[topoAEpp] explicit yet concise(r) class names

Author: julien-tierny

core/base/dimensionReduction/CMakeLists.txt

@@ -6,7 +6,7 @@ ttk_add_base_library(dimensionReduction
   DEPENDS
     triangulation
     topoMap
-    topologicallyConstrainedDimensionReduction
+    topologicalDimensionReduction
   )
 
 install(

core/base/dimensionReduction/DimensionReduction.cpp

@@ -77,7 +77,7 @@ int DimensionReduction::execute(
 
   if(this->Method == METHOD::AE) {
 #ifdef TTK_ENABLE_TORCH
-    TopologicallyConstrainedDimensionalityReduction tcdr(
+    TopologicalDimensionReduction tcdr(
       ae_CUDA, ae_Deterministic, ae_Seed, NumberOfComponents, ae_Epochs,
       ae_LearningRate, ae_Optimizer, ae_Method, ae_Model, ae_Architecture,
       ae_Activation, ae_BatchSize, ae_BatchNormalization, ae_RegCoefficient,

core/base/dimensionReduction/DimensionReduction.h

@@ -73,7 +73,7 @@
 
 #include <Debug.h>
 #include <TopoMap.h>
-#include <TopologicallyConstrainedDimensionReduction.h>
+#include <TopologicalDimensionReduction.h>
 
 namespace ttk {
 
@@ -353,13 +353,12 @@ namespace ttk {
     int ae_Seed{0};
     int ae_Epochs{1000};
     double ae_LearningRate{1e-2};
-    TopologicallyConstrainedDimensionalityReduction::OPTIMIZER ae_Optimizer{
-      TopologicallyConstrainedDimensionalityReduction::OPTIMIZER::ADAM};
-    TopologicallyConstrainedDimensionalityReduction::REGUL ae_Method{
-      TopologicallyConstrainedDimensionalityReduction::REGUL::
-        ASYMMETRIC_CASCADE};
-    TopologicallyConstrainedDimensionalityReduction::MODEL ae_Model{
-      TopologicallyConstrainedDimensionalityReduction::MODEL::AUTOENCODER};
+    TopologicalDimensionReduction::OPTIMIZER ae_Optimizer{
+      TopologicalDimensionReduction::OPTIMIZER::ADAM};
+    TopologicalDimensionReduction::REGUL ae_Method{
+      TopologicalDimensionReduction::REGUL::ASYMMETRIC_CASCADE};
+    TopologicalDimensionReduction::MODEL ae_Model{
+      TopologicalDimensionReduction::MODEL::AUTOENCODER};
     std::string ae_Architecture{"32 32"};
     std::string ae_Activation{"ReLU"};
     int ae_BatchSize{0};

core/base/topologicalDimensionReduction/CMakeLists.txt

@@ -0,0 +1,18 @@
+ttk_add_base_library(topologicalDimensionReduction 
+  SOURCES
+    DimensionReductionModel.cpp 
+    TopologicalLoss.cpp 
+    TopologicalDimensionReduction.cpp 
+  HEADERS 
+    DimensionReductionModel.h 
+    TopologicalLoss.h 
+    TopologicalDimensionReduction.h 
+  DEPENDS
+    persistenceDiagramWarmRestartAuction 
+    ripsPersistenceDiagram)
+
+if(TTK_ENABLE_TORCH)
+target_link_libraries(topologicalDimensionReduction PUBLIC "${TORCH_LIBRARIES}")
+target_include_directories(topologicalDimensionReduction PUBLIC ${TORCH_INCLUDE_DIRS})
+target_compile_definitions(topologicalDimensionReduction PUBLIC TTK_ENABLE_TORCH) 
+endif()

…ionReduction/DimensionReductionModel.cpp …ionReduction/DimensionReductionModel.cppcore/base/topologicallyConstrainedDimensionReduction/DimensionReductionModel.cpp renamed to core/base/topologicalDimensionReduction/DimensionReductionModel.cpp core/base/topologicallyConstrainedDimensionReduction/DimensionReductionModel.cpp renamed to core/base/topologicalDimensionReduction/DimensionReductionModel.cpp

@@ -13,7 +13,7 @@
 /// DirectOptimization
 /// ConvolutionalAutoEncoder
 ///
-/// \sa TopologicallyConstrainedDimensionReduction.cpp %for a usage example.
+/// \sa TopologicalDimensionReduction.cpp %for a usage example.
 
