Ah, of course! reshape the view! Sometimes once things are put open in front of you, one cannot help to wonder: "Why I ddin't think of that!".
Thanks a lot! On Monday, October 3, 2016 at 4:21:32 AM UTC+2, Chris Rackauckas wrote: > > Fengyang's reshape((@view x[1:6]), (3, 2)) will work well and will be > essentially cost-free since reshape creates a view, and a view of a view is > still just a view (no copy). Another way to write it is > reshape(view(x,1:6), (3, 2)). For example: > > function f(t,u,du) > x = reshape(view(x,1:6), (3, 2)) > # Use x and u[7], u[8], u[9], and u[10] to write directly to du > nothing > end > > should be a good way to write the function for Sundials.jl, > DifferentialEquations.jl, ODE.jl (after the iterator PR). > > On Sunday, October 2, 2016 at 5:43:01 AM UTC-7, Alexey Cherkaev wrote: >> >> I have the model where it is convenient to represent one of the variables >> as a matrix. This variable, however, is obtained as a solution of ODEs >> (among other variables). I'm using Sundials to solve ODEs and >> `Sundials.cvode` requires the ODE RHS function to take a vector. So, it >> seems logical to pack the variables into a vector to pass to `cvode` and >> unpack them for more convenient use in my code. >> >> For example, consider `x = fill(1.0, 10)` and the first 6 entries are >> actually a matrix of size 3x2, other 4: other variables. So, I can do `s = >> reshape(x[1:6], (3,2))`. However, this creates a copy, which I would want >> to avoid. And I couldn't find a way to do the view-reshaping by applying >> `view()` function or doing `SubArray` directly. For now I settle on to >> using indices of the form `(i-1)*M + j +1` to retrieve `s[i,j] = x[(i-1)*M >> + j +1]`. But, (1) julia's 1-based arrays make it awkward to use this >> notation and (2) matrix (not element-wise) operations are not available. >> >
