Merge branch 'new_radiation_test_cases' of https://github.com/CSMMLab…

…/KiT-RT into new_radiation_test_cases
KiT-RT · Jan 2, 2024 · bc40e88 · bc40e88
2 parents 1ead3a1 + 45fafdb
commit bc40e88
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Showing 4 changed files with 12 additions and 10 deletions.
diff --git a/src/common/io.cpp b/src/common/io.cpp
@@ -296,7 +296,7 @@ Mesh* LoadSU2MeshFromFile( const Config* settings ) {
         ErrorMessages::Error( "Cannot open mesh file '" + settings->GetMeshFile() + "!", CURRENT_FUNCTION );
     }
     ifs.close();
-    // log->info( "| Mesh imported." );
+    log->info( "| Mesh imported." );
     return new Mesh( nodes, cells, boundaries );
 }
 

diff --git a/src/common/mesh.cpp b/src/common/mesh.cpp
@@ -168,6 +168,7 @@ void Mesh::ComputeConnectivity() {
 
     // assign boundary types to all cells
     _cellBoundaryTypes.resize( _numCells, BOUNDARY_TYPE::NONE );
+#pragma omp parallel for
     for( unsigned i = 0; i < _numCells; ++i ) {
         if( std::any_of( _cellNeighbors[i].begin(), _cellNeighbors[i].end(), [this]( unsigned i ) {
                 return i == _ghostCellID;

diff --git a/src/optimizers/neuralnetworkoptimizer.cpp b/src/optimizers/neuralnetworkoptimizer.cpp
@@ -70,20 +70,19 @@ NeuralNetworkOptimizer::NeuralNetworkOptimizer( Config* settings ) : OptimizerBa
     _tfModel             = new cppflow::model( tfModelPath );    // load model
     unsigned servingSize = _settings->GetNCells();
     if( _settings->GetEnforceNeuralRotationalSymmetry() ) {
-        if( _settings->GetMaxMomentDegree() > 2 ) {
+        if( _settings->GetMaxMomentDegree() > 3 ) {
             ErrorMessages::Error( "This postprocessing step is currently only for M1 and M2 models available.", CURRENT_FUNCTION );
         }
         servingSize *= 2;    // Double number of vectors, since we mirror the rotated vector
         _rotationMats.resize( _settings->GetNCells() );
         _rotationMatsT.resize( _settings->GetNCells() );
     }
 
-    if (_settings->GetMaxMomentDegree() == 1 && _settings->GetDim() ==2 && _settings->GetEnforceNeuralRotationalSymmetry()){
+    if( _settings->GetMaxMomentDegree() == 1 && _settings->GetDim() == 2 && _settings->GetEnforceNeuralRotationalSymmetry() ) {
         _modelServingVectorU.resize( servingSize * ( _nSystem - 2 ) );    // reserve size for model servitor
     }
-    else
-    {
-    _modelServingVectorU.resize( servingSize * ( _nSystem - 1 ) );    // reserve size for model servitor
+    else {
+        _modelServingVectorU.resize( servingSize * ( _nSystem - 1 ) );    // reserve size for model servitor
     }
     // Specify model input name
     // Call Model (change call depending on model mk) (Seems to be randomly assigned by tensorflow)
@@ -367,7 +366,7 @@ void NeuralNetworkOptimizer::InferenceMonomial( VectorVector& alpha, const Vecto
         }
         servingSize *= 2;
     }
-    else {    // No Preprocessing
+    else {    // No Postprocessing
 #pragma omp parallel for
         for( unsigned idx_cell = 0; idx_cell < _settings->GetNCells(); idx_cell++ ) {
             for( unsigned idx_sys = 0; idx_sys < _nSystem - 1; idx_sys++ ) {
@@ -402,6 +401,7 @@ void NeuralNetworkOptimizer::InferenceMonomial( VectorVector& alpha, const Vecto
                     // Mirror order 1 Moments
                     alphaRedMirror[idx_sys] =
                         -1 * (double)_modelServingVectorAlpha[( _settings->GetNCells() + idx_cell ) * ( _nSystem - 1 ) + idx_sys];
+
                     alphaRed[idx_sys] = ( alphaRed[idx_sys] + alphaRedMirror[idx_sys] ) / 2;    // average (and store in alphaRed)
                     // alphaCorr[idx_sys+1] = alphaRed[idx_sys];
                 }
@@ -460,6 +460,7 @@ void NeuralNetworkOptimizer::InferenceMonomial( VectorVector& alpha, const Vecto
                     }
                     alphaRed[idx_sys] = ( alphaRed[idx_sys] + alphaRedMirror[idx_sys] ) / 2;    // average (and store in alphaRed)
                 }
+                alpha_norms[idx_cell] = norm( alphaRed ) * norm( alphaRed );
 
                 // Rotate Back
                 Vector alpha1{ alphaRed[0], alphaRed[1] };
@@ -594,7 +595,7 @@ void NeuralNetworkOptimizer::InferenceSphericalHarmonics2D( VectorVector& alpha,
             Vector alphaTempFull   = Vector( _nSystem, 0.0 );    // local reduced mirrored alpha (with dummy entry at 0)
             Vector alphaTempMirror = Vector( _nSystem, 0.0 );    // local reduced mirrored alpha (with dummy entry at 0)
 
-            if( _settings->GetMaxMomentDegree() == 1 ) {         // Using this
+            if( _settings->GetMaxMomentDegree() == 1 ) {    // Using this
                 for( unsigned idx_sys = 0; idx_sys < _nSystem - 2; idx_sys++ ) {
                     alphaTempFull[idx_sys + 1] = (double)_modelServingVectorAlpha[idx_cell * ( _nSystem - 2 ) + idx_sys];
                     alphaTempMirror[idx_sys + 1] =
@@ -754,7 +755,7 @@ void NeuralNetworkOptimizer::InferenceSphericalHarmonics( VectorVector& alpha,
                 alpha_P_Mirror[idx_sys + 1] = (double)_modelServingVectorAlpha[( _settings->GetNCells() + idx_cell ) * ( _nSystem - 1 ) + idx_sys];
             }
             alpha_P_Mirror  = rot180 * alpha_P_Mirror;
-            alpha[idx_cell] = ( alphaP + alpha_P_Mirror ) / 2;               // average (and store in alpha)
+            alpha[idx_cell] = ( alphaP + alpha_P_Mirror ) / 2;    // average (and store in alpha)
 
             alpha[idx_cell] = _rotationMatsT[idx_cell] * alpha[idx_cell];    // Rotate back
             // alpha[idx_cell][2] = 0.0;    //manually enforce slab geometry

diff --git a/tools/docker/docker_run_interactive_specify_cores.sh b/tools/docker/docker_run_interactive_specify_cores.sh
@@ -1 +1 @@
-docker run -i -t --rm --cpuset-cpus=0-12 -v $(pwd)/../..:/mnt kitrt/test_ml:latest /bin/bash  
+docker run -i -t --rm --cpuset-cpus=0-23 -v $(pwd)/../..:/mnt kitrt/test_ml:latest /bin/bash
Original file line number	Diff line number	Diff line change
		@@ -1 +1 @@
		docker run -i -t --rm --cpuset-cpus=0-12 -v $(pwd)/../..:/mnt kitrt/test_ml:latest /bin/bash
		docker run -i -t --rm --cpuset-cpus=0-23 -v $(pwd)/../..:/mnt kitrt/test_ml:latest /bin/bash