/// <summary>
/// Smaller operator of <![CDATA[ILArray<>]]> with scalar
/// </summary>
/// <param name="in1">ILArray</param>
/// <param name="in2">Scalar</param>
/// <returns>ILLogicalArray of same size than in1, with elements having 'true' values
/// for all corresponding elements of in1 beeing smaller in2, false if they are not.
/// </returns>
/// <remarks>This operator is overloaded for
/// all numeric types of <![CDATA[ILArray<>]]> for in1. The type of in2 is always double. </remarks>
public static ILLogicalArray operator <(ILArray <BaseT> in1, double in2)
{
if (false)
{
#region HYCALPER LOOPSTART
}
else if (in1 is /*!HC:inCls1*/ ILArray <double> )
{
return(ILMath.lt(in1 as /*!HC:inCls1*/ ILArray <double>, (/*!HC:inArr2*/ double )in2));
#endregion HYCALPER LOOPEND
#region HYCALPER AUTO GENERATED CODE
// DO NOT EDIT INSIDE THIS REGION !! CHANGES WILL BE LOST !!
}
else if (in1 is ILArray <complex> )
{
return(ILMath.lt(in1 as ILArray <complex>, ( complex )in2));
}
else if (in1 is ILArray <byte> )
{
return(ILMath.lt(in1 as ILArray <byte>, ( byte )in2));
#endregion HYCALPER AUTO GENERATED CODE
}
else
{
throw new ILArgumentTypeException("Operator '<' is not defined for ILArrays of type "
+ in1.GetType().Name);
}
}
public static void forwBackwCheck2D(ILArray <double> A, ILArray <complex> Result)
{
try {
ILArray <complex> B = fft2(A);
//double errMult = 1/(A.Dimensions.NumberOfElements * Math.Pow(10,A.Dimensions.NumberOfDimensions));
double errMult = Math.Pow(0.1, A.Dimensions.NumberOfDimensions) / A.Dimensions.NumberOfElements;
if (!A.IsScalar)
{
errMult /= (double)A.Dimensions[A.Dimensions.FirstNonSingleton()];
}
if (sumall(abs(subtract(Result, B))) * errMult > (double)MachineParameterDouble.eps)
{
throw new Exception("invalid value");
}
ILArray <double> ResultR = ifft2sym(B);
if (ILMath.sumall(ILMath.abs(ResultR - A)) * errMult > (double)ILMath.MachineParameterDouble.eps)
{
throw new Exception("invalid value");
}
B = ifft2(B);
if (ILMath.sumall(ILMath.abs(ILMath.tocomplex(A) - B)) * errMult > (double)ILMath.MachineParameterDouble.eps)
{
throw new Exception("invalid value");
}
} catch (ILNumerics.Exceptions.ILArgumentException) {
throw new Exception("unexpected exception was thrown -> error!");
}
}
//protected static bool isempty(string str)
//{
// return (str == string.Empty);
//}
protected static double randn()
{
//get
{
return((double)(ILMath.randn()));
}
}
/// <summary>
/// For optimization, we generate a column for the data matrix only once. The rows of the columns represent the configurations of the learning set.
/// The cells contain the value of the feature in the respective configuration. (see comment on createDataMatrix(..) function for more detail).
