public void LinearAlgebraComplexMatrix()
{
//using DotNumerics.LinearAlgebra;
//using DotNumerics;
ComplexMatrix A = new ComplexMatrix(3, 3);
A[0, 0] = new Complex(3, 9); A[0, 1] = new Complex(4, 6); A[0, 2] = new Complex(1, 8);
A[1, 0] = new Complex(8, 3); A[1, 1] = new Complex(2, 4); A[1, 2] = new Complex(5, 5);
A[2, 0] = new Complex(2, 5); A[2, 1] = new Complex(7, 2); A[2, 2] = new Complex(5, 5);
EigenSystem es = new EigenSystem();
ComplexMatrix eigenvectors;
ComplexMatrix eigenvalues = es.GetEigenvalues(A, out eigenvectors);
//Ax-lX=0
Complex lambda = eigenvalues[0, 0];
ComplexVector X = eigenvectors.GetColumnVectors()[0];
ComplexMatrix AXmlambdaX = A * X - lambda * X;
ObjectDumper.Write("A=");
ObjectDumper.Write(A.MatrixToString("0.000"));
ObjectDumper.Write("Eigenvalues:");
ObjectDumper.Write(eigenvalues.MatrixToString("0.000"));
ObjectDumper.Write("Eigenvectors:");
ObjectDumper.Write(eigenvectors.MatrixToString("0.000"));
ObjectDumper.Write("A * X - lambda * X = ");
ObjectDumper.Write(AXmlambdaX.MatrixToString("0.000"));
}
/// <summary>
/// Gets a column vector from the matrix.
/// </summary>
/// <param name="Column">Zero-based column index into the matrix.</param>
/// <param name="Vector">New column vector.</param>
public void SetColumn(int Column, IVector Vector)
{
if (Column < 0 || Column >= this.columns)
{
throw new ScriptException("Index out of bounds.");
}
if (Vector.Dimension != this.rows)
{
throw new ScriptException("Vector dimension does not match number of rows");
}
ComplexVector V = Vector as ComplexVector;
if (V == null)
{
throw new ScriptException("Column vectors in a Complex matrix must be Complex vectors.");
}
Complex[] V2 = V.Values;
Complex[,] M = this.Values;
this.elements = null;
int i = 0;
for (i = 0; i < this.rows; i++)
{
M[i, Column] = V2[i];
}
}
/// <summary>
/// Use the Durand-Kerner method to find the roots of a polynomial
/// </summary>
/// <param name="p"></param>
/// <returns></returns>
public static List <Complex> DurandKerner(RealPolynomial p)
{
// According to Wikipedia, radius of initial condition should be 1 + max(|a_1|,|a_2|,...,|a_n-1|)
ComplexVector current = InitialCondition(p.Degree, 1 + p.Coefficients.Select(d => System.Math.Abs(d)).Max());
ComplexVector Iterate(ComplexVector v)
{
ComplexVector newVector = new ComplexVector(v);
for (int i = 0; i < v.Dimension; i++)
{
}
return(v);
}
ComplexVector next = new ComplexVector(current.Dimension);
while (!next.CloseTo(current))
{
next = Iterate(current);
}
return(null);
}
/// <summary>
/// Быстрое кепстральное преобразование
/// </summary>
/// <param name="signal">Сигнал</param>
/// <returns></returns>
public static Vector FKT(ComplexVector signal)
{
ComplexVector spectr = Furie.fft(signal);
Vector Aspectr = MathFunc.ln(spectr.MagnitudeToVector().TransformVector(x => x * x));
return(Furie.fft(Aspectr).RealToVector() / Aspectr.N);
}
/// <summary>
/// Передискретизация сигнала
/// (повышение частоты дискретизации в целое число раз)
/// </summary>
/// <param name="inp">Входной вектор</param>
/// <param name="fd">Старая частота дискретизации</param>
/// <param name="newfd">Новая частота дикретизации</param>
/// <returns>Вектор тойже длительности, что и входной,
/// но с более высокой частотой дискретизации</returns>
public static Vector Perediscr(Vector inp, int fd, int newfd)
{
int k = newfd / fd;
ComplexVector inputSpectr = Furie.fft(inp);
int len = inp.N * (k - 1), lenFull = inp.N * k;
int i = 0;
ComplexVector cV = new ComplexVector(lenFull);
int end = inp.N / 2;
for (; i < end; i++)
{
cV[i] = inputSpectr[i];
}
end = lenFull - inp.N / 2;
for (; i < end; i++)
{
cV[i] = new System.Numerics.Complex(0, 0);
}
for (int j = inp.N / 2; i < lenFull; i++)
{
cV[i] = inputSpectr[j];
}
return(Furie.ifft(cV).RealToVector());
}
// Генерация вектора фич
private Vector GenFeature()
{
ComplexVector cV = Furie.fft(points);
double k, cP1, cP2;
Complex kR;
if (!_isScale)
{
cP1 = cV[0].Magnitude;
cP2 = cV[cV.N - 1].Magnitude;
k = Math.Sqrt(cP1 * cP1 + cP2 * cP2);
cV /= k;
}
if (!_isRot)
{
cP1 = cV[0].Phase;
cP2 = cV[cV.N - 1].Phase;
kR = Complex.Exp(new Complex(0, 1) * (cP2 - cP1) / 2.0);
cV *= kR;
}
if (!_isMove)
{
cV[0] = 0;
}
cV = cV.CutAndZero(n);
Vector modules = cV.MagnitudeToVector();
Vector phases = cV.PhaseToVector();
return(phases);//Vector.Concatinate(new Vector[]{modules, phases});
}
/// <summary>
/// Sets an element in the vector.
