Welcome to ESEm’s documentation!

Contents:

• Installing ESEm
  • Using PyPi
  • Using conda
  • Dependencies
• What’s new in ESEm
  • What’s new in ESEm 1.1
• Emulating with ESEm
  • Gaussian processes emulation
  • Neural network emulation
  • Random forest emulation
  • Data processing
  • Feature selection
• Calibrating with ESEm
  • Using approximate Bayesian computation (ABC)
  • Using Markov-chain Monte-Carlo
• Examples
  • Emulating using GPs
  • Emulating using CNNs
  • Random Forest Example: Cloud-resolving model sensitivity
  • Calibrating GPs using ABC
  • Calibrating GPs using MCMC
  • CMIP6 Emulation
  • Create paper emulation figure
• API reference
  • Top-level functions
  • Emulator
  • Sampler
  • Wrappers
  • ModelAdaptor
  • DataProcessor
  • Utilities
• ESEm design
  • Emulation
  • Calibration
• Glossary

Indices and tables

• Index

• Module Index

• Search Page