public void FeedForwardNeuralNetwork_LoadModelSparseMatrix()
{
var target = new FeedForwardNeuralNetwork <double>(
new[] { 2L, 3L, 2L });
var parser = new DoubleParser <string>();
var matrix = TestsHelper.ReadMatrix(
5,
5,
"[[-1.0, 1.0, 0.5, 0, 0], [1.0, -1.0, 0.5, 0, 0], [0, 0, 0, -1.0, 2.0], [0, 0, 0, 0.5, -1.5], [0, 0, 0, 1.0, -0.5]]",
(i, j) => new SparseDictionaryMatrix <double>(i, j, 0),
parser,
true);
var vector = TestsHelper.ReadVector(
5,
"[-1.0, 0.0, 1.0, -0.5, 0.5]",
new SparseDictionaryMathVectorFactory <double>(),
parser,
true);
var model = new NeuralNetworkModel <double, SparseDictionaryMatrix <double>, IMathVector <double> >(
matrix,
vector);
target.LoadModelSparse <SparseDictionaryMatrix <double>, ILongSparseMatrixLine <double>, IMathVector <double> >(
model);
this.AssertTargetFromMatrix(
model,
target);
}
public void RunTest_OneEquality()
{
var inputConstraintsMatrixText = "[[1,0,3],[0,2,2]]";
var inputConstraintsVectorText = "[4,12,18]";
var cost = new SimplexMaximumNumberField <double>(0, -18);
var nonBasicVariables = new[] { 0, 1 };
var basicVariables = new[] { 2, 3, 4 };
// Leitura da matriz das retrições.
var doubleElementsParser = new DoubleParser <string>();
var inputConstraintsMatrix = TestsHelper.ReadMatrix <double>(
3,
2,
inputConstraintsMatrixText,
(i, j) => new ArrayMathMatrix <double>(i, j),
doubleElementsParser,
true);
// Leitura do vector de restrições.
var vectorFactory = new ArrayVectorFactory <double>();
var inputConstraintsVector = TestsHelper.ReadVector <double>(
3,
inputConstraintsVectorText,
vectorFactory,
doubleElementsParser,
true);
// Introdução da função objectivo.
var inputObjectiveFunction = new ArrayMathVector <SimplexMaximumNumberField <double> >(2);
inputObjectiveFunction[0] = new SimplexMaximumNumberField <double>(
-3,
-3);
inputObjectiveFunction[1] = new SimplexMaximumNumberField <double>(
-5,
-2);
// Objecto de entrada para o algoritmo do simplex.
var simplexInput = new SimplexInput <double, SimplexMaximumNumberField <double> >(
basicVariables,
nonBasicVariables,
inputObjectiveFunction,
cost,
inputConstraintsMatrix,
inputConstraintsVector);
var doubleField = new DoubleField();
var target = new SimplexAlgorithm <double>(Comparer <double> .Default, doubleField);
var actual = target.Run(simplexInput);
// Verifica o custo
Assert.AreEqual(36, actual.Cost);
// Verifica a solução
Assert.AreEqual(2, actual.Solution[0]);
Assert.AreEqual(6, actual.Solution[1]);
}
public void RunSimplexTest_NoFeasibleSolution()
{
var inputConstraintsMatrixText = "[[0.3,0.5,0.6],[0.1,0.5,0.4],[0,0,-1]]";
var inputConstraintsVectorText = "[1.8,6,6]";
var cost = new SimplexMaximumNumberField <double>(0, -12);
var nonBasicVariables = new[] { 0, 1, 2 };
var basicVariables = new[] { 3, 4, 5 };
// Leitura da matriz das retrições.
var doubleElementsParser = new DoubleParser <string>();
var inputConstraintsMatrix = TestsHelper.ReadMatrix <double>(
3,
3,
inputConstraintsMatrixText,
(i, j) => new ArrayMathMatrix <double>(i, j),
doubleElementsParser,
true);
// Leitura do vector de restrições.
var vectorFactory = new ArrayVectorFactory <double>();
var inputConstraintsVector = TestsHelper.ReadVector <double>(
3,
inputConstraintsVectorText,
vectorFactory,
doubleElementsParser,
true);
// Introdução da função objectivo.
var inputObjectiveFunction = new ArrayMathVector <SimplexMaximumNumberField <double> >(3);
inputObjectiveFunction[0] = new SimplexMaximumNumberField <double>(
0.4,
-1.1);
inputObjectiveFunction[1] = new SimplexMaximumNumberField <double>(
0.5,
-0.9);
inputObjectiveFunction[2] = new SimplexMaximumNumberField <double>(
0,
1);
// Objecto de entrada para o algoritmo do simplex.
var simplexInput = new SimplexInput <double, SimplexMaximumNumberField <double> >(
basicVariables,
nonBasicVariables,
inputObjectiveFunction,
cost,
inputConstraintsMatrix,
inputConstraintsVector);
var doubleField = new DoubleField();
var target = new SimplexAlgorithm <double>(Comparer <double> .Default, doubleField);
var actual = target.Run(simplexInput);
// O problema tem uma solução cujo custo é inifito.
