EMInsight is a powerful toolkit designed to enhance the visualization, diagnostics, and analysis of marine geophysical controlled-source electromagnetic (CSEM) response data. This web-based application offers improved data visualizations and hopefully some insights for your CSEM data processing.

• Advanced Data Visualization: Interactive charts and plots for better understanding of marine CSEM responses. Currently only support MARE2DEM data files.
• Scalable Performance: Optimized for large-scale datasets, ensuring smooth performance even with high-resolution data.
• User-Friendly Interface: Built with React, Vite, and TypeScript for an intuitive and responsive user experience.

• Extended Data Format Support: Adding compatibility for more marine EM data and general geophysical data formats.
• Expanded Visualizations: e.g., Navigation dashboard
• Data Editing: Integrating in-app data editing functionality for streamlined workflows. For now, it is highly recommended to perform any data edits in the original data files before uploading them into the app for visualization and analysis. This approach ensures the integrity of the data and allows the app to serve as a powerful decision-making tool based on visualized insights.
• Export results: Export results for further analysis or publication.

Follow these steps to set up EMInsight on your local machine:

• Frontend
  • Node.js (tested on v22)
  • Vite for project build and development
  • React and TypeScript
  • Package manager: Bun (preferred), npm, or yarn
• Backend
  • Python (tested on 3.12+) for backend data pre-processing and scientific computation

Cross-Platform Support: This project works on both macOS and Windows. The setup instructions below are designed to work on both platforms.

For macOS/Linux users:

git clone https://github.com/ycli0536/CSEMInsight.git
cd CSEMInsight
./setup.sh

For Windows users:

git clone https://github.com/ycli0536/CSEMInsight.git
cd CSEMInsight
setup.bat

The setup scripts will automatically detect your system and package managers, then install all dependencies.

If you prefer to set up manually or the automated scripts don't work:

1. Clone the repository:

   git clone https://github.com/ycli0536/CSEMInsight.git
   cd CSEMInsight

2. Install the dependencies (frontend):

   Using Bun (recommended):

   cd frontend
   bun install

   Using npm:

   cd frontend
   npm install

   Using yarn:

   cd frontend
   yarn install

3. Run the development server (frontend):

   Using Bun:

   cd frontend
   bun run dev:bun

   Using npm/yarn:

   cd frontend
   npm run dev
   # or
   yarn dev

4. Set up a Python environment (backend):

   On macOS/Linux:

   cd backend
   python -m venv env
   source env/bin/activate
   pip install -r requirements.txt

   On Windows:

   cd backend
   python -m venv env
   env\Scripts\activate
   pip install -r requirements.txt

   Alternative (PowerShell on Windows):

   cd backend
   python -m venv env
   env\Scripts\Activate.ps1
   pip install -r requirements.txt

5. Run python script (backend) to deploy a development (Not Production!) server:

   cd backend
   python main.py

6. Open the app in your browser at http://localhost:5173.

Windows-specific:

• If you get a "python not found" error, make sure Python is added to your PATH during installation
• Use PowerShell or Command Prompt as administrator if you encounter permission issues
• If virtual environment activation fails, try: env\Scripts\Activate.ps1 in PowerShell

macOS-specific:

• If you encounter permission issues, you may need to use sudo for global installations
• On Apple Silicon Macs, make sure you're using compatible versions of Node.js and Python

General:

• Ensure you have Python 3.12+ and Node.js v22+
• If package installation fails, try clearing cache:
  • npm: npm cache clean --force
  • yarn: yarn cache clean
  • bun: bun install --force

• Frontend runs on port 5173, backend on port 3354 (Flask default)
• If ports are in use, kill existing processes or change ports in the configuration files

To create an optimized production build (frontend) under frontend/dist:

Using Bun:

cd frontend
bun run build

Using npm/yarn:

cd frontend
npm run build
# or
yarn build

Once installed, you can upload your CSEM data file directly into the web app to visualize and analyze them. EMInsight provides tools to:

1. Plot CSEM responses and perform interactive data visualization.
2. Customize visualizations based on user preferences.

This project is licensed under the MIT License. See the LICENSE file for details.