Merge pull request #1417 from pints-team/i-1067-generic-stochastic-model

Generic stochastic model

Author: ben18785

CHANGELOG.md

@@ -5,6 +5,7 @@ All notable changes to this project will be documented in this file.
 ## Unreleased
 
 ### Added
+- [#1417](https://github.com/pints-team/pints/pull/1417) Added a module `toy.stochastic` for stochastic models. In particular, `toy.stochastic.MarkovJumpModel` implements Gillespie's algorithm for easier future implementation of stochastic models.
 - [#1420](https://github.com/pints-team/pints/pull/1420) The `Optimiser` class now distinguishes between a best-visited point (`x_best`, with score `f_best`) and a best-guessed point (`x_guessed`, with approximate score `f_guessed`). For most optimisers, the two values are equivalent. The `OptimisationController` still tracks `x_best` and `f_best` by default, but this can be modified using the methods `set_f_guessed_tracking` and `f_guessed_tracking`.
 
 ### Changed

LICENSE.md

@@ -1,6 +1,6 @@
 BSD 3-Clause License
 
-Copyright (c) 2017-2021, University of Oxford (University of Oxford means the
+Copyright (c) 2017-2022, University of Oxford (University of Oxford means the
 Chancellor, Masters and Scholars of the University of Oxford, having an
 administrative office at Wellington Square, Oxford OX1 2JD, UK).
 All rights reserved.

docs/source/index.rst

@@ -39,6 +39,7 @@ Contents
     optimisers/index
     noise_model_diagnostics
     toy/index
+    toy/stochastic/index
     transformations
     utilities
 

docs/source/toy/index.rst

@@ -37,6 +37,5 @@ Some toy classes provide extra functionality defined in the
     simple_egg_box_logpdf
     simple_harmonic_oscillator_model
     sir_model
-    stochastic_degradation_model
     stochastic_logistic_model
     twisted_gaussian_logpdf

docs/source/toy/stochastic/index.rst

@@ -0,0 +1,15 @@
+***********************
+Stochastic Toy Problems
+***********************
+
+The `stochastic` module provides toy :class:`models<pints.toy.stochastic.MarkovJumpModel>`,
+:class:`distributions<pints.LogPrior>` and
+:class:`error measures<pints.ErrorMeasure>` that can be used for tests and in
+examples.
+
+
+.. toctree::
+
+    markov_jump_model
+    stochastic_degradation_model
+    stochastic_michaelis_menten_model

docs/source/toy/stochastic/markov_jump_model.rst

@@ -0,0 +1,7 @@
+*****************
+Markov Jump Model
+*****************
+
+.. currentmodule:: pints.toy.stochastic
+
+.. autoclass:: MarkovJumpModel

docs/source/toy/stochastic_degradation_model.rst renamed to docs/source/toy/stochastic/stochastic_degradation_model.rst

@@ -2,6 +2,6 @@
 Stochastic degradation model
 ****************************
 
-.. currentmodule:: pints.toy
+.. currentmodule:: pints.toy.stochastic
 
-.. autoclass:: StochasticDegradationModel
+.. autoclass:: DegradationModel

docs/source/toy/stochastic/stochastic_michaelis_menten_model.rst

@@ -0,0 +1,7 @@
+*********************************
+Stochastic Michaelis Menten model
+*********************************
+
+.. currentmodule:: pints.toy.stochastic
+
+.. autoclass:: MichaelisMentenModel

examples/README.md

@@ -103,7 +103,7 @@ relevant code.
 
 ## Toy problems
 
-### Models
+### Deterministic Models
 - [Beeler-Reuter action potential model](./toy/model-beeler-reuter-ap.ipynb)
 - [Constant model](./toy/model-constant.ipynb)
 - [Fitzhugh-Nagumo model](./toy/model-fitzhugh-nagumo.ipynb)
@@ -115,8 +115,11 @@ relevant code.
 - [Repressilator model](./toy/model-repressilator.ipynb)
 - [Simple Harmonic Oscillator model](./toy/model-simple-harmonic-oscillator.ipynb)
 - [SIR Epidemiology model](./toy/model-sir.ipynb)
+
+### Stochastic Models
 - [Stochastic Degradation model](./toy/model-stochastic-degradation.ipynb)
 - [Stochastic Logistic model](./toy/model-stochastic-logistic-growth.ipynb)
+- [Stochastic Michaelis Menten model](./toy/model-stochastic-michaelis-menten.ipynb)
 
 ### Distributions
 - [Annulus](./toy/distribution-annulus.ipynb)