| public GetIntegerOrThrowException ( String argumentName, String functionName ) : int | ||
| argumentName | String | The name of the variable that is requested. |
| functionName | String | The name of the function where this is requested. |
| Résultat | int | |
public MatrixValue Function(ScalarValue start, ScalarValue end, ScalarValue steps)
{
var s = steps.GetIntegerOrThrowException("steps", Name);
var m = new Mandelbrot();
return(m.CalculateMatrix(start.Re, end.Re, start.Im, end.Im, s, s));
}
public BarPlotValue Function(MatrixValue Y, ScalarValue nbins)
{
var nn = nbins.GetIntegerOrThrowException("nbins", Name);
var bp = new BarPlotValue();
if (Y.IsVector)
{
bp.AddPoints(YMath.Histogram(Y, nn));
}
else
{
var M = new MatrixValue();
for (var i = 1; i <= Y.DimensionX; i++)
{
var N = YMath.Histogram(Y.GetColumnVector(i), nn);
for (var j = 1; j <= N.Length; j++)
{
M[j, i] = N[j];
}
}
bp.AddPoints(M);
}
return bp;
}
public ArgumentsValue Function(ScalarValue n)
{
var nn = n.GetIntegerOrThrowException("n", Name);
int dim = nn + 1;
if (dim < 2)
throw new YAMPArgumentRangeException("n", 1.0);
var X = new MatrixValue(dim, dim); // x = sin(phi) * cos(theta)
var Y = new MatrixValue(dim, dim); // y = sin(phi) * sin(theta)
var Z = new MatrixValue(dim, dim); // z = cos(phi)
var stheta = Table(0.0, 2.0 * Math.PI, dim, Math.Sin);
var ctheta = Table(0.0, 2.0 * Math.PI, dim, Math.Cos);
var sphi = Table(0.0, Math.PI, dim, Math.Sin);
var cphi = Table(0.0, Math.PI, dim, Math.Cos);
for (var j = 0; j < dim; j++)
{
var col = j + 1;
for (var i = 0; i < dim; i++)
{
var row = i + 1;
X[row, col] = new ScalarValue(sphi[j] * ctheta[i]);
Y[row, col] = new ScalarValue(sphi[j] * stheta[i]);
Z[row, col] = new ScalarValue(cphi[j]);
}
}
return new ArgumentsValue(X, Y, Z);
}
public MatrixValue Function(MatrixValue x, MatrixValue y, ScalarValue n)
{
if (x.Length != y.Length)
throw new YAMPDifferentLengthsException(x.Length, y.Length);
var nn = n.GetIntegerOrThrowException("n", Name);
var m = nn + 1;
if (m < 2)
throw new YAMPArgumentRangeException("n", 0.0);
var M = new MatrixValue(x.Length, m);
var b = new MatrixValue(x.Length, 1);
for (var j = 1; j <= M.Rows; j++)
{
var el = ScalarValue.One;
var z = x[j];
for (var i = 1; i <= M.Columns; i++)
{
M[j, i] = el;
el *= z;
}
b[j, 1] = y[j];
}
var qr = QRDecomposition.Create(M);
return qr.Solve(b);
}
public MatrixValue Function(ScalarValue x0, ScalarValue xn, ScalarValue y0, ScalarValue yn, ScalarValue xsteps, ScalarValue ysteps)
{
var xs = xsteps.GetIntegerOrThrowException("xsteps", Name);
var ys = ysteps.GetIntegerOrThrowException("ysteps", Name);
var m = new Mandelbrot();
return m.CalculateMatrix(x0.Re, xn.Re, y0.Re, yn.Re, xs, ys);
}
public ArgumentsValue Function(ScalarValue n)
{
var nn = n.GetIntegerOrThrowException("n", Name);
int dim = nn + 1;
if (dim < 2)
{
throw new YAMPArgumentRangeException("n", 1.0);
}
var X = new MatrixValue(dim, dim); // x = sin(phi) * cos(theta)
var Y = new MatrixValue(dim, dim); // y = sin(phi) * sin(theta)
var Z = new MatrixValue(dim, dim); // z = cos(phi)
var stheta = Table(0.0, 2.0 * Math.PI, dim, Math.Sin);
var ctheta = Table(0.0, 2.0 * Math.PI, dim, Math.Cos);
var sphi = Table(0.0, Math.PI, dim, Math.Sin);
var cphi = Table(0.0, Math.PI, dim, Math.Cos);
for (var j = 0; j < dim; j++)
{
var col = j + 1;
for (var i = 0; i < dim; i++)
{
var row = i + 1;
X[row, col] = new ScalarValue(sphi[j] * ctheta[i]);
Y[row, col] = new ScalarValue(sphi[j] * stheta[i]);
Z[row, col] = new ScalarValue(cphi[j]);
}
}
return(new ArgumentsValue(X, Y, Z));
}
public BarPlotValue Function(MatrixValue Y, ScalarValue nbins)
{
var nn = nbins.GetIntegerOrThrowException("nbins", Name);
var bp = new BarPlotValue();
if (Y.IsVector)
{
bp.AddPoints(YMath.Histogram(Y, nn));
}
else
{
var M = new MatrixValue();