/// </summary>
/// <param name="Index">Index.</param>
/// <param name="Value">Element to set.</param>
public void SetElement(int Index, IElement Value)
{
if (Index < 0 || Index >= this.rows)
{
throw new ScriptException("Index out of bounds.");
}
ComplexVector V = Value as ComplexVector;
if (V == null)
{
throw new ScriptException("Row vectors in a Complex matrix are required to be Complex vectors.");
}
if (V.Dimension != this.columns)
{
throw new ScriptException("Dimension mismatch.");
}
Complex[] V2 = V.Values;
Complex[,] M = this.Values;
this.elements = null;
int i;
for (i = 0; i < this.columns; i++)
{
M[Index, i] = V2[i];
}
}
protected override void OnHFieldsAtSiteCalculated(ObservationSite site,
ComplexVector normalField, ComplexVector anomalyField)
{
var e = new MtFieldsAtSiteCalculatedEventArgs(CurrentSource, site, normalField, anomalyField);
HFieldsAtSiteCalculated?.Invoke(this, e);
}
public void LinearAlgebraEigenvaluesAndEigenvectors()
{
//using DotNumerics.LinearAlgebra;
//using DotNumerics;
Matrix A = new Matrix(3, 3);
A[0, 0] = 2; A[0, 1] = 5; A[0, 2] = 3;
A[1, 0] = 1; A[1, 1] = 5; A[1, 2] = 7;
A[2, 0] = 8; A[2, 1] = 2; A[2, 2] = 3;
EigenSystem es = new EigenSystem();
ComplexMatrix eigenvectors;
ComplexMatrix eigenvalues = es.GetEigenvalues(A, out eigenvectors);
//Ax-lX=0
Complex lambda = eigenvalues[0, 0];
ComplexVector X = eigenvectors.GetColumnVectors()[0];
ComplexMatrix AXmlambdaX = A.CopyToComplex() * X - lambda * X;
ObjectDumper.Write("A=");
ObjectDumper.Write(A.MatrixToString("0.000"));
ObjectDumper.Write("Eigenvalues:");
ObjectDumper.Write(eigenvalues.MatrixToString("0.000"));
ObjectDumper.Write("Eigenvectors:");
ObjectDumper.Write(eigenvectors.MatrixToString("0.000"));
ObjectDumper.Write("A * X - lambda * X = ");
ObjectDumper.Write(AXmlambdaX.MatrixToString("0.000"));
}
public void VectorInverse()
{
var expected = new ComplexVector(
new Complex[] { new Complex(-6, 4), new Complex(-7, -3), new Complex(-4.2, 8.1), new Complex(0, 3) });
var result = v1.Inverse;
Assert.AreEqual(expected, result);
}
public void VectorSubtraction()
{
var expected = new ComplexVector(
new Complex[] { new Complex(-10, -6.3), new Complex(7, 10), new Complex(-1.8, -8.1), new Complex(0, 1) });
var result = v1 - v2;
Assert.AreEqual(expected, result);
}
public void MatrixColumn()
{
var expected = new ComplexVector(
new Complex[] { new Complex(5, -4), new Complex(1, -1), new Complex(-4, 2) });
var result = m1.Column(3);
Assert.AreEqual(expected, result);
}
public void MatrixRow()
{
var expected = new ComplexVector(
new Complex[] { new Complex(3, -1), new Complex(1, 4), new Complex(-2, 1), new Complex(1, -1) });
var result = m1.Row(1);
Assert.AreEqual(expected, result);
}
public void VectorConjugate()
{
var expected = new ComplexVector(
new Complex[] { new Complex(6, -3), new Complex(0, 0), new Complex(5, -1), new Complex(4, 0) });
var result = v3.Conjugate;
Assert.AreEqual(expected, result);
}
public void VectorAddition()
{
var expected = new ComplexVector(
new Complex[] { new Complex(22, -1.7), new Complex(7, -4), new Complex(10.2, -8.1), new Complex(0, -7) });
var result = v1 + v2;
Assert.AreEqual(expected, result);
}
public void VectorScalarMultiplication()
{
var expected = new ComplexVector(
new Complex[] { new Complex(12, 21), new Complex(0, 0), new Complex(13, 13), new Complex(12, 8) });
var result = v3.ScalarProduct(c9);
Assert.AreEqual(expected, result);
}
public void TestSerializeComplexVector()
{
ComplexVector before = ComplexVector.Random(10, _random);
ComplexVector after = SerializeDeserialize(before);
Assert.That(after, Is.Not.Null, "Not Null");
Assert.That(after, Is.EqualTo(before), "Equal");
Assert.That(after, NumericIs.AlmostEqualTo(before), "Almost Equal");
}
/// <summary>
/// Арктангенс
/// </summary>
/// <param name="Inp">Комплексный вектор значений для преобразования</param>
public static ComplexVector arctg(ComplexVector Inp)
{
ComplexVector A = new ComplexVector(Inp.N);
for (int i = 0; i < Inp.N; i++)
{
A.DataInVector[i] = Complex.Atan(Inp.DataInVector[i]);
}
return(A);
}
/// <summary>
/// Модуль
/// </summary>
/// <param name="Inp">Комплексный вектор значений для преобразования</param>
public static Vector abs(ComplexVector Inp)
{
Vector A = new Vector(Inp.N);
for (int i = 0; i < Inp.N; i++)
{
A.DataInVector[i] = Complex.Abs(Inp.DataInVector[i]);
}
return(A);
}
public static void Start(REngine engine)
{
Console.WriteLine("\n\nExporting Objects\n\n");
string RCodeString = string.Empty;
//R character vector -- R.NET RDotNet.RDotNet.CharacterVector
Console.WriteLine("\nR character vector\n");
string[] myStringArray = new string[] { "PIDataLink", "PIProcessBook", "PIWebParts" };
CharacterVector myCharacterVector = engine.CreateCharacterVector(myStringArray.AsEnumerable());
engine.SetSymbol("mycharvector", myCharacterVector);
engine.Evaluate("print(mycharvector)");
//R integer vector -- R.NET RDotNet.NumericVector
Console.WriteLine("\nR int vector\n");
int[] myIntegerArray = new int[] { 4, 6, 10, 140, 54, 25 };
IntegerVector myIntegerVector = engine.CreateIntegerVector(myIntegerArray);
engine.SetSymbol("myintvector", myIntegerVector);
engine.Evaluate("print(myintvector)");
//R real vector -- R.NET RDotNet.NumericVector
Console.WriteLine("\nR real vector\n");
NumericVector myNumericVector = engine.CreateNumericVector(new double[] { 30.02, 29.99, 30.11, 29.97, 30.01, 29.99 });
engine.SetSymbol("mynumvector", myNumericVector);
engine.Evaluate("print(mynumvector)");
//R complex vector -- R.NET RDotNet.ComplexVector
Console.WriteLine("\nR complex vector\n");
Complex[] myComplexArray = new Complex[] { Complex.FromPolarCoordinates(10, 0.524), new Complex(12, 6), new Complex(14, 3), (Complex)12.3m, Complex.One + Complex.One };
ComplexVector myComplexVector = engine.CreateComplexVector(myComplexArray);
engine.SetSymbol("mycomplexvector", myComplexVector);
engine.Evaluate("print(mycomplexvector)");
//R raw vector -- R.NET RDotNet.RawVector
Console.WriteLine("\nR raw vector\n");
byte[] myByteArray = System.Text.Encoding.ASCII.GetBytes("u03a0");
RawVector myRawVector = engine.CreateRawVector(myByteArray);
engine.SetSymbol("myrawvector", myRawVector);
engine.Evaluate("print(myrawvector)");
//R logical vector -- R.NET RDotNet.LogicalVector
Console.WriteLine("\nR logical vector\n");
LogicalVector myLogicalVector = engine.CreateLogicalVector(new Boolean[] { true, false, false, false, true });
engine.SetSymbol("mylogicalvector", myLogicalVector);
engine.Evaluate("print(mylogicalvector)");
}
/// <summary>
/// Householder Reflection: Evaluate symmetric? unitary Q such that Q*v = -sigma*||v||*e1
/// </summary>
public static ComplexMatrix Reflection(ComplexVector v)
{
Complex sigma = v[0].Sign;
ComplexVector u = v.Clone();
u[0] += sigma * v.Norm();
ComplexMatrix m = ComplexMatrix.Identity(v.Length, v.Length);
m.MultiplyAccumulateInplace(u.TensorMultiply(u), -2d / u.ScalarMultiply(u));
return m;
}
/// <summary>
/// Аналитический сигнал
/// </summary>
/// <param name="st">Входной сигнал</param>
public static ComplexVector GetAnalSig(Vector st)
{
ComplexVector cv = new ComplexVector(st.N);
Vector stH = ConjugateToTheHilbert(st);
for (int i = 0; i < st.N; i++)
{
cv.DataInVector[i] = new Complex(st.DataInVector[i], stH.DataInVector[i]);
}
return(cv);
}
/// <summary>
/// Gets the eigenvalues of the given matrix, calculated numerically from the
/// characteristic polynomial of this matrix. Continues until all eigenvalues
/// have been found.
