Add Linux specific options to compile

.clang-uml

@@ -1,19 +1,31 @@
 compilation_database_dir: build
 output_directory: puml
 diagrams:
-  myproject_class:
+  BayesNet:
     type: class
     glob:
-      - src/bayesnet/*.cc
+      - src/BayesNet/*.cc
-      - src/platform/*.cc
+      - src/Platform/*.cc
     using_namespace: bayesnet
     include:
       namespaces:
         - bayesnet
         - platform
-    exclude:
-      namespaces:
-        - myproject::detail
     plantuml:
       after:
-        - 'note left of {{ alias("MyProjectMain") }}: Main class of myproject library.'
+        - "note left of {{ alias(\"MyProjectMain\") }}: Main class of myproject library."
+  sequence:
+    type: sequence
+    glob:
+      - src/Platform/main.cc
+    combine_free_functions_into_file_participants: true
+    using_namespace:
+      - std
+      - bayesnet
+      - platform
+    include:
+      paths:
+        - src/BayesNet
+        - src/Platform
+    start_from:
+      - function: main(int,const char **)

.gitignore

@@ -35,3 +35,4 @@ build/
 *.dSYM/**
 cmake-build*/**
 .idea
+puml/**

CMakeLists.txt

@@ -30,7 +30,7 @@ set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${TORCH_CXX_FLAGS}")
 option(ENABLE_CLANG_TIDY "Enable to add clang tidy."              OFF)
 option(ENABLE_TESTING "Unit testing build"                        OFF)
 option(CODE_COVERAGE "Collect coverage from test library"         OFF)
-
+SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pthread")
 # CMakes modules
 # --------------
 set(CMAKE_MODULE_PATH ${CMAKE_CURRENT_SOURCE_DIR}/cmake/modules ${CMAKE_MODULE_PATH})

Makefile

@@ -32,6 +32,9 @@ clean: ## Clean the debug info
 	find . -name "*.gcda" -print0 | xargs -0 rm
 	@echo ">>> Done";
 
+clang-uml: ## Create uml class and sequence diagrams
+	clang-uml -p --add-compile-flag -I /usr/lib/gcc/x86_64-redhat-linux/8/include/
+
 debug: ## Build a debug version of the project
 	@echo ">>> Building Debug BayesNet ...";
 	@if [ -d ./build ]; then rm -rf ./build; fi

TAN_iris.dot

@@ -1,12 +0,0 @@
-digraph BayesNet {
-label=<BayesNet >
-fontsize=30
-fontcolor=blue
-labelloc=t
-layout=circo
- class [shape=circle, fontcolor=red, fillcolor=lightblue, style=filled ] 
- class -> sepallength class -> sepalwidth class -> petallength class -> petalwidth petallength [shape=circle] 
- petallength -> sepallength petalwidth [shape=circle] 
- sepallength [shape=circle] 
- sepallength -> sepalwidth sepalwidth [shape=circle] 
- sepalwidth -> petalwidth }

sample/sample.cc

@@ -10,7 +10,7 @@
 #include "Folding.h"
 #include "Models.h"
 #include "modelRegister.h"
-
+#include <fstream>
 
 using namespace std;
 
@@ -195,11 +195,11 @@ int main(int argc, char** argv)
         Xt.index_put_({ i, "..." }, torch::tensor(Xd[i], torch::kInt32));
     }
     float total_score = 0, total_score_train = 0, score_train, score_test;
-    Fold* fold;
+    platform::Fold* fold;
     if (stratified)
-        fold = new StratifiedKFold(nFolds, y, seed);
+        fold = new platform::StratifiedKFold(nFolds, y, seed);
     else
-        fold = new KFold(nFolds, y.size(), seed);
+        fold = new platform::KFold(nFolds, y.size(), seed);
     for (auto i = 0; i < nFolds; ++i) {
         auto [train, test] = fold->getFold(i);
         cout << "Fold: " << i + 1 << endl;

src/Platform/Datasets.cc

@@ -1,6 +1,7 @@
 #include "Datasets.h"
 #include "platformUtils.h"
 #include "ArffFiles.h"
+#include <fstream>
 namespace platform {
     void Datasets::load()
     {

src/Platform/Experiment.cc

@@ -2,7 +2,7 @@
 #include "Datasets.h"
 #include "Models.h"
 #include "ReportConsole.h"
-
+#include <fstream>
 namespace platform {
     using json = nlohmann::json;
     string get_date()

