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minor style change test

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This commit is contained in:
NanuSai
2021-06-08 10:20:45 +05:30
parent 08b24f1bc8
commit fefcaa6b1f
1 changed files with 128 additions and 103 deletions
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tests/moead_test.cpp
+128 -103
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@@ -33,7 +33,130 @@ bool InBounds(const double& value, const double& low, const double& high)
}
/**
* Optimize for the Fonseca Fleming function using MOEA/D optimizer.
* Optimize for the Schaffer N.1 function using MOEA/D-DE optimizer.
*/
TEST_CASE("MOEADSchafferN1Test", "[MOEADTest]")
{
SchafferFunctionN1<arma::mat> SCH;
double lowerBound = -1000;
const double upperBound = 1000;
const double strength = 1e-3;
MOEAD opt(150, // population size
10, // num generations
0.6, // cross over prob
0.7, // mutation prob
strength, // mutation strength
10, //neighbor size
0.5, //distribution index
0.5, //neighbor prob
0.8, //differential weight
10, //maxreplace,
true, //Preserve diversity
lowerBound, //lower bound
upperBound //upper bound
);
typedef decltype(SCH.objectiveA) ObjectiveTypeA;
typedef decltype(SCH.objectiveB) ObjectiveTypeB;
// We allow a few trials in case of poor convergence.
bool success = false;
for (size_t trial = 0; trial < 3; ++trial)
{
arma::mat coords = SCH.GetInitialPoint();
std::tuple<ObjectiveTypeA, ObjectiveTypeB> objectives = SCH.GetObjectives();
opt.Optimize(objectives, coords);
std::vector<arma::mat> bestFront = opt.Front();
bool allInRange = true;
double minimumPositive = 1000;
for (arma::mat solution: bestFront)
{
double val = arma::as_scalar(solution);
if(val >= 0.0)
minimumPositive = std::min(minimumPositive, val);
if ((val < 0.0 && std::abs(val) >= minimumPositive) || val > 2.0)
{
allInRange = false;
break;
}
}
if (allInRange)
{
success = true;
break;
}
}
REQUIRE(success == true);
}
/**
* Optimize for the Schaffer N.1 function using MOEA/D-DE optimizer.
*/
TEST_CASE("MOEADSchafferN1VectorBoundsTest", "[MOEADTest]")
{
SchafferFunctionN1<arma::mat> SCH;
arma::vec lowerBound = {-1000};
arma::vec upperBound = {1000};
const double strength = 1e-3;
MOEAD opt(150, // population size
10, // num generations
0.6, // cross over prob
0.7, // mutation prob
strength, // mutation strength
10, //neighbor size
0.5, //distribution index
0.5, //neighbor prob
0.8, //differential weight
10, //maxreplace,
true, //Preserve diversity
lowerBound, //lower bound
upperBound //upper bound
);
typedef decltype(SCH.objectiveA) ObjectiveTypeA;
typedef decltype(SCH.objectiveB) ObjectiveTypeB;
bool success = false;
for (size_t trial = 0; trial < 3; ++trial)
{
arma::mat coords = SCH.GetInitialPoint();
std::tuple<ObjectiveTypeA, ObjectiveTypeB> objectives = SCH.GetObjectives();
opt.Optimize(objectives, coords);
std::vector<arma::mat> bestFront = opt.Front();
bool allInRange = true;
for (arma::mat solution: bestFront)
{
double val = arma::as_scalar(solution);
if (val < 0.0 || val > 2.0)
{
allInRange = false;
break;
}
}
if (allInRange)
{
success = true;
break;
}
}
REQUIRE(success == true);
}
/**
* Optimize for the Fonseca Fleming function using MOEA/D-DE optimizer.