/// </summary>
/// <param name="m"></param>
/// <returns></returns>
public static RealVector RealEigenValues(this RealMatrix m)
{
if (!m.IsSquare())
{
throw new IncompatibleOperationException(MatrixOperationType.Eigenvalue);
}
ComplexVector values = new ComplexVector(m.Width);
throw new NotImplementedException();
}
/// <summary>
/// Реализация простого фильтра
/// </summary>
/// <param name="st">Вектор сигнала</param>
/// <param name="kw">АЧХ</param>
/// <returns>Фильтрованный сигнал</returns>
public static Vector Filter(Vector st, Vector kw)
{
Vector newSt = st.CutAndZero(Functions.NextPow2(st.N));
Vector newKw = kw.CutAndZero(newSt.N / 2);
newKw = newKw.AddSimmetr();
//newKw.Visual();
ComplexVector Sw = Furie.fft(newSt);
Sw = Sw * newKw;
newSt = Furie.ifft(Sw).RealToVector();
return(newSt.CutAndZero(st.N));//newSt.N;
}
/// <summary>
/// Householder Reflection: Evaluate symmetric? unitary Q such that Q*v = -sigma*||v||*e1
/// </summary>
public static ComplexMatrix Reflection(ComplexVector v)
{
Complex sigma = v[0].Sign;
ComplexVector u = v.Clone();
u[0] += sigma * v.Norm();
ComplexMatrix m = ComplexMatrix.Identity(v.Length, v.Length);
m.MultiplyAccumulateInplace(u.TensorMultiply(u), -2d / u.ScalarMultiply(u));
return(m);
}
// Дискретное преобразование Фурье
public ComplexVector DFT(Vector vector)
{
ComplexVector complex = new ComplexVector(vector.Count);
for (int i = 0; i < vector.Count; i++)
{
for (int j = 0; j < complex.Count; j++)
{
complex[i] += vector[j] * Complex.Exp(-Complex.ImaginaryOne * 2.0 * Math.PI * i * j / complex.Count);
}
}
return(complex / complex.Count);
}
/// <summary>
/// Evaluates the function on a vector argument.
/// </summary>
/// <param name="Argument">Function argument.</param>
/// <param name="Variables">Variables collection.</param>
/// <returns>Function result.</returns>
public override IElement EvaluateVector(ComplexVector Argument, Variables Variables)
{
int i, c = Argument.Dimension;
Complex[] E = new Complex[c];
Complex[] V = Argument.Values;
for (i = 0; i < c; i++)
{
E[c - i - 1] = V[i];
}
return(new ComplexVector(E));
}
/// <summary>
/// Creates n
/// </summary>
/// <param name="n"></param>
/// <param name="first"></param>
/// <param name="radius"></param>
/// <returns></returns>
private static ComplexVector InitialCondition(int n, double radius, Complex first)
{
ComplexVector vector = new ComplexVector(n);
// A unit vector in the same direction
Complex unit = first / first.Modulus;
for (int i = 0; i < vector.Dimension; i++)
{
vector[i] = radius * (unit ^ i);
}
return(vector);
}
public AllFieldsAtSite(AllFieldsAtSite site)
{
Site = site.Site;
NormalE1 = new ComplexVector(site.NormalE1);
NormalE2 = new ComplexVector(site.NormalE2);
NormalH1 = new ComplexVector(site.NormalH1);
NormalH2 = new ComplexVector(site.NormalH2);
AnomalyE1 = new ComplexVector(site.AnomalyE1);
AnomalyE2 = new ComplexVector(site.AnomalyE2);
AnomalyH1 = new ComplexVector(site.AnomalyH1);
AnomalyH2 = new ComplexVector(site.AnomalyH2);
}
/// <summary>
/// Выделение огибающей на базе квадратурн. сост
/// </summary>
public static Vector OgibNew(Vector t, Vector st, double f0)
{
ComplexVector cV = new ComplexVector(t.N);
for (int i = 0; i < t.N; i++)
{
cV[i] = Complex.Exp(-new Complex(0, 1) * Math.PI * 2 * f0 * t[i]);
}
ComplexVector newSt = st * cV;
return(newSt.RealToVector() + newSt.ImgToVector());
}
public static Tipper CalculateTipper(ComplexVector h1, ComplexVector h2)
{
var determinant = h1.X * h2.Y - h2.X * h1.Y;
var hi11 = h2.Y / determinant;
var hi12 = -h2.X / determinant;
var hi21 = -h1.Y / determinant;
var hi22 = h1.X / determinant;
var wzx = h1.Z * hi11 + h2.Z * hi21;
var wzy = h1.Z * hi12 + h2.Z * hi22;
return(new Tipper(wzx, wzy));
}
public void TestOrthogonalReflectionComplex()
{
StandardDistribution gaussian = new StandardDistribution();
for(int i = 0; i < 100; i++)
{
ComplexVector v = new ComplexVector(new Complex[] { Complex.Random(gaussian), Complex.Random(gaussian), Complex.Random(gaussian), Complex.Random(gaussian) });
ComplexMatrix reflection = Orthogonal.Reflection(v);
ComplexVector res = reflection * v;
Assert.That(reflection.HermitianTranspose() * reflection, NumericIs.AlmostEqualTo(ComplexMatrix.Identity(4, 4)), "orthogonal reflection matrix");
Assert.That(reflection[0, 0].IsReal, "c1 real");
Assert.That(reflection[1, 1].IsReal, "c2 real");
Assert.That(reflection[2, 2].IsReal, "c3 real");
Assert.That(reflection[3, 3].IsReal, "c4 real");
Assert.That(res[0].Modulus, NumericIs.AlmostEqualTo(v.Norm(), 1e-12), "res(1)");
Assert.That(res[1], NumericIs.AlmostEqualTo((Complex) 0, 1e-12), "res(2)");
Assert.That(res[2], NumericIs.AlmostEqualTo((Complex) 0, 1e-12), "res(3)");
Assert.That(res[3], NumericIs.AlmostEqualTo((Complex) 0, 1e-12), "res(4)");
}
}
////OnDemandComputation<ComplexVector> _eigenValuesOnDemand;
/// <summary>
/// Initializes a new instance of the EigenvalueDecomposition class, which check
/// the matrix for symmetry and then construct the eigenvalue decomposition.
/// </summary>
/// <remarks>Provides access to D and V</remarks>
/// <param name="arg">Square matrix</param>
public EigenvalueDecomposition(Matrix arg)
{
double[][] a = arg;
_n = arg.ColumnCount;
_v = Matrix.CreateMatrixData(_n, _n);
_d = new double[_n];
_e = new double[_n];
_isSymmetric = true;
for(int j = 0; (j < _n) & _isSymmetric; j++)
{
for(int i = 0; (i < _n) & _isSymmetric; i++)
{
_isSymmetric &= (a[i][j] == a[j][i]);
}
}
if(_isSymmetric)
{
for(int i = 0; i < _n; i++)
{
for(int j = 0; j < _n; j++)
{
_v[i][j] = a[i][j];
}
}
SymmetricTridiagonalize();
SymmetricDiagonalize();
}
else
{
_h = new double[_n][];
for(int i = 0; i < _n; i++)
{
double[] hi = new double[_n];
double[] ai = a[i];
for(int j = 0; j < _n; j++)
{
hi[j] = ai[j];
}
_h[i] = hi;
}
NonsymmetricReduceToHessenberg();
NonsymmetricReduceHessenberToRealSchur();
}
_eigenValuesReal = new Vector(_d);
_eigenValuesImag = new Vector(_e);
_eigenValues = ComplexVector.Create(_d, _e);
InitOnDemandComputations();
}
public void TestComplexMatrix_Multiplicative()
{
/*
MATLAB:
prod_cc = ca3x2 * cd2x4
prod_cm = ca3x2 * md2x4
prod_cs = ca3x2 * s
prod_cc2 = cc2x2 * cc2x2
prod_cm2 = cc2x2 * mc2x2
prod_cs2 = cc2x2 * s
prod_ccv = ca3x2 * cv2.'
prod_cv = ca3x2 * v2.'