for (var i = 1; i <= Y.DimensionX; i++)
{
var N = YMath.Histogram(Y.GetColumnVector(i), nn);
for (var j = 1; j <= N.Length; j++)
{
M[j, i] = N[j];
}
}
bp.AddPoints(M);
}
return(bp);
}
public void Function(ScalarValue digits)
{
var n = digits.GetIntegerOrThrowException("digits", Name);
Context.Precision = n;
Parser.RaiseNotification(Context, new NotificationEventArgs(NotificationType.Information, "Output precision changed to " + Context.Precision + " digits."));
}
public MatrixValue Function(ScalarValue n, ScalarValue m)
{
var nn = n.GetIntegerOrThrowException("n", Name);
var nm = m.GetIntegerOrThrowException("m", Name);
return(MatrixValue.One(nn, nm));
}
public MatrixValue Function(ScalarValue x0, ScalarValue xn, ScalarValue y0, ScalarValue yn, ScalarValue xsteps, ScalarValue ysteps)
{
var xs = xsteps.GetIntegerOrThrowException("xsteps", Name);
var ys = ysteps.GetIntegerOrThrowException("ysteps", Name);
var m = new Mandelbrot();
return(m.CalculateMatrix(x0.Re, xn.Re, y0.Re, yn.Re, xs, ys));
}
public ScalarValue Function(ScalarValue n, ScalarValue z)
{
var nn = n.GetIntegerOrThrowException("n", Name);
if (nn < 0)
throw new Exception("Hermite polynomial of order n < 0 does not make sense.");
return HermitePolynomial(nn, z);
}
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 ScalarValue Function(ScalarValue n, ScalarValue alpha, ScalarValue beta, ScalarValue z)
{
var nn = n.GetIntegerOrThrowException("n", Name);
if (nn < 0)
throw new Exception("Jacobi polynomial of order n < 0 does not make sense.");
return JacobiPolynomial(nn, alpha, beta, z);
}
public ScalarValue Function(ScalarValue l, ScalarValue m, ScalarValue theta, ScalarValue phi)
{
var nn = l.GetIntegerOrThrowException("l", Name);
if (nn < 0)
throw new Exception("Spherical harmonics of order l < 0 does not make sense.");
var nm = m.GetIntegerOrThrowException("m", Name);
return Ylm(nn, nm, theta.Re, phi.Re);
}
public ScalarValue Function(ScalarValue n, ScalarValue x)
{
var nn = n.GetIntegerOrThrowException("n", Name);
if (nn < 0)
throw new Exception("Chebyshev polynomial of order n < 0 does not make sense.");
var f = GetPolynom(nn);
return new ScalarValue(f(x.Re));
}
public SubPlotValue Function(ScalarValue rows, ScalarValue columns)
{
var r = rows.GetIntegerOrThrowException("rows", Name);
var c = columns.GetIntegerOrThrowException("columns", Name);
var subplot = new SubPlotValue();
subplot.Rows = r;
subplot.Columns = c;
return(subplot);
}
public MatrixValue Function(ScalarValue s, MatrixValue Z)
{
var n = s.GetIntegerOrThrowException("s", Name);
var M = new MatrixValue(Z.DimensionY, Z.DimensionX);
for (var j = 1; j <= Z.DimensionY; j++)
for (var i = 1; i <= Z.DimensionX; i++)
M[j, i] = GetValue(n, Z[j, i]);
return M;
}
public MatrixValue Function(ScalarValue from, ScalarValue to, ScalarValue count)
{
var c = count.GetIntegerOrThrowException("count", Name);
if (c < 2)
{
throw new ArgumentException("linspace");
}
var step = (to.Re - from.Re) / (c - 1);
return new RangeValue(from.Re, to.Re, step);
}
public void Function(ScalarValue timeout)
{
var n = timeout.GetIntegerOrThrowException("timeout", Name);
var start = Environment.TickCount;
using (var blocking = new ManualResetEvent(false))
{
blocking.WaitOne(n);
}
var time = Environment.TickCount - start;
Context.RaiseNotification(new NotificationEventArgs(NotificationType.Information, "Slept " + time + "ms."));
}
public MatrixValue Function(ScalarValue from, ScalarValue to, ScalarValue count)
{
var c = count.GetIntegerOrThrowException("count", Name);
if (c < 2)
{
throw new ArgumentException("linspace");
}
var step = (to.Re - from.Re) / (c - 1);
return(new RangeValue(from.Re, to.Re, step));
}
public MatrixValue Function(ScalarValue start, ScalarValue end, ScalarValue count, ScalarValue basis)
{
