本文整理汇总了C#中MathNet.Numerics.LinearAlgebra.Double.DenseMatrix类的典型用法代码示例。如果您正苦于以下问题:C# DenseMatrix类的具体用法?C# DenseMatrix怎么用?C# DenseMatrix使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
DenseMatrix类属于MathNet.Numerics.LinearAlgebra.Double命名空间,在下文中一共展示了DenseMatrix类的20个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的C#代码示例。
示例1: Matrix3d
public Matrix3d(int NumberOfRows, int NumberOfColumns, int NumberOfLayers)
{
_data = new DenseMatrix[NumberOfLayers];
for (int i = 0; i < NumberOfLayers; i++)
_data[i] = new DenseMatrix(NumberOfRows, NumberOfColumns);
}
开发者ID:XiBeichuan,项目名称:hydronumerics,代码行数:7,代码来源:Matrix3d.cs
示例2: ToMatrix
public static DenseMatrix ToMatrix(this object[,] data, int rowStart, int rowEnd, int colStart, int colEnd,
bool reverseColumns)
{
var d = new DenseMatrix(rowEnd - rowStart + 1, colEnd - colStart + 1);
if (reverseColumns)
{
for (int i = rowEnd; i >= rowStart; i--)
{
for (int j = colStart; j <= colEnd; j++)
{
d[rowEnd - i, j - colStart] = (double) data[i, j];
}
}
}
else
{
for (int i = rowStart; i <= rowEnd; i++)
{
for (int j = colStart; j <= colEnd; j++)
{
d[i - rowStart, j - colStart] = (double) data[i, j];
}
}
}
return d;
}
开发者ID:ifzz,项目名称:QuantSys,代码行数:28,代码来源:ExcelUtil.cs
示例3: SalesmanProblem
public SalesmanProblem(DenseMatrix costs, double startRecord, IEnumerable<int> startChain)
: this(costs)
{
Record = startRecord;
RecordChain = new List<int>(startChain);
AnswerFound = true;
}
开发者ID:Kant8,项目名称:IOp,代码行数:7,代码来源:SalesmanProblem.cs
示例4: Input
/// <summary>
/// Creates a new Input from double values.
/// Note that we store each example as a row in the X matrix. While calculating Theta vector, we need to insert the top column of all ones into the X matrix - this will allow us to treat theta0 as just another feature.
/// </summary>
internal Input(double[,] x, double[] y, int skip, int take)
{
if (take == 0) {
X = null;
Y = null;
return;
}
var samples = x.GetLength(0);
var features = x.GetLength(1);
//make sure we add first column of ones
var x1 = new double[take, features + 1];
var y1 = new double[take];
for (int sample = 0; sample < samples; sample++) {
if (sample < skip) {
continue;
}
for (int feature = 0; feature < features + 1; feature++) {
x1[sample - skip, feature] = (feature == 0) ? 1 : x[sample, feature - 1];
}
y1[sample - skip] = y[sample];
take--;
if (take == 0) {
break;
}
}
X = new DenseMatrix(x1);
Y = new DenseVector(y1).ToColumnMatrix();
}
开发者ID:andreister,项目名称:NMachine,代码行数:37,代码来源:Input.cs
示例5: Factorize
public void Factorize(Matrix meanMatrix)
{
int count = 0;
movieCount = meanMatrix.RowCount;
userCount = meanMatrix.ColumnCount;
convergedMovie = DenseMatrix.Build.Dense(K, movieCount, 0);
convergedUser = DenseMatrix.Build.Dense(userCount, K, 0);
A = new DenseMatrix(DenseColumnMajorMatrixStorage<double>.OfMatrix(DenseMatrix.Build.Dense(K, movieCount, 0.1).Storage));
B = new DenseMatrix(DenseColumnMajorMatrixStorage<double>.OfMatrix(DenseMatrix.Build.Dense(userCount, K, 0.1).Storage));
while (count < 50)
{
for (int k = 0; k < K; k++)
{
for (int m = 0; m < movieCount; m++)
{
for (int u = 0; u < userCount; u++)
{
train(k, u, m, meanMatrix[m, u]);
}
}
}
Console.WriteLine(count++);
if (IsConverged())
break;
}
}
开发者ID:thilemann,项目名称:WebIntelligence,代码行数:28,代码来源:Factorization.cs
示例6: Compute
public void Compute(DenseMatrix x1, int size)
{
//Setting Preparation.....................................................................................................
_estimationLength = x1.Values.Length;
//Creation of a Z matrix..................................................................................................
