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CHANGELOG.md

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Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

Unreleased

v0.1.7 - 2021-10-18

Added

  • it's possible to set explicit time dependence of rates now when starting a simulation

Fixed

  • changed references to deprecated classes in examples and docstrings
  • better handling of detecting explicit time-dependence in functional rates.

v0.1.6 - 2021-07-30

Changed

  • renamed a parameter in StochasticEpiModel.simulate to stop_simulation_on_vanishing_total_event_rate, because it describes the mechanism better (adjusted TemporalNetwork) accordingly

Fixed

  • Disallowing resizing a visualization app on Linux OSes to avoid a recursion error
  • metadata such as epipack.__version__ is now correctly given out

Added

  • a SymbolicSEIRModel
  • a routine to generate random geometric graphs
  • the possiblity to add a callback function in StochasticEpiModel.simulate such that event tracking is possible

v0.1.5 - 2021-06-08

Added

  • methods to the IntegratorMixin class that allow integration until a stop condition is reached

Fixed

  • specified for MatrixEpiModel that the leading eigenvalue of a Jacobian should be measured by largest real part
  • specified for MatrixEpiModel that the leading eigenvalue of the next generation matrix should be measured by largest magnitude (because R is the matrix's spectral radius)
  • in StochasticEpiModel, convert rate values to float by default

v0.1.4 - 2021-05-18

Added

  • A new small-world network styling method based on 1d lattice distance (in epipack.networks)
  • methods to compute Jacobian and next generation matrices (NGMs) in MatrixEpiModel, as well as R0 from said NGMs (TODO: add docs)
  • tests for these methods
  • epipack.distributions module, which deals with fitting empirical distributions to sums of exponentially distributed random variables (still in dev mode, also TODO: add docs)
  • tests for this module
  • methods to EpiModel that save events that have been set. This will be used to generate model flowcharts with graphviz at some point
  • the possibility to pass a function to StochasticEpiModel.simulate that checks for a custom stop condition

v0.1.3 - 2021-04-07

Fixed

  • dependency issues with pyglet, apparently the "shapes" module did not appear until lately. Defined a range of versions for pyglet
  • bug in example code in README.md

v0.1.2 - 2021-04-01

Fixed

  • A bug where the reset_events-flag was ignored when setting processes

v0.1.1 - 2021-03-03

Added

  • GeneralInteractiveWidget was added to allow interactive display of general functions
  • a very basic SDE integrator was added (no diffusion coefficent matrix, and no system-dependent diffusion coefficients)

Changed

  • InteractiveIntegrator can now plot derivatives
  • Range and LogRange classes will behave like floats whenever necessary

Fixed

  • behavior of the SamplableSet class
  • a bug where the reaction rate of nodes in weighted networks is scaled by the node's degree and not by its strength

v0.1.0 - 2020-10-21

Added

  • epipack.interactive: contains a class that adds an interactive widget to Jupyter notebooks with which one may control the parameter values of a SymbolicEpiModel instance
  • epipack.temporal_networks: set up temporal networks and model simulations on them
  • SymbolicODEModel: A model that's defined via ODEs in sympy format.

[v0.0.5] - 2020-08-14

Changed

  • DeterministicEpiModel is now MatrixEpiModel
  • SymbolicEpiModel is now SymbolicMatrixEpiModel
  • in StochasticEpiModel and during visualization, a more efficient mechanism checks for whether the simulation has ended for good

Added

  • Added models that are based entirely on events. In this way, we can easily implement time-dependent rates and have single models that can do everything at once: symbolic evaluations, numerical evaluations, and stochastic mean-field simulations
  • time-dependent rates are integrated using a time-varying Gillespie algorithm
  • EpiModel, StochasticSIModel, StochasticSIRModel, StochasticSISModel, SymbolicEpiModel (based on events rather than rates)

v0.0.4 - 2020-08-03

Changed

  • SymbolicEpiModel: raise error when disease_free_state is not given explicitly and no S-compartment can be found
  • allow non-unity initial conditions for SymbolicEpiModel and DeterministicEpiModel
  • population_size is now explicitly regarded in SymbolicEpiModel
  • in DeterministicEpiModel, instead of raising errors, warnings are raised for nonzero column sums
  • in StochasticEpiModel, save the current state after the end of the simulation

Added

  • A complete visualization framework and network grid layout
  • in StochasticEpiModel, a callback function can be passed that's called whenever a sample is taken during the simimulation

Fixed

  • fixed bug where fission processes were converted to quadratic rates

v0.0.3 - 2020-06-30

Added

  • Catch situations where the true total event is zero but the maximum total event rate is non-zero

v0.0.2 - 2020-06-29

Changed

  • Catching ModuleNotFoundError properly

v0.0.1 - 2020-06-25

Added

  • Working package

v0.0.0 - 2020-06-22

Changed

  • initialized