Small helper package that provides a struct for sequence learning with Neural ODEs. It behaves roughly similar to Flux' Dataloader but the individual samples overlap, so that it is suitable for learning sequences.
Prepare a DE solution
f(u,p,t) = 1.01*u
u0 = 1/2
tspan = (0.0,10.0)
prob = ODEProblem(f,u0,tspan)
sol = solve(prob, Tsit5(), reltol=1e-8, abstol=1e-8)and either interpolate the result
data = NODEDataloader(sol, 20, dt=0.2)or use their original timesteps
data = NODEDataloader(sol, 20)In these examples each batch is N_length=20 elements long, i.e data[i], is a tuple with (t, data(t)) each with 20 elements. data[1] are the first N_length elements, data[2] are the 2:N_length+1 elements and so on.
The pacakge also provides a wrapper around NODEDataloader for larger than RAM datasets. The data is split into temporary files on the harddrive and can be easiliy loaded. See LargeNODEDataloader