C++ (Cpp) Col::load Examples

Example #1

File: testWeierstrassFunction.cpp Project: hnkien/Mantella

  TestWeierstrassFunction weierstrassFunction(40);
    
  SECTION(".getObjectiveValueImplementation") {
    SECTION("Returns the objective value") {
      arma::Mat<double> rotationR;
      REQUIRE(rotationR.load(testDirectory + "/data/optimisationProblem/blackBoxOptimisationBenchmark/_rotationMatrix_40x40_1.input"));
      weierstrassFunction.setRotationR(rotationR);

      arma::Mat<double> rotationQ;
      REQUIRE(rotationQ.load(testDirectory + "/data/optimisationProblem/blackBoxOptimisationBenchmark/_rotationMatrix_40x40_2.input"));
      weierstrassFunction.setRotationQ(rotationQ);

      arma::Mat<double> parameters;
      REQUIRE(parameters.load(testDirectory + "/data/optimisationProblem/blackBoxOptimisationBenchmark/_parameters_40x100.input"));

      arma::Col<double> expectedObjectiveValues;
      REQUIRE(expectedObjectiveValues.load(testDirectory + "/data/optimisationProblem/blackBoxOptimisationBenchmark/bbob_weierstrassFunction_dim40_1x100.expected"));

      for (arma::uword n = 0; n < parameters.n_cols; ++n) {
        CHECK(weierstrassFunction.getObjectiveValueImplementation(parameters.col(n)) == Approx(expectedObjectiveValues(n)));
      }
    }
  }

  SECTION(".toString") {
    SECTION("Returns a (filesystem friendly) name for the class.") {
      CHECK(weierstrassFunction.toString() == "bbob_weierstrass_function");
    }
  }
}

Example #2

File: testWeierstrassFunction.cpp Project: xlong88/Mantella

SCENARIO("bbob::WeierstrassFunction.objectiveFunction_", "[bbob::WeierstrassFunction][bbob::WeierstrassFunction.objectiveFunction_]") {
  GIVEN("Some parameters") {
    // All expected objective values where generated for a 40-dimensional problem instance.
    const arma::uword numberOfDimensions = 40;
    CAPTURE(numberOfDimensions);
    TestWeierstrassFunction optimisationProblem(numberOfDimensions);

    REQUIRE(optimisationProblem.rotationR_.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_rotationMatrix_40x40_1.input"));
    REQUIRE(optimisationProblem.rotationQ_.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_rotationMatrix_40x40_2.input"));

    arma::Mat<double> parameters;
    REQUIRE(parameters.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_parameters_40x100.input"));

    THEN("Return their objective value") {
      arma::Col<double> expectedObjectiveValues;
      REQUIRE(expectedObjectiveValues.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/weierstrassFunction_dim40_1x100.expected"));

      for (arma::uword n = 0; n < parameters.n_cols; ++n) {
        CHECK(optimisationProblem.objectiveFunction_(parameters.col(n)) == Approx(expectedObjectiveValues(n)));
      }
    }
  }
}

SCENARIO("bbob::WeierstrassFunction.getNormalisedObjectiveValue", "[bbob::WeierstrassFunction][bbob::WeierstrassFunction.getNormalisedObjectiveValue]") {
  GIVEN("A parameter") {
    const arma::uword numberOfDimensions = SYNCHRONISED(1 + discreteRandomNumber());
    CAPTURE(numberOfDimensions);

    const arma::Col<double>& parameter = arma::normalise(continuousRandomNumbers(numberOfDimensions));
    CAPTURE(parameter);

Example #3

File: testSchaffersF7FunctionIllConditioned.cpp Project: xlong88/Mantella

SCENARIO("bbob::SchaffersF7FunctionIllConditioned.objectiveFunction_", "[bbob::SchaffersF7FunctionIllConditioned][bbob::SchaffersF7FunctionIllConditioned.objectiveFunction_]") {
  GIVEN("Some parameters") {
    // All expected objective values where generated for a 40-dimensional problem instance.
    const arma::uword numberOfDimensions = 40;
    CAPTURE(numberOfDimensions);
    TestSchaffersF7FunctionIllConditioned optimisationProblem(numberOfDimensions);

    REQUIRE(optimisationProblem.rotationQ_.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_rotationMatrix_40x40_2.input"));

    arma::Mat<double> parameters;
    REQUIRE(parameters.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_parameters_40x100.input"));

    THEN("Return their objective value") {
      arma::Col<double> expectedObjectiveValues;
      REQUIRE(expectedObjectiveValues.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/schaffersF7FunctionIllConditioned_dim40_1x100.expected"));

      for (arma::uword n = 0; n < parameters.n_cols; ++n) {
        CHECK(optimisationProblem.objectiveFunction_(parameters.col(n)) == Approx(expectedObjectiveValues(n)));
      }
    }
  }
}

SCENARIO("bbob::SchaffersF7FunctionIllConditioned.getNormalisedObjectiveValue", "[bbob::SchaffersF7FunctionIllConditioned][bbob::SchaffersF7FunctionIllConditioned.getNormalisedObjectiveValue]") {
  GIVEN("A parameter") {
    const arma::uword numberOfDimensions = SYNCHRONISED(1 + discreteRandomNumber());
    CAPTURE(numberOfDimensions);

    const arma::Col<double>& parameter = arma::normalise(continuousRandomNumbers(numberOfDimensions));
    CAPTURE(parameter);

