mirror of
https://github.com/cosmo-sims/MUSIC.git
synced 2024-09-19 17:03:46 +02:00
dropped real-space convolutions entirely. removed many unused functions from mesh.hh
This commit is contained in:
Oliver Hahn
parent
58d68ec1f6
commit
5bd8c45341
3 changed files with 1422 additions and 2470 deletions
223
src/densities.cc
223
src/densities.cc
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@ -605,9 +605,8 @@ void GenerateDensityHierarchy(config_file &cf, transfer_function *ptf, tf_type t
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convolution::kernel *the_tf_kernel = the_kernel_creator->create(cf, ptf, refh, type);
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/***** PERFORM CONVOLUTIONS *****/
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if (kspaceTF)
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assert(kspaceTF);
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{
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//... create and initialize density grids with white noise
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DensityGrid<real_t> *top(NULL);
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PaddedDensitySubGrid<real_t> *coarse(NULL), *fine(NULL);
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@ -634,11 +633,11 @@ void GenerateDensityHierarchy(config_file &cf, transfer_function *ptf, tf_type t
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refh.size(levelmin + i, 1), refh.size(levelmin + i, 2));
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fine = new PaddedDensitySubGrid<real_t>(refh.offset(levelmin + i, 0),
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refh.offset(levelmin + i, 1),
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refh.offset(levelmin + i, 2),
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refh.size(levelmin + i, 0),
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refh.size(levelmin + i, 1),
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refh.size(levelmin + i, 2));
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refh.offset(levelmin + i, 1),
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refh.offset(levelmin + i, 2),
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refh.size(levelmin + i, 0),
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refh.size(levelmin + i, 1),
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refh.size(levelmin + i, 2));
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/////////////////////////////////////////////////////////////////////////
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// load white noise for patch
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@ -671,216 +670,6 @@ void GenerateDensityHierarchy(config_file &cf, transfer_function *ptf, tf_type t
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delete coarse;
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}
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else
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{
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//... create and initialize density grids with white noise
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PaddedDensitySubGrid<real_t> *coarse(NULL), *fine(NULL);
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DensityGrid<real_t> *top(NULL);
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if (levelmax == levelmin)
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{
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std::cout << " - Performing noise convolution on level "
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<< std::setw(2) << levelmax << " ..." << std::endl;
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LOGUSER("Performing noise convolution on level %3d...", levelmax);
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top = new DensityGrid<real_t>(nbase, nbase, nbase);
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//rand_gen.load( *top, levelmin );
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rand.load(*top, levelmin);
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convolution::perform<real_t>(the_tf_kernel->fetch_kernel(levelmax),
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reinterpret_cast<void *>(top->get_data_ptr()),
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shift, fix, flip);
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the_tf_kernel->deallocate();
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delta.create_base_hierarchy(levelmin);
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top->copy(*delta.get_grid(levelmin));
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delete top;
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}
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for (int i = 0; i < (int)levelmax - (int)levelmin; ++i)
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{
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//.......................................................................................................//
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//... GENERATE/FILL WITH RANDOM NUMBERS .................................................................//
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//.......................................................................................................//
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if (i == 0)
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{
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top = new DensityGrid<real_t>(nbase, nbase, nbase);
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rand.load(*top, levelmin);
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}
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fine = new PaddedDensitySubGrid<real_t>(refh.offset(levelmin + i + 1, 0),
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refh.offset(levelmin + i + 1, 1),
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refh.offset(levelmin + i + 1, 2),
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refh.size(levelmin + i + 1, 0),
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refh.size(levelmin + i + 1, 1),
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refh.size(levelmin + i + 1, 2));
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rand.load(*fine, levelmin + i + 1);
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//.......................................................................................................//
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//... PERFORM CONVOLUTIONS ..............................................................................//
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//.......................................................................................................//
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if (i == 0)
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{
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/**********************************************************************************************************\
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* multi-grid: top-level grid grids .....
