From f66d6da9dfccda011e161058606530c61920fdf6 Mon Sep 17 00:00:00 2001 From: Bruno Blais Date: Tue, 8 Jun 2021 17:42:17 -0400 Subject: [PATCH] Remove last non-necessary note --- include/deal.II/particles/particle_handler.h | 22 -------------------- 1 file changed, 22 deletions(-) diff --git a/include/deal.II/particles/particle_handler.h b/include/deal.II/particles/particle_handler.h index 678b6e2829..13382cc361 100644 --- a/include/deal.II/particles/particle_handler.h +++ b/include/deal.II/particles/particle_handler.h @@ -207,28 +207,6 @@ namespace Particles /** * Return the number of particles that live on the given cell. - * - * @note - * //TODO this not true now no? - * While this function is used in step-19, it is not an efficient - * function to use if the number of particles is large. That is because - * to find the particles that are located in one cell costs - * ${\cal O}(\log N)$ where $N$ is the number of overall particles. Since - * you will likely do this for every cell, and assuming that the number - * of particles and the number of cells are roughly proportional, - * you end up with an ${\cal O}(N \log N)$ algorithm. A better approach - * is to use the fact that internally, particles are arranged in the - * order of the active cells they are in. In other words, if you iterate - * over all particles, you will encounter them in the same order as - * you walk over the active cells. You can exploit this by keeping an - * iterator to the first particle of the first cell, and when you move - * to the next cell, you increment the particle iterator as well until - * you find a particle located on that next cell. Counting how many - * steps this took will then give you the number you are looking for, - * at a cost of ${\cal O}(\log N)$ when accumulated over all cells. - * This is the approach used in step-70, for example. The approach is - * also detailed in the "Possibilities for extensions section" - * of step-19. */ types::particle_index n_particles_in_cell( -- 2.39.5