prod_ccvdl = diag(cv2) * cc2x2
prod_ccvdr = cc2x2 * diag(cv2)
prod_cvdl = diag(v2) * cc2x2
prod_cvdr = cc2x2 * diag(v2)
*/
// ComplexMatrix * ComplexMatrix
ComplexMatrix prod_cc = new ComplexMatrix(new Complex[][] {
new Complex[] { -66+12*j, -66+72*j, -66-228*j, -66+672*j },
new Complex[] { -154+268*j, -154+300*j, -154+308*j, -154+368*j },
new Complex[] { -352+424*j, -352+582*j, -352+44*j, -352+1784*j }});
NumericAssert.AreAlmostEqual(prod_cc, ca3x2 * cd2x4, "prod cc 1");
NumericAssert.AreAlmostEqual(prod_cc, ca3x2.Multiply(cd2x4), "prod cc 2");
// ComplexMatrix * Matrix
ComplexMatrix prod_cm = new ComplexMatrix(new Complex[][] {
new Complex[] { 6-12*j, 12-24*j, -18+36*j, 72-144*j },
new Complex[] { 38-76*j,41.2-82.4*j, 42-84*j, 48-96*j },
new Complex[] { 68-136*j, 83.8-167.6*j, 30-60*j, 204-408*j }});
NumericAssert.AreAlmostEqual(prod_cm, ca3x2 * md2x4, "prod cm 1");
NumericAssert.AreAlmostEqual(prod_cm, ca3x2.Multiply(md2x4), "prod cm 2");
// ComplexMatrix * Complex
ComplexMatrix prod_cs = new ComplexMatrix(new Complex[][] {
new Complex[] { 18-6*j, 0 },
new Complex[] { 6-2*j,36-12*j },
new Complex[] { 42-14*j, 54-18*j }});
NumericAssert.AreAlmostEqual(prod_cs, ca3x2 * s, "prod cs 1");
NumericAssert.AreAlmostEqual(prod_cs, ca3x2.Multiply(s), "prod cs 2");
// ComplexMatrix * ComplexMatrix (Square)
ComplexMatrix prod_cc2 = new ComplexMatrix(new Complex[][] {
new Complex[] { -1232-924*j, -1368-1026*j },
new Complex[] { -1520-1140*j, -1688-1266*j }});
NumericAssert.AreAlmostEqual(prod_cc2, cc2x2 * cc2x2, "prod cc2 1");
NumericAssert.AreAlmostEqual(prod_cc2, cc2x2.Multiply(cc2x2), "prod cc2 2");
ComplexMatrix prod_cc2_inplace = cc2x2.Clone();
prod_cc2_inplace.MultiplyInplace(cc2x2);
NumericAssert.AreAlmostEqual(prod_cc2, prod_cc2_inplace, "prod cc2 3");
// ComplexMatrix * Matrix (Square)
ComplexMatrix prod_cm2 = new ComplexMatrix(new Complex[][] {
new Complex[] { 35-105*j, 52-156*j },
new Complex[] { 43-129*j, 64-192*j }});
NumericAssert.AreAlmostEqual(prod_cm2, cc2x2 * mc2x2, "prod cm2 1");
NumericAssert.AreAlmostEqual(prod_cm2, cc2x2.Multiply(mc2x2), "prod cm2 2");
ComplexMatrix prod_cm2_inplace = cc2x2.Clone();
prod_cm2_inplace.MultiplyInplace(mc2x2);
NumericAssert.AreAlmostEqual(prod_cm2, prod_cm2_inplace, "prod cm2 3");
// ComplexMatrix * Complex (Square)
ComplexMatrix prod_cs2 = new ComplexMatrix(new Complex[][] {
new Complex[] { 32-16*j, 36-18*j },
new Complex[] { 40-20*j, 44-22*j }});
NumericAssert.AreAlmostEqual(prod_cs2, cc2x2 * s, "prod cs2 1");
NumericAssert.AreAlmostEqual(prod_cs2, cc2x2.Multiply(s), "prod cs2 2");
ComplexMatrix prod_cs2_inplace = cc2x2.Clone();
prod_cs2_inplace.MultiplyInplace(s);
NumericAssert.AreAlmostEqual(prod_cs2, prod_cs2_inplace, "prod cs2 3");
// ComplexMatrix * ComplexVector (Column)
ComplexVector prod_ccv = new ComplexVector(new Complex[] { 42 - 54 * j, 62 + 66 * j, 170 });
NumericAssert.AreAlmostEqual(prod_ccv, ca3x2 * cv2, "prod ccv 1");
NumericAssert.AreAlmostEqual(prod_ccv, ca3x2.MultiplyRightColumn(cv2), "prod ccv 2");
// ComplexMatrix * Vector (Column)
ComplexVector prod_cv = new ComplexVector(new Complex[] { 30 - 60 * j, -14 + 28 * j, 34 - 68 * j });
NumericAssert.AreAlmostEqual(prod_cv, ca3x2 * v2, "prod cv 1");
NumericAssert.AreAlmostEqual(prod_cv, ca3x2.MultiplyRightColumn(v2), "prod cv 2");
// ComplexMatrix * ComplexVector (Diagonal, Left)
ComplexMatrix prod_ccvdl = new ComplexMatrix(new Complex[][] {
new Complex[] { 64-112*j, 72-126*j },
new Complex[] { 70+90*j, 77+99*j }});
NumericAssert.AreAlmostEqual(prod_ccvdl, cc2x2.MultiplyLeftDiagonal(cv2), "prod ccv dl 1");
ComplexMatrix prod_ccvdl_inplace = cc2x2.Clone();
prod_ccvdl_inplace.MultiplyLeftDiagonalInplace(cv2);
NumericAssert.AreAlmostEqual(prod_ccvdl, prod_ccvdl_inplace, "prod ccv dl 2");
NumericAssert.AreAlmostEqual(prod_ccvdl, ComplexMatrix.Diagonal(cv2) * cc2x2, "prod ccv dl 3");
// ComplexMatrix * Vector (Diagonal, Left)
ComplexMatrix prod_cvdl = new ComplexMatrix(new Complex[][] {
new Complex[] { 40-120*j, 45-135*j },
new Complex[] { -20+60*j, -22+66*j }});
NumericAssert.AreAlmostEqual(prod_cvdl, cc2x2.MultiplyLeftDiagonal(v2), "prod cv dl 1");
ComplexMatrix prod_cvdl_inplace = cc2x2.Clone();
prod_cvdl_inplace.MultiplyLeftDiagonalInplace(v2);
NumericAssert.AreAlmostEqual(prod_cvdl, prod_cvdl_inplace, "prod cv dl 2");
// ComplexMatrix * ComplexVector (Diagonal, Right)
ComplexMatrix prod_ccvdr = new ComplexMatrix(new Complex[][] {
new Complex[] { 64-112*j, 63+81*j },
new Complex[] { 80-140*j, 77+99*j }});
NumericAssert.AreAlmostEqual(prod_ccvdr, cc2x2.MultiplyRightDiagonal(cv2), "prod ccv dr 1");
ComplexMatrix prod_ccvdr_inplace = cc2x2.Clone();
prod_ccvdr_inplace.MultiplyRightDiagonalInplace(cv2);
NumericAssert.AreAlmostEqual(prod_ccvdr, prod_ccvdr_inplace, "prod ccv dr 2");
NumericAssert.AreAlmostEqual(prod_ccvdr, cc2x2 * ComplexMatrix.Diagonal(cv2), "prod ccv dr 3");
// ComplexMatrix * Vector (Diagonal, Right)
ComplexMatrix prod_cvdr = new ComplexMatrix(new Complex[][] {
new Complex[] { 40-120*j, -18+54*j },
new Complex[] { 50-150*j, -22+66*j }});
NumericAssert.AreAlmostEqual(prod_cvdr, cc2x2.MultiplyRightDiagonal(v2), "prod cv dr 1");
ComplexMatrix prod_cvdr_inplace = cc2x2.Clone();