var c = count.GetIntegerOrThrowException("count", Name);
if (c < 2)
{
throw new ArgumentException("logspace");
}
var s = (end.Re - start.Re) / (c - 1);
var r = new RangeValue(start.Re, end.Re, s);
return MatrixValue.PowSM(basis, r);
}
public MatrixValue Function(ScalarValue start, ScalarValue end, ScalarValue count, ScalarValue basis)
{
var c = count.GetIntegerOrThrowException("count", Name);
if (c < 2)
{
throw new ArgumentException("logspace");
}
var s = (end.Re - start.Re) / (c - 1);
var r = new RangeValue(start.Re, end.Re, s);
return(MatrixValue.PowSM(basis, r));
}
public void Function(ScalarValue timeout)
{
var n = timeout.GetIntegerOrThrowException("timeout", Name);
var start = Environment.TickCount;
using (var blocking = new ManualResetEvent(false))
{
blocking.WaitOne(n);
}
var time = Environment.TickCount - start;
Parser.RaiseNotification(Context, new NotificationEventArgs(NotificationType.Information, "Slept " + time + "ms."));
}
public MatrixValue Function(ScalarValue n, MatrixValue Z)
{
var nn = n.GetIntegerOrThrowException("n", Name);
if (nn < 0)
throw new Exception("Hermite polynomial of order n < 0 does not make sense.");
var M = new MatrixValue(Z.DimensionY, Z.DimensionX);
for (var i = 1; i <= Z.Length; i++)
M[i] = HermitePolynomial(nn, Z[i]);
return M;
}
public MatrixValue Function(ScalarValue order, MatrixValue argument)
{
var n = order.GetIntegerOrThrowException("order", Name);
var M = new MatrixValue(argument.DimensionY, argument.DimensionX);
for (var j = 1; j <= argument.DimensionY; j++)
{
for (var i = 1; i <= argument.DimensionX; i++)
{
M[j, i] = GetValue(n, argument[j, i].Re);
}
}
return M;
}
public MatrixValue Function(ScalarValue n, MatrixValue X)
{
var nn = n.GetIntegerOrThrowException("n", Name);
if (nn < 0)
throw new Exception("Chebyshev polynomial of order n < 0 does not make sense.");
var M = new MatrixValue(X.DimensionY, X.DimensionX);
var f = GetPolynom(nn);
for (var i = 1; i <= X.Length; i++)
M[i] = new ScalarValue(f(X[i].Re));
return M;
}
public MatrixValue Function(ScalarValue order, MatrixValue argument)
{
var n = order.GetIntegerOrThrowException("order", Name);
var M = new MatrixValue(argument.DimensionY, argument.DimensionX);
for (var j = 1; j <= argument.DimensionY; j++)
{
for (var i = 1; i <= argument.DimensionX; i++)
{
M[j, i] = GetValue(n, argument[j, i].Re);
}
}
return(M);
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue mu, ScalarValue b)
{
var n = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(n, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= n; j++)
{
m[j, i] = new ScalarValue(Laplace(mu.Re, b.Re));
}
}
return m;
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue lambda)
{
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Exponential(lambda.Re));
}
}
return m;
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue theta, ScalarValue k)
{
var n = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(n, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= n; j++)
{
m[j, i] = new ScalarValue(Gamma(theta.Re, k.Re));
}
}
return(m);
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue mu, ScalarValue sigma)
{
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Gaussian(sigma.Re, mu.Re));
}
}
return(m);
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols)
{
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Distribution.NextDouble());
}
}
return m;
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue mu, ScalarValue sigma)
{
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Gaussian(sigma.Re, mu.Re));
}
}
return m;
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols)
{
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Distribution.NextDouble());
}
}
return(m);
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue theta, ScalarValue k)
