tspan
? I haven't settled on anything but am wondering where you're taking it.
A-B-M is @obiajulu's work: JuliaLang/ODE.jl#106
There is some work on stiff solvers: JuliaLang/ODE.jl#72 and @obiajulu is starting on RADAU, but nothing finished.
Anyway, have a look at the iterator work and see whether you like it. If so you could consider wrapping that instead of the old one. Also, wrapping outside solvers should be easy with that, and is planned.
tspan
, see https://github.com/JuliaODE/ODE.jl/blob/dev/src/types.jl for our latest thoughts.
ode = ODE.ExplicitODE(t0,y0,(t,y,dy)->dy[1]=y[1])
opts = Dict(:initstep=>0.1,
:tspan=>[0.,0.5,1.],
:points=>:specified,
:reltol=>1e-5,
:abstol=>1e-5)
stepper = ODE.RKStepperAdaptive{:rk45}
sol = ODE.solve(ode,stepper;opts...)
for (t,y) in sol # iterate over the solution
println((t,y))
end
println(collect(sol)) # get all the solution at once
sol = ODE.solve(ode,stepper;opts...)
be the main one?
ODE.solve(ode,stepper;opts...)
calls.
solve(prob,tspan,alg=:algorithm)