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\**********************************************************************************************************/
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std::cout << " - Performing noise convolution on level "
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<< std::setw(2) << levelmin + i << " ..." << std::endl;
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LOGUSER("Performing noise convolution on level %3d", levelmin + i);
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LOGUSER("Creating base hierarchy...");
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delta.create_base_hierarchy(levelmin);
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DensityGrid<real_t> top_save(*top);
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the_tf_kernel->fetch_kernel(levelmin);
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//... 1) compute standard convolution for levelmin
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LOGUSER("Computing density self-contribution");
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convolution::perform<real_t>(the_tf_kernel, reinterpret_cast<void *>(top->get_data_ptr()), shift, fix, flip);
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top->copy(*delta.get_grid(levelmin));
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//... 2) compute contribution to finer grids from non-refined region
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LOGUSER("Computing long-range component for finer grid.");
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*top = top_save;
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top_save.clear();
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top->zero_subgrid(refh.offset(levelmin + i + 1, 0), refh.offset(levelmin + i + 1, 1), refh.offset(levelmin + i + 1, 2),
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refh.size(levelmin + i + 1, 0) / 2, refh.size(levelmin + i + 1, 1) / 2, refh.size(levelmin + i + 1, 2) / 2);
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convolution::perform<real_t>(the_tf_kernel, reinterpret_cast<void *>(top->get_data_ptr()), shift, fix, flip);
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the_tf_kernel->deallocate();
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meshvar_bnd delta_longrange(*delta.get_grid(levelmin));
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top->copy(delta_longrange);
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delete top;
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//... inject these contributions to the next level
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LOGUSER("Allocating refinement patch");
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LOGUSER(" offset=(%5d,%5d,%5d)", refh.offset(levelmin + 1, 0), refh.offset(levelmin + 1, 1), refh.offset(levelmin + 1, 2));
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LOGUSER(" size =(%5d,%5d,%5d)", refh.size(levelmin + 1, 0), refh.size(levelmin + 1, 1), refh.size(levelmin + 1, 2));
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delta.add_patch(refh.offset(levelmin + 1, 0), refh.offset(levelmin + 1, 1), refh.offset(levelmin + 1, 2),
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refh.size(levelmin + 1, 0), refh.size(levelmin + 1, 1), refh.size(levelmin + 1, 2));
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LOGUSER("Injecting long range component");
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//mg_straight().prolong( delta_longrange, *delta.get_grid(levelmin+1) );
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//mg_cubic_mult().prolong( delta_longrange, *delta.get_grid(levelmin+1) );
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mg_cubic().prolong(delta_longrange, *delta.get_grid(levelmin + 1));
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}
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else
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{
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/**********************************************************************************************************\
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* multi-grid: intermediate sub-grids .....
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\**********************************************************************************************************/
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std::cout << " - Performing noise convolution on level " << std::setw(2) << levelmin + i << " ..." << std::endl;
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LOGUSER("Performing noise convolution on level %3d", levelmin + i);
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//... add new refinement patch
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LOGUSER("Allocating refinement patch");
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LOGUSER(" offset=(%5d,%5d,%5d)", refh.offset(levelmin + i + 1, 0), refh.offset(levelmin + i + 1, 1), refh.offset(levelmin + i + 1, 2));
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LOGUSER(" size =(%5d,%5d,%5d)", refh.size(levelmin + i + 1, 0), refh.size(levelmin + i + 1, 1), refh.size(levelmin + i + 1, 2));
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delta.add_patch(refh.offset(levelmin + i + 1, 0), refh.offset(levelmin + i + 1, 1), refh.offset(levelmin + i + 1, 2),
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refh.size(levelmin + i + 1, 0), refh.size(levelmin + i + 1, 1), refh.size(levelmin + i + 1, 2));
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//... copy coarse grid long-range component to fine grid
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LOGUSER("Injecting long range component");
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//mg_straight().prolong( *delta.get_grid(levelmin+i), *delta.get_grid(levelmin+i+1) );
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mg_cubic().prolong(*delta.get_grid(levelmin + i), *delta.get_grid(levelmin + i + 1));
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PaddedDensitySubGrid<real_t> coarse_save(*coarse);
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the_tf_kernel->fetch_kernel(levelmin + i);
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//... 1) the inner region
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LOGUSER("Computing density self-contribution");
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coarse->subtract_boundary_oct_mean();