{
var n = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(n, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= n; j++)
{
m[j, i] = new ScalarValue(Gamma(theta.Re, k.Re));
}
}
return m;
}
public MatrixValue Function(ScalarValue l, ScalarValue m, MatrixValue theta, MatrixValue phi)
{
var nn = l.GetIntegerOrThrowException("l", Name);
if (nn < 0)
throw new Exception("Spherical harmonics of order l < 0 does not make sense.");
var M = new MatrixValue(theta.Length, phi.Length);
var nm = m.GetIntegerOrThrowException("m", Name);
for (var i = 1; i <= phi.Length; i++)
for (var j = 1; j <= theta.Length; j++)
M[j, i] = Ylm(nn, nm, theta[j].Re, phi[i].Re);
return M;
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue lambda)
{
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Exponential(lambda.Re));
}
}
return(m);
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue mu, ScalarValue b)
{
var n = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(n, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= n; j++)
{
m[j, i] = new ScalarValue(Laplace(mu.Re, b.Re));
}
}
return(m);
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue p, ScalarValue n)
{
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var nn = n.GetIntegerOrThrowException("n", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Binomial(p.Re, nn));
}
}
return m;
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue p, ScalarValue n)
{
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var nn = n.GetIntegerOrThrowException("n", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Binomial(p.Re, nn));
}
}
return(m);
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue min, ScalarValue max)
{
Distribution.Alpha = min.GetIntegerOrThrowException("min", Name);
Distribution.Beta = max.GetIntegerOrThrowException("max", Name);
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Distribution.Next());
}
}
return m;
}
public MatrixValue Function(ScalarValue rows, ScalarValue cols, ScalarValue min, ScalarValue max)
{
ran.Alpha = min.GetIntegerOrThrowException("min", Name);
ran.Beta = max.GetIntegerOrThrowException("max", Name);
var k = rows.GetIntegerOrThrowException("rows", Name);
var l = cols.GetIntegerOrThrowException("cols", Name);
var m = new MatrixValue(k, l);
for (var i = 1; i <= l; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(ran.Next());
}
}
return(m);
}
public void Function(PlotValue plot, ScalarValue series, StringValue property, Value newValue)
{
if (plot.Count == 0)
{
throw new YAMPNoSeriesAvailableException("The given plot contains no series.");
}
var n = series.GetIntegerOrThrowException("series", Name);
if (n < 1 || n > plot.Count)
{
throw new YAMPArgumentRangeException("series", 1, plot.Count);
}
AlterSeriesProperty(plot, n - 1, property.Value, newValue);
plot.UpdateProperties();
Context.RaiseNotification(new NotificationEventArgs(NotificationType.Success, "Series " + n + " changed."));
}
public ScalarValue Function(ScalarValue action)
{
var n = action.GetIntegerOrThrowException("action", Name);
switch (n)
{
case -1:
Reset();
break;
case 0:
Stop();
break;
case 1:
Start();
break;
}
return Function();
}
public MatrixValue Function(MatrixValue M, ScalarValue nLag)
{
if (M.Length <= 1)
{
return(new MatrixValue());
}
var nOffset = nLag.GetIntegerOrThrowException("nLag", Name);
if (nOffset < 0)
{
nOffset = 0;
}
else if (nOffset >= M.Length)
{
nOffset = M.Length - 1;
}
return(YMath.CrossCorrelation(M, M, nOffset));
}
public MatrixValue Function(MatrixValue M, ScalarValue nLag)
{
if (M.Length > 1)
{
var nOffset = nLag.GetIntegerOrThrowException("nLag", Name);
if (nOffset < 0)
{
nOffset = 0;
}
else if (nOffset >= M.Length)
{
nOffset = M.Length - 1;
}
return YMath.CrossCorrelation(M, M, nOffset);
}