prod_cvdr_inplace.MultiplyRightDiagonalInplace(v2);
NumericAssert.AreAlmostEqual(prod_cvdr, prod_cvdr_inplace, "prod cv dr 2");
}
public void TestComplexMatrix_Setup()
{
/*
MATLAB:
ma3x2 = [1 -2;-1 4;5 7]
mb3x2 = [10 2.5;-3 -1.5;19 -6]
mc2x2 = [1 2;3 4]
md2x4 = [1 2 -3 12;3 3.1 4 2]
ra3x2 = ma3x2 + 2
rb3x2 = mb3x2 - 1
rc2x2 = mc2x2 + 5
rd2x4 = md2x4 * 2
ia3x2 = (ra3x2 * 2) * j
ib3x2 = (rb3x2 * 3 + 1) * j
ic2x2 = (rc2x2 + 2) * j
id2x4 = (rd2x4 - 5) * j
ca3x2 = 2*ra3x2 - 2*ia3x2
cb3x2 = rb3x2 + 3*ib3x2
cc2x2 = rc2x2 + 2 - 3*ic2x2
cd2x4 = -2*rd2x4 + id2x4 + 1-j
v2 = [5 -2]
cv2 = [5+j, -2+3j]
*/
ma3x2 = new Matrix(new double[][] {
new double[] { 1, -2 },
new double[] { -1, 4 },
new double[] { 5, 7 }});
mb3x2 = new Matrix(new double[][] {
new double[] { 10, 2.5 },
new double[] { -3, -1.5 },
new double[] { 19, -6 }});
mc2x2 = new Matrix(new double[][] {
new double[] { 1, 2 },
new double[] { 3, 4 }});
md2x4 = new Matrix(new double[][] {
new double[] { 1, 2, -3, 12 },
new double[] { 3, 3.1, 4, 2 }});
ra3x2 = ComplexMatrix.Create(ma3x2) + 2;
rb3x2 = ComplexMatrix.Create(mb3x2) - 1;
rc2x2 = ComplexMatrix.Create(mc2x2) + 5;
rd2x4 = ComplexMatrix.Create(md2x4) * 2;
ia3x2 = (ra3x2 * 2) * j;
ib3x2 = (rb3x2 * 3 + 1) * j;
ic2x2 = (rc2x2 + 2) * j;
id2x4 = (rd2x4 - 5) * j;
ca3x2 = 2 * ra3x2 - 2 * ia3x2;
cb3x2 = rb3x2 + 3 * ib3x2;
cc2x2 = rc2x2 + 2 - 3 * ic2x2;
cd2x4 = -2 * rd2x4 + id2x4 + (1 - j);
v2 = new Vector(new double[] { 5, -2 });
cv2 = new ComplexVector(new Complex[] { 5 + j, -2 + 3 * j });
}
public static Animation ShowMatrixMultiplication(TimeSpan period,
Rect pos,
ComplexMatrix u,
ComplexVector v,
Ani<Brush> or,
Ani<Brush> blu,
Ani<Brush> bla)
{
var d = Math.Min(pos.Width/(u.Columns.Count + 2), pos.Height/u.Rows.Count)/2;
pos = new Rect(pos.TopLeft, new Size(d * (u.Columns.Count + 2)*2, d*u.Rows.Count*2));
var ur = d;
var animation = new Animation {
new RectDesc(new Rect(pos.X + d * 2, pos.Y, pos.Width - d * 4, pos.Height),
Brushes.Black,
strokeThickness: 0.6,
dashed: 5),
new RectDesc(new Rect(pos.X, pos.Y, d * 2, pos.Height),
Brushes.Black,
strokeThickness: 0.6,
dashed: 5),
new RectDesc(new Rect(pos.Right - d*2, pos.Y, d * 2, pos.Height),
Brushes.Black,
strokeThickness: 0.6,
dashed: 5)
};
var per = animation.Periodic(period);
var s0 = per.LimitedSameTime(0.Seconds(), period.DividedBy(4));
foreach (var r in u.Rows.Count.Range()) {
var pp = s0.Proper;
// input vector
var p1 = pos.TopLeft + new Vector(d, d + r*d*2);
var p2 = pos.TopLeft + new Vector(d*3 + r*d*2, 0);
var p3 = pos.TopLeft + new Vector(d*3 + r*d*2, u.Rows.Count*d*2);
s0.Add(ShowComplex(pp.Combine(blu, (p, b) => b.LerpToTransparent(p.SmoothTransition(0, 0, 1))),
pp.Combine(bla, (p, b) => b.LerpToTransparent(p.SmoothTransition(0, 0, 1))),
v.Values[r],
pp.Select(p => p.SmoothTransition(p1, p1, p2, p3)),
ur,
rotation: pp.Select(t => Turn.FromNaturalAngle(t.SmoothTransition(0, Math.PI/2, Math.PI/2)))));
foreach (var c in u.Columns.Count.Range()) {
// vector copied into matrix
s0.Add(ShowComplex(pp.Combine(blu, (p, b) => b.LerpToTransparent(p.SmoothTransition(1, 1, 0))),
pp.Combine(bla, (p, b) => b.LerpToTransparent(p.SmoothTransition(1, 1, 0))),
v.Values[c],
(pos.TopLeft + new Vector(d*3 + c*d*2, d + r*d*2)),
ur,
Brushes.Transparent,
rotation: Turn.FromNaturalAngle(Math.PI/2)));
// matrix
s0.Add(ShowComplex(pp.Combine(or, (p, b) => b.LerpToTransparent(p.SmoothTransition(0, 0, 0))),
pp.Combine(bla, (p, b) => b.LerpToTransparent(p.SmoothTransition(0, 0, 0))),
u.Rows[r][c],
(pos.TopLeft + new Vector(d*3 + c*d*2, d + r*d*2)),
ur));
}
}
var s1 = per.LimitedSameTime(period.Times(0.25), period.Times(0.5));
foreach (var r in u.Rows.Count.Range()) {
foreach (var c in u.Columns.Count.Range()) {
s1.Add(
ShowComplexProduct(
blu,
or,
bla,
bla,
v.Values[c],
u.Rows[r][c],
(pos.TopLeft + new Vector(d*3 + c*d*2, d + r*d*2)),
ur,
s1.Proper));
}
}
var s2 = per.LimitedSameTime(period.Times(0.5), period);
foreach (var r in u.Rows.Count.Range()) {
s2.Add(
ShowComplexSum(
blu,
blu,
bla,
u.Rows[r].Count.Range()
.Select(e => u.Rows[r][e]*v.Values[e])
.Select(e => new ConstantAni<Complex>(e)),
(pos.TopLeft + new Vector(d*3, d + r*d*2)),
(pos.TopLeft + new Vector(d*3 + u.Columns.Count*d*2, d + r*d*2)),
new Vector(d*2, 0),
ur,
s2.Proper));
}
return animation;
}
public static Animation CreateTelepathyAnimation()
{
var i = Complex.ImaginaryOne;
var beamSplit = ComplexMatrix.FromSquareData(
1, i,
i, 1) / Math.Sqrt(2);
var swap = ComplexMatrix.FromSquareData(
1, 0, 0, 0,
0, 0, 1, 0,
0, 1, 0, 0,
0, 0, 0, 1);
var controlledNot2When1 = ComplexMatrix.FromSquareData(
1, 0, 0, 0,
0, 1, 0, 0,
0, 0, 0, 1,
0, 0, 1, 0);
var H = ComplexMatrix.MakeUnitaryHadamard(1);
var v = new ComplexVector(new Complex[] { 0.5, 0, 0, 0, 0, 0.5, 0, 0, 0, 0, 0.5, 0, 0, 0, 0, 0.5 });
var controlledNot1When2 = ComplexMatrix.FromSquareData(
1, 0, 0, 0,
0, 0, 0, 1,
0, 0, 1, 0,
0, 1, 0, 0);
var gates = new[] {
H.TensorProduct(ComplexMatrix.MakeIdentity(2)).TensorProduct(ComplexMatrix.MakeIdentity(4)), //alice bottom 1
ComplexMatrix.MakeIdentity(4).TensorProduct(controlledNot1When2), // bob left 1
ComplexMatrix.MakeIdentity(4).TensorProduct(beamSplit.TensorSquare()), // bob left 2
controlledNot2When1.TensorProduct(ComplexMatrix.MakeIdentity(4)), //alice bottom 2