 #pragma once
 
@@ -153,4 +153,4 @@ namespace ttk {
 
 } // namespace ttk
 
-#endif
+#endif

…nsionReduction/DimensionReductionModel.h …nsionReduction/DimensionReductionModel.hcore/base/topologicallyConstrainedDimensionReduction/DimensionReductionModel.h renamed to core/base/topologicalDimensionReduction/DimensionReductionModel.h core/base/topologicallyConstrainedDimensionReduction/DimensionReductionModel.h renamed to core/base/topologicalDimensionReduction/DimensionReductionModel.h

@@ -1,33 +1,32 @@
-#include <TopologicallyConstrainedDimensionReduction.h>
+#include <TopologicalDimensionReduction.h>
 
 #ifdef TTK_ENABLE_TORCH
 
 using namespace torch::indexing;
 
-ttk::TopologicallyConstrainedDimensionalityReduction::
-  TopologicallyConstrainedDimensionalityReduction(
-    bool useCUDA,
-    bool deterministic,
-    int seed,
-    int numberOfComponents,
-    int epochs,
-    double learningRate,
-    OPTIMIZER optimizer,
-    REGUL method,
-    MODEL modelType,
-    const std::string &architecture,
-    const std::string &activation,
-    int batchSize,
-    bool batchNormalization,
-    double regCoefficient,
-    bool inputIsImages)
+ttk::TopologicalDimensionReduction::TopologicalDimensionReduction(
+  bool useCUDA,
+  bool deterministic,
+  int seed,
+  int numberOfComponents,
+  int epochs,
+  double learningRate,
+  OPTIMIZER optimizer,
+  REGUL method,
+  MODEL modelType,
+  const std::string &architecture,
+  const std::string &activation,
+  int batchSize,
+  bool batchNormalization,
+  double regCoefficient,
+  bool inputIsImages)
   : NumberOfComponents(numberOfComponents), Epochs(epochs),
     LearningRate(learningRate), Optimizer(optimizer), Method(method),
     ModelType(modelType), InputIsImages(inputIsImages),
     Architecture(architecture), Activation(activation), BatchSize(batchSize),
     BatchNormalization(batchNormalization), RegCoefficient(regCoefficient) {
   // inherited from Debug: prefix will be printed at the beginning of every msg
-  this->setDebugMsgPrefix("TopologicallyConstrainedDimensionalityReduction");
+  this->setDebugMsgPrefix("TopologicalDimensionReduction");
 
   if(torch::cuda::is_available() && useCUDA && !deterministic)
     device = torch::kCUDA;
@@ -42,8 +41,8 @@ ttk::TopologicallyConstrainedDimensionalityReduction::
   }
 }
 
-int ttk::TopologicallyConstrainedDimensionalityReduction::initializeModel(
-  int inputSize, int inputDimension) {
+int ttk::TopologicalDimensionReduction::initializeModel(int inputSize,
+                                                        int inputDimension) {
   if((!InputIsImages && !AutoEncoder::isStringValid(Architecture))
      || (InputIsImages
          && !ConvolutionalAutoEncoder::isStringValid(Architecture))) {
@@ -69,8 +68,7 @@ int ttk::TopologicallyConstrainedDimensionalityReduction::initializeModel(
   return 0;
 }
 
-void ttk::TopologicallyConstrainedDimensionalityReduction::
-  initializeOptimizer() {
+void ttk::TopologicalDimensionReduction::initializeOptimizer() {
   if(Optimizer == OPTIMIZER::ADAM)
     torchOptimizer = std::make_unique<torch::optim::Adam>(
       model->parameters(), /*lr=*/LearningRate);
@@ -82,7 +80,7 @@ void ttk::TopologicallyConstrainedDimensionalityReduction::
       model->parameters(), /*lr=*/LearningRate);
 }
 
-int ttk::TopologicallyConstrainedDimensionalityReduction::execute(
+int ttk::TopologicalDimensionReduction::execute(
   std::vector<std::vector<double>> &outputEmbedding,
   const std::vector<double> &inputMatrix,
   size_t n) {
@@ -150,9 +148,8 @@ int ttk::TopologicallyConstrainedDimensionalityReduction::execute(
   return 0;
 }
 
-void ttk::TopologicallyConstrainedDimensionalityReduction::
-  setLatentInitialization(
-    std::vector<std::vector<double>> const &latentInitialization) {
+void ttk::TopologicalDimensionReduction::setLatentInitialization(
+  std::vector<std::vector<double>> const &latentInitialization) {
   std::vector<torch::Tensor> tensors;
   for(auto const &column : latentInitialization)
     tensors.push_back(torch::from_blob(const_cast<double *>(column.data()),
@@ -163,7 +160,7 @@ void ttk::TopologicallyConstrainedDimensionalityReduction::
   latentInitialization_ = torch::stack(tensors).transpose(0, 1);
 }
 
-void ttk::TopologicallyConstrainedDimensionalityReduction::optimizeSimple(
+void ttk::TopologicalDimensionReduction::optimizeSimple(
   const torch::Tensor &input) const {
   int epoch = 0;
 
@@ -192,7 +189,7 @@ void ttk::TopologicallyConstrainedDimensionalityReduction::optimizeSimple(
     torchOptimizer->step(closure);
 }
 
-void ttk::TopologicallyConstrainedDimensionalityReduction::optimize(
+void ttk::TopologicalDimensionReduction::optimize(
   const torch::Tensor &input) const {
   int epoch = 0;
 
@@ -219,7 +216,7 @@ void ttk::TopologicallyConstrainedDimensionalityReduction::optimize(
     torchOptimizer->step(closure);
 }
 
