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Getting Started with Diffid

Welcome to Diffid! This section will help you get up and running with time-series inference and optimisation.

Learning Path

We recommend following this sequence:

  1. Installation - Platform-specific installation instructions and troubleshooting
  2. 5-Minute Quickstart - Simple scalar optimisation with the Rosenbrock function
  3. First ODE Fit - Fitting differential equations to data with DiffSL
  4. Core Concepts - Understanding builders, problems, and the ask/tell pattern

Prerequisites

  • Python >= 3.11
  • Basic understanding of Python programming
  • Familiarity with NumPy arrays (helpful but not required)
  • For ODE fitting: basic knowledge of differential equations

What You'll Learn

By the end of this section, you will be able to:

  • Install Diffid on your platform
  • Create and solve scalar optimisation problems
  • Fit differential equations to experimental data
  • Understand the builder pattern and problem types
  • Choose between optimisers and samplers for your use case

Need Help?

If you encounter issues:

  1. Check the Troubleshooting guide
  2. Browse the examples gallery
  3. Open an issue on GitHub

Ready to begin? Start with Installation.