// ReSharper disable once CSharpWarnings::CS0618
var z = new DenseMatrix(_estimationLength, size, 1.0);
for (var i = 0; i <= _estimationLength - 1; i++)
{
for (var j = 0; j <= size - 1; j++)
{
z[i, j] = Math.Pow(i,j);
}
}
//Computation of Theta matrix.............................................................................................
var zt = z.Transpose();
var ztz = zt * z;
var theta = ztz.Inverse() * zt * x1;
// ReSharper disable once CSharpWarnings::CS0618
_output = new DenseMatrix(_estimationLength, 1, 1.0);
//Output creation.........................................................................................................
for (var i = 0; i <= _estimationLength - 1; i++)
{
for (var j = 0; j <= size - 1; j++)
{
_output[i, 0] += theta[j,0]*Math.Pow(i,j);
}
}
_estimationDone = true;
}
开发者ID:KH8,项目名称:AmpIdent,代码行数:34,代码来源:Interpolation.cs
示例7: CalculateFuzzyMatrix
/// <summary>
/// 计算模糊矩阵
/// </summary>
private void CalculateFuzzyMatrix()
{
MemberShipFun _memeberShipFun = new MemberShipFun();
for (int i = AHPIndexHierarchyUtil.totalLevelCount - 2; i >= 0; i--)
{
List<AHPIndexHierarchy> iLevelAhpIndexs = _ahpIndexUtil.FindbyLevel(i);
foreach (AHPIndexHierarchy _iLevelAhpIndex in iLevelAhpIndexs)
{
List<string> childrenNames = _iLevelAhpIndex.ChildrenNames;
DenseMatrix _iLevelMatrix = new DenseMatrix(childrenNames.Count, MemberShipFun.HealthLevelCount);
DenseVector _childrenValue = new DenseVector(childrenNames.Count);
for (int j = 0; j < childrenNames.Count; j++)
{
string name = childrenNames[j];
AHPIndexHierarchy _ahpIndex = _ahpIndexUtil.FindbyName(name);
if (i == AHPIndexHierarchyUtil.totalLevelCount - 2)//是底层
{
_ahpIndex.FuzzyValue = _memeberShipFun.TrapezoiMebership(_ahpIndex.IndexValue);
}
_iLevelMatrix = (DenseMatrix)_iLevelMatrix.InsertRow(j, _ahpIndex.FuzzyValue);
_iLevelMatrix = (DenseMatrix)_iLevelMatrix.RemoveRow(j + 1);
//_ahpIndex.ChildrenFuzzyMatrix = (DenseMatrix)_iLevelMatrix;
_childrenValue[j] = _ahpIndex.IndexValue;
}
_iLevelAhpIndex.ChildrenFuzzyMatrix = _iLevelMatrix;
_iLevelAhpIndex.IndexValue = _iLevelAhpIndex.ChildrenWeightVector * _childrenValue;
_iLevelAhpIndex.FuzzyValue = FuzzyOperator.WeightedAverage(_iLevelAhpIndex.ChildrenWeightVector, _iLevelAhpIndex.ChildrenFuzzyMatrix);
}
}
}
开发者ID:zeuscn,项目名称:ShieldTunnelHealthEvaluation,代码行数:34,代码来源:Calculation.cs
示例8: Optimize
public void Optimize(Dictionary<double, double> values)
{
var n = _f.Functions.Count();
var xs = values.Select(v => v.Key).ToList();
var ys = values.Select(v => v.Value).ToList();
var fs = new List<List<double>>(n);
for (var i = 0; i < n; i++)
{
fs[i] = _f.Functions[i].Evaluate(xs);
}
var matrix = new DenseMatrix(n, n);
var vector = new DenseVector(n);
for (var i = 0; i < n; i++)
{
for (var j = 0; j < n; j++)
{
matrix[i, j] = fs[i].ScalarProduct(fs[j]);
}
vector[i] = ys.ScalarProduct(fs[i]);
}
var matrixInverse = matrix.Inverse();
var result = matrixInverse * vector;
for (var i = 0; i < n; i++)
{
_f.LinearParameters[i].Value = result[i];
}
}
开发者ID:LucasFievet,项目名称:Tomorrow,代码行数:32,代码来源:LCFunctionLinearOptimizer.cs
示例9: Load
public void Load(string FileName)
{
using (StreamReader sr = new StreamReader(FileName))
{
string line = sr.ReadLine();
NumberOfColumns = int.Parse(line.Split(new Char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries)[1]);
line = sr.ReadLine();
NumberOfRows = int.Parse(line.Split(new Char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries)[1]);
line = sr.ReadLine();
XOrigin = double.Parse(line.Split(new Char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries)[1]);
line = sr.ReadLine();
YOrigin = double.Parse(line.Split(new Char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries)[1]);
line = sr.ReadLine();
GridSize = double.Parse(line.Split(new Char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries)[1]);
