public Plot2DValue Function(MatrixValue m, MatrixValue n)
{
var plot = new Plot2DValue();
plot.AddPoints(m, n);
plot.IsLogX = true;
return plot;
}
public ContourPlotValue Function(MatrixValue X, MatrixValue Y, MatrixValue Z, MatrixValue v)
{
var plot = new ContourPlotValue();
plot.AddPoints(X, Y, Z);
plot.SetLevels(v);
return plot;
}
public MatrixValue Function(FunctionValue f, ScalarValue n, ScalarValue dt, ArgumentsValue args)
{
var numberOfMeasurements = (Int32)n.Value;
var timeBetweenMeasurements = (Int32)Math.Floor(dt.Value * 1000);
var results = new MatrixValue(numberOfMeasurements, 2);
var time = 0.0;
for (var i = 1; i <= numberOfMeasurements; i++)
{
Thread.Sleep(timeBetweenMeasurements);
var result = f.Perform(context, args);
results[i, 1] = new ScalarValue(time);
if (result is ScalarValue)
{
results[i, 2] = result as ScalarValue;
}
else if (result is MatrixValue)
{
var m = result as MatrixValue;
for (var j = 1; j <= m.Length; j++)
{
results[i, 1 + j] = m[j];
}
}
time += dt.Value;
}
return results;
}
public MatrixValue Function(MatrixValue M)
{
var m = new MatrixValue();
m[1, 1] = new ScalarValue(M.DimensionY);
m[1, 2] = new ScalarValue(M.DimensionX);
return m;
}
public MatrixValue Function(ScalarValue x)
{
var m = new MatrixValue();
m[1, 1] = new ScalarValue(1);
m[1, 2] = new ScalarValue(1);
return m;
}
public ArgumentsValue Function(MatrixValue x, MatrixValue y)
{
var M = x.Length;
var N = y.Length;
var X = new MatrixValue(N, M);
var Y = new MatrixValue(N, M);
for (var i = 1; i <= N; i++)
{
for (var j = 1; j <= M; j++)
{
X[i, j] = x[j].Clone();
}
}
for (var i = 1; i <= N; i++)
{
for (var j = 1; j <= M; j++)
{
Y[i, j] = y[i].Clone();
}
}
return new ArgumentsValue(X, Y);
}
public MatrixValue Function(StringValue str)
{
var m = new MatrixValue();
m[1, 1] = new ScalarValue(1);
m[1, 2] = new ScalarValue(str.Value.Length);
return m;
}
/// <summary>
/// Creates a new instance.
/// </summary>
/// <param name="samples">The given sample values - the matrix has to be Nx2 with the
/// first column for the x values and the second column for the y values.</param>
public Interpolation(MatrixValue samples)
{
_samples = samples;
np = samples.DimensionY;
if (samples.DimensionX != 2)
new YAMPMatrixDimensionException(samples.DimensionY, 2, samples.DimensionY, samples.DimensionX);
}
public ContourPlotValue Function(MatrixValue X, MatrixValue Y, MatrixValue Z, ScalarValue n)
{
var nn = n.GetIntegerOrThrowException("n", Name);
var plot = new ContourPlotValue();
plot.AddPoints(X, Y, Z);
plot.SetLevels(nn);
return plot;
}
public ArgumentsValue Function(ScalarValue Coarsening)
{
var result = _sensor.Capture(Coarsening.Value).Result;
var red = new MatrixValue(result.Red);
var green = new MatrixValue(result.Green);
var blue = new MatrixValue(result.Blue);
return new ArgumentsValue(red, green, blue);
}
public SurfacePlotValue Function(MatrixValue X, MatrixValue Y, MatrixValue Z)
{
var splot = new SurfacePlotValue();
splot.AddPoints(X, Y, Z);
splot.IsMesh = true;
splot.IsSurf = false;
return splot;
}
protected void TestValue(String query, MatrixValue result)
{
var parser = new Parser();
parser.LoadPlugin(typeof(SetsPlugin).Assembly);
parser.UseScripting = true;
var value = parser.Evaluate(query);
var mat = ((MatrixValue)value);
Assert.AreEqual(result, mat);
}
/// <summary>
/// Creates the class for a GMRES(k) solver.
