Add conda-based Docker support for pager - containerize PAGE algorithm workflows

[Copilot]

This PR implements comprehensive Docker support for the pager repository, addressing issue #7 by providing a complete containerization solution for PAGE algorithm analysis workflows that follows the conda-based setup described in the README.

Key Features

Conda-based Environment Setup

• Uses miniconda for Python environment management following README instructions
• Creates 'pager' conda environment as specified in the manual installation guide
• Installs Python dependencies (pandas, numpy, matplotlib) via conda instead of system packages
• Sets environment variables using conda env config vars exactly as described in README
• Automatically activates conda environment when container runs

Complete Docker Implementation

• Dockerfile: Full containerization using Ubuntu 22.04 with miniconda and all required dependencies
• docker-compose.yml: Simplified container management with volume mounting support
• .dockerignore: Optimized build context excluding unnecessary files
• docker_test.sh: Validation script to test container functionality and conda environment

Enhanced Documentation
Updated README.md with comprehensive Docker usage instructions including:

• Docker as the recommended installation method
• Multiple usage patterns (basic container, data mounting, external tool integration)
• Practical examples for common workflows using conda environment
• Docker Compose usage examples

Usage Examples

# Build and run basic container
docker build -t pager . && docker run pager

# Interactive session with data mounting
docker run -v ./data:/data -it pager /bin/bash

# Full functionality with external tools
docker run -v /path/to/PAGE:/opt/PAGE -v /path/to/TEISER:/opt/TEISER -v ./data:/data -it pager

# Using docker-compose
docker compose build && docker compose run pager

Benefits

• Consistency: Uses the same conda-based setup as manual installation
• Portability: Eliminates dependency management across different environments
• Accessibility: Users can run PAGE analysis workflows without complex local setup
• Reproducibility: Consistent conda environment for scientific analysis

The implementation mirrors the conda environment setup from the README, ensuring users get the same experience whether installing manually or using Docker.

Fixes #7

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[abearab]

@copilot make sure you are using conda properly as described in README within your docker configuration.

[Copilot]

@copilot make sure you are using conda properly as described in README within your docker configuration.

Updated the Docker configuration to properly use conda as described in the README. The implementation now:

• Installs miniconda and creates the 'pager' conda environment
• Uses conda to install Python dependencies (pandas, numpy, matplotlib)
• Sets environment variables using conda env config vars as shown in the README
• Activates the conda environment by default when the container runs

All functionality has been tested and validated with the conda-based setup. Commit: 4d6853e