line = sr.ReadLine();
DeleteValue = double.Parse(line.Split(new Char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries)[1]);
Data = new DenseMatrix(NumberOfRows, NumberOfColumns);
string[] DataRead;
for (int j = 0; j < NumberOfRows; j++)
{
DataRead = sr.ReadLine().Split(new Char[] { ' ' }, StringSplitOptions.RemoveEmptyEntries);
for (int i = 0; i < NumberOfColumns; i++)
{
Data[NumberOfRows - j - 1, i] = double.Parse(DataRead[i]);
}
}
}
}
开发者ID:XiBeichuan,项目名称:hydronumerics,代码行数:31,代码来源:ASCIIGrid.cs
示例10: Normalize2D
// Returns normalisation matrix : xn = Mx
// Uses list of points : each point is 3-vector
// Assusmes that weight of each point is 1
public static Matrix<double> Normalize2D(List<Vector<double>> points)
{
Matrix<double> norm = new DenseMatrix(3, 3);
int n = points.Count;
// Compute center of image points
double xc = 0, yc = 0;
for(int c = 0; c < n; ++c)
{
xc += points[c].At(0);
yc += points[c].At(1);
}
xc /= n;
yc /= n;
// Get mean distance of points from center
double dist = 0;
for(int c = 0; c < n; ++c)
{
dist += Math.Sqrt((points[c].At(0) - xc) * (points[c].At(0) - xc) +
(points[c].At(1) - yc) * (points[c].At(1) - yc));
}
dist /= n;
// Normalize in a way that mean dist = sqrt(2)
double ratio = Math.Sqrt(2) / dist;
// Noramlize matrix - homonogeus point must be multiplied by it
norm[0, 0] = ratio;
norm[1, 1] = ratio;
norm[0, 2] = -ratio * xc;
norm[1, 2] = -ratio * yc;
norm[2, 2] = 1.0;
return norm;
}
开发者ID:KFlaga,项目名称:Cam3D,代码行数:35,代码来源:PointNormalizer.cs
示例11: Convolve
// Return convolution A * B
// Size of returned matrix = size of A, but
// elements on boundaries ( of length rows(cols) of B / 2 )
// are not computed and set to 0
// Size of B must be odd
public static Matrix Convolve(Matrix A, Matrix B)
{
Matrix conv = new DenseMatrix(A.RowCount, A.ColumnCount);
int row2 = B.RowCount / 2;
int col2 = B.ColumnCount / 2;
int xmax = A.ColumnCount - col2;
int ymax = A.RowCount - row2;
int y, x, dx, dy;
double maskSum;
for ( y = row2; y < ymax; ++y)
for ( x = col2; x < xmax; ++x)
{
maskSum = 0.0f;
for ( dy = -row2; dy <= row2; ++dy)
for ( dx = -col2; dx <= col2; ++dx)
{
maskSum += A[y + dy, x + dx] * B[row2 + dy, col2 + dx];
}
conv[y, x] = maskSum;
}
return conv;
}
开发者ID:KFlaga,项目名称:Cam3D,代码行数:31,代码来源:ImageProcessingUtils.cs
示例12: WriteDataToJson
public static void WriteDataToJson(string[] symbols, DateTime[] dateTimes, DenseMatrix data, string filename)
{
StringBuilder jsonStringBuilder = new StringBuilder();
jsonStringBuilder.Append("[");
for (int i = 0; i < data.ColumnCount; i++)
{
jsonStringBuilder.Append("[");
jsonStringBuilder.Append(dateTimes[i].Subtract(new DateTime(1970, 1, 1, 0, 0, 0, DateTimeKind.Utc)).TotalMilliseconds.ToString());
foreach (double d in data.Column(i))
{
jsonStringBuilder.Append(",");
jsonStringBuilder.Append((d.Equals(double.NaN) ? "null" : Math.Round(d, 8).ToString()));
}
jsonStringBuilder.Append("]");
if (i != data.ColumnCount - 1) jsonStringBuilder.Append(",\n");
}
jsonStringBuilder.Append("]");
using (var file = new StreamWriter(QSConstants.DEFAULT_DATA_FILEPATH + @filename))
{
file.WriteLine(jsonStringBuilder.ToString());
}
}
开发者ID:ifzz,项目名称:QuantSys,代码行数:25,代码来源:Visualize.cs
示例13: CreateDCTMatrix
public static Matrix<double> CreateDCTMatrix(int n)
{
if (dctMatrixes.ContainsKey(n))
{
return dctMatrixes[n];
}
var matrix = new DenseMatrix(n);
var val = 1d / Math.Sqrt(n);
for (int i = 0; i < n; i++)
{
matrix[0, i] = val;
}
var sqrt2 = Math.Sqrt(2d / n);
for (int x = 0; x < n; x++)
{
for (int y = 1; y < n; y++)
{
matrix[x, y] = sqrt2 * Math.Cos((Math.PI / 2 / n) * y * (2 * x + 1));
}
}
dctMatrixes[n] = matrix;
return matrix;
}
开发者ID:dEMonaRE,项目名称:HearthstoneTracker,代码行数:26,代码来源:DCTMatrix.cs
示例14: CD_HMM
DenseMatrix[] sigmas; //covariance of the 3D gaussians.
