Improve save_idxs #180
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Improve save_idxs #180
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@@ Coverage Diff @@
## master #180 +/- ##
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+ Coverage 71.75% 71.83% +0.08%
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Files 61 61
Lines 21165 21230 +65
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+ Hits 15187 15251 +64
- Misses 5978 5979 +1
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| @@ -107,8 +107,8 @@ function ode_interpolation(tvals,id,idxs,deriv) | |||
| tdir*tvals[idx[1]] < tdir*ts[1] && error("Solution interpolation cannot extrapolate before the first timepoint. Either start solving earlier or use the local extrapolation from the integrator interface.") | |||
| if typeof(idxs) <: Number | |||
| vals = Vector{eltype(first(timeseries))}(length(tvals)) | |||
| elseif typeof(idxs) <: AbstractVector | |||
| vals = Vector{Vector{eltype(first(timeseries))}}(length(tvals)) | |||
| elseif typeof(idxs) <: AbstractArray | |||
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...! Thanks. For some reason I couldn't find out how to do this before haha
ChrisRackauckas
approved these changes
Aug 29, 2017
|
Thanks. I actually just couldn't find out how to do this before. Would you mind making similar changes to StochasticDiffEq.jl? It should be incorrect in the same ways since the code is so similar. |
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When I wrote a notebook of benchmarks for DelayDiffEq, I discovered that
save_idxsdoes not seem to work completely correct. First I thought this is a problem in DelayDiffEq (and there might still be issues there), but it is at least partly also a problem in OrdinaryDiffEq: Usingsave_idxssuch thattypeof(u[save_idxs]) != typeof(u)does not work. So e.g. it is not possible to extract single components of the state vector with scalars, and maybe even worse it is not possible to extract a vector or vectorized component of a matrix. When I had fixed this issue and finally could extract arbitrary components I noticed another issue: it is not possible to plot solutions retrieved by scalar indexing since the interpolation of exactly that case is broken. Hence this PR additionally includes an improved interpolation that covers this case. Use cases and examples are given in the added test file.