/// </summary>
/// <param name="A">The matrix A to consider as system of linear equations.</param>
/// <param name="restart">Should restarts be executed?</param>
public GMRESkSolver(MatrixValue A, bool restart)
: base(A)
{
MaxIterations = A.Length;
if(restart)
Restart = MaxIterations / 10;
else //No Restart
Restart = MaxIterations;
}
/// <summary>
/// Uses the abstract Compute() methods to compute ALL values.
/// </summary>
/// <param name="x">The matrix with given x values.</param>
/// <returns>The interpolated y values.</returns>
public virtual MatrixValue ComputeValues(MatrixValue x)
{
var y = new MatrixValue(x.DimensionY, x.DimensionX);
for (var i = 1; i <= x.DimensionX; i++)
for (var j = 1; j <= x.DimensionY; j++)
y[j, i].Re = ComputeValue(x[j, i].Re);
return y;
}
static ScalarValue GetVectorSum(MatrixValue vec)
{
var sum = ScalarValue.Zero;
for (var i = 1; i <= vec.Length; i++)
{
sum = sum + vec[i];
}
return sum;
}
static ScalarValue GetVectorProduct(MatrixValue vec)
{
var prod = ScalarValue.One;
for (var i = 1; i <= vec.Length; i++)
{
prod = prod * vec[i];
}
return prod;
}
MatrixValue GetVectorProd(MatrixValue vec)
{
var m = new MatrixValue(vec.DimensionY, vec.DimensionX);
var prod = ScalarValue.One;
for (var i = 1; i <= vec.Length; i++)
{
prod *= vec[i];
m[i] = prod;
}
return m;
}
static MatrixValue GetVectorSum(MatrixValue vec)
{
var m = new MatrixValue(vec.DimensionY, vec.DimensionX);
var sum = ScalarValue.Zero;
for (var i = 1; i <= vec.Length; i++)
{
sum += vec[i];
m[i] = sum;
}
return m;
}
public static MatrixValue Mod(MatrixValue numerator, ScalarValue denominator)
{
var m = new MatrixValue(numerator.DimensionY, numerator.DimensionX);
for (var i = 1; i <= numerator.DimensionX; i++)
{
for (var j = 1; j <= numerator.DimensionY; j++)
{
m[j, i] = numerator[j, i] % denominator;
}
}
return m;
}
public MatrixValue Function(MatrixValue func)
{
var adm = new MatrixValue(func.DimensionY, func.DimensionX - 1);
for (var i = 1; i <= func.DimensionY; i++)
{
for (var t = 1; t <= func.DimensionX - 1; t++)
{
adm[i, t] = new ScalarValue(func[i, t + 1].Re - func[i, t].Re);
}
}
return adm;
}
public MatrixValue Function(MatrixValue M)
{
var v = new MatrixValue(M.Length, 1);
var k = 1;
for (var i = 1; i <= M.DimensionX; i++)
{
for (var j = 1; j <= M.DimensionY; j++)
{
v[k++] = M[j, i];
}
}
return v;
}
public MatrixValue Function(ScalarValue n, ScalarValue alpha, MatrixValue Z)
{
var nn = n.GetIntegerOrThrowException("n", Name);
var M = new MatrixValue(Z.DimensionY, Z.DimensionX);
for (var i = 1; i <= Z.DimensionX; i++)
{
for (var j = 1; j <= Z.DimensionY; j++)
{
M[j, i] = Gegenbauer(nn, alpha.Re, Z[j, i]);
}
}
return M;
}
/// <summary>
/// Performs the integration.
