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v0.1.0 - First Stable Release

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@psaboia psaboia released this 28 Jun 23:49
· 33 commits to main since this release
v0.1.0
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🎉 First Stable Release

This is the first stable release of pad-analytics, ready for production use!

✨ Key Features

  • Complete PAD (Paper Analytical Device) data analysis workflow
  • Machine learning model integration (Neural Networks + PLS regression)
  • Interactive Jupyter notebook widgets for data visualization
  • Comprehensive API for pharmaceutical quality analysis
  • Dataset discovery and management system

🔧 Recent Fixes

  • Dataset Path Resolution: Fixed critical file path issues for pip installations
  • Robust Package Structure: Works reliably in all deployment scenarios
  • Enhanced Error Handling: Better error messages and debugging information
  • Production Ready: Thoroughly tested for PyPI deployment

📦 Installation

pip install git+https://github.com/PaperAnalyticalDeviceND/pad-analytics.git

🚀 Quick Start

import pad_analytics as pad

# Explore available projects and models
projects = pad.get_projects()
models = pad.get_models()

# Analyze a PAD card
actual, prediction = pad.predict(card_id=19208, model_id=18)

# Work with datasets
mapping = pad.get_model_dataset_mapping()
datasets = pad.get_dataset_list()

📊 What's Included

  • ✅ 35+ analysis functions
  • ✅ Dataset discovery and management
  • ✅ Model prediction and evaluation
  • ✅ RMSE calculation and analysis tools
  • ✅ Visualization and reporting widgets
  • ✅ Complete API for PAD data access

🎯 Use Cases

  • Pharmaceutical quality control analysis
  • PAD image processing and colorimetric analysis
  • Machine learning model application on PAD data
  • Research and development workflows
  • Educational and training purposes

🛠️ Technical Details

  • Python Support: 3.9, 3.10, 3.11
  • Key Dependencies: TensorFlow, Pandas, OpenCV, Scikit-learn
  • Package Structure: Professional src/ layout
  • Testing: Comprehensive test suite
  • Documentation: Complete API documentation

Ready for research, development, and production use! 🎯

📋 Next Steps

  • Consider starring the repository ⭐
  • Check out the examples in the /examples directory
  • Visit our documentation for detailed guides
  • Report issues or contribute via GitHub Issues/PRs

For questions or support, please open an issue on GitHub.

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