/// </summary>
/// <param name="feature">The feature for which we compute the data column.</param>
protected void generateDM_column(Feature feature)
{
ILArray <double> column = ILMath.zeros(this.learningSet.Count);
if (feature.participatingBoolOptions.Count == 1 && feature.participatingNumOptions.Count == 0 && feature.participatingBoolOptions.Contains(this.infModel.Vm.Root))
{
for (int r = 0; r < this.learningSet.Count; r++)
{
column[r] = 1;
}
this.DM_columns.Add(feature, column);
return;
}
int i = 0;
foreach (Configuration config in this.learningSet)
{
if (feature.validConfig(config))
{
column[i] = feature.eval(config);
}
i++;
}
this.DM_columns.Add(feature, column);
}
public void MeasurePool()
{
Info("Measuring memory pool performance");
Info("---------------------------------");
ILArray <int> Lengths = ILMath.toint32(ILMath.vector(1000000, 1000, 1000000));
ILArray <int> PoolSizes = ILMath.toint32(ILMath.vector(00, 10, 250));
ILArray <double> result = ILMath.zeros(Lengths.Length, PoolSizes.Length);
ILArray <double> dataA = ILMath.ones(1000, 1000);
ILArray <double> dataB = ILMath.ones(1000, 1000);
int counter = 1, countAll = Lengths.Length * PoolSizes.Length;
for (int p = 0; p < PoolSizes.Length; p++)
{
for (int s = 0; s < Lengths.Length; s++)
{
result[s, p] = MeasurePoolParameter((int)Lengths[s], (int)PoolSizes[p], 100, dataA, dataB);
Console.Out.Write(String.Format("\r... step {0} of {1} completed", counter++, countAll));
}
}
result.Name = "results";
ILMatFile mf = new ILMatFile();
mf["results"] = result;
mf["lengths"] = Lengths;
mf["poolSizes"] = PoolSizes;
mf.Write(new FileStream("memoryPoolTestPerf.mat", FileMode.Create));
}
private void TestQuickSortGen(ILArray <double> input, int dim, bool desc)
{
try {
ILArray <int> A = ILMath.toint32(input);
try {
ILMatFile f1 = new ILMatFile("tempADebugQuickSort.mat");
A = (ILArray <int>)f1["DebugQuickSort"];
} catch (Exception) {}
ILArray <int> result;
System.Diagnostics.Stopwatch sw = new System.Diagnostics.Stopwatch();
sw.Start();
result = ILMath.sort(A, dim, desc);
sw.Stop();
if (!isSorted(ILMath.todouble(result), dim, desc))
{
//ILMatFile f = new ILMatFile();
//A.Name = "DebugQuickSort";
//f.Add(A);
//System.IO.Stream s = new System.IO.FileStream("tempADebugQuickSort.mat",System.IO.FileMode.CreateNew);
//f.Write(s);
throw new Exception("invalid values");
}
Success(input.Dimensions.ToString() + "(Int32) needed: " + sw.ElapsedMilliseconds + " ms");
} catch (Exception e) {
Error(0, e.Message);
}
}
public void Test_LDA_Performance2000_var(int rep)
{
int errorCode = 0;
try {
LDA lda = new LDA();
ILArray <double> X = ILMath.horzcat(ILMath.randn(2, 2000) * 2.0, ILMath.randn(2, 2000) * -2.0);
ILLogicalArray labels = ILMath.tological(ILMath.horzcat(ILMath.ones(1, 2000), ILMath.zeros(1, 2000)));
labels = labels.Concat(ILMath.tological(ILMath.zeros(1, 2000).Concat(ILMath.ones(1, 2000), 1)), 0);
ILPerformer timer = new ILPerformer();
LDA.Hyperplane C;
int oldRefMin = ILNumerics.Settings.ILSettings.MinimumRefDimensions;
ILNumerics.Settings.ILSettings.MinimumRefDimensions = 2;
timer.Tic();
for (int i = 0; i < rep; i++)
{
C = lda.TrainLDA(X, labels, 0.4);
}
timer.Toc();