/// </summary>
/// <param name="x">The x values.</param>
/// <returns>The result of the integration.</returns>
public override ScalarValue Integrate(MatrixValue x)
{
var y = Values;
if (x.Length != y.Length)
throw new YAMPDifferentLengthsException(x.Length, y.Length);
var sum = 0.0;
for (var i = 1; i < N - 1; i += 2)
{
sum += (x[i + 2].Re - x[i].Re) * (y[i].Re + 4.0 * y[i + 1].Re + y[i + 2].Re);
}
return new ScalarValue(sum / 6.0);
}
public MatrixValue Function(ScalarValue n, ScalarValue m, MatrixValue Z)
{
var nn = n.GetIntegerOrThrowException("n", Name);
var nm = m.GetIntegerOrThrowException("m", Name);
var M = new MatrixValue(Z.DimensionY, Z.DimensionX);
for (var i = 1; i <= Z.DimensionX; i++)
{
for (var j = 1; j <= Z.DimensionY; j++)
{
M[j, i] = Zernike(nn, nm, Z[j, i]);
}
}
return M;
}
public MatrixValue Function(MatrixValue Z, MatrixValue N)
{
if (Z.DimensionY != N.DimensionY || Z.DimensionX != N.DimensionX)
throw new YAMPDifferentDimensionsException(Z, N);
var M = new MatrixValue(Z.DimensionY, Z.DimensionX);
for (var i = 1; i <= M.DimensionX; i++)
{
for (var j = 1; j <= M.DimensionY; j++)
{
M[j, i] = Gamma.LinearGamma(Z[j, i] + N[j, i]) / Gamma.LinearGamma(Z[j, i]);
}
}
return M;
}
MatrixValue fft(MatrixValue x)
{
var length = x.Length;
if (length == 1)
{
return x.Clone();
}
// Cooley-Tukey FFT
if (length % 2 != 0)
throw new YAMPDifferentLengthsException(length, "2^n");
// even fft
var even = new MatrixValue(length / 2, 1);
for (var k = 1; k <= even.Length; k++)
{
even[k] = x[2 * k];
}
var q = fft(even);
// odd fft;
var odd = even;
for (var k = 1; k <= odd.Length; k++)
{
odd[k] = x[2 * k - 1];
}
var r = fft(odd);
// combine
var y = new MatrixValue(length, 1);
for (var k = 1; k <= odd.Length; k++)
{
var value = -2 * (k - 1) * Math.PI / length;
var wk = new ScalarValue(Math.Cos(value), Math.Sin(value));
y[k] = q[k] + (wk * r[k]);
y[k + odd.Length] = q[k] - (wk * r[k]);
}
return y;
}
/// <summary>
/// Creates a new householder decomposition.
/// </summary>
/// <param name="A">The matrix to decompose.</param>
public HouseholderDecomposition(MatrixValue A)
: base(A)
{
QR = A.GetComplexMatrix();
Rdiag = new ScalarValue[n];
// Main loop.
for (int k = 0; k < n; k++)
{
var nrm = 0.0;
for (int i = k; i < m; i++)
nrm = Helpers.Hypot(nrm, QR[i][k].Re);
if (nrm != 0.0)
{
// Form k-th Householder vector.
if (QR[k][k].Re < 0)
nrm = -nrm;
for (int i = k; i < m; i++)
QR[i][k] /= nrm;
QR[k][k] += ScalarValue.One;
// Apply transformation to remaining columns.
