Merge pull request #2 from DIGNEA/develop

Introduces a number of new test cases to evaluate the proper functionality of the new features.

.github/workflows/coverage.yml

@@ -50,7 +50,7 @@ jobs:
           make
           make digneaTestCoverage
           mkdir ${{github.workspace}}/coverage 
-          lcov --remove digneaTestCoverage.info "/usr/*" "*/build/_deps/*" "*/examples/*" "*/lib/*" "*/test/" -o ${{github.workspace}}/coverage/lcov.info
+          lcov --remove digneaTestCoverage.info "/usr/*" "*/build/_deps/*" "*/examples/*" "*/lib/*" "*/test/" "*/algorithms/kp_heuristics/Combo*" "*/algorithms/kp_heuristics/ExpKnap*" "*/algorithms/kp_heuristics/MinKnap*" "*/utilities/PCA*" -o ${{github.workspace}}/coverage/lcov.info
 
       - name: Send to Coveralls
         uses: coverallsapp/github-action@master

CMakeLists.txt

@@ -44,7 +44,7 @@ FetchContent_MakeAvailable(Catch2)
 
 FetchContent_Declare(NumCpp
         GIT_REPOSITORY https://github.com/dpilger26/NumCpp
-        GIT_TAG Version_2.10.1)
+        GIT_TAG Version_2.12.1)
 FetchContent_MakeAvailable(NumCpp)
 
 add_subdirectory(lib/fmt)
@@ -317,6 +317,8 @@ if(CMAKE_BUILD_TYPE STREQUAL "Debug" OR INCLUDE_TESTS)
                 test/experiment/ExperimentTest.cpp
                 test/generator/evaluations/EasyInstancesTest.cpp
                 test/generator/evaluations/WeightedTest.cpp
+                test/generator/evaluations/PisPerformanceTest.cpp
+
                 test/generator/EIGTest.cpp
 
                 # test/generator/MOEIGTest.cpp
@@ -376,6 +378,8 @@ if(CMAKE_BUILD_TYPE STREQUAL "Debug" OR INCLUDE_TESTS)
                 test/distances/ManhattanTest.cpp
                 test/distances/HammingTest.cpp
                 test/searches/NSFeaturesTest.cpp
+                test/searches/NSPerformanceTest.cpp
+
                 src/dignea/problems/TSP.cpp
                 test/problems/TSPTest.cpp
                 test/mutations/SwapMutationTest.cpp

README.md

@@ -5,7 +5,7 @@
 [![Build](https://github.com/DIGNEA/dignea/actions/workflows/cmake.yml/badge.svg)](https://github.com/DIGNEA/dignea/actions/workflows/cmake.yml/badge.svg)
 [![Test](https://github.com/DIGNEA/dignea/actions/workflows/catch.yml/badge.svg)](https://github.com/DIGNEA/dignea/actions/workflows/catch.yml//badge.svg)
 [![Cpp-check](https://github.com/DIGNEA/dignea/actions/workflows/cppcheck.yml/badge.svg)](https://github.com/DIGNEA/dignea/actions/workflows/cppcheck.yml//badge.svg)
-[![Coverage Status](https://coveralls.io/repos/github/DIGNEA/dignea/badge.svg?branch=master)](https://coveralls.io/github/DIGNEA/dignea?branch=master)
+[![Coverage Status](https://coveralls.io/repos/github/DIGNEA/dignea/badge.svg?branch=main)](https://coveralls.io/github/DIGNEA/dignea?branch=main)
 [![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
 [![Documentation](https://github.com/DIGNEA/dignea/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/DIGNEA/dignea/actions/workflows/pages/pages-build-deployment//badge.svg)
 </center>

include/dignea/core/Solution.h

@@ -40,8 +40,6 @@ class Solution {
 
     bool operator==(const Solution &other) const;
 
-    virtual unique_ptr<Solution<V, O>> clone();
-
     /**
      * @brief Returns the objective values of the solution
      *
@@ -358,31 +356,6 @@ Solution<V, O>::~Solution() {
     constraints.shrink_to_fit();
 }
 
