PyCC.id documentation

User guide:

• 👋 PyCC
• 🎯 Why PyCC
  • 💡 The PyCC approach: A schematic workflow
  • 🔬 Application example to a second order system
  • 📝 Formalism
  • ✨ Key Features
• Installation
  • Installation with pip (Recommended)
• Usage

Functions:

• pycc.train()
  • Overview
  • Method-Specific Details
• pycc.simulate()
  • Overview
  • Method-Specific Details
• pycc.post_processing()
  • Symbolic Regression (method='SymbR')

Examples:

• Example 1: Function y=f(x)
• Example 2: 2nd-order ODE
• Example 3: 3rd-order ODE
• Example 4: 1st-order ODE with f in denominator
• Example 5: 2nd-order ODE - Parametric method with post-fine-tuning

Tips:

• Practical Tips
  • NN-CC: The Core Method
  • Alternative Methods: Poly-CC and SymbR-CC
• Workflow 1
• Workflow 2
• Workflow 3

Links:

• Community & Useful Links
  • Contact

References:

• How to cite this package
  • References
  • BibTeX