for (int j = k + 1; j < n; j++)
{
var s = ScalarValue.Zero;
for (int i = k; i < m; i++)
s += QR[i][k] * QR[i][j];
s = (-s) / QR[k][k];
for (int i = k; i < m; i++)
QR[i][j] += s * QR[i][k];
}
}
else
FullRank = false;
Rdiag[k] = new ScalarValue(-nrm);
}
}
public MatrixValue Function(MatrixValue M)
{
if (!M.IsVector)
{
var result = new MatrixValue();
for (var i = 0; i < M.DimensionY; i++)
{
var vec = M.GetSubMatrix(i, i + 1, 0, M.DimensionX);
vec = vec.VectorSort();
result = result.AddRow(vec);
}
return result;
}
return M.VectorSort();
}
public MatrixValue Function(MatrixValue A, MatrixValue B)
{
//TODO: Additional options like ( http://www.mathworks.de/de/help/matlab/ref/convn.html )
//i.e. "full" (default - it is this), "same" (only same length), "valid" (see formula on the website)
var result = new MatrixValue(A.Length + B.Length - 1, 1);
for (var i = 1; i <= A.Length; i++)
{
var k = i;
for (var j = 1; j <= B.Length; j++)
{
result[k++] += A[i] * B[j];
}
}
return result;
}
public ArgumentsValue Function(MatrixValue M)
{
var rvalues = new MatrixValue(M.DimensionY, M.DimensionX);
var gvalues = new MatrixValue(M.DimensionY, M.DimensionX);
var bvalues = new MatrixValue(M.DimensionY, M.DimensionX);
for (var i = 1; i <= M.DimensionY; i++)
{
for (var j = 1; j <= M.DimensionX; j++)
{
int value = M[i, j].IntValue;
rvalues[i, j] = new ScalarValue((value / rfactor) % 256);
gvalues[i, j] = new ScalarValue((value / gfactor) % 256);
bvalues[i, j] = new ScalarValue((value / bfactor) % 256);
}
}
return new ArgumentsValue(rvalues, gvalues, bvalues);
}
public MatrixValue Function(MatrixValue M)
{
return(GetIndices(M, M.Length, 0));
}
public MatrixValue Function(MatrixValue M, ScalarValue n, ScalarValue sigma)
{
return(GetIndices(M, n.GetIntegerOrThrowException("n", Name), sigma.GetIntegerOrThrowException("sigma", Name)));
}
public MatrixValue Function(MatrixValue M, ScalarValue n)
{
return(GetIndices(M, n.GetIntegerOrThrowException("n", Name), 0));
}
public override MatrixValue Function(MatrixValue x)
{
return(base.Function(x));
}
public ArgumentsValue Function(MatrixValue M)
{
var qr = QRDecomposition.Create(M);
return(new ArgumentsValue(qr.Q, qr.R));
}
public MatrixValue Function()
{
return(MatrixValue.One(1));
}
public MatrixValue Function(MatrixValue cfgs, ScalarValue n, FunctionValue f, ArgumentsValue P)
{
var numberOfBlocks = n.GetIntegerOrThrowException("n", Name);
var nConfigs = cfgs.DimensionY;
var nData = cfgs.DimensionX;
if (numberOfBlocks > nConfigs)
{
throw new YAMPException("Jackknife: The number of measurements n is greater than the number of configurations cfgs!");
}
if (numberOfBlocks <= 1)
{
throw new YAMPException("Jackknife: The number of measurements n <= 1!");
}
var parameters = new ArgumentsValue(cfgs);
foreach (var m in P.Values)
{
parameters.Insert(m);
}
var temp = f.Perform(Context, parameters);
int nResult;//dimension of the result
if (temp is ScalarValue)
{
nResult = 1;
}
else if (temp is MatrixValue)
{
nResult = (temp as MatrixValue).Length;
}
else
{
throw new YAMPException("Jackknife: Observable f has to return either a scalar or a matrix!");
}
var JackknifeObservable = new MatrixValue(numberOfBlocks, nResult);
var BlockSize = nConfigs / numberOfBlocks;
var nConfigsBlocked = BlockSize * numberOfBlocks;
var residualConfigs = nConfigs - nConfigsBlocked;
for (int i = 1; i <= numberOfBlocks; i++)
{
if (i <= numberOfBlocks - residualConfigs)
{
//the first (NumberOfBlocks - residualConfigs) blocks discard (BlockSize) elements ...