Info("Test_LDA_Performance: with reference - data: 2x2000 run " + rep.ToString() + " times in: " + timer.Duration + "ms");
ILNumerics.Settings.ILSettings.MinimumRefDimensions = 3;
timer.Tic();
for (int i = 0; i < rep; i++)
{
C = lda.TrainLDA(X, labels, 0.4);
}
timer.Toc();
ILNumerics.Settings.ILSettings.MinimumRefDimensions = oldRefMin;
Info("Test_LDA_Performance: without reference - data: 2x2000 run " + rep.ToString() + " times in: " + timer.Duration + "ms");
Success();
}catch (Exception e) {
Error(errorCode, e.Message);
}
}
// Initial plot setup, modify this as needed
private void ilPanel1_Load(object sender, EventArgs e)
{
// create some test data, using our private computation module as inner class
ILArray <float> Pos = Computation.CreateData(4, 300);
// setup the plot (modify as needed)
ilPanel1.Scene.Add(new ILPlotCube(twoDMode: false)
{
new ILLinePlot(Pos, tag: "mylineplot")
{
Line =
{
Width = 2,
Color = Color.Red,
Antialiasing = true,
DashStyle = DashStyle.Dotted
}
}
});
// register event handler for allowing updates on right mouse click:
ilPanel1.Scene.First <ILLinePlot>().MouseClick += (_s, _a) =>
{
if (_a.Button == MouseButtons.Right)
{
Update(ILMath.rand(3, 30));
}
};
}
// Initial plot setup, modify this as needed
private void ilPanel1_Load(object sender, EventArgs e)
{
// setup the plot (modify as needed)
ilPanel1.Scene.Add(new ILPlotCube(twoDMode: false)
{
new ILLinePlot(Points, tag: "points")
{
Line =
{
Width = 2,
Color = Color.Red,
Antialiasing = true,
DashStyle = DashStyle.Dotted
}
},
new ILLinePlot(PointsPerceptron, tag: "points")
{
Line =
{
Width = 2,
Color = Color.Blue,
Antialiasing = true,
DashStyle = DashStyle.Dotted
}
}
});
// register event handler for allowing updates on right mouse click:
ilPanel1.Scene.First <ILLinePlot>().MouseClick += (_s, _a) =>
{
if (_a.Button == MouseButtons.Right)
{
Update(ILMath.rand(3, 30));
}
};
}
/// <summary>
/// Computes FFT for the given sampleset.
/// </summary>
/// <param name="Samples">Sampleset on which to compute a FFT</param>
public FFT(List <double> Samples, List <BandFrequencyDefinition> CustomBands = null)
{
using (ILScope.Enter())
{
ILInArray <double> inArr = Samples.ToArray();
ILRetArray <complex> output = ILMath.fft(inArr);
rawFFTOutput = output.ToArray();
}
ComputeFrequencyPowerSamples();
//FrequencyBands
ComputeAbsoluteBandPower(BandFrequencyDefinition.Delta);
ComputeAbsoluteBandPower(BandFrequencyDefinition.Theta);
ComputeAbsoluteBandPower(BandFrequencyDefinition.Alpha);
ComputeAbsoluteBandPower(BandFrequencyDefinition.Beta);
ComputeAbsoluteBandPower(BandFrequencyDefinition.Gamma);
if (CustomBands != null)
{
foreach (BandFrequencyDefinition customBand in CustomBands)
{
ComputeAbsoluteBandPower(customBand);
}
}
}
public ILArray </*!HC:HCretArr*/ complex> /*!HC:funcName*/ FFTForward(ILArray </*!HC:HCinArr*/ double> A, int firstDim, int nDims)
{
if (A == null || nDims < 0 || firstDim < 0)
{
throw new ILArgumentException("invalid parameter!");
}
if (A.IsEmpty)
{
return(ILArray </*!HC:HCretArr*/ complex> .empty(A.Dimensions));
}
if (A.IsScalar || (A.Dimensions[firstDim] == 1 && nDims == 1))
{
return /*!HC:convRet*/ (ILMath.tocomplex(A));
}
if (nDims > A.Dimensions.NumberOfDimensions)
{
