Add constant references to Statistics

src/Platform/BestResults.cc

@@ -282,12 +282,15 @@ namespace platform {
         // Print the table of results
         printTableResults(models, table);
         // Compute the Friedman test
+        map<string, map<string, float>> ranksModels;
         if (friedman) {
             Statistics stats(models, datasets, table, significance);
             auto result = stats.friedmanTest();
             stats.postHocHolmTest(result);
+            ranksModels = stats.getRanks();
         }
         if (excel) {
+            // BestResultsExcel excel(score, models, datasets, ranksModels, table, friedman, significance);
             BestResultsExcel excel(score, models, datasets, table, friedman, significance);
             excel.build();
             cout << Colors::YELLOW() << "** Excel file generated: " << excel.getFileName() << Colors::RESET() << endl;

src/Platform/BestResultsExcel.cc

@@ -4,7 +4,8 @@
 #include "Statistics.h"
 
 namespace platform {
-    BestResultsExcel::BestResultsExcel(string score, vector<string> models, vector<string> datasets, json table, bool friedman, double significance) : score(score), models(models), datasets(datasets), table(table), friedman(friedman), significance(significance)
+    BestResultsExcel::BestResultsExcel(const string& score, const vector<string>& models, const vector<string>& datasets, const json& table, bool friedman, double significance) :
+        score(score), models(models), datasets(datasets), table(table), friedman(friedman), significance(significance)
     {
         workbook = workbook_new((Paths::excel() + fileName).c_str());
         worksheet = workbook_add_worksheet(workbook, "Best Results");

src/Platform/BestResultsExcel.h

@@ -2,6 +2,7 @@
 #define BESTRESULTS_EXCEL_H
 #include "ExcelFile.h"
 #include <vector>
+#include <map>
 #include <nlohmann/json.hpp>
 
 using namespace std;
@@ -11,7 +12,7 @@ namespace platform {
 
     class BestResultsExcel : ExcelFile {
     public:
-        BestResultsExcel(string score, vector<string> models, vector<string> datasets, json table, bool friedman, double significance);
+        BestResultsExcel(const string& score, const vector<string>& models, const vector<string>& datasets, const json& table, bool friedman, double significance);
         ~BestResultsExcel();
         void build();
         string getFileName();
@@ -21,14 +22,15 @@ namespace platform {
         void footer();
         void formatColumns();
         const string fileName = "BestResults.xlsx";
-        string score;
-        vector<string> models;
-        vector<string> datasets;
-        json table;
+        const string& score;
+        const vector<string>& models;
+        const vector<string>& datasets;
+        const json& table;
         bool friedman;
         double significance;
         int modelNameSize = 12; // Min size of the column
         int datasetNameSize = 25; // Min size of the column
+        // map<string, map<string, float>>& ranksModels;
     };
 }
 #endif //BESTRESULTS_EXCEL_H

src/Platform/Statistics.cc

@@ -7,7 +7,7 @@
 
 namespace platform {
 
-    Statistics::Statistics(vector<string>& models, vector<string>& datasets, json data, double significance, bool output) :
+    Statistics::Statistics(const vector<string>& models, const vector<string>& datasets, const json& data, double significance, bool output) :
         models(models), datasets(datasets), data(data), significance(significance), output(output)
     {
         nModels = models.size();
@@ -21,6 +21,7 @@ namespace platform {
             cerr << "nDatasets: " << nDatasets << endl;
             throw runtime_error("Can't make the Friedman test with less than 3 models and/or less than 3 datasets.");
         }
+        ranksModels.clear();
         computeRanks();
         // Set the control model as the one with the lowest average rank
         controlIdx = distance(ranks.begin(), min_element(ranks.begin(), ranks.end(), [](const auto& l, const auto& r) { return l.second < r.second; }));
@@ -68,6 +69,8 @@ namespace platform {
             }
             // Assign the ranks
             ranksLine = assignRanks(ranksOrder);
+            // Store the ranks of the dataset
+            ranksModels[dataset] = ranksLine;
             if (ranks.size() == 0) {
                 ranks = ranksLine;
             } else {
@@ -239,4 +242,8 @@ namespace platform {
     {
         return holmResult;
     }
+    map<string, map<string, float>>& Statistics::getRanks()
+    {
+        return ranksModels;
+    }
 } // namespace platform

src/Platform/Statistics.h

@@ -2,6 +2,7 @@
 #define STATISTICS_H
 #include <iostream>
 #include <vector>
+#include <map>
 #include <nlohmann/json.hpp>
 
 using namespace std;
@@ -32,18 +33,19 @@ namespace platform {
     };
     class Statistics {
     public:
-        Statistics(vector<string>& models, vector<string>& datasets, json data, double significance = 0.05, bool output = true);
+        Statistics(const vector<string>& models, const vector<string>& datasets, const json& data, double significance = 0.05, bool output = true);
         bool friedmanTest();
         void postHocHolmTest(bool friedmanResult);
         FriedmanResult& getFriedmanResult();
         HolmResult& getHolmResult();
+        map<string, map<string, float>>& getRanks();
     private:
         void fit();
         void computeRanks();
         void computeWTL();
-        vector<string> models;
-        vector<string> datasets;
-        json data;
+        const vector<string>& models;
+        const vector<string>& datasets;
+        const json& data;
         double significance;
         bool output;
         bool fitted = false;
@@ -56,6 +58,7 @@ namespace platform {
         int maxDatasetName = 0;
         FriedmanResult friedmanResult;
         HolmResult holmResult;
+        map<string, map<string, float>> ranksModels;
     };
 }
 #endif // !STATISTICS_H