Example #4

File: testGallaghersGaussian101mePeaksFunction.cpp Project: xlong88/Mantella

  GIVEN("Some parameters") {
    // All expected objective values where generated for a 40-dimensional problem instance.
    const arma::uword numberOfDimensions = 40;
    CAPTURE(numberOfDimensions);
    TestGallaghersGaussian101mePeaksFunction optimisationProblem(numberOfDimensions);

    REQUIRE(optimisationProblem.rotationQ_.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_rotationMatrix_40x40_1.input"));
    REQUIRE(optimisationProblem.localParameterConditionings_.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_localParameterConditionings_40x101.input"));
    REQUIRE(optimisationProblem.localParameterTranslations_.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_localParameterTranslations_40x101.input"));

    arma::Mat<double> parameters;
    REQUIRE(parameters.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_parameters_40x100.input"));

    THEN("Return their objective value") {
      arma::Col<double> expectedObjectiveValues;
      REQUIRE(expectedObjectiveValues.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/gallaghersGaussian101mePeaksFunction_dim40_1x100.expected"));

      for (arma::uword n = 0; n < parameters.n_cols; ++n) {
        CHECK(optimisationProblem.objectiveFunction_(parameters.col(n)) == Approx(expectedObjectiveValues(n)));
      }
    }
  }
}

SCENARIO("bbob::GallaghersGaussian101mePeaksFunction.getNormalisedObjectiveValue", "[bbob::GallaghersGaussian101mePeaksFunction][bbob::GallaghersGaussian101mePeaksFunction.getNormalisedObjectiveValue]") {
  GIVEN("A parameter") {
    const arma::uword numberOfDimensions = SYNCHRONISED(1 + discreteRandomNumber());
    CAPTURE(numberOfDimensions);

    const arma::Col<double>& parameter = arma::normalise(continuousRandomNumbers(numberOfDimensions));
    CAPTURE(parameter);

Example #5

File: testRosenbrockFunctionRotated.cpp Project: xlong88/Mantella

  using mant::bbob::RosenbrockFunctionRotated::objectiveFunction_;
};

SCENARIO("bbob::RosenbrockFunctionRotated.objectiveFunction_", "[bbob::RosenbrockFunctionRotated][bbob::RosenbrockFunctionRotated.objectiveFunction_]") {
  GIVEN("Some parameters") {
    // All expected objective values where generated for a 40-dimensional problem instance.
    const arma::uword numberOfDimensions = 40;
    CAPTURE(numberOfDimensions);
    TestRosenbrockFunctionRotated optimisationProblem(numberOfDimensions);

    arma::Mat<double> parameters;
    REQUIRE(parameters.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/_parameters_40x100.input"));

    THEN("Return their objective value") {
      arma::Col<double> expectedObjectiveValues;
      REQUIRE(expectedObjectiveValues.load(::rootTestDataDirectory + "/optimisationProblem/benchmarkOptimisationProblem/blackBoxOptimisationBenchmark/rosenbrockFunctionRotated_dim40_1x100.expected"));

      for (arma::uword n = 0; n < parameters.n_cols; ++n) {
        CHECK(optimisationProblem.objectiveFunction_(parameters.col(n)) == Approx(expectedObjectiveValues(n)));
      }
    }
  }
}

SCENARIO("bbob::RosenbrockFunctionRotated.getNormalisedObjectiveValue", "[bbob::RosenbrockFunctionRotated][bbob::RosenbrockFunctionRotated.getNormalisedObjectiveValue]") {
  GIVEN("A parameter") {
    const arma::uword numberOfDimensions = SYNCHRONISED(1 + discreteRandomNumber());
    CAPTURE(numberOfDimensions);

    const arma::Col<double>& parameter = arma::normalise(continuousRandomNumbers(numberOfDimensions));
    CAPTURE(parameter);

Example #6

File: testLunacekBiRastriginFunction.cpp Project: hnkien/Mantella

    SECTION(".getObjectiveValueImplementation") {
        SECTION("Returns the objective value") {
            arma::Mat<double> rotationR;
            REQUIRE(rotationR.load(testDirectory + "/data/optimisationProblem/blackBoxOptimisationBenchmark/_rotationMatrix_40x40_1.input"));
            lunacekBiRastriginFunction.setRotationR(rotationR);

            arma::Mat<double> rotationQ;
            REQUIRE(rotationQ.load(testDirectory + "/data/optimisationProblem/blackBoxOptimisationBenchmark/_rotationMatrix_40x40_2.input"));
            lunacekBiRastriginFunction.setRotationQ(rotationQ);

            arma::Mat<double> parameters;
            REQUIRE(parameters.load(testDirectory + "/data/optimisationProblem/blackBoxOptimisationBenchmark/_parameters_40x100.input"));

            arma::Col<double> expectedObjectiveValues;
            REQUIRE(expectedObjectiveValues.load(testDirectory + "/data/optimisationProblem/blackBoxOptimisationBenchmark/bbob_lunacekBiRastriginFunction_dim40_1x100.expected"));


            for (arma::uword n = 0; n < parameters.n_cols; ++n) {
                CHECK(lunacekBiRastriginFunction.getObjectiveValueImplementation(parameters.col(n)) == Approx(expectedObjectiveValues(n)));
            }
        }
    }

    SECTION(".toString") {
        SECTION("Returns a (filesystem friendly) name for the class.") {
            CHECK(lunacekBiRastriginFunction.toString() =="bbob_lunacek_bi_rastrigin_function");
        }
    }
}