Miguel Angel Salazar de Troya writes:
> Sorry to be pushy, but could anyone help me on this?
Your last email didn't have a specific question, so I'm not sure how to
answer. What you want to do is possible, but not trivial and might
require library modifications to avoid doing something perverse
Sorry to be pushy, but could anyone help me on this?
Thanks
Miguel
On Thu, Oct 23, 2014 at 10:46 AM, Miguel Angel Salazar de Troya <
salazardetr...@gmail.com> wrote:
> I decided to implement the continuous adjoint because it is clearer to me
> how to do it and the gradient will converge anyways.
I decided to implement the continuous adjoint because it is clearer to me
how to do it and the gradient will converge anyways. I was trying to
interpolate the solution, but in the adjoint analysis I need to do it once
the simulation has finished. I have saved all the solutions for each time
step. M
That might be a reasonable argument, but I'm not sure. This is one of the
papers that explains it. I'm re-reading to see if I skipped any details:
http://www.sciencedirect.com/science/article/pii/S0377042709006062
Miguel
On Mon, Oct 20, 2014 at 11:42 PM, Jed Brown wrote:
> Miguel Angel Salazar
Miguel Angel Salazar de Troya writes:
> Thanks for your response
>
> I'm struggling with this problem because the literature is not clear for me
> on how to calculate the discrete adjoint with adaptive time stepping
> algorithms. They cover the details when automatic differentiation tools are
> u
Thanks for your response
I'm struggling with this problem because the literature is not clear for me
on how to calculate the discrete adjoint with adaptive time stepping
algorithms. They cover the details when automatic differentiation tools are
used. They mention that because the time step depend
Miguel Angel Salazar de Troya writes:
> Hi all
>
> I'm trying to find out what is the adaptive controller scheme used in the
> Runge-Kutta time stepping algorithm. Basically I want to know the function
> that determines the next time step. I see that the next time step is set
> with the function
Hi all
I'm trying to find out what is the adaptive controller scheme used in the
Runge-Kutta time stepping algorithm. Basically I want to know the function
that determines the next time step. I see that the next time step is set
with the function TSAdaptChoose(), which calls the pointer function
(