ComplexMatrix.MakeIdentity(4).TensorProduct(swap), // bob left 3
H.TensorProduct(ComplexMatrix.MakeIdentity(2)).TensorProduct(ComplexMatrix.MakeIdentity(4)) //alice bottom 3
};
var ackGates = gates.Stream(ComplexMatrix.MakeIdentity(16), (a, m) => m * a, streamSeed: true).ToArray();
var start = new Point(200, 200);
return new Animation {
MakeTransformAnimation(
start,
v.Values,
Ani.Anon(t => {
var p = t.TotalSeconds%(ackGates.Length + 4) - 1;
var pi = (int)Math.Floor(p);
var pd = p - pi;
pd = (pd*2 - 1).Clamp(0, 1);
var g1 = ackGates[pi.Clamp(0, ackGates.Length - 1)];
var g2 = ackGates[(pi + 1).Clamp(0, ackGates.Length - 1)];
return (g1*(1 - pd) + g2*pd);
}),
new[] {
"c₁ (win)", "c₂ (win)", "c₃", "c₄", "c₅", "c₆", "c₇ (win)", "c₈ (win)", "c₉", "c₁₀", "c₁₁ (win)", "c₁₂ (win)", "c₁₃ (win)", "c₁₄ (win)",
"c₁₅", "c₁₆"
}),
MakeAxies(new Point(350, 295)),
new TextDesc("Quantum Pseudotelepathy", new Point(400/2, 5), new Point(0.5, 0), fontSize: 20),
new TextDesc("Applying Alice's and Bob's Gates for Bottom Left Case", new Point(400/2, 30), new Point(0.5, 0)),
new TextDesc("(makes about as much sense as [insert political joke])", new Point(400/2, 50), new Point(0.5, 0), fontSize: 8),
};
}
public static Animation CreateComplexTransformationAnimation()
{
var matrixFill = (Brush)Brushes.Orange.LerpToTransparent(0.5);
var vectorFill = (Brush)Brushes.Blue.LerpToTransparent(0.7);
var s = new Complex(Math.Sqrt(0.5), 0);
var si = new Complex(0, s.Real);
var c1 = Complex.FromPolarCoordinates(Math.Sqrt(0.75), 0);
var c2 = Complex.FromPolarCoordinates(Math.Sqrt(0.2), Math.PI / 4);
var m = ComplexMatrix.FromSquareData(s, si, -s, si);
var v = new ComplexVector(new[] { c1, c2 });
var u = 50;
var animation = new Animation {
new TextDesc("Matrix Multiplication with Complex Numbers",
new Point(25 + u*(v.Values.Count + 2), 5),
new Point(0.5, 0),
fontSize: 15,
foreground: Brushes.Gray),
};
var r = new Rect(25, 25, u*2*(v.Values.Count + 2), u*2*v.Values.Count);
var p = animation.Dilated(0.5.Seconds()).Periodic(10.Seconds());
var qx1 = p.Proper.Select(e => (e * 10 - 9).Clamp(0, 1));
var qx2 = p.Proper.Select(e => ((e - 0.6) * 10).Clamp(0, 1));
p.Add(ShowMatrixMultiplication(
10.Seconds(),
r,
m,
v,
qx1.Select(matrixFill.LerpToTransparent),
qx1.Select(vectorFill.LerpToTransparent),
qx1.Select(x => (Brush)Brushes.Black.LerpToTransparent(x))));
p.LimitedSameTime(0.Seconds(), 10.Seconds()).Add(ShowMatrixMultiplication(
100000000.Seconds(),
r,
m,
v,
qx2.Select(x => matrixFill.LerpToTransparent(1 - x)),
qx2.Select(x => vectorFill.LerpToTransparent(1 - x)),
qx2.Select(x => (Brush)Brushes.Black.LerpToTransparent(1 - x))));
return animation;
}
public void Setup()
{
// MATLAB: ma3x2 = [1 -2;-1 4;5 7]
_ma3X2 = new Matrix(new double[][] {
new double[] { 1, -2 },
new double[] { -1, 4 },
new double[] { 5, 7 }
});
// MATLAB: mb3x2 = [10 2.5;-3 -1.5;19 -6]
_mb3X2 = new Matrix(new double[][] {
new double[] { 10, 2.5 },
new double[] { -3, -1.5 },
new double[] { 19, -6 }
});
// MATLAB: mc2x2 = [1 2;3 4]
_mc2X2 = new Matrix(new double[][] {
new double[] { 1, 2 },
new double[] { 3, 4 }
});
// MATLAB: md2x4 = [1 2 -3 12;3 3.1 4 2]
_md2X4 = new Matrix(new double[][] {
new double[] { 1, 2, -3, 12 },
new double[] { 3, 3.1, 4, 2 }
});
// MATLAB: ra3x2 = ma3x2 + 2
_ra3X2 = ComplexMatrix.Create(_ma3X2) + 2;
// MATLAB: rb3x2 = mb3x2 - 1
_rb3X2 = ComplexMatrix.Create(_mb3X2) - 1;
// MATLAB: rc2x2 = mc2x2 + 5
_rc2X2 = ComplexMatrix.Create(_mc2X2) + 5;
// MATLAB: rd2x4 = md2x4 * 2
_rd2X4 = ComplexMatrix.Create(_md2X4) * 2;
// MATLAB: ia3x2 = (ra3x2 * 2) * j
_ia3X2 = (_ra3X2 * 2) * j;
// MATLAB: ib3x2 = (rb3x2 * 3 + 1) * j
_ib3X2 = ((_rb3X2 * 3) + 1) * j;
// MATLAB: ic2x2 = (rc2x2 + 2) * j
_ic2X2 = (_rc2X2 + 2) * j;
// MATLAB: id2x4 = (rd2x4 - 5) * j
_id2X4 = (_rd2X4 - 5) * j;
// MATLAB: ca3x2 = 2*ra3x2 - 2*ia3x2
_ca3X2 = (2 * _ra3X2) - (2 * _ia3X2);
// MATLAB: cb3x2 = rb3x2 + 3*ib3x2
_cb3X2 = _rb3X2 + (3 * _ib3X2);
// MATLAB: cc2x2 = rc2x2 + 2 - 3*ic2x2
_cc2X2 = _rc2X2 + 2 - (3 * _ic2X2);
// MATLAB: cd2x4 = -2*rd2x4 + id2x4 + 1-j
_cd2X4 = (-2 * _rd2X4) + _id2X4 + (1 - j);
// MATLAB: v2 = [5 -2]
_v2 = new Vector(new double[] { 5, -2 });
// MATLAB: cv2 = [5+j, -2+3j]
_cv2 = new ComplexVector(new Complex[] { 5 + j, -2 + (3 * j) });
}
EigenvalueDecomposition(
Matrix Arg
)
{
double[][] A = Arg;
n = Arg.ColumnCount;
V = Matrix.CreateMatrixData(n, n);
d = new double[n];
e = new double[n];
isSymmetric = true;
for(int j = 0; (j < n) & isSymmetric; j++)
{
for(int i = 0; (i < n) & isSymmetric; i++)
{
isSymmetric &= (A[i][j] == A[j][i]);
}
}
if(isSymmetric)
{
for(int i = 0; i < n; i++)
{
for(int j = 0; j < n; j++)
{
V[i][j] = A[i][j];
}
}
SymmetricTridiagonalize();
SymmetricDiagonalize();
}
else
{
H = new double[n][];
for(int i = 0; i < n; i++)
{
double[] Hi = new double[n];
double[] Ai = A[i];
for(int j = 0; j < n; j++)
{
Hi[j] = Ai[j];
}
H[i] = Hi;
}
NonsymmetricReduceToHessenberg();
NonsymmetricReduceHessenberToRealSchur();
}
_eigenValuesReal = new Vector(d);
_eigenValuesImag = new Vector(e);
_eigenValues = ComplexVector.Create(d, e);
InitOnDemandComputations();
}
EigenvalueDecomposition(
double[] d,
double[] e
)
{
// TODO: unit test missing for EigenvalueDecomposition constructor.
