execution). This saves all plots automatically; however, customization options (e.g., axis limits or number of genes) are not available.
Using Python Notebooks Two dedicated notebooks allow interactive exploration of results from the genetic algorithm and MCMC analyses. These notebooks include plotting functions with editable parameters to fine-tune the visualizations. A detailed guide for using and customizing these notebooks follows.

Installation and Running of the Notebooks¶

The notebooks can be launched from a terminal or used within an integrated development environment (IDE) such as Visual Studio Code. Instructions for different platforms are provided below.

Running Notebooks from the Terminal¶

To run the Jupyter Notebooks from a terminal on Linux, Windows, or macOS, follow these steps:

Ensure Jupyter is installed If Jupyter is not installed, install it with:
```
pip install notebook
```
Navigate to the notebook directory
```
cd path/to/notebooks
```
Launch Jupyter Notebook
```
jupyter notebook
```
A web browser will open displaying the Jupyter Notebook interface. From here, select and open the desired notebook.

Using Notebooks in Visual Studio Code¶

Visual Studio Code has built-in support for Jupyter Notebooks through extensions. To use the notebooks within VS Code, follow these steps:

Install VS Code (if not already installed) Download and install from https://code.visualstudio.com/.
Install the Python extension - Open VS Code and access the Extensions Marketplace (Ctrl+Shift+X or Cmd+Shift+X on macOS). - Search for “Python” and install the official Microsoft extension.
Ensure Jupyter is installed If not installed, run:
```
pip install jupyter
```
Open the notebook in VS Code - Navigate to the folder containing the notebook (.ipynb file). - Open the notebook in VS Code. - Use the “Run Cell” button to execute code interactively.

How to Use Jupyter Notebooks¶

Jupyter Notebooks provide an interactive Python environment. Basic operations include:

Executing a Cell¶

Select a code cell and press Ctrl + Enter to run it.

Modifying Variables and Re-executing Cells¶

Change the value of a variable in a previously run cell, then rerun the cell with Ctrl + Enter.

Adding a New Cell¶

Click the + button in the toolbar to insert a new cell.

Restarting the Kernel¶

To restart execution, click “Kernel” > “Restart Kernel” and rerun necessary cells.

By following these instructions, users on Linux, Windows, or macOS can efficiently utilize Jupyter Notebooks for visualization using this Python tool.