var JackknifeConfigs = new MatrixValue(nConfigs - BlockSize, nData);
int j = 1;
for (; j <= (i - 1) * BlockSize; j++)
{
for (int k = 1; k <= nData; k++)
{
JackknifeConfigs[j, k] = cfgs[j, k];
}
}
j += BlockSize;
for (; j <= nConfigs; j++)
{
for (int k = 1; k <= nData; k++)
{
JackknifeConfigs[j - BlockSize, k] = cfgs[j, k];
}
}
parameters = new ArgumentsValue(JackknifeConfigs);
}
else
{
//... whereas the residual (residualConfigs) blocks discard (BlockSize + 1) elements
var JackknifeConfigs = new MatrixValue(nConfigs - BlockSize - 1, nData);
int j = 1;
for (; j <= nConfigs - (numberOfBlocks - (i - 1)) * (BlockSize + 1); j++)
{
for (int k = 1; k <= nData; k++)
{
JackknifeConfigs[j, k] = cfgs[j, k];
}
}
j += BlockSize + 1;
for (; j <= nConfigs; j++)
{
for (int k = 1; k <= nData; k++)
{
JackknifeConfigs[j - BlockSize - 1, k] = cfgs[j, k];
}
}
parameters = new ArgumentsValue(JackknifeConfigs);
}
foreach (var m in P.Values)
{
parameters.Insert(m);
}
temp = f.Perform(Context, parameters);
if (temp is ScalarValue)
{
JackknifeObservable[i] = (ScalarValue)temp;
}
else
{
var T = (MatrixValue)temp;
for (int k = 1; k <= nResult; k++)
{
JackknifeObservable[i, k] = T[k];
}
}
}
temp = YMath.Average(JackknifeObservable);
for (int i = 1; i <= numberOfBlocks; i++)
{
if (temp is ScalarValue)
{
JackknifeObservable[i] -= temp as ScalarValue;
JackknifeObservable[i] *= JackknifeObservable[i];
}
else
{
var m = (MatrixValue)temp;
for (int k = 1; k <= nResult; k++)
{
JackknifeObservable[i, k] -= m[k];
JackknifeObservable[i, k] *= JackknifeObservable[i, k];
}
}
}
var error = YMath.Average(JackknifeObservable);
var scale = numberOfBlocks - 1.0;
if (error is ScalarValue)
{
error = ((ScalarValue)error) * scale;
}
else
{
var e = (MatrixValue)error;
for (var i = 1; i <= e.DimensionY; i++)
{
for (int j = 1; j <= e.DimensionX; j++)
{
e[i, j] *= scale;
}
}
}
var sqrt = new SqrtFunction();
error = sqrt.Perform(error);
var result = new MatrixValue(2, nResult);
if (temp is ScalarValue)
{
result[1] = (ScalarValue)temp;
result[2] = (ScalarValue)error;
}
else
{
var T = (MatrixValue)temp;
var E = (MatrixValue)error;
for (int k = 1; k <= nResult; k++)
{
result[1, k] = T[k];
result[2, k] = E[k];
}
}
return(result);
}
public MatrixValue(MatrixValue v)
{
Route = v.Route;
_value = v._value;
IsInfinity = v.IsInfinity;
}
public ContourPlotValue Function(MatrixValue X, MatrixValue Y, MatrixValue Z, MatrixValue v)
{
var plot = new ContourPlotValue();
plot.AddPoints(X, Y, Z);
plot.SetLevels(v);
return(plot);
}
public MatrixValue Function(MatrixValue A, MatrixValue b)
{
var gmres = new GMRESkSolver(A);
return(gmres.Solve(b));
}
/// <summary> /// Adds points to the plot. /// </summary> /// <param name="m">The given matrix.</param> public abstract void AddPoints(MatrixValue m);
private void InitMatrix()
{
MatrixValue matrix = (MatrixValue)_currentQuestionEntity.Question;
if (QuestionMatrix.Children.Count == 0)
{
for (int i = 0; i < matrix.Matrix.Length + 1; i++)
{
QuestionMatrix.RowDefinitions.Add(new RowDefinition()
