Welcome to the NPZ/NPY Web Viewer, a modern, feature-rich tool designed for interactive visualization and exploration of .npz and .npy files.

• Upload .npz or .npy files to visualize multidimensional arrays directly in your browser.
• Handles multiple arrays in a single .npz file seamlessly.

• View arrays with multiple chart types:
  • 🟠 3D Scatter Plot
  • 🟢 3D Surface Plot
  • 🔵 Scatter Plot
  • 🔗 Line Chart
  • ⚪ Grayscale Image
• Switch between chart types interactively for deeper insights.

• Apply machine learning algorithms directly to your data:
  • Clustering:
    • K-means clustering with customizable number of clusters
    • DBSCAN clustering with adjustable epsilon and minimum samples
  • Dimensionality Reduction:
    • Principal Component Analysis (PCA) with selectable components
• Interactive visualizations of ML results with detailed metrics
• Normalize data option for better algorithm performance

• Download CSV: Convert arrays into .csv files for easy sharing and analysis.
• Save 3D Plots: Export interactive 3D plots for use in presentations or reports.

• Intuitive dropdowns for selecting chart types.
• Dynamic resizing and rendering for smooth user experience.

• Powered by Next.js with React for a seamless UI.
• All processing happens client-side — no backend required.

• Node.js >= 18.x
• Docker (optional)

1. Clone the repository:

   git clone https://github.com/<your-username>/npz-web-viewer.git
   cd npz-web-viewer/npz_viewer_client

2. Install dependencies:

   npm install

3. Start the development server:

   npm run dev

4. Access the app in your browser:

   http://localhost:3000
   

To run both the backend and the frontend services together:

1. Navigate to the Project Root:

   cd /path/to/your/project

2. Run the Services: Use the following command to start the backend and frontend:

   docker-compose up

   This will:

   • Build the frontend Docker image.
   • Start the service and expose it on:
     • Frontend: http://localhost:3000

If you want the services to run in the background:

docker-compose up -d

• View any .npz or .npy file effortlessly.

• Switch between visualization modes:
  • 3D Scatter, 3D Surface, Line Chart, and more!

• Cluster your data with K-means or DBSCAN
• Reduce dimensions with PCA
• Visualize results with interactive plots
• Adjust algorithm parameters in real-time

• Export data as .csv or save interactive plots for offline use.

We welcome contributions! Feel free to fork the repo and submit pull requests to improve this project.

This project is licensed under the BSD 3-Clause. See the LICENSE file for details.