n = d.Length;
V = Matrix.CreateMatrixData(n, n);
this.d = new double[n];
Array.Copy(d, 0, this.d, 0, n);
this.e = new double[n];
Array.Copy(e, 0, this.e, 1, n - 1);
for(int i = 0; i < n; i++)
{
V[i][i] = 1;
}
SymmetricDiagonalize();
_eigenValuesReal = new Vector(this.d);
_eigenValuesImag = new Vector(this.e);
_eigenValues = ComplexVector.Create(this.d, this.e);
InitOnDemandComputations();
}
/// <summary>
/// Initializes a new instance of the EigenvalueDecomposition class,
/// by decomposing symmetrical, tridiagonal matrices.
/// </summary>
public EigenvalueDecomposition(
double[] d,
double[] e)
{
/* TODO: unit test missing for EigenvalueDecomposition constructor. */
_n = d.Length;
_v = Matrix.CreateMatrixData(_n, _n);
_d = new double[_n];
Array.Copy(d, 0, _d, 0, _n);
_e = new double[_n];
Array.Copy(e, 0, _e, 1, _n - 1);
for(int i = 0; i < _n; i++)
{
_v[i][i] = 1;
}
SymmetricDiagonalize();
_eigenValuesReal = new Vector(_d);
_eigenValuesImag = new Vector(_e);
_eigenValues = ComplexVector.Create(_d, _e);
InitOnDemandComputations();
}
/// <summary>
/// Givens Rotation: Evaluate unitary G = [c,s;-s,c] such that |G*v| = [norm(v);0] and c is real.
/// </summary>
public static ComplexMatrix Rotation(ComplexVector v)
{
double c;
Complex s;
Rotation(v[0], v[1], out c, out s);
Complex[][] m = ComplexMatrix.CreateMatrixData(2, 2);
m[0][0] = c;
m[0][1] = s;
m[1][0] = -s.Conjugate;
m[1][1] = c;
return new ComplexMatrix(m);
}
private static Animation MakeTransformAnimation(Point center, IEnumerable<Complex> input, Ani<ComplexMatrix> transform, string[] labels = null)
{
var vector = new ComplexVector(input);
var aniValues = from m in transform
select (m * vector).Values;
var valuesAni = vector.Values.Count.Range().Select(i => from values in aniValues
select values[i]);
var colors = new[] { 0x3366CC, 0xdc3912, 0xff9900, 0x109618, 0x990099, 0x0099c6, 0xdd4477, 0x66aa00,
0xb82e2e, 0x316395, 0x994499, 0x22aa99, 0xaaaa11, 0x6633cc, 0xe67300, 0x8b0707}
.Select(e => Color.FromRgb((byte)(e >> 16), (byte)(e >> 8), (byte)(e >> 0)))
.Select(e => new SolidColorBrush(e))
.Cast<Brush>()
.ToArray();
labels = labels ?? new[] { "c₁", "c₂", "c₃", "c₄", "c₅", "c₆", "c₇", "c₈", "c₉", "c₁₀", "c₁₁", "c₁₂", "c₁₃", "c₁₄", "c₁₅", "c₁₆" };
var labelledAniValues = labels
.Zip(valuesAni, (label, v) => new KeyValuePair<string, Ani<Complex>>(label, v))
.ToDictionary(e => e.Key, e => e.Value);
var ani = new Animation {
MakeSuperpositionAnimation(
center,
labelledAniValues,
colors)
};
return ani;
}
public static Animation CreateFullGroverAnimation(int numWire)
{
var vectorFill = (Brush)Brushes.Blue.LerpToTransparent(0.7);
var H = ComplexMatrix.MakeUnitaryHadamard(numWire);
var I2 = ComplexMatrix.MakeSinglePhaseInverter(1 << numWire, 0);
var D = H * I2 * H;
var U = ComplexMatrix.MakeSinglePhaseInverter(1 << numWire, 1);
var S = U*D;
var input = new ComplexVector(new Complex[] {1}.Concat(Complex.Zero.Repeat((1 << numWire) - 1)).ToArray());
var steps = (int)Math.Round(Math.PI/4*Math.Sqrt(1 << numWire));
var GS = new CircuitOperationWithStyle {
Description = "Step",
MinWire = 0,
MaxWire = numWire-1,
Operation = S,
Width = 80,
WireHints=new[] {"Off"}.Concat("On".Repeat(numWire-1)).ToArray()
};
return CreateCircuitAnimation(
900,
20.Seconds(),
new[] {
new CircuitOperationWithStyle {
Description="H",
MinWire=0,
MaxWire=numWire-1,
Operation=H,
Width=80
}
}.Concat(GS.Repeat(steps)).ToArray(),
ReadOnlyList.Repeat(
new CircuitInputWithStyle {
Value = input,
Color = vectorFill
},
steps+2),
"Grover's Algorithm",
showMatrix: false,
wireSpace: numWire * 80 / 3.0);
}
public static void AreAlmostEqual(ComplexVector expected, ComplexVector actual, double relativeAccuracy, string message)
{
Assert.DoAssert(new AlmostEqualAsserter(expected.Norm1(), actual.Norm1(), (expected - actual).Norm1(), relativeAccuracy, message));
}
public void ComplexMatrixMultiplication()
{
/*
MATLAB:
prod_cc = ca3x2 * cd2x4
prod_cm = ca3x2 * md2x4
prod_cs = ca3x2 * s
prod_cc2 = cc2x2 * cc2x2
prod_cm2 = cc2x2 * mc2x2
prod_cs2 = cc2x2 * s
prod_ccv = ca3x2 * cv2.'
prod_cv = ca3x2 * v2.'
