[julia-users] Re: View (a portion of a) vector as a matrix
You can also express this as a two-dimensional index: @view x[[1:3 4:6]] # or @view x[reshape(1:6, 2,3)] In this case, though, the reshaped view should a bit more performant. On Monday, October 3, 2016 at 10:33:34 AM UTC-5, Alexey Cherkaev wrote: > > 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. >>> >>
[julia-users] Re: View (a portion of a) vector as a matrix
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. >> >
[julia-users] Re: View (a portion of a) vector as a matrix
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. >
[julia-users] Re: View (a portion of a) vector as a matrix
There should be no copy if you reshape a view.
julia> reshape((@view x[1:6]), (3, 2))
3×2
Base.ReshapedArray{Float64,2,SubArray{Float64,1,Array{Float64,1},Tuple{UnitRange{Int64}},true},Tuple{}}:
1.0 1.0
1.0 1.0
1.0 1.0
On Sunday, October 2, 2016 at 8:43:01 AM UTC-4, 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.
>