nDims = A.Dimensions.NumberOfDimensions;
}
// prepare output array
ILArray </*!HC:HCretArr*/ complex> ret = /*!HC:convRet*/ ILMath.tocomplex(A);
IntPtr plan = IntPtr.Zero;
int hrank = 2;
FFTW_DIRECTION dir = /*!HC:HCdir*/ FFTW_DIRECTION.FORWARD;
lock (_lockobject) {
FFTW_PLANCREATION flags = FFTW_PLANCREATION.ESTIMATE;
if (nDims > m_n.Length)
{
resizeCache(nDims);
}
for (int i = 0; i < nDims; i++)
{
m_n[i] = A.Dimensions[i + firstDim];
m_is[i] = A.Dimensions.SequentialIndexDistance(i + firstDim);
m_os[i] = m_is[i];
}
m_hn[0] = A.Dimensions.SequentialIndexDistance(firstDim);
m_his[0] = 1;
m_hos[0] = 1;
m_his[1] = A.Dimensions.SequentialIndexDistance(nDims + firstDim);
m_hn[1] = A.Dimensions.NumberOfElements / m_his[1];
m_hos[1] = m_his[1];
fixed(/*!HC:HCretArr*/ complex *retArr = ret.m_data)
{
/*!HC:HCplanfun*/ dfftw_plan_guru_dft_(ref plan, ref nDims, m_n, m_is, m_os,
ref hrank, m_hn, m_his, m_hos,
retArr, retArr,
ref dir, ref flags);
}
}
if (plan == IntPtr.Zero)
{
throw new ILInvalidOperationException("error creating plan for fftw3 (guru interface)");
}
dfftw_execute_(ref plan);
dfftw_destroy_plan_(ref plan);
/*!HC:HCbackwScale*/
return(ret);
}
private void PlotSurfaceBtn_Click(object sender, RoutedEventArgs e)
{
var B = ILMath.tosingle(sigma);
var scene = new PlotCube(twoDMode: false)
{
// add a surface
new Surface(B)
{
// make thin transparent wireframes
Wireframe = { Color = Color.FromArgb(50, Color.LightGray) },
// choose a different colormap
Colormap = Colormaps.Jet,
}
};
scene.Axes.XAxis.Max = (float)arguments[0].Maximum;
scene.Axes.XAxis.Min = (float)arguments[0].Minimum;
scene.Axes.YAxis.Max = (float)arguments[1].Maximum;
scene.Axes.YAxis.Min = (float)arguments[1].Minimum;
scene.First <PlotCube>().Rotation = Matrix4.Rotation(new Vector3(1f, 0.23f, 1), 0.7f);
PlotSurface form = new PlotSurface(scene);
form.Refresh();
form.ShowDialog();
}
public ILArray <double> GetInverseMatrixOfMatrix(ILArray <double> inputMatrix, int dimension)
{
ILArray <double> identityMatrix = ILMath.eye(dimension, dimension);
ILArray <double> inverseCovMatrix = ILMath.linsolve(inputMatrix, identityMatrix);
return(inverseCovMatrix);
}
public double GetSDNLL_MDF(ILArray <double> mdfVector)
{
double firstPart = 0;
double secondPart = 0;
double thirdPart = 0;
if (this.items.Count < 2)
{
this.covarianceMatrixMDF = this.GetVarianceMatrix_MDF();
}
int q = this.meanMDF.Length;
// get matrix W
ILArray <double> W = this.GetMatrixW_MDF();
ILArray <double> WInverse = this.GetInverseMatrixOfMatrix(W, q);
/*if (Double.IsNaN(WInverse.ToArray()[0]))
* {
* //throw new InvalidDataException("inverse of covariance matrix MDF is NaN");
* WInverse = ILMath.eye(this.parent.VarianceMDF.Length, this.parent.VarianceMDF.Length);
* Debug.Assert(true, "Problem with covariance gaussian matrix.");
* }*/
ILArray <double> vector1 = mdfVector - this.meanMDF;
ILArray <double> tmpArray = ILMath.multiply(WInverse, vector1);
firstPart = 0.5 * ILMath.multiply(vector1.T, tmpArray).ToArray()[0];
secondPart = q / 2 * ILMath.log(2 * Math.PI).ToArray()[0];
thirdPart = 0.5 * ILMath.log(ILMath.det(W)).ToArray()[0];
return(firstPart + secondPart + thirdPart);
}
private static void sortIDXTestHelper001(int dim, int[] dims, ref ILArray <double> expectInd, int[] dimsEx)