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convolution::perform<real_t>(the_tf_kernel, reinterpret_cast<void *>(coarse->get_data_ptr()), shift, fix, flip);
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coarse->copy_add_unpad(*delta.get_grid(levelmin + i));
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//... 2) the 'BC' for the next finer grid
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LOGUSER("Computing long-range component for finer grid.");
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*coarse = coarse_save;
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coarse->subtract_boundary_oct_mean();
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coarse->zero_subgrid(refh.offset(levelmin + i + 1, 0), refh.offset(levelmin + i + 1, 1), refh.offset(levelmin + i + 1, 2),
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refh.size(levelmin + i + 1, 0) / 2, refh.size(levelmin + i + 1, 1) / 2, refh.size(levelmin + i + 1, 2) / 2);
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convolution::perform<real_t>(the_tf_kernel, reinterpret_cast<void *>(coarse->get_data_ptr()), shift, fix, flip);
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//... interpolate to finer grid(s)
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meshvar_bnd delta_longrange(*delta.get_grid(levelmin + i));
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coarse->copy_unpad(delta_longrange);
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LOGUSER("Injecting long range component");
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//mg_straight().prolong_add( delta_longrange, *delta.get_grid(levelmin+i+1) );
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mg_cubic().prolong_add(delta_longrange, *delta.get_grid(levelmin + i + 1));
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//... 3) the coarse-grid correction
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LOGUSER("Computing coarse grid correction");
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*coarse = coarse_save;
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coarse->subtract_oct_mean();
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convolution::perform<real_t>(the_tf_kernel, reinterpret_cast<void *>(coarse->get_data_ptr()), shift, fix, flip);
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coarse->subtract_mean();
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coarse->upload_bnd_add(*delta.get_grid(levelmin + i - 1));
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//... clean up
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the_tf_kernel->deallocate();
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delete coarse;
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}
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coarse = fine;
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}
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//... and convolution for finest grid (outside loop)
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if (levelmax > levelmin)
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{
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/**********************************************************************************************************\
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* multi-grid: finest sub-grid .....
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\**********************************************************************************************************/
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std::cout << " - Performing noise convolution on level " << std::setw(2) << levelmax << " ..." << std::endl;
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LOGUSER("Performing noise convolution on level %3d", levelmax);
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//... 1) grid self-contribution
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LOGUSER("Computing density self-contribution");
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PaddedDensitySubGrid<real_t> coarse_save(*coarse);
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//... create convolution kernel
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the_tf_kernel->fetch_kernel(levelmax);
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//... subtract oct mean on boundary but not in interior
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coarse->subtract_boundary_oct_mean();
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//... perform convolution
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convolution::perform<real_t>(the_tf_kernel, reinterpret_cast<void *>(coarse->get_data_ptr()), shift, fix, flip);
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//... copy to grid hierarchy
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coarse->copy_add_unpad(*delta.get_grid(levelmax));
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//... 2) boundary correction to top grid
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LOGUSER("Computing coarse grid correction");
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*coarse = coarse_save;
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//... subtract oct mean
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coarse->subtract_oct_mean();
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//... perform convolution
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convolution::perform<real_t>(the_tf_kernel, reinterpret_cast<void *>(coarse->get_data_ptr()), shift, fix, flip);
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the_tf_kernel->deallocate();
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coarse->subtract_mean();
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//... upload data to coarser grid
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coarse->upload_bnd_add(*delta.get_grid(levelmax - 1));
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delete coarse;
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}
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}
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delete the_tf_kernel;
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1117
src/densities.hh
1117
src/densities.hh
File diff suppressed because it is too large
Load diff
2552
src/mesh.hh
2552
src/mesh.hh
File diff suppressed because it is too large
Load diff
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