DDALAB

A graphical user interface for analyzing time series data using Delay Differential Analysis (DDA). This computational tool provides researchers with methods to study temporal dynamics and patterns through mathematical modeling and visualization techniques.

🚀

Easy to Use

Intuitive interface designed for both beginners and experts

⚡

Fast Processing

Optimized algorithms for real-time analysis and visualization

🔧

Customizable

Flexible parameters and configurations for your specific needs

DDALAB System Architecture

The following diagram illustrates the comprehensive architecture of DDALAB, showing the interconnected components that enable delay differential analysis of time series data.

DDALAB Deployment Architecture

User Access

👤

User

Web Browser

↓

HTTPS Security Proxy

🛡️

Traefik Proxy

HTTPS Termination & Secure Routing

All requests secured via HTTPS

↓

Authentication

🔐

Login System

User Authentication & Authorization

Protected by HTTPS proxy

↓

Application Services

⚛️

NextJS Frontend

React-based Web Interface

🐳 Docker Container

On/Off-Premise

🚀

FastAPI Server

Python API Backend

🐳 Docker Container

On/Off-Premise

🔄 REST API Requests

Core DDALAB Services (Docker Containers)

📐

DDA Engine

🐳

💾

Database

🐳

📊

Analytics

🐳

🔧

Utils

🐳

⚙️

Configuration Manager

Centralized DDALAB Service Management

🟢 Start Services

🔴 Stop Services

📋 Monitor Status

🐳 All services containerized with Docker for easy deployment and scaling

Deployment Architecture Components:

Frontend (NextJS): React-based web interface running in Docker, accessible on/off-premise

Backend (FastAPI): Python API server in Docker container handling all computational requests

Security Layer: Traefik proxy with integrated authentication and secure connection management

Service Management: Configuration manager for easy orchestration of all DDALAB services