Assert.IsFalse(actual.HasSolution);
}
public void ReplaceTest_ReplaceByMatrixWithMatrixAlgebra()
{
// Representação dos polinómios.
var polynomText = "x^2 + 2*x + 1";
var variableName = "x";
var integerDomain = new IntegerDomain();
var integerToIntegerConv = new ElementToElementConversion <int>();
var integerParser = new IntegerParser <string>();
var fractionField = new FractionField <int>(integerDomain);
var fractionFieldParser = new FieldDrivenExpressionParser <Fraction <int> >(
new SimpleElementFractionParser <int>(integerParser, integerDomain),
fractionField);
var polynomial = TestsHelper.ReadUnivarPolynomial <Fraction <int> >(
polynomText,
fractionField,
fractionFieldParser,
new ElementFractionConversion <int>(integerDomain),
variableName);
// Leitura da matriz.
var matrix = TestsHelper.ReadMatrix <Fraction <int> >(
2,
2,
"[[1/2+1/3,1/2-1/3],[1/5+1/4,1/5-1/4]]",
(i, j) => new ArrayMathMatrix <Fraction <int> >(i, j),
fractionFieldParser);
var matrixAlgebra = new GeneralMatrixAlgebra <Fraction <int> >(
2,
new ArrayMathMatrixFactory <Fraction <int> >(),
fractionField);
var actual = polynomial.Replace(matrix, matrixAlgebra);
var expected = TestsHelper.ReadMatrix <Fraction <int> >(
2,
2,
"[[1237/360,167/360],[501/400,391/400]]",
(i, j) => new ArrayMathMatrix <Fraction <int> >(i, j),
fractionFieldParser);
for (int i = 0; i < 2; ++i)
{
for (int j = 0; j < 2; ++j)
{
Assert.AreEqual(expected[i, j], actual[i, j]);
}
}
}
public void RunTest()
{
var inputMatrix = "[[1,2,1],[2,-1,-1],[1,-1,3]]";
var inputVector = "[[1,2,3]]";
var expectedText = "[[21/19,-6/19,10/19]]";
var integerDomain = new BigIntegerDomain();
var integerParser = new BigIntegerParser <string>();
var fractionField = new FractionField <BigInteger>(integerDomain);
var fractionFieldParser = new FieldDrivenExpressionParser <Fraction <BigInteger> >(
new SimpleElementFractionParser <BigInteger>(integerParser, integerDomain),
fractionField);
var matrixFactory = new ArrayMathMatrixFactory <Fraction <BigInteger> >();
// Leitura da matriz que representa o sistema de equações.
var coeffsMatrix = TestsHelper.ReadMatrix <Fraction <BigInteger> >(
3,
3,
inputMatrix,
(i, j) => new ArrayMathMatrix <Fraction <BigInteger> >(i, j),
fractionFieldParser);
// Leitura do vector de termos independente.
var vectorMatrix = TestsHelper.ReadMatrix <Fraction <BigInteger> >(
3,
1,
inputVector,
(i, j) => new ArrayMathMatrix <Fraction <BigInteger> >(i, j),
fractionFieldParser);
var expectedMatrix = TestsHelper.ReadMatrix <Fraction <BigInteger> >(
3,
1,
expectedText,
(i, j) => new ArrayMathMatrix <Fraction <BigInteger> >(i, j),
fractionFieldParser);
var systemSolver = new SequentialLanczosAlgorithm <Fraction <BigInteger>, FractionField <BigInteger> >(
matrixFactory,
fractionField);
var squareMatrix = (coeffsMatrix as ArrayMathMatrix <Fraction <BigInteger> >).AsSquare();
var actual = systemSolver.Run(squareMatrix, vectorMatrix);
for (int i = 0; i < 3; ++i)
{
Assert.AreEqual(expectedMatrix[i, 0], actual[i, 0]);
}
}
public void RunTest()
{
var coefficientsMatrixText = "[[1,0,0],[0,0,0],[0,3,3],[2,0,1]]";
var independentVectorText = "[[1,3,3]]";
var expectedText = "[[1,0,1,0]]";
var integerDomain = new IntegerDomain();
var integerParser = new IntegerParser <string>();
var fractionField = new FractionField <int>(integerDomain);
var fractionFieldParser = new FieldDrivenExpressionParser <Fraction <int> >(
new SimpleElementFractionParser <int>(integerParser, integerDomain),
fractionField);
var matrixFactory = new ArrayMatrixFactory <Fraction <int> >();
// Leitura da matriz que representa o sistema de equações.
