🌌 Exoplanet Analysis & Visualization Dashboard

An interactive, AI-powered dashboard for visualizing exoplanet systems, anomaly detection, and atmospheric analysis — blending data science and space visualization.

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🚀 Overview

The Exoplanet Analysis Dashboard visualizes real astronomical datasets and ML-based predictions in an immersive, cinematic way.
It integrates data-driven insights, machine learning predictions, and interactive orbit visualizations for each detected planet system.

✨ Features include:

• 🪐 Real-time animated orbital systems (2D + 3D views)
• 🔭 AI-powered planet classification and anomaly detection
• 🌈 Atmospheric composition, confidence scoring, and visual trends
• 📊 Dynamic feature importance visualization
• 🛰️ Gemini-based AI insights (if API key configured)
• 🌠 Twinkling starfield, nebula glows, and parallax camera motion

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🧠 Tech Stack

Layer	Technology	Purpose
Frontend	React + TypeScript + Vite	High-performance UI
Styling	TailwindCSS + ShadCN/UI	Modern, clean design system
Charts	Recharts	Atmospheric and data trend visualization
Backend	FastAPI (Python)	REST API for analysis and ML inference
Database	SQLite / PostgreSQL	Persistent data store
ML/AI	Scikit-learn, Gemini API	Outlier detection, classification, explanations

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📂 Project Structure

.
├── backend/
│   ├── main.py                # FastAPI entry point
│   ├── models.py              # Database & ML models
│   ├── routes/
│   │   └── analysis.py        # /analysis/<id> endpoint
│   └── utils/
│       └── ml_engine.py       # ML inference, outlier detection
│
├── frontend/
│   ├── src/
│   │   ├── components/
│   │   │   ├── StarSystem.tsx    # 3D orbital visualization
│   │   │   └── StarSystem2D.tsx  # 2D flat projection
│   │   ├── pages/
│   │   │   └── Analysis.tsx      # Main dashboard page
│   │   ├── App.tsx
│   │   └── main.tsx
│   └── index.html
│
└── README.md

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⚙️ Setup & Installation

1️⃣ Clone the repository

git clone https://github.com/yourusername/exoplanet-visualizer.git
cd exoplanet-visualizer

2️⃣ Backend setup (FastAPI)

cd backend
pip install -r requirements.txt
uvicorn main:app --reload

API will run at: http://localhost:8000

3️⃣ Frontend setup (React)

cd frontend
npm install
npm run dev

App runs at: http://localhost:5173

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🌍 Usage

1. Open the web app in your browser.
2. Choose an analysis record (/analysis/<id>) to visualize.
3. Explore:
   • 3D mode: Orbital animation, parallax motion, and nebula glow
   • 2D mode: Clear system layout with orbits and anomaly-coded colors
4. Check Prediction Summary, Atmosphere, and Feature Importance panels for insights.
5. Watch trends update in real-time.

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🪩 Visualization Highlights

🪐 3D Orbital System

• Smooth planet orbits with dynamic anomalies
• Twinkling background stars with parallax drift
• Nebula gradients and subtle rotational motion

🌈 2D System View

• Clear static orbit visualization
• Confidence and anomaly indicators
• Light nebula overlays and soft UI glow

📊 Feature Importance

• Dynamic bar visualizations from model weights
• Adaptive scaling and Tailwind-based color gradients

🔬 Atmospheric Analysis

• Trend chart with real-time simulated updates (O₂, CH₄)
• Confidence and color-coded stability indicators

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🔧 Configuration

Variable	Description	Default
GEMINI_API_KEY	Optional key for Gemini-based explanations	None
PORT	FastAPI port	8000
DATABASE_URL	Database connection string	SQLite local
FRONTEND_PORT	React dev server port	5173

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📈 Example API Response

{
  "prediction": "Habitable",
  "confidence": 0.92,
  "reliability": { "label": "High", "score": 0.89 },
  "likely_atmosphere": {
    "likely_gases": [
      { "element": "O₂", "percentage": "21%" },
      { "element": "CH₄", "percentage": "1.7%" }
    ],
    "confidence": "High"
  },
  "outliers": [
    { "feature": "koi_depth", "z": 8.9 },
    { "feature": "koi_period", "z": 9.3 }
  ],
  "planet_type": {
    "ml_prediction": "Super-Earth",
    "rule_based_prediction": "Rocky",
    "agreement": true
  }
}

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💫 Screenshots

3D System	2D System	Insights

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🧩 Future Enhancements

• 🌌 WebGL-based 3D starfield (Three.js)
• 🪙 Export data as CSV or PDF report
• 🧬 Planet comparison mode
• 🌐 Deploy to Vercel + Render stack

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🛡 License

This project is licensed under the MIT License — feel free to use, modify, and distribute.

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👨‍🚀 Author

Saptarshi Mondal
Data Visualization Engineer • Space Enthusiast 🚀

📫 Reach out: saptarshidev169@gmail.com
🌐 Portfolio / Website