{
int i;
for (i = 0; i < dimsEx.Length; i++)
{
if (i <= dim)
{
dimsEx[i] = dims[i];
}
else
{
dimsEx[i] = 1;
}
}
expectInd = ILMath.reshape(expectInd, dimsEx);
for (i = 0; i < dimsEx.Length; i++)
{
if (i <= dim)
{
dimsEx[i] = 1;
}
else
{
dimsEx[i] = dims[i];
}
}
}
public ILArray <T> Load <T>()
{
int i = 0;
int nrow = 0;
int ncol = 0;
string header = "";
GetCotentInfo(ref nrow, ref ncol, ref header);
ILArray <T> array = ILMath.zeros <T>(nrow, ncol);
StreamReader sr = new StreamReader(_Filename);
try
{
header = sr.ReadLine();
string line = "";
for (i = 0; i < nrow; i++)
{
line = sr.ReadLine();
var buf = TypeConverterEx.Split <T>(line);
for (int j = 0; j < ncol; j++)
{
array.SetValue(buf[j], i, j);
}
}
}
catch (Exception ex)
{
ErrorMessage = ex.Message;
}
sr.Close();
return(array);
}
private void TestQuickSortDesc()
{
try {
ILArray <double> A = ILMath.counter(5, 4, 3);
System.Diagnostics.Debug.Assert(!A.IsReference);
ILArray <double> result = ILMath.sort(A, 1, true);
ILArray <double> expect = A[":;3,2,1,0;:"];
if (!result.Equals(expect))
{
throw new Exception("invalid values");
}
// test scalar
A = 3.0;
result = ILMath.sort(A, 0, true);
if (result != 3.0)
{
throw new Exception("invalid values: scalar");
}
// test empty
A = ILArray <double> .empty();
if (!ILMath.sort(A, 0, true).IsEmpty)
{
throw new Exception("invalid values: empty");
}
Success();
} catch (Exception e) {
Error(0, e.Message);
}
}
private void Plot2D(int selectedFuncId)
{
var range = 7000;
float[][] points = _benchmark.GeneratePoints(range);
ILArray <float> A = ILMath.zeros <float>(3, points.GetLength(0));
for (int i = 0; i < points.GetLength(0); i++)
{
A[0, i] = points[i][0];
A[1, i] = CallFunction(selectedFuncId, points[i]);
}
_scene = new ILScene();
_scene.Add(new ILPlotCube(twoDMode: true)
{
new ILPoints
{
Positions = ILMath.tosingle(A)
}
});
ilPanel1.Scene = _scene;
ilPanel1.Refresh();
return;
}
private void TestQuickSortLoop(int len, int rep)
{
try {
m_stopwatch.Stop();
m_stopwatch.Reset();
for (int r = 0; r < rep; r++)
{
double[] p = ILMath.rand(1, len).m_data;
m_stopwatch.Start();
ILQuickSort.QuickSortAscSolid_IT(p, 0, len - 1, 1);
m_stopwatch.Stop();
if (!ILMath.IsSorted(p, false))
{
throw new Exception("unsorted values detected (asc). Size: " + p.Length);
}
// descending
ILQuickSort.QuickSortDescSolid_IT(p, 0, len - 1, 1);
if (!ILMath.IsSorted(p, true))
{
throw new Exception("unsorted values detected (desc). Size: " + p.Length);
}
}
Success(" elapsed: " + m_stopwatch.ElapsedMilliseconds + " ms");
} catch (Exception e) {
Error(0, e.Message);
}
}
/// <summary>
/// update composite shape
/// </summary>
/// <param name="X">x coordinates, vector of length <see cref="ILNumerics.Drawing.Shapes.ILShape.VertexCount"/></param>
/// <param name="Y">y coordinates, vector of length <see cref="ILNumerics.Drawing.Shapes.ILShape.VertexCount"/></param>
/// <param name="Z">z coordinates, vector of length <see cref="ILNumerics.Drawing.Shapes.ILShape.VertexCount"/></param>
/// <param name="mapping">Mapping of shapes, composes shapes out of vertices. Matrix having
/// <see cref="ILNumerics.Drawing.Shapes.ILShape<T>.VerticesPerShape"/> rows.
