public void CanClearSubMatrixEx()
{
var dmr = new MatlabMatrixReader("./data/Matlab/sparse-small.mat");
var matrix = dmr.ReadMatrix("S");
var matrix2 = matrix.Clone();
// Zero the 40th row
for (int column = 0; column < matrix.ColumnCount; column++)
{
matrix.At(39, column, 0.0);
}
matrix2.ClearRow(39);
// Zero the 4th column
for (int row = 0; row < matrix.RowCount; row++)
{
matrix.At(row, 3, 0.0);
}
matrix2.ClearColumn(3);
// Zero submatrix rows 20..30 columns 8..10
for (int row = 19; row <= 29; row++)
{
for (int column = 7; column <= 9; column++)
{
matrix.At(row, column, 0.0);
}
}
matrix2.ClearSubMatrix(19, 11, 7, 3);
Assert.That(matrix2.Equals(matrix), Is.True);
}
// [TestMethod()]
public void SavitzkyGolayTest()
{
// int winSize = 5; // TODO: 初始化为适当的值
var target = new SavitzkyGolay(31); // TODO: 初始