*/
TEST_CASE("MOEADFonsecaFlemingTest", "[MOEADTest]")
{
@@ -43,6 +166,7 @@ TEST_CASE("MOEADFonsecaFlemingTest", "[MOEADTest]")
const double strength = 1e-3;
const double expectedLowerBound = -1.0 / sqrt(3);
const double expectedUpperBound = 1.0 / sqrt(3);
MOEAD opt(150, // population size
10, // num generations
0.6, // cross over prob
@@ -60,6 +184,7 @@ TEST_CASE("MOEADFonsecaFlemingTest", "[MOEADTest]")
typedef decltype(FON.objectiveA) ObjectiveTypeA;
typedef decltype(FON.objectiveB) ObjectiveTypeB;
arma::mat coords = FON.GetInitialPoint();
std::tuple<ObjectiveTypeA, ObjectiveTypeB> objectives = FON.GetObjectives();
opt.Optimize(objectives, coords);
@@ -85,7 +210,7 @@ TEST_CASE("MOEADFonsecaFlemingTest", "[MOEADTest]")
}
/**
* Optimize for the Fonseca Fleming function using MOEA/D optimizer.
* Optimize for the Fonseca Fleming function using MOEA/D-DE optimizer.
*/
TEST_CASE("MOEADFonsecaFlemingVectorBoundsTest", "[MOEADTest]")
{
@@ -132,104 +257,4 @@ TEST_CASE("MOEADFonsecaFlemingVectorBoundsTest", "[MOEADTest]")
}
}
REQUIRE(allInRange);
}
/**
* Optimize for the function using MOEA/D optimizer.
*/
TEST_CASE("MOEADSchafferN1Test", "[MOEADTest]")
{
SchafferFunctionN1<arma::mat> SCH;
double lowerBound = {-1000};
const double upperBound = {1000};
const double strength = 1e-3;
MOEAD opt(150, // population size
10, // num generations
0.6, // cross over prob
0.7, // mutation prob
strength, // mutation strength
10, //neighbor size
0.5, //distribution index
0.5, //neighbor prob
0.8, //differential weight
10, //maxreplace,
true, //Preserve diversity
lowerBound, //lower bound
upperBound //upper bound
);
typedef decltype(SCH.objectiveA) ObjectiveTypeA;
typedef decltype(SCH.objectiveB) ObjectiveTypeB;
arma::mat coords = SCH.GetInitialPoint();
std::tuple<ObjectiveTypeA, ObjectiveTypeB> objectives =
SCH.GetObjectives();
opt.Optimize(objectives, coords);
std::vector<arma::mat> bestFronts = opt.Front();
bool allInRange = true;
double minimumPositive = 1000;
for (arma::mat solution: bestFronts)
{
const double val = arma::as_scalar(solution);
minimumPositive = std::min(minimumPositive, val>=0 ? val : 1000);
std::cout<<val<<"\n";
if (val < 0.0 || val > 2.0)
{
allInRange = false;
break;
}
}
REQUIRE(allInRange);
}
/**
* Optimize for the function using MOEA/D optimizer.
*/
TEST_CASE("MOEADSchafferN1VectorBoundsTest", "[MOEADTest]")
{
SchafferFunctionN1<arma::mat> SCH;
arma::vec lowerBound = {-1000};
arma::vec upperBound = {1000};
const double strength = 1e-3;
MOEAD opt(150, // population size
10, // num generations
0.6, // cross over prob
0.7, // mutation prob
strength, // mutation strength
10, //neighbor size
0.5, //distribution index
0.5, //neighbor prob
0.8, //differential weight
10, //maxreplace,
true, //Preserve diversity
lowerBound, //lower bound
upperBound //upper bound
);
typedef decltype(SCH.objectiveA) ObjectiveTypeA;
typedef decltype(SCH.objectiveB) ObjectiveTypeB;
arma::mat coords = SCH.GetInitialPoint();
std::tuple<ObjectiveTypeA, ObjectiveTypeB> objectives =
SCH.GetObjectives();
opt.Optimize(objectives, coords);
std::vector<arma::mat> bestFronts = opt.Front();
bool allInRange = true;
double minimumPositive = 1000;
for (arma::mat solution: bestFronts)
{
double val = arma::as_scalar(solution);
minimumPositive = std::min(minimumPositive, val>=0 ? val : 1000);
if (val < 0.00 || val > 2.0)
{
allInRange = false;
break;
}
}
REQUIRE(allInRange);
}
}