README.md

Examples

This page contains a number of examples showing how to use Pints.

Each example was created as a Jupyter notebook (http://jupyter.org/). These notebooks can be downloaded and used, or you can simply copy/paste the relevant code.

Getting started

• Optimisation: First example
• Sampling: First example
• Writing a model
• Writing a custom LogPDF
• Writing a custom LogPrior

Optimisation

Particle-based methods

• CMA-ES
• PSO
• SNES
• XNES

Local optimisers

• Nelder-Mead

Further optimisation

• Ask-and-tell interface
• Convenience methods fmin() and curve_fit()
• Multiple objectives
• Optimisation on a loglikelihood
• Transformed parameter space

Sampling

MCMC without gradients

• Adaptive Covariance MCMC
• Differential Evolution MCMC
• DREAM MCMC
• Emcee Hammer
• Metropolis Random Walk MCMC
• Population MCMC
• Slice Sampling: Stepout MCMC
• Slice Sampling: Doubling MCMC
• Slice Sampling: Overrelaxation MCMC
• Slice Sampling: Hyperrectangles MCMC

MCMC with gradients

• Hamiltonian MCMC
• MALA MCMC
• Slice Sampling: Adaptive Hyperrectangles MCMC

Nested sampling

• Ellipsoidal nested rejection sampling

Analysing sampling results

• Autocorrelation
• Effective sample size
• Pairwise scatterplots
• Pairwise scatterplots with KDE
• Predicted time series
• Trace plots

Statistical modelling

• Autoregressive moving average errors
• Cauchy sampling error
• Integrated noise model
• Log priors
• Student-t noise model

Toy problems

Models

• Beeler-Reuter action potential model
• Constant model
• Fitzhugh-Nagumo model
• Goodwin oscillator model
• HES1 Michaelis-Menten model
• Hodgkin-Huxley Potassium current model
• Logistic growth model
• Lotka-Volterra predator-prey model
• Repressilator model
• SIR Epidemiology model

Distributions

• Annulus
• Cone
• High dimensional gaussian
• Multimodal gaussian distribution
• Neals Funnel
• Rosenbrock function
• Simple Egg Box
• Twisted Gaussian Banana

Miscellaneous

• The example shown on the landing page