return new MatrixValue();
}
public MatrixValue Function(MatrixValue M, MatrixValue N, ScalarValue lag)
{
if (M.Length != N.Length || M.Length <= 1)
{
return(new MatrixValue());
}
int nOffset = lag.GetIntegerOrThrowException("lag", Name);
if (nOffset < 0)
{
nOffset = 0;
}
else if (nOffset >= M.Length)
{
nOffset = M.Length - 1;
}
return(YMath.CrossCorrelation(M, N, nOffset));
}
public MatrixValue Function(ScalarValue dim)
{
var k = dim.GetIntegerOrThrowException("dim", Name);
if (k < 1)
{
k = 1;
}
var m = new MatrixValue(k, k);
for (var i = 1; i <= k; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Distribution.NextDouble());
}
}
return(m);
}
public ScalarValue Function(ScalarValue action)
{
var n = action.GetIntegerOrThrowException("action", Name);
switch (n)
{
case -1:
Reset();
break;
case 0:
Stop();
break;
case 1:
Start();
break;
}
return(Function());
}
public MatrixValue Function(ScalarValue dim)
{
var k = dim.GetIntegerOrThrowException("dim", Name);
if (k < 1)
{
k = 1;
}
var m = new MatrixValue(k, k);
for (var i = 1; i <= k; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Distribution.NextDouble());
}
}
return m;
}
public MatrixValue Function(MatrixValue Y, ScalarValue nbins)
{
var nn = nbins.GetIntegerOrThrowException("nbins", Name);
if (!Y.IsVector)
{
var M = new MatrixValue();
for (var i = 1; i <= Y.DimensionX; i++)
{
var N = YMath.Histogram(Y.GetColumnVector(i), nn);
for (var j = 1; j <= N.Length; j++)
{
M[j, i] = N[j];
}
}
return M;
}
return YMath.Histogram(Y, nn);
}
public MatrixValue Function(ScalarValue dim, ScalarValue min, ScalarValue max)
{
Distribution.Alpha = min.GetIntegerOrThrowException("min", Name);
Distribution.Beta = max.GetIntegerOrThrowException("max", Name);
var k = dim.GetIntegerOrThrowException("dim", Name);
if (k < 1)
{
k = 1;
}
var m = new MatrixValue(k, k);
for (var i = 1; i <= k; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(Distribution.Next());
}
}
return m;
}
public MatrixValue Function(ScalarValue dim, ScalarValue min, ScalarValue max)
{
ran.Alpha = min.GetIntegerOrThrowException("min", Name);
ran.Beta = max.GetIntegerOrThrowException("max", Name);
var k = dim.GetIntegerOrThrowException("dim", Name);
if (k < 1)
{
k = 1;
}
var m = new MatrixValue(k, k);
for (var i = 1; i <= k; i++)
{
for (var j = 1; j <= k; j++)
{
m[j, i] = new ScalarValue(ran.Next());
}
}
return(m);
}
public MatrixValue Function(MatrixValue x, MatrixValue y, ScalarValue n)
{
if (x.Length != y.Length)
{
throw new YAMPDifferentLengthsException(x.Length, y.Length);
}
var nn = n.GetIntegerOrThrowException("n", Name);
var m = nn + 1;
if (m < 2)
{
throw new YAMPArgumentRangeException("n", 0.0);
}
var M = new MatrixValue(x.Length, m);
var b = new MatrixValue(x.Length, 1);
for (var j = 1; j <= M.Rows; j++)
{
var el = ScalarValue.One;
var z = x[j];
for (var i = 1; i <= M.Columns; i++)
{
M[j, i] = el;
el *= z;
}
b[j, 1] = y[j];
}
var qr = QRDecomposition.Create(M);
return(qr.Solve(b));
}
public MatrixValue Function(MatrixValue M, ScalarValue n, ScalarValue sigma)
{
return GetIndices(M, n.GetIntegerOrThrowException("n", Name), sigma.GetIntegerOrThrowException("sigma", Name));
}
public ScalarValue Function(ScalarValue s, ScalarValue z)
{
var n = s.GetIntegerOrThrowException("s", Name);
return Polylog(n, z);
}
public ScalarValue Function(ScalarValue min, ScalarValue max)
{
ran.Alpha = min.GetIntegerOrThrowException("min", Name);
ran.Beta = max.GetIntegerOrThrowException("max", Name);
return(new ScalarValue(ran.Next()));
}
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 = ((MatrixValue)temp).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 (var i = 1; i <= numberOfBlocks; i++)
{
if (i <= numberOfBlocks - residualConfigs)
{
//the first (NumberOfBlocks - residualConfigs) blocks discard (BlockSize) elements ...
