public void Statistics_DicModeAlgTest()
{
var target = new DicModeAlgorithm <int>();
var source = new IntegerSequence();
for (var i = 0; i < 1000; ++i)
{
source.Clear();
source.Add(0, i);
var innerActual = target.Run(source);
Assert.AreEqual(source.Count, innerActual.Count);
innerActual.Sort();
for (var j = 0; j < source.Count; ++j)
{
Assert.AreEqual(source[j], innerActual[j]);
}
}
var arraySource = new int[] { 1, 3, 2, 2, 1, 3, 3, 3, 3, 4, 2 };
var expected = 3;
var actual = target.Run(arraySource);
Assert.AreEqual(1, actual.Count);
Assert.AreEqual(expected, actual[0]);
}
public void Statistics_DicMedianAlgTest()
{
var target = new DicMedianAlgorithm <int>();
var source = new IntegerSequence();
var expected = 1;
for (var i = 1; i < 1000; i += 2)
{
source.Clear();
source.Add(1, i);
var actual = target.Run(source);
Assert.AreEqual(expected, actual.Item1);
Assert.AreEqual(expected, actual.Item2);
++expected;
}
expected = 1;
for (var i = 2; i < 1000; i += 2)
{
source.Clear();
source.Add(1, i);
var actual = target.Run(source);
Assert.AreEqual(expected++, actual.Item1);
Assert.AreEqual(expected, actual.Item2);
}
var arraySource = new int[] { 1, 3, 2, 2, 1, 3, 3, 3, 3, 4, 2 };
expected = 3;
var outerActual = target.Run(arraySource);
Assert.AreEqual(expected, outerActual.Item1);
Assert.AreEqual(expected, outerActual.Item2);
arraySource = new int[] { 1, 3, 2, 2, 1, 3, 3, 3, 4, 2 };
expected = 2;
outerActual = target.Run(arraySource);
Assert.AreEqual(expected++, outerActual.Item1);
Assert.AreEqual(expected, outerActual.Item2);
}
/// <summary>
/// Determina o polinómio característico de uma matriz.
/// </summary>
/// <param name="data">A matriz.</param>
/// <returns>O polinómio característico.</returns>
public UnivariatePolynomialNormalForm <ElementType> Run(ISquareMathMatrix <ElementType> data)
{
if (data == null)
{
return(new UnivariatePolynomialNormalForm <ElementType>(this.variableName));
}
else
{
var lines = data.GetLength(0);
if (lines == 0)
{
return(new UnivariatePolynomialNormalForm <ElementType>(this.variableName));
}
else if (lines == 1)
{
var entry = data[0, 0];
var result = new UnivariatePolynomialNormalForm <ElementType>(
this.ring.MultiplicativeUnity,
1,
this.variableName,
this.ring);
result = result.Add(this.ring.AdditiveInverse(entry), 0, this.ring);
return(result);
}
else if (lines == 2)
{
var variablePol = new UnivariatePolynomialNormalForm <ElementType>(
this.ring.MultiplicativeUnity,
1,
this.variableName,
this.ring);
var firstDiagonalElement = variablePol.Add(
this.ring.AdditiveInverse(data[0, 0]),
this.ring);
var secondDiagonalElement = variablePol.Add(
this.ring.AdditiveInverse(data[1, 1]),
this.ring);
var result = firstDiagonalElement.Multiply(secondDiagonalElement, this.ring);
result = result.Add(
this.ring.AdditiveInverse(this.ring.Multiply(data[0, 1], data[1, 0])),
this.ring);
return(result);
}
else
{
var matrixFactory = new ArrayMathMatrixFactory <ElementType>();
var matrixMultiplicator = new MatrixMultiplicationOperation <ElementType>(
matrixFactory, this.ring, this.ring);
var subMatrixSequence = new IntegerSequence();
var singleValueSequence = new IntegerSequence();
IMatrix <ElementType> multiplicationMatrix = new ArrayMathMatrix <ElementType>(
lines + 1,
lines,
this.ring.AdditiveUnity);
subMatrixSequence.Add(1, lines - 1);
singleValueSequence.Add(0);
this.FillMultiplicationMatrix(
data,
data[0, 0],
subMatrixSequence,
singleValueSequence,
matrixMultiplicator,
multiplicationMatrix);
var currentDimension = 1;
while (currentDimension < lines - 1)
{
subMatrixSequence.Clear();
singleValueSequence.Clear();
subMatrixSequence.Add(currentDimension + 1, lines - 1);
singleValueSequence.Add(currentDimension);
var otherLines = lines - currentDimension;
var otherMultiplicationMatrix = new ArrayMathMatrix <ElementType>(
otherLines + 1,
otherLines,
this.ring.AdditiveUnity);
this.FillMultiplicationMatrix(
data,
data[currentDimension, currentDimension],
subMatrixSequence,
singleValueSequence,
matrixMultiplicator,
otherMultiplicationMatrix);
multiplicationMatrix = matrixMultiplicator.Multiply(
multiplicationMatrix,
otherMultiplicationMatrix);
++currentDimension;
}
var lastOtherMultiplicationMatrix = new ArrayMathMatrix <ElementType>(
2,
1,
this.ring.AdditiveUnity);
lastOtherMultiplicationMatrix[0, 0] = this.ring.MultiplicativeUnity;
lastOtherMultiplicationMatrix[1, 0] = this.ring.AdditiveInverse(data[currentDimension, currentDimension]);
multiplicationMatrix = matrixMultiplicator.Multiply(
multiplicationMatrix,
lastOtherMultiplicationMatrix);
var result = new UnivariatePolynomialNormalForm <ElementType>(
multiplicationMatrix[0, 0],
lines,
this.variableName,
this.ring);
for (int i = 1; i <= lines; ++i)
{
result = result.Add(multiplicationMatrix[i, 0], lines - i, this.ring);
}
return(result);
}
}
}