prod_ccvdl = diag(cv2) * cc2x2
prod_ccvdr = cc2x2 * diag(cv2)
prod_cvdl = diag(v2) * cc2x2
prod_cvdr = cc2x2 * diag(v2)
*/
// ComplexMatrix * ComplexMatrix
ComplexMatrix prodCmCm = new ComplexMatrix(new Complex[][] {
new Complex[] { -66+(12*j), -66+(72*j), -66-(228*j), -66+(672*j) },
new Complex[] { -154+(268*j), -154+(300*j), -154+(308*j), -154+(368*j) },
new Complex[] { -352+(424*j), -352+(582*j), -352+(44*j), -352+(1784*j) }
});
Assert.That(_ca3X2 * _cd2X4, NumericIs.AlmostEqualTo(prodCmCm), "prod cc 1");
Assert.That(_ca3X2.Multiply(_cd2X4), NumericIs.AlmostEqualTo(prodCmCm), "prod cc 2");
// ComplexMatrix * Matrix
ComplexMatrix prodCmM = new ComplexMatrix(new Complex[][] {
new Complex[] { 6-(12*j), 12-(24*j), -18+(36*j), 72-(144*j) },
new Complex[] { 38-(76*j), 41.2-(82.4*j), 42-(84*j), 48-(96*j) },
new Complex[] { 68-(136*j), 83.8-(167.6*j), 30-(60*j), 204-(408*j) }
});
Assert.That(_ca3X2 * _md2X4, NumericIs.AlmostEqualTo(prodCmM), "prod cm 1");
Assert.That(_ca3X2.Multiply(_md2X4), NumericIs.AlmostEqualTo(prodCmM), "prod cm 2");
// ComplexMatrix * Complex
ComplexMatrix prodCmC = new ComplexMatrix(new Complex[][] {
new Complex[] { 18-(6*j), 0 },
new Complex[] { 6-(2*j), 36-(12*j) },
new Complex[] { 42-(14*j), 54-(18*j) }
});
Assert.That(_ca3X2 * _s, NumericIs.AlmostEqualTo(prodCmC), "prod cs 1");
Assert.That(_ca3X2.Multiply(_s), NumericIs.AlmostEqualTo(prodCmC), "prod cs 2");
// ComplexMatrix * ComplexMatrix (Square)
ComplexMatrix prodCmCmSquare = new ComplexMatrix(new Complex[][] {
new Complex[] { -1232-(924*j), -1368-(1026*j) },
new Complex[] { -1520-(1140*j), -1688-(1266*j) }
});
Assert.That(_cc2X2 * _cc2X2, NumericIs.AlmostEqualTo(prodCmCmSquare), "prod cc2 1");
Assert.That(_cc2X2.Multiply(_cc2X2), NumericIs.AlmostEqualTo(prodCmCmSquare), "prod cc2 2");
ComplexMatrix prodCmCmSquareInplace = _cc2X2.Clone();
prodCmCmSquareInplace.MultiplyInplace(_cc2X2);
Assert.That(prodCmCmSquareInplace, NumericIs.AlmostEqualTo(prodCmCmSquare), "prod cc2 3");
// ComplexMatrix * Matrix (Square)
ComplexMatrix prodCmMSquare = new ComplexMatrix(new Complex[][] {
new Complex[] { 35-(105*j), 52-(156*j) },
new Complex[] { 43-(129*j), 64-(192*j) }
});
Assert.That(_cc2X2 * _mc2X2, NumericIs.AlmostEqualTo(prodCmMSquare), "prod cm2 1");
Assert.That(_cc2X2.Multiply(_mc2X2), NumericIs.AlmostEqualTo(prodCmMSquare), "prod cm2 2");
ComplexMatrix prodCmMSquareInplace = _cc2X2.Clone();
prodCmMSquareInplace.MultiplyInplace(_mc2X2);
Assert.That(prodCmMSquareInplace, NumericIs.AlmostEqualTo(prodCmMSquare), "prod cm2 3");
// ComplexMatrix * Complex (Square)
ComplexMatrix prodCmCSquare = new ComplexMatrix(new Complex[][] {
new Complex[] { 32-(16*j), 36-(18*j) },
new Complex[] { 40-(20*j), 44-(22*j) }
});
Assert.That(_cc2X2 * _s, NumericIs.AlmostEqualTo(prodCmCSquare), "prod cs2 1");
Assert.That(_cc2X2.Multiply(_s), NumericIs.AlmostEqualTo(prodCmCSquare), "prod cs2 2");
ComplexMatrix prodCmCSquareInplace = _cc2X2.Clone();
prodCmCSquareInplace.MultiplyInplace(_s);
Assert.That(prodCmCSquareInplace, NumericIs.AlmostEqualTo(prodCmCSquare), "prod cs2 3");
// ComplexMatrix * ComplexVector (Column)
ComplexVector prodCmCvc = new ComplexVector(new Complex[] { 42 - (54 * j), 62 + (66 * j), 170 });
Assert.That(_ca3X2 * _cv2, NumericIs.AlmostEqualTo(prodCmCvc), "prod ccv 1");
Assert.That(_ca3X2.MultiplyRightColumn(_cv2), NumericIs.AlmostEqualTo(prodCmCvc), "prod ccv 2");
// ComplexMatrix * Vector (Column)
ComplexVector prodCmVc = new ComplexVector(new Complex[] { 30 - (60 * j), -14 + (28 * j), 34 - (68 * j) });
Assert.That(_ca3X2 * _v2, NumericIs.AlmostEqualTo(prodCmVc), "prod cv 1");
Assert.That(_ca3X2.MultiplyRightColumn(_v2), NumericIs.AlmostEqualTo(prodCmVc), "prod cv 2");
// ComplexMatrix * ComplexVector (Diagonal, Left)
ComplexMatrix prodCmCvdl = new ComplexMatrix(new Complex[][] {
new Complex[] { 64-(112*j), 72-(126*j) },
new Complex[] { 70+(90*j), 77+(99*j) }
});
Assert.That(_cc2X2.MultiplyLeftDiagonal(_cv2), NumericIs.AlmostEqualTo(prodCmCvdl), "prod ccv dl 1");
ComplexMatrix prodCmCvdlInplace = _cc2X2.Clone();
prodCmCvdlInplace.MultiplyLeftDiagonalInplace(_cv2);
Assert.That(prodCmCvdlInplace, NumericIs.AlmostEqualTo(prodCmCvdl), "prod ccv dl 2");
Assert.That(ComplexMatrix.Diagonal(_cv2) * _cc2X2, NumericIs.AlmostEqualTo(prodCmCvdl), "prod ccv dl 3");
// ComplexMatrix * Vector (Diagonal, Left)
ComplexMatrix prodCmVdl = new ComplexMatrix(new Complex[][] {
new Complex[] { 40-(120*j), 45-(135*j) },
new Complex[] { -20+(60*j), -22+(66*j) }
});
Assert.That(_cc2X2.MultiplyLeftDiagonal(_v2), NumericIs.AlmostEqualTo(prodCmVdl), "prod cv dl 1");
ComplexMatrix prodCmVdlInplace = _cc2X2.Clone();
prodCmVdlInplace.MultiplyLeftDiagonalInplace(_v2);
Assert.That(prodCmVdlInplace, NumericIs.AlmostEqualTo(prodCmVdl), "prod cv dl 2");
// ComplexMatrix * ComplexVector (Diagonal, Right)
ComplexMatrix prodCmCvdr = new ComplexMatrix(new Complex[][] {
new Complex[] { 64-(112*j), 63+(81*j) },
new Complex[] { 80-(140*j), 77+(99*j) }
});
Assert.That(_cc2X2.MultiplyRightDiagonal(_cv2), NumericIs.AlmostEqualTo(prodCmCvdr), "prod ccv dr 1");
ComplexMatrix prodCmCvdrInplace = _cc2X2.Clone();
prodCmCvdrInplace.MultiplyRightDiagonalInplace(_cv2);
Assert.That(prodCmCvdrInplace, NumericIs.AlmostEqualTo(prodCmCvdr), "prod ccv dr 2");
Assert.That(_cc2X2 * ComplexMatrix.Diagonal(_cv2), NumericIs.AlmostEqualTo(prodCmCvdr), "prod ccv dr 3");
// ComplexMatrix * Vector (Diagonal, Right)
ComplexMatrix prodCmVdr = new ComplexMatrix(new Complex[][] {
new Complex[] { 40-(120*j), -18+(54*j) },
new Complex[] { 50-(150*j), -22+(66*j) }
});
Assert.That(_cc2X2.MultiplyRightDiagonal(_v2), NumericIs.AlmostEqualTo(prodCmVdr), "prod cv dr 1");
ComplexMatrix prodCmVdrInplace = _cc2X2.Clone();
prodCmVdrInplace.MultiplyRightDiagonalInplace(_v2);
Assert.That(prodCmVdrInplace, NumericIs.AlmostEqualTo(prodCmVdr), "prod cv dr 2");
}