/// Every element in a column specifies the index of a vertex according to its position in X,Y,Z.
/// The <see cref="ILNumerics.Drawing.Shapes.ILShape<T>.VerticesPerShape"/> elements in a column therefore
/// compose a single shape. Vertices may get used arbitrary times (or not at all). All elements must be
/// positive integer values in range 0...[<see cref="ILNumerics.Drawing.Shapes.ILShape.VertexCount"/>-1].</param>
/// <remarks>All vertices of the shape are updated with the data specified in X,Y and Z. Neither the colors or any
/// other data of vertices are changed. The shape is invalidated for reconfiguration at next redraw. </remarks>
public void Update(ILBaseArray X, ILBaseArray Y, ILBaseArray Z, ILBaseArray mapping)
{
if (!X.IsVector || !Y.IsVector || !Z.IsVector || X.Length != Y.Length || Y.Length != Z.Length)
{
throw new ILArgumentException("numeric vectors of same length expected for: X, Y and Z");
}
if (mapping == null || mapping.IsEmpty || !mapping.IsMatrix || !mapping.IsNumeric || mapping.Dimensions[0] != VerticesPerShape)
{
throw new ILArgumentException("mapping must be a numeric matrix, " + VerticesPerShape.ToString() + " rows, each column specifies indices for the vertices of a single shape.");
}
if (mapping is ILArray <int> )
{
m_shapeIndices = (mapping as ILArray <int>).C;
}
else
{
m_shapeIndices = ILMath.toint32(mapping);
}
ILArray <float> fX = ILMath.tosingle(X);
ILArray <float> fY = ILMath.tosingle(Y);
ILArray <float> fZ = ILMath.tosingle(Z);
for (int i = 0; i < m_vertices.Length; i++)
{
m_vertices[i].XPosition = fX.GetValue(i);
m_vertices[i].YPosition = fY.GetValue(i);
m_vertices[i].ZPosition = fZ.GetValue(i);
}
Invalidate();
}
// the callback from naudio
void waveInStream_DataAvailable(object sender, WaveInEventArgs e)
{
if (m_shutdown)
{
return;
}
using (ILScope.Enter()) {
// prepare variables for requesting X values and the index of the maximum value
ILArray <int> maxID = 1;
// convert the recorded samples in computation module:
ILArray <float> Y = Computation.GetMagnitudes(e.Buffer, e.BytesRecorded, m_fftlen, maxID);
// update the line shape
Line.Update(Y);
// update the marker point
ILArray <float> markerPoints = ILMath.zeros <float>(2, maxID.S[0]);
markerPoints[0, ":"] = ILMath.tosingle(maxID);
markerPoints[1, ":"] = Y[maxID];
Marker.Update(markerPoints);
// on the first only run we zoom to content
if (m_startup)
{
m_startup = false;
ilPanel1.Scene.First <ILPlotCube>().Reset();
}
// redraw the scene
ilPanel1.Refresh();
}
}
/// <summary>
/// create composite shape
/// </summary>
/// <param name="panel">scene hosting the scene</param>
/// <param name="numVertices">number of overall vertices for the shape</param>
/// <param name="verticesPerShape">Number of vertices per shape</param>
public ILCompositeShape(ILPanel panel, int numVertices, int verticesPerShape)
: base(panel, numVertices, verticesPerShape)
{
Opacity = 255;
m_shapeIndices = ILMath.toint32(
ILMath.counter(0.0, 1.0, VerticesPerShape, numVertices / VerticesPerShape));
}