-/**\deprecated Clones the solution and returns a new unique_ptr with the exact
- * same information.
- *
- *
- * @tparam V
- * @tparam O
- * @return unique_ptr<Solution<V, O>>
- */
-template <typename V, typename O>
-unique_ptr<Solution<V, O>> Solution<V, O>::clone() {
-    auto solution = make_unique<Solution<V, O>>(nVars, nObjs, nCons);
-    solution->fitness = this->fitness;
-    solution->constraintCoeff = this->constraintCoeff;
-    for (int i = 0; i < this->nVars; i++) {
-        solution->variables[i] = this->variables[i];
-    }
-    for (int i = 0; i < this->nObjs; i++) {
-        solution->objectives[i] = this->objectives[i];
-    }
-    for (int i = 0; i < this->nCons; i++) {
-        solution->constraints[i] = this->constraints[i];
-    }
-    return solution;
-}
-
 /**
  * @brief Updates the ith variable of the solution with the value v
  *

include/dignea/evolution/Evolution.h

@@ -29,6 +29,8 @@ class Evolution {
 
     virtual map<int, float> results();
 
+    virtual inline bool empty() { return solutions.empty(); }
+
    protected:
     vector<float> solutions;
     vector<int> checkpoints;

include/dignea/generator/MapElites.h

@@ -26,8 +26,7 @@
 #include <vector>
 
 #include "NumCpp.hpp"
-#include "NumCpp/Functions/unique.hpp"
-#include "NumCpp/NdArray.hpp"
+
 using namespace std;
 /**
  * @brief FeatureInfo defines the information for a specific feature.
@@ -227,7 +226,7 @@ void MapElites<IP, IS, OP, OS>::setFeaturesInfo(const Features &f) {
     // Calculate the bins
     for (int i = 0; i < 8; i++) {
         auto [start, stop, num] = this->features[i];
-        bins[i] = nc::linspace(start, stop, num, true);
+        bins[i] = nc::linspace(start, stop, num);
     }
 }
 

include/dignea/searches/NoveltySearch.h

@@ -75,7 +75,7 @@ class NoveltySearch : public Search<S> {
 
     float getK() const { return this->k; }
 
-    float getFinalThresh() const { return this->finalThresh; }
+    float getFinalThresh() const { return this->finalSThreshold; }
 
    protected:
     virtual vector<Descriptor> beforeRun(const vector<S> &population);

include/dignea/utilities/KNN.h

@@ -80,9 +80,6 @@ class KNN {
 
     neighMatrix run(const vector<Descriptor> &population,
                     Distance<float> *metric, const int &k = 3);
-
-    neighMatrix inverse(const vector<Descriptor> &population,
-                        Distance<float> *metric, const int &k = 3);
 };
 
 /**

src/dignea/utilities/KNN.cpp

@@ -66,40 +66,6 @@ neighMatrix KNN::run(const vector<Descriptor> &population,
     return nearest;
 }
 
-/**
- * @brief Computes the inverse of KNN
- *
- * @tparam S
- * @tparam T
- * @param population
- * @param metric
- * @param k
- * @return neighMatrix<T>
- */
-neighMatrix KNN::inverse(const vector<Descriptor> &population,
-                         Distance<float> *metric, const int &k) {
-    if ((unsigned int)k > population.size()) {
-        throw runtime_error(
-            "K is " + to_string(k) +
-            " and population are only: " + to_string(population.size()));
-    }
-    neighMatrix nearest;
-    nearest.reserve(population.size());
-    for (unsigned int i = 0; i < population.size(); i++) {
-        neighVector distances = {};
-        distances.reserve(population.size() - 1);
-        for (unsigned int j = 0; j < population.size(); j++) {
-            if (i == j) continue;
-            float dist = metric->compute(population[i], population[j]);
-            distances.push_back({dist, j});
-        }
-        // Ordenamos los vecinos de I por su distancia a I
-        sort(distances.rbegin(), distances.rend());
-        nearest.push_back({distances.begin(), distances.begin() + k});
-    }
-    return nearest;
-}
-
 /**
  * @brief Computes the sparseness of all individuals in the population vector
  * Based on the Novelty Search from Exploiting Open-Endedness to Solve Problems

test/algorithms/multiobjective/NSGA2Test.cpp

@@ -15,12 +15,11 @@
 #include <dignea/problems/DoubleSphere.h>
 #include <dignea/selections/BinaryTournamentSelection.h>
 
+#include <catch2/catch_all.hpp>
 #include <memory>
 #include <nlohmann/json.hpp>
 #include <vector>
 
-#include <catch2/catch_all.hpp>
-
 using namespace std;
 using json = nlohmann::json;
 