{
Height = new GridLength(1, GridUnitType.Star)
});
QuestionMatrix.ColumnDefinitions.Add(new ColumnDefinition()
{
Width = new GridLength(1, GridUnitType.Star)
});
}
}
else
{
_textAnswer.Clear();
QuestionMatrix.Children.Clear();
}
for (int i = 0; i < matrix.Matrix.Length; i++)
{
for (int j = 0; j < matrix.Matrix[i].Length; j++)
{
TextBlock textBlock = new TextBlock();
textBlock.IsEnabled = false;
textBlock.Margin = new Thickness(3);
textBlock.FontSize = 12;
textBlock.Text = matrix.Matrix[i][j];
QuestionMatrix.Children.Add(textBlock);
Grid.SetRow(textBlock, i);
Grid.SetColumn(textBlock, j);
}
}
for (int i = 0; i < matrix.Matrix.Length + 1; i++)
{
for (int j = 0; j < matrix.Matrix.Length + 1; j++)
{
if (_currentQuestionEntity.CodeType == CodeType.Encoding)
{
if (i != j && (matrix.Matrix.Length == i) && matrix.Matrix[0].Length != j)
{
TextBox textBlock = new TextBox();
textBlock.Margin = new Thickness(3);
textBlock.FontSize = 12;
textBlock.Text = "0";
QuestionMatrix.Children.Add(textBlock);
_textAnswer.Add(textBlock);
Grid.SetRow(textBlock, i);
Grid.SetColumn(textBlock, j);
}
}
else
{
if (i != j && (matrix.Matrix[0].Length == j) && (matrix.Matrix.Length != i))
{
TextBox textBlock = new TextBox();
textBlock.Margin = new Thickness(5);
textBlock.FontSize = 17;
textBlock.Text = "0";
QuestionMatrix.Children.Add(textBlock);
_textAnswer.Add(textBlock);
Grid.SetRow(textBlock, i);
Grid.SetColumn(textBlock, j);
}
}
}
}
}
private void StaertTest_Click(object sender, RoutedEventArgs e)
{
MatrixValue matrix = (MatrixValue)_currentQuestionEntity.Question;
string[][] answer = null;
if (_currentQuestionEntity.CodeType == CodeType.Encoding)
{
try
{
answer = new string[1][];
answer[1] = new string[_textAnswer.Count];
for (int i = 0; i < _textAnswer.Count; i++)
{
answer[1][i] = _textAnswer[i].Text;
}
}
catch { }
}
else
{
try
{
answer = new string[_textAnswer.Count][];
for (int i = 0; i < _textAnswer.Count; i++)
{
answer[i] = new string[1];
answer[i][1] = _textAnswer[i].Text;
}
}
catch { }
}
StateType stateType = _answerCheker.CheckQuestion(new TestAnswerEntity()
{
AllCount = _questionEntities.Count,
Answer = new MatrixValue()
{
Matrix = answer
},
CurrentCount = number,
NameTest = QuestionType.RidaMallera.ToString(),
QuestionEntity = _currentQuestionEntity
}).Data;
_currentQuestionEntity = _questionEntities
.FirstOrDefault(p => p.StateType == StateType.Default);
if (_currentQuestionEntity != null)
{
InitMatrix();
DescriptionText.Text = _currentQuestionEntity?.Description;
number++;
Number.Text = number.ToString();
Correct.Text = $"{_questionEntities.Count(p => p.StateType == StateType.Corect)}/{_questionEntities.Count}";
}
else
{
_grid.Children.Clear();
_grid.Children.Add(new ResultView(_grid, this));
}
}
public ArgumentsValue Function(MatrixValue M)
{
var svd = new SingularValueDecomposition(M);
return(new ArgumentsValue(svd.S, svd.GetU(), svd.GetV()));
}
/// <summary>
/// A complex plot cannot have any points assigned. You have to
/// assign a function instead.