-void ttk::TopologicallyConstrainedDimensionalityReduction::preOptimize(
+void ttk::TopologicalDimensionReduction::preOptimize(
   const torch::Tensor &input, const torch::Tensor &target) const {
   int epoch = 0;
 
@@ -244,8 +241,8 @@ void ttk::TopologicallyConstrainedDimensionalityReduction::preOptimize(
     torchOptimizer->step(closure);
 }
 
-void ttk::TopologicallyConstrainedDimensionalityReduction::printLoss(
-  int epoch, double loss) const {
+void ttk::TopologicalDimensionReduction::printLoss(int epoch,
+                                                   double loss) const {
   if(epoch % std::max(1, Epochs / 10) == 0)
     printMsg(
       "Loss at epoch " + std::to_string(epoch) + " : " + std::to_string(loss),

…gicallyConstrainedDimensionReduction.cpp …uction/TopologicalDimensionReduction.cppcore/base/topologicallyConstrainedDimensionReduction/TopologicallyConstrainedDimensionReduction.cpp renamed to core/base/topologicalDimensionReduction/TopologicalDimensionReduction.cpp core/base/topologicallyConstrainedDimensionReduction/TopologicallyConstrainedDimensionReduction.cpp renamed to core/base/topologicalDimensionReduction/TopologicalDimensionReduction.cpp

@@ -1,12 +1,12 @@
 /// \ingroup base
-/// \class ttk::TopologicallyConstrainedDimensionalityReduction
+/// \class ttk::TopologicalDimensionReduction
 /// \author Mattéo Clémot <matteo.clemot@univ-lyon1.fr>
 /// \date 2024.
 ///
 /// \brief TTK base class that embeds points into 2D, under topological
 /// constraints
 ///
-/// This module defines the %TopologicallyConstrainedDimensionalityReduction
+/// This module defines the %TopologicalDimensionReduction
 /// class that serves as a backend for the DimensionReduction module. It embeds
 /// high-dimensional point clouds into 2D, under topological constraints, with
 /// an autoencoder-based approach.
@@ -46,12 +46,12 @@
 namespace ttk {
 
   /**
-   * The TopologicallyConstrainedDimensionalityReduction class provides a
+   * The TopologicalDimensionReduction class provides a
    * backend for dimension reduction using autoencoders, with possible
    * constraints on the preservation of the topology of the input high
    * dimensional point cloud when projecting in low dimension
    */
-  class TopologicallyConstrainedDimensionalityReduction : virtual public Debug {
+  class TopologicalDimensionReduction : virtual public Debug {
 
   public:
     enum class OPTIMIZER : std::uint8_t {
@@ -76,22 +76,21 @@ namespace ttk {
 
 #ifdef TTK_ENABLE_TORCH
 
-    TopologicallyConstrainedDimensionalityReduction(
-      bool useCUDA,
-      bool deterministic,
-      int seed,
-      int numberOfComponents,
-      int epochs,
-      double learningRate,
-      OPTIMIZER optimizer,
-      REGUL method,
-      MODEL modelType,
-      const std::string &architecture,
-      const std::string &activation,
-      int batchSize,
-      bool batchNormalization,
-      double regCoefficient,
-      bool inputIsImages);
+    TopologicalDimensionReduction(bool useCUDA,
+                                  bool deterministic,
+                                  int seed,
+                                  int numberOfComponents,
+                                  int epochs,
+                                  double learningRate,
+                                  OPTIMIZER optimizer,
+                                  REGUL method,
+                                  MODEL modelType,
+                                  const std::string &architecture,
+                                  const std::string &activation,
+                                  int batchSize,
+                                  bool batchNormalization,
+                                  double regCoefficient,
+                                  bool inputIsImages);
 
     /**
      * @brief Computes the projection with an AutoEncoder
@@ -145,6 +144,6 @@ namespace ttk {
 
 #endif
 
-  }; // TopologicallyConstrainedDimensionalityReduction class
+  }; // TopologicalDimensionReduction class
 
 } // namespace ttk

…logicallyConstrainedDimensionReduction.h …eduction/TopologicalDimensionReduction.hcore/base/topologicallyConstrainedDimensionReduction/TopologicallyConstrainedDimensionReduction.h renamed to core/base/topologicalDimensionReduction/TopologicalDimensionReduction.h core/base/topologicallyConstrainedDimensionReduction/TopologicallyConstrainedDimensionReduction.h renamed to core/base/topologicalDimensionReduction/TopologicalDimensionReduction.h

@@ -16,7 +16,7 @@
 /// (4) : asymmetric cascade-extended "Topological Autoencoder" loss
 /// (5) : Wasserstein distance between 1-dimensional persistence diagrams
 ///
-/// \sa TopologicallyConstrainedDimensionReduction.cpp %for a usage example.
+/// \sa TopologicalDimensionReduction.cpp %for a usage example.
 
 #pragma once
 
@@ -112,4 +112,4 @@ namespace ttk {
 
 #endif
   };
-} // namespace ttk
+} // namespace ttk