src/Platform/Folding.cc

@@ -1,19 +1,20 @@
 #include "Folding.h"
 #include <algorithm>
 #include <map>
-Fold::Fold(int k, int n, int seed) : k(k), n(n), seed(seed)
+namespace platform {
-{
+    Fold::Fold(int k, int n, int seed) : k(k), n(n), seed(seed)
+    {
         random_device rd;
         random_seed = default_random_engine(seed == -1 ? rd() : seed);
         srand(seed == -1 ? time(0) : seed);
-}
+    }
-KFold::KFold(int k, int n, int seed) : Fold(k, n, seed), indices(vector<int>(n))
+    KFold::KFold(int k, int n, int seed) : Fold(k, n, seed), indices(vector<int>(n))
-{
+    {
         iota(begin(indices), end(indices), 0); // fill with 0, 1, ..., n - 1
         shuffle(indices.begin(), indices.end(), random_seed);
-}
+    }
-pair<vector<int>, vector<int>> KFold::getFold(int nFold)
+    pair<vector<int>, vector<int>> KFold::getFold(int nFold)
-{
+    {
         if (nFold >= k || nFold < 0) {
             throw out_of_range("nFold (" + to_string(nFold) + ") must be less than k (" + to_string(k) + ")");
         }
@@ -28,22 +29,22 @@ pair<vector<int>, vector<int>> KFold::getFold(int nFold)
             }
         }
         return { train, test };
-}
+    }
-StratifiedKFold::StratifiedKFold(int k, torch::Tensor& y, int seed) : Fold(k, y.numel(), seed)
+    StratifiedKFold::StratifiedKFold(int k, torch::Tensor& y, int seed) : Fold(k, y.numel(), seed)
-{
+    {
         n = y.numel();
         this->y = vector<int>(y.data_ptr<int>(), y.data_ptr<int>() + n);
         build();
-}
+    }
-StratifiedKFold::StratifiedKFold(int k, const vector<int>& y, int seed)
+    StratifiedKFold::StratifiedKFold(int k, const vector<int>& y, int seed)
         : Fold(k, y.size(), seed)
-{
+    {
         this->y = y;
         n = y.size();
         build();
-}
+    }
-void StratifiedKFold::build()
+    void StratifiedKFold::build()
-{
+    {
         stratified_indices = vector<vector<int>>(k);
         int fold_size = n / k;
         // Compute class counts and indices
@@ -79,9 +80,9 @@ void StratifiedKFold::build()
                 remainder_samples_to_take--;
             }
         }
-}
+    }
-pair<vector<int>, vector<int>> StratifiedKFold::getFold(int nFold)
+    pair<vector<int>, vector<int>> StratifiedKFold::getFold(int nFold)
-{
+    {
         if (nFold >= k || nFold < 0) {
             throw out_of_range("nFold (" + to_string(nFold) + ") must be less than k (" + to_string(k) + ")");
         }
@@ -92,4 +93,5 @@ pair<vector<int>, vector<int>> StratifiedKFold::getFold(int nFold)
             train_indices.insert(train_indices.end(), stratified_indices[i].begin(), stratified_indices[i].end());
         }
         return { train_indices, test_indices };
+    }
 }

src/Platform/Folding.h

@@ -4,34 +4,35 @@
 #include <vector>
 #include <random> 
 using namespace std;
-
+namespace platform {
-class Fold {
+    class Fold {
-protected:
+    protected:
         int k;
         int n;
         int seed;
         default_random_engine random_seed;
-public:
+    public:
         Fold(int k, int n, int seed = -1);
         virtual pair<vector<int>, vector<int>> getFold(int nFold) = 0;
         virtual ~Fold() = default;
         int getNumberOfFolds() { return k; }
-};
+    };
-class KFold : public Fold {
+    class KFold : public Fold {
-private:
+    private:
         vector<int> indices;
-public:
+    public:
         KFold(int k, int n, int seed = -1);
         pair<vector<int>, vector<int>> getFold(int nFold) override;
-};
+    };
-class StratifiedKFold : public Fold {
+    class StratifiedKFold : public Fold {
-private:
+    private:
         vector<int> y;
         vector<vector<int>> stratified_indices;
         void build();
-public:
+    public:
         StratifiedKFold(int k, const vector<int>& y, int seed = -1);
         StratifiedKFold(int k, torch::Tensor& y, int seed = -1);
         pair<vector<int>, vector<int>> getFold(int nFold) override;
-};
+    };
+}
 #endif