var coeffsMatrix = TestsHelper.ReadMatrix <Fraction <int> >(
3,
4,
coefficientsMatrixText,
matrixFactory,
fractionFieldParser);
// Leitura do vector de termos independente.
var vectorMatrix = TestsHelper.ReadMatrix <Fraction <int> >(
3,
1,
independentVectorText,
new ArrayMatrixFactory <Fraction <int> >(),
fractionFieldParser);
var expectedMatrixVector = TestsHelper.ReadMatrix <Fraction <int> >(
4,
1,
expectedText,
matrixFactory,
fractionFieldParser);
var algorithm = new DenseCondensationLinSysAlgorithm <Fraction <int> >(fractionField);
var actual = algorithm.Run(coeffsMatrix, vectorMatrix);
Assert.AreEqual(expectedMatrixVector.GetLength(0), actual.Vector.Length);
for (int i = 0; i < actual.Vector.Length; ++i)
{
Assert.AreEqual(expectedMatrixVector[i, 0], actual.Vector[i]);
}
}
public void RunTest_BigIntegerMatrix()
{
// A leitura é realizada por colunas.
var matrixText = "[[100000,1001,20005], [32534,4245341,56134513451], [21346136,1134613,1136135613]]";
var integerDomain = new BigIntegerDomain();
var variableName = "x";
var integerParser = new BigIntegerParser <string>();
var conversion = new BigIntegerToIntegerConversion();
var matrix = TestsHelper.ReadMatrix <BigInteger>(
3,
3,
matrixText,
(i, j) => new ArraySquareMathMatrix <BigInteger>(i),
integerParser);
var fastDivFreeCharacPolAlg = new FastDivisionFreeCharPolynomCalculator <BigInteger>(variableName, integerDomain);
var expected = TestsHelper.ReadUnivarPolynomial("1*x^3+-1140480954*x^2-58754054577367644*x+4689162494877443109176", integerDomain, integerParser, conversion, variableName);
var actual = fastDivFreeCharacPolAlg.Run(matrix as ISquareMathMatrix <BigInteger>);
Assert.AreEqual(expected, actual);
}
public void RunTest_IntegerMatrix()
{
// A leitura é realizada por colunas.
var matrixText = "[[1,-1,2], [3,4,5], [2,1,1]]";
var integerDomain = new IntegerDomain();
var variableName = "x";
var integerParser = new IntegerParser <string>();
var conversion = new ElementToElementConversion <int>();
var matrix = TestsHelper.ReadMatrix <int>(
3,
3,
matrixText,
(i, j) => new ArraySquareMathMatrix <int>(i),
integerParser,
true);
var fastDivFreeCharacPolAlg = new FastDivisionFreeCharPolynomCalculator <int>(variableName, integerDomain);
var expected = TestsHelper.ReadUnivarPolynomial("x^3-6*x^2+3*x+18", integerDomain, integerParser, conversion, variableName);
var actual = fastDivFreeCharacPolAlg.Run(matrix as ISquareMathMatrix <int>);
Assert.AreEqual(expected, actual);
}
public void FeedFrowardNeuralNetwork_InternalComputeOutputs()
{
var target = new FeedForwardNeuralNetwork <double>(
new[] { 2L, 3L, 2L });
var parser = new DoubleParser <string>();
var matrix = TestsHelper.ReadMatrix(
5,
5,
"[[-1.0, 1.0, 0.5, 0, 0], [1.0, -1.0, 0.5, 0, 0], [0, 0, 0, -1.0, 2.0], [0, 0, 0, 0.5, -1.5], [0, 0, 0, 1.0, -0.5]]",
(i, j) => new SparseDictionaryMatrix <double>(i, j, 0),
parser,
true);
var vector = TestsHelper.ReadVector(
5,
"[0.5, 0.5, 0.5, 0.5, 0.5]",
new SparseDictionaryMathVectorFactory <double>(),
parser,
true);
var model = new NeuralNetworkModel <double, SparseDictionaryMatrix <double>, IMathVector <double> >(
matrix,
vector);
target.LoadModel(model);
var outputMatrix = target.InternalReserveOutput();
target.InternalComputeLayerOutputs(
new ArrayMathVector <double>(new[] { 1.0, -1.0 }),
outputMatrix,
(d1, d2) =>
{
if (d2 > d1)
{
return(1.0);
}
else
{
return(0.0);
}
},
(u, v, l) =>
{
var result = 0.0;
for (var i = 0L; i < l; ++i)
{
result += u[i] * v[i];
}
return(result);
});
Assert.AreEqual(target.Schema.LongCount() - 1L, outputMatrix.LongLength);
var currOut = outputMatrix[0];