var JackknifeConfigs = new MatrixValue(nConfigs - BlockSize, nData);
var j = 1;
for (; j <= (i - 1) * BlockSize; j++)
{
for (var k = 1; k <= nData; k++)
{
JackknifeConfigs[j, k] = cfgs[j, k];
}
}
j += BlockSize;
for (; j <= nConfigs; j++)
{
for (var 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);
var j = 1;
for (; j <= nConfigs - (numberOfBlocks - (i - 1)) * (BlockSize + 1); j++)
{
for (var k = 1; k <= nData; k++)
{
JackknifeConfigs[j, k] = cfgs[j, k];
}
}
j += BlockSize + 1;
for (; j <= nConfigs; j++)
{
for (var 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 (var k = 1; k <= nResult; k++)
{
JackknifeObservable[i, k] = T[k];
}
}
}
temp = YMath.Average(JackknifeObservable);
for (var i = 1; i <= numberOfBlocks; i++)
{
if (temp is ScalarValue)
{
JackknifeObservable[i] -= temp as ScalarValue;
JackknifeObservable[i] *= JackknifeObservable[i];
}
else
{
var m = (MatrixValue)temp;
for (var 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 (var 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 (var k = 1; k <= nResult; k++)
{
result[1, k] = T[k];
result[2, k] = E[k];
}
}
return(result);
}
public MatrixValue Function(MatrixValue cfgs, ScalarValue n, FunctionValue f, ArgumentsValue P)
{
var numberOfBootstrapSamples = n.GetIntegerOrThrowException("n", Name);
var nConfigs = cfgs.DimensionY;
var nData = cfgs.DimensionX;
var distribution = new DiscreteUniformDistribution(Rng)
{
Beta = nConfigs,
Alpha = 1
};
if (numberOfBootstrapSamples <= 1)
{
throw new YAMPException("Bootstrap: The number of bootstrap samples n is smaller or equal to 1!");
}
var parameters = new ArgumentsValue(cfgs);
foreach (var m in P.Values)
{
parameters.Insert(m);
}
var temp = f.Perform(Context, parameters);
var nResult = 0;//dimension of the result
if (temp is ScalarValue)
{
nResult = 1;
}
else if (temp is MatrixValue)
{
nResult = ((MatrixValue)temp).Length;
}
else
{
throw new YAMPException("Bootstrap: The observable f has to return either a scalar or a matrix!");
}
var BootstrapObservable = new MatrixValue(numberOfBootstrapSamples, nResult);
for (var i = 1; i <= numberOfBootstrapSamples; i++)
{
var BootstrapConfigs = new MatrixValue(nConfigs, nData);
for (var j = 1; j <= nConfigs; j++)
{
var idx = distribution.Next();
for (var k = 1; k <= nData; k++)
{
BootstrapConfigs[j, k] = cfgs[idx, k];
}
}
parameters = new ArgumentsValue(BootstrapConfigs);
foreach (var m in P.Values)
{
parameters.Insert(m);
}
temp = f.Perform(Context, parameters);
if (temp is ScalarValue)
{
BootstrapObservable[i] = (ScalarValue)temp;
}
else
{
var m = (MatrixValue)temp;
for (var k = 1; k <= nResult; k++)
{
BootstrapObservable[i, k] = m[k];
}
}
}
temp = YMath.Average(BootstrapObservable);
for (var i = 1; i <= numberOfBootstrapSamples; i++)
{
if (temp is ScalarValue)
{
BootstrapObservable[i] -= temp as ScalarValue;
BootstrapObservable[i] *= BootstrapObservable[i];
}
else
{
var T = temp as MatrixValue;
for (var k = 1; k <= nResult; k++)
{
BootstrapObservable[i, k] -= T[k];
BootstrapObservable[i, k] *= BootstrapObservable[i, k];
}
}
}
var error = YMath.Average(BootstrapObservable);
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 (var k = 1; k <= nResult; k++)
{
result[1, k] = T[k];
result[2, k] = E[k];
}
}
return(result);
}
public MatrixValue Function(ScalarValue n)
{
var d = n.GetIntegerOrThrowException("n", Name);
return(Generate(d, d));
}