private void Test_isConj(ILArray <complex> A, ILArray <complex> conjA)
{
try {
if (A.IsEmpty)
{
if (!conjA.IsEmpty)
{
throw new Exception("conj of empty array must be empty!");
}
else
{
Success();
return;
}
}
if (!A.Dimensions.IsSameSize(conjA.Dimensions))
{
throw new Exception("dimensions must match!");
}
if (ILMath.sumall(ILMath.real(A) != ILMath.real(conjA)) > 0.0)
{
throw new Exception("real parts must match!");
}
if (ILMath.sumall(-ILMath.imag(A) != ILMath.imag(conjA)) > 0.0)
{
throw new Exception("imag parts must be the inverse of each other!");
}
Success();
} catch (Exception exc) {
Error(exc.Message);
}
}
public Bars AddBars(ILArray <double> barStart, ILArray <double> barEnd, ILArray <double> barPosition, ILArray <double> barThickness, BarType barType)
{
int n = barStart.Dimensions[0];
if (barThickness.IsScalar)
{
barThickness = ILMath.ones(n) * barThickness;
}
Bars bars = new Bars(this, barStart, barEnd, barPosition, barThickness, barType);
barsList.Add(bars);
foreach (Path rectangle in bars.Paths)
{
canvas.Children.Add(rectangle);
IBoundableFromChild.Add((object)(rectangle), bars);
}
if (graphToCanvas.Matrix.M11 != 0)
{
ViewedRegion = GetCanvasChildrenBounds();
}
else
{
ViewedRegion = bars.Bounds;
}
return(bars);
}
public DataCube(int nvar, int ntime, int ncell, bool islazy = false)
{
_isLazy = islazy;
_nvar = nvar;
_ntime = ntime;
_ncell = ncell;
_size = new int[] { nvar, ntime, ncell };
_arrays = new ILArray <T> [nvar];
if (!islazy)
{
for (int i = 0; i < nvar; i++)
{
_arrays[i] = ILMath.zeros <T>(ntime, ncell);
}
DataCubeType = Data.DataCubeType.General;
}
else
{
DataCubeType = Data.DataCubeType.Varient;
}
Name = "default";
PopulateVariables();
InitFlags(Size[0], Size[1]);
AllowTableEdit = false;
TimeBrowsable = false;
}
private void TestBucketSortArrayMatrixRow()
{
try {
ILArray <string> A = new ILArray <string>(3, 4);
A[0, 0] = "abc";
A[0, 1] = "rtu";
A[0, 2] = "sfkw";
A[0, 3] = "lsdkfi";
A[1, 0] = "iowejkc";
A[1, 1] = "cjks";
A[1, 2] = "wokys";
A[1, 3] = "suem,";
A[2, 0] = "fgj";
A[2, 1] = "JKSF";
A[2, 2] = "SEs";
A[2, 3] = "SEFsr";
ILArray <double> ind;
ILArray <string> res = ILMath.sort(A, out ind, 0, false);
if (!res.Equals(A[ind]))
{
throw new Exception("invalid indices/values detected");
}
ILArray <Int16> indI = ILMath.toint16(ILMath.counter(0.0, 1.0, A.Dimensions.ToIntArray()));
res = ILMath.sort(A, ref indI, 0, true, new ILASCIIKeyMapper());
if (!res.Equals(A[indI]))
{
throw new Exception("invalid indices/values detected");
}
Success(" elapsed: " + m_stopwatch.ElapsedMilliseconds + " ms");
} catch (Exception e) {
Error(0, e.Message);
}
}
public static void forwBackwCheck1DAlongD(ILArray <float> A, ILArray <fcomplex> Result, int p)
{
try {
ILArray <fcomplex> B = fft(A, p);
//double errMult = 1/(A.Dimensions.NumberOfElements * Math.Pow(10,A.Dimensions.NumberOfDimensions));
float errMult = (float)Math.Pow(0.1f, A.Dimensions.NumberOfDimensions) / A.Dimensions.NumberOfElements;
if (!A.IsScalar)
{
errMult /= (float)A.Dimensions[A.Dimensions.FirstNonSingleton()];