Assert.AreEqual(0.0, currOut[0]);
Assert.AreEqual(1.0, currOut[1]);
Assert.AreEqual(0.0, currOut[2]);
currOut = outputMatrix[1];
Assert.AreEqual(0.0, currOut[0]);
Assert.AreEqual(0.0, currOut[1]);
}
public void FeedFrowardNeuralNetwork_RunSimpleMatrixTest()
{
var target = new FeedForwardNeuralNetwork <double>(
new[] { 2L, 3L, 2L });
var parser = new DoubleParser <string>();
var matrix = TestsHelper.ReadMatrix(
5,
5,
"[[-1.0, 1.0, 0.5, 0, 0], [1.0, -1.0, 0.5, 0, 0], [0, 0, 0, -1.0, 2.0], [0, 0, 0, 0.5, -1.5], [0, 0, 0, 1.0, -0.5]]",
(i, j) => new SparseDictionaryMatrix <double>(i, j, 0),
parser,
true);
var vector = TestsHelper.ReadVector(
5,
"[0.5, 0.5, 0.5, 0.5, 0.5]",
new SparseDictionaryMathVectorFactory <double>(),
parser,
true);
var model = new NeuralNetworkModel <double, SparseDictionaryMatrix <double>, IMathVector <double> >(
matrix,
vector);
target.LoadModel(model);
var actual = target.Run(
new[] { 1.0, 0.0 },
(u, v, l) =>
{
var result = 0.0;
for (var i = 0L; i < l; ++i)
{
result += u[i] * v[i];
}
return(result);
},
(d1, d2) =>
{
if (d2 > d1)
{
return(1.0);
}
else
{
return(0.0);
}
});
var expected = new[] { 0.0, 0.0 };
CollectionAssert.AreEqual(expected, actual);
actual = target.Run(
new[] { 0.0, 1.0 },
(u, v, l) =>
{
var result = 0.0;
for (var i = 0L; i < l; ++i)
{
result += u[i] * v[i];
}
return(result);
},
(d1, d2) =>
{
if (d2 > d1)
{
return(1.0);
}
else
{
return(0.0);
}
});
expected = new[] { 0.0, 1.0 };
CollectionAssert.AreEqual(expected, actual);
actual = target.Run(
new[] { 1.0, -1.0 },
(u, v, l) =>
{
var result = 0.0;
for (var i = 0L; i < l; ++i)
{
result += u[i] * v[i];
}
return(result);
},
(d1, d2) =>
{
if (d2 > d1)
{
return(1.0);
}
else
{
return(0.0);
}
});
expected = new[] { 0.0, 0.0 };
CollectionAssert.AreEqual(expected, actual);
}
public void RunTest_OnlyInequalitiesDouble()
{
var inputConstraintsMatrixText = "[[1,0,3],[0,2,2]]";
var inputConstraintsVectorText = "[4,12,18]";
var inputObjectiveFuncText = "[-3,-5]";
var inverseMatrixText = "[[1,0,0],[0,1,0],[0,0,1]]";
var cost = 0.0;
var nonBasicVariables = new[] { 0, 1 };
var basicVariables = new[] { 2, 3, 4 };
// Leitura da matriz das retrições.
var doubleElementsParser = new DoubleParser <string>();
var inputConstraintsMatrix = TestsHelper.ReadMatrix <double>(
3,
2,
inputConstraintsMatrixText,
(i, j) => new ArrayMathMatrix <double>(i, j),
doubleElementsParser,
true);
// Leitura da matriz inversa.
var inverseMatrix = TestsHelper.ReadMatrix <double>(
3,
3,
inverseMatrixText,
(i, j) => new ArraySquareMathMatrix <double>(i),
doubleElementsParser,
true) as ISquareMathMatrix <double>;
// Leitura do vector de restrições.
var vectorFactory = new ArrayVectorFactory <double>();
var inputConstraintsVector = TestsHelper.ReadVector <double>(
3,
inputConstraintsVectorText,
vectorFactory,
doubleElementsParser,
true);
// Leitura da função objectivo.
var inputObjectiveFunction = TestsHelper.ReadVector <double>(
2,
inputObjectiveFuncText,
vectorFactory,
doubleElementsParser,
true);
// Objecto de entrada para o algoritmo do simplex.
var simplexInput = new RevisedSimplexInput <double, double>(
basicVariables,
nonBasicVariables,
inputObjectiveFunction,
cost,
inputConstraintsMatrix,
inputConstraintsVector,
inverseMatrix);
// Executa o algoritmo do simplex.
var doubleField = new DoubleField();
var target = new RevisedSimplexAlgorithm <double>(Comparer <double> .Default, doubleField);
var actual = target.Run(simplexInput);
// Verifica o custo
Assert.AreEqual(36, actual.Cost);
// Verifica a solução
Assert.AreEqual(2, actual.Solution[0]);
Assert.AreEqual(6, actual.Solution[1]);
}
