DANDI_Interactive_Plot_Selector

This repo contains a python script and also a jupyter notebook that creates a Interactive Plot Selector HTML page for DANDI dataset.

Setting Up a Python Virtual Environment with a Hidden .venv Directory

Pre-requisites

1. Python 3.x: Ensure Python is installed in your environment.

   • Check your Python version:

     python3 --version

   • If Python is not installed, install it:

     sudo apt update
     sudo apt install python3 python3-venv python3-pip

2. Virtual environment module: The venv module is typically included with Python 3.x. If not, install it using:

sudo apt install python3-venv

Step 1: Create a Python Virtual Environment

1. Navigate to this git-repo directory in your terminal.

2. Create a virtual environment named .venv to keep it hidden:

python3 -m venv .venv

Step 2: Activate the Virtual Environment

• Activate the virtual environment in terminal:

source .venv/bin/activate

After activation, the terminal prompt will indicate the active environment, typically by showing (venv).

Step 3: Deactivate the Virtual Environment

• To deactivate the virtual environment, run:

deactivate

Install Project Dependencies

To install the dependencies (which will be isolated in this environment) after activating the virtual environment, run:

pip install -r requirements.txt

Running Python Script or Jupyter Notebook

The main purpose of the Python Script is to create the DANDI_interactive_plot_selector.html, an interactive plot selector HTML page. The Jupyter Notebook is primarily used for testing purposes

The Python Script - dashboard.py

After activating the virtual environment, run:

python3 dashboard.py

• Upon complition you will see this message:

  HTML file generated as 'DANDI_interactive_plot_selector.html'

  DANDI_interactive_plot_selector.html is the webpage containing the interactive plots.

Note: Along with the DANDI_interactive_plot_selector.html file, dashboard.py also creates a ./plots folder, which contains all the interactive plots for the subjects as well as the Modality X Subject plot, which are used by the DANDI_interactive_plot_selector.html file.

The Jupyter Notebook - dashboard.ipynb

1. Open the dashboard.ipynb jupyter notebook either in you IDE (e.g., VS Code) or via jupyter notebook environment interface (in you terminal run: jupyter notebook) and select dashboard.ipynb in the web interface.

2. Select the Kernel .venv (Python {version}) using the Select Kernel option.

3. Run the cells, play around and enjoy!

Note: The dashboard.ipynb creates an additional folder ./objs along with DANDI_interactive_plot_selector.html and ./plots. The ./objs folder contains pickle objects as checkpoint files, this allows users to avoid reloading or filtering the data repeatedly when testing during later stages of the notebook.