@@ -43,12 +42,18 @@ TEST_CASE("Non-Dominated Sorting Genetic Algorith II Tests", "[NSGA-II]") {
         REQUIRE(ga->getSelection() == nullptr);
     }
 
-    SECTION("Getting NSGA-II") {
+    SECTION("Getting NSGA-II ID") {
         unique_ptr<AbstractGA<FloatSolution>> ga =
             make_unique<NSGA2<FloatSolution>>();
         REQUIRE(ga->getID() == "NSGA-II");
     }
 
+    SECTION("Getting NSGA-II name") {
+        unique_ptr<AbstractGA<FloatSolution>> ga =
+            make_unique<NSGA2<FloatSolution>>();
+        REQUIRE(ga->getName() == "Non-dominated Sorting Genetic Algorithm II");
+    }
+
     SECTION("Setting maxEvaluations") {
         unique_ptr<AbstractGA<FloatSolution>> ga =
             make_unique<NSGA2<FloatSolution>>();
@@ -117,4 +122,24 @@ TEST_CASE("Non-Dominated Sorting Genetic Algorith II Tests", "[NSGA-II]") {
                 .runDuring(evals);
         REQUIRE(ga);
     }
+
+    SECTION("NSGA2 run to solve Double Sphere") {
+        unique_ptr<AbstractGA<FloatSolution>> ga =
+            GABuilder<FloatSolution>::create(GAType::NSGA2)
+                .toSolve(make_unique<DoubleSphere>(dimension))
+                .with()
+                .populationOf(populationSize)
+                .with()
+                .mutation(MutType::UniformAll)
+                .crossover(CXType::Uniform)
+                .selection(SelType::Binary)
+                .withMutRate(0.05)
+                .withCrossRate(0.8)
+                .runDuring(evals);
+        REQUIRE_NOTHROW(ga->run());
+        Front result = ga->getResults();
+        REQUIRE_FALSE(result.empty());
+        vector bestObjs = result.getSolutions()[0].getObjectives();
+        REQUIRE(bestObjs[0] == bestObjs[1]);
+    }
 }

test/algorithms/singleobjective/SteadyGATest.cpp

@@ -9,11 +9,10 @@
 #include <dignea/problems/Sphere.h>
 #include <dignea/selections/BinaryTournamentSelection.h>
 
+#include <catch2/catch_all.hpp>
 #include <memory>
 #include <vector>
 
-#include <catch2/catch_all.hpp>
-
 using namespace std;
 
 TEST_CASE("Steady Genetic Algorithm Tests", "[SteadyGA]") {
@@ -115,4 +114,22 @@ TEST_CASE("Steady Genetic Algorithm Tests", "[SteadyGA]") {
         Front<FloatSolution> solutions = ga->getResults();
         REQUIRE_FALSE(solutions.getNumOfSolutions() == 0);
     }
+
+    SECTION("SteadyGA checks evolution") {
+        unique_ptr<AbstractGA<FloatSolution>> ga =
+            GABuilder<FloatSolution>::create(GAType::Steady)
+                .toSolve(make_unique<Sphere>(dimension))
+                .with()
+                .populationOf(populationSize)
+                .with()
+                .mutation(MutType::UniformAll)
+                .crossover(CXType::Uniform)
+                .selection(SelType::Binary)
+                .withMutRate(mutationRate)
+                .withCrossRate(crossoverRate)
+                .runDuring(evals);
+        ga->run();
+        auto evolution = ga->getEvolution();
+        REQUIRE_FALSE(evolution.empty());
+    }
 }

test/builders/EIGBuilderTest.cpp

@@ -32,6 +32,7 @@ TEST_CASE("EIGBuilder tests", "[EIGBuilder]") {
     const int upperBound = 1000;
     const int nIterationsEIG = 1000;
     const int reps = 10;
+
     SECTION("Creates a EIG for KNP") {
         // configurations
         vector<unique_ptr<EA>> algorithms;
@@ -86,6 +87,105 @@ TEST_CASE("EIGBuilder tests", "[EIGBuilder]") {
         REQUIRE(generator->getPortfolio().size() == 3);
     }
 
