Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)
We currently always wrap user affect function to ensure they return nothing, thereby making sure the affect functions all have the same return type. We should see if this has any performance impact, and if so, make a kwarg a user can set to disable this (i.e. by promising they have properly constructed their affect functions to return nothing).
We should also update the docs to always include the nothing return.
We currently always wrap user affect function to ensure they return
nothing, thereby making sure the affect functions all have the same return type. We should see if this has any performance impact, and if so, make a kwarg a user can set to disable this (i.e. by promising they have properly constructed their affect functions to return nothing).We should also update the docs to always include the
nothingreturn.