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Breaking updates and feature summaries across releases

JumpProcesses unreleased (master branch)

9.13

  • Added a default aggregator selection algorithm based on the number of passed in jumps. i.e. the following now auto-selects an aggregator (Direct in this case):

    using JumpProcesses
rate(u, p, t) = u[1]
affect(integrator) = (integrator.u[1] -= 1; nothing)
crj = ConstantRateJump(rate, affect)
dprob = DiscreteProblem([10], (0.0, 10.0))
jprob = JumpProblem(dprob, crj)
sol = solve(jprob, SSAStepper())

  • For JumpProblems over DiscreteProblems that only have MassActionJumps, ConstantRateJumps, and bounded VariableRateJumps, one no longer needs to specify SSAStepper() when calling solve, i.e. the following now works for the previous example and is equivalent to manually passing SSAStepper():

    sol = solve(jprob)

  • Plotting a solution generated with save_positions = (false, false) now uses piecewise linear plots between any saved time points specified via saveat instead (previously the plots appeared piecewise constant even though each jump was not being shown). Note that solution objects still use piecewise constant interpolation, see the docs for details.

9.7

  • Coevolve was updated to support use with coupled ODEs/SDEs. See the updated documentation for details, and note the comments there about one needing to ensure rate bounds hold however the ODE/SDE stepper could modify dependent variables during a timestep.

9.3

  • Support for "bounded" VariableRateJumps that can be used with the Coevolve aggregator for faster simulation of jump processes with time-dependent rates. In particular, if all VariableRateJumps in a pure-jump system are bounded one can use Coevolve with SSAStepper for better performance. See the documentation, particularly the first and second tutorials, for details on defining and using bounded VariableRateJumps.