+    SECTION("Creates a MAP-Elites generator for KNP") {
+        // configurations
+        vector<unique_ptr<EA>> algorithms;
+        auto instKP = make_unique<KPDomain>(instanceSize, 1, nInstances, 1,
+                                            upperBound, 1, upperBound);
+        for (const float cRate : crossRates) {
+            unique_ptr<ParallelGeneticAlgorithm<OS>> algorithm =
+                ParGABuilder<OS>::create()
+                    .usingCores(32)
+                    .with()
+                    .mutation(MutType::UniformOne)
+                    .crossover(CXType::Uniform)
+                    .selection(SelType::Binary)
+                    .populationOf(popSize)
+                    .withMutRate(mutationRate)
+                    .withCrossRate(cRate)
+                    .runDuring(maxEvals);
+            // Two configurations for EIG
+            algorithms.push_back(move(algorithm));
+        }
+        unique_ptr<InstanceFitness> easyEvaluator =
+            make_unique<EasyInstances>();
+
+        unique_ptr<EIG<IP, IS, OP, OS>> generator =
+            EIGBuilder<IP, IS, OP, OS>::create(GeneratorType::MapElites)
+                .toSolve(move(instKP))
+                .with()
+                .portfolio(algorithms)
+                .evalWith(move(easyEvaluator))
+                .repeating(reps)
+                .withSearch(NSType::Features, make_unique<Euclidean<float>>(),
+                            3.0, 3.0, 15)
+                .with()
+                .crossover(CXType::Uniform)
+                .mutation(MutType::UniformOne)
+                .selection(SelType::Binary)
+                .withMutRate(mutationRate)
+                .withCrossRate(meaCXRate)
+                .populationOf(nInstances)
+                .runDuring(nIterationsEIG);
+        REQUIRE(generator);
+        REQUIRE(generator->getName() == "MapElites");
+        REQUIRE(generator->getSelection()->getName() ==
+                "Binary Tournament Selection");
+        REQUIRE(generator->getCrossover()->getName() ==
+                "Uniform One Crossover");
+        REQUIRE(generator->getMutation()->getName() == "Uniform One Mutation");
+        REQUIRE(generator->getPopulationSize() == nInstances);
+        REQUIRE(generator->getGenerations() == nIterationsEIG);
+        REQUIRE(generator->getMutationRate() == mutationRate);
+        REQUIRE(generator->getCrossoverRate() == meaCXRate);
+        REQUIRE(generator->getRepetitions() == reps);
+        REQUIRE(generator->getPortfolio().size() == 3);
+    }
+
+    SECTION("Creates a EIG when unknown type") {
+        // configurations
+        vector<unique_ptr<EA>> algorithms;
+        auto instKP = make_unique<KPDomain>(instanceSize, 1, nInstances, 1,
+                                            upperBound, 1, upperBound);
+        for (const float cRate : crossRates) {
+            unique_ptr<ParallelGeneticAlgorithm<OS>> algorithm =
+                ParGABuilder<OS>::create()
+                    .usingCores(32)
+                    .with()
+                    .mutation(MutType::UniformOne)
+                    .crossover(CXType::Uniform)
+                    .selection(SelType::Binary)
+                    .populationOf(popSize)
+                    .withMutRate(mutationRate)
+                    .withCrossRate(cRate)
+                    .runDuring(maxEvals);
+            // Two configurations for EIG
+            algorithms.push_back(move(algorithm));
+        }
+        unique_ptr<InstanceFitness> easyEvaluator =
+            make_unique<EasyInstances>();
+
+        unique_ptr<EIG<IP, IS, OP, OS>> generator =
+            EIGBuilder<IP, IS, OP, OS>::create(GeneratorType::MultiObjective)
+                .toSolve(move(instKP))
+                .with()
+                .portfolio(algorithms)
+                .evalWith(move(easyEvaluator))
+                .repeating(reps)
+                .withSearch(NSType::Features, make_unique<Euclidean<float>>(),
+                            3.0, 3.0, 15)
+                .with()
+                .crossover(CXType::Uniform)
+                .mutation(MutType::UniformOne)
+                .selection(SelType::Binary)
+                .withMutRate(mutationRate)
+                .withCrossRate(meaCXRate)
+                .populationOf(nInstances)
+                .runDuring(nIterationsEIG);
+        REQUIRE(generator);
+        REQUIRE(generator->getName() == "EIG");
+    }
+
     SECTION("Throws exception if component is missing") {
         // configurations
         vector<unique_ptr<EA>> algorithms;