#endregion Fields
#region Constructors
public CD_HMM(MarkovChain A, DenseVector pi, DenseVector[] mus, DenseMatrix[] sigmas)
{
this.A = A;
this.pi = pi;
this.mus = mus;
this.sigmas = sigmas;
}
开发者ID:Daniel-Nichol,项目名称:sign-align,代码行数:13,代码来源:CD-HMM.cs
示例15: FindTransformation
public void FindTransformation(ArrayList kinectCoors, ArrayList projectorCoors)
{
PrepareMatrices(kinectCoors, projectorCoors);
DenseMatrix problem = foundCoordinatesMatrix;
result = (DenseMatrix) problem.QR().Solve(rightSideMatrix);
Console.Out.WriteLine(result);
}
开发者ID:awais045,项目名称:kinect-1,代码行数:7,代码来源:SolveForBlog.cs
示例16: MainWindow
public MainWindow()
{
InitializeComponent();
Graph = new UserControl1();
this.Content = Graph;
var t = Generate();
// var s = t.Item1.Svd(true);
//var nd = t.Item1.Multiply(s.VT().SubMatrix(0, 8, 0, 8));
var mlp = new MLP(8, 100, 1);
var r = mlp.Train(t.Item1, t.Item2, null, null, 2500);
Graph.Set(r.TrainingSquaredError, r.TrainingError);
DenseMatrix data = new DenseMatrix(new double[,] { { 1, 1 }, { 1, 0 }, { 0, 0 }, { 0, 1 } });
DenseMatrix labels = new DenseMatrix(new double[,] { { 1, 0 }, { 0, 1 }, { 1, 0 }, { 0, 1 } });
//var mlp = new MLP(2, 100, 2);
//var r = mlp.Train(data, labels, data, labels, 5000);
//Graph.Set(r.TrainingSquaredError, r.TrainingError);
}
开发者ID:maxbogue,项目名称:numpy-neuralnet,代码行数:27,代码来源:MainWindow.xaml.cs
示例17: GetLinRegArgs
private static void GetLinRegArgs(IEnumerable<double[]> items, out DenseMatrix xM, out DenseVector yV)
{
var original = items;
var transformed = original.Select(a => new Tuple<double[], double>(Phi(a), a[2])).ToList();
xM = DenseMatrix.Create(transformed.Count, transformed[0].Item1.Length, (r, c) => transformed[r].Item1[c]);
yV = DenseVector.OfEnumerable(transformed.Select(t => t.Item2));
}
开发者ID:jschlitz,项目名称:LFD-WeightDecay,代码行数:7,代码来源:Program.cs
示例18: CorrelationMatrix
public static Matrix<double> CorrelationMatrix(List<List<double>> x)
{
Matrix<double> correlM = new DenseMatrix(x.Count, x.Count);
//off diagonal elements
for (int i = 0; i < x.Count; i++)
{
var rowx = x[i];
for (int j = 0; j < x.Count; j++)
{
var rowy = x[j];
if (i < j)
{
correlM[i, j] = Correlation.Pearson(rowx, rowy);
}
if (i > j)
{
correlM[i, j] = correlM[j, i];
}
}
}
//Diagonal elements
for (int i = 0; i < x.Count; i++)
{
correlM[i, i] = 1;
}
return correlM;
}
开发者ID:QANTau,项目名称:QPAS,代码行数:29,代码来源:MathUtils.cs
示例19: ToMatrix
public DenseMatrix ToMatrix()
{
var res = new DenseMatrix(3, 1);
res[0, 0] = this.X;
res[1, 0] = this.Y;
res[2, 0] = this.Z;
return res;
}
开发者ID:homoluden,项目名称:fedkf-ga,代码行数:8,代码来源:Vector3.cs
示例20: BasicFuncBoxes
/// <summary>
/// ctor with params
/// </summary>
/// <param name="N">number of rows of each matrix, point count</param>
/// <param name="L">number of cols of each matrix, it is height of the tree</param>
public BasicFuncBoxes(int N,int L)
{
n = N;
l = L;
x = new DenseMatrix(n, l);
y = new DenseMatrix(n, l);
z = new DenseMatrix(n, l);
}
开发者ID:Yapko,项目名称:ACASparseMatrix,代码行数:13,代码来源:BasicFuncBoxes.cs
注:本文中的MathNet.Numerics.LinearAlgebra.Double.DenseMatrix类示例由纯净天空整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。 |
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