/// </summary>
/// <param name="m">Useless.</param>
public override void AddPoints(MatrixValue m)
{
//Leave empty
}
public MatrixValue Function(MatrixValue Z)
{
return(Function(Z, new ScalarValue(Math.E)));
}
public MatrixValue Function(ScalarValue dim)
{
var n = dim.GetIntegerOrThrowException("dim", Name);
return(MatrixValue.One(n));
}
public ScalarValue Function(MatrixValue y, MatrixValue x)
{
var integral = new SimpsonIntegrator(y);
return(integral.Integrate(x));
}
public BarPlotValue Function(MatrixValue Y)
{
return(Function(Y, new ScalarValue(10)));
}
/// <summary>
/// Creates a new instance.
/// </summary>
/// <param name="A">The matrix A for which to solve.</param>
public CGSolver(MatrixValue A) : base(A)
{
}
/// <summary>
/// Sets the z values given in the matrix m with the corresponding x and y values.
/// </summary>
/// <param name="x">The matrix with the x values.</param>
/// <param name="y">The matrix with the y values.</param>
/// <param name="z">The matrix with the function values / z values.</param>
public void AddPoints(MatrixValue x, MatrixValue y, MatrixValue z)
{
data.Clear();
if (x.Length > 0)
{
MinX = x[1, 1].Re;
MaxX = x[1, 1].Re;
}
else
{
MinX = 0;
MaxX = 0;
}
if (y.Length > 0)
{
MinY = y[1, 1].Re;
MaxY = y[1, 1].Re;
}
else
{
MinY = 0;
MaxY = 0;
}
if (z.Length > 0)
{
MinZ = z[1, 1].Re;
MaxZ = z[1, 1].Re;
}
else
{
MinZ = 0;
MaxZ = 0;
}
if (x.IsVector && y.IsVector)
{
var cols = Math.Min(x.Length, z.Columns);
var rows = Math.Min(y.Length, z.Rows);
Nx = cols;
Ny = rows;
for (var j = 1; j <= rows; j++)
{
for (var i = 1; i <= cols; i++)
{
var v = new Vertex
{
X = x[i].Re,
Y = y[j].Re,
Z = z[j, i].Re
};
data.Add(v);
MinX = Math.Min(MinX, v.X);
MaxX = Math.Max(MaxX, v.X);
MinY = Math.Min(MinY, v.Y);
MaxY = Math.Max(MaxY, v.Y);
MinZ = Math.Min(MinZ, v.Z);
MaxZ = Math.Max(MaxZ, v.Z);
}
}
}
else
{
var cols = Math.Min(x.Columns, Math.Min(y.Columns, z.Columns));
var rows = Math.Min(x.Rows, Math.Min(y.Rows, z.Rows));
Nx = cols;
Ny = rows;
for (var j = 1; j <= rows; j++)
{
for (var i = 1; i <= cols; i++)
{
var v = new Vertex
{
X = x[j, i].Re,
Y = y[j, i].Re,
Z = z[j, i].Re
};
data.Add(v);
MinX = Math.Min(MinX, v.X);
MaxX = Math.Max(MaxX, v.X);
MinY = Math.Min(MinY, v.Y);
MaxY = Math.Max(MaxY, v.Y);
MinZ = Math.Min(MinZ, v.Z);
MaxZ = Math.Max(MaxZ, v.Z);
}
}
}
}
public MatrixValue Function(MatrixValue cfgs, ScalarValue n, FunctionValue f)
{
return(Function(cfgs, n, f, new ArgumentsValue()));
}