}
if (sumall(abs(subtract(Result, B))) * errMult > (double)MachineParameterFloat.eps)
{
throw new Exception("invalid value");
}
ILArray <float> ResultR = ifftsym(B, p);
if (ILMath.sumall(ILMath.abs(ResultR - A)) * errMult > (double)ILMath.MachineParameterFloat.eps)
{
throw new Exception("invalid value");
}
B = ifft(B, p);
if (ILMath.sumall(ILMath.abs(ILMath.tofcomplex(A) - B)) * errMult > (double)ILMath.MachineParameterFloat.eps)
{
throw new Exception("invalid value");
}
} catch (ILNumerics.Exceptions.ILArgumentException) {
throw new Exception("unexpected exception was thrown -> error!");
}
}
private void ilPanel1_Load(object sender, EventArgs e)
{
var inrows = 0;
inrows = inrows + 1;
tempX.Add(float.Parse(Gyrox, CultureInfo.InvariantCulture));
tempY.Add(float.Parse(Gyroy, CultureInfo.InvariantCulture));
tempZ.Add(float.Parse(Gyroz, CultureInfo.InvariantCulture));
ILArray <float> datasamples = ILMath.zeros <float>(3, (int)inrows);
datasamples["0;:"] = tempX.ToArray();
datasamples["1;:"] = tempY.ToArray();
datasamples["2;:"] = tempZ.ToArray();
tempX.Clear();
tempY.Clear();
tempZ.Clear();
var scene = new ILScene
{
new ILPlotCube(twoDMode: false)
{
new ILPoints
{
Positions = datasamples,
Color = Color.Blue,
Size = 10
}
}
};
ilPanel1.Scene = scene;
}
private double calcVarianceFunctionIL(double[] xi, double[] xj, ILArray <double> dispersion)
{
ILArray <double> xiIL = xi;
ILArray <double> xjIL = xj;
return((double)ILMath.multiply(ILMath.multiply(xiIL.T, dispersion), xjIL));
}
/// <summary>
/// greater operator of <![CDATA[ILArray<>]]> with <![CDATA[ILArray<>]]>
/// </summary>
/// <param name="in1"><![CDATA[ILArray<>]]></param>
/// <param name="in2"><![CDATA[ILArray<>]]></param>
/// <returns>ILLogicalArray of same size than in1, with elements having 'true' values
/// for all corresponding elements of in1 greater in2's elements, false if they are not.
/// </returns>
/// <remarks>Dimension of in1 and in2 must match. This operator is overloaded for
/// all numeric types of <![CDATA[ILArray<>]]>. The type of in1 must be the same as the
/// type of in2.</remarks>
public static ILLogicalArray operator >(ILArray <BaseT> in1, ILArray <BaseT> in2)
{
if (false)
{
#region HYCALPER LOOPSTART GT
}
else if (in1 is /*!HC:inCls1*/ ILArray <double> && in2 is /*!HC:inCls2*/ ILArray <double> )
{
return(ILMath.gt(in1 as /*!HC:inCls1*/ ILArray <double>, in2 as /*!HC:inCls2*/ ILArray <double>));
#endregion HYCALPER LOOPEND GT
#region HYCALPER AUTO GENERATED CODE
// DO NOT EDIT INSIDE THIS REGION !! CHANGES WILL BE LOST !!
}
else if (in1 is ILArray <complex> && in2 is ILArray <complex> )
{
return(ILMath.gt(in1 as ILArray <complex>, in2 as ILArray <complex>));
}
else if (in1 is ILArray <byte> && in2 is ILArray <byte> )
{
return(ILMath.gt(in1 as ILArray <byte>, in2 as ILArray <byte>));
#endregion HYCALPER AUTO GENERATED CODE
}
else
{
throw new ILArgumentTypeException("Operator '>' is not defined for ILArrays of type "
+ in1.GetType().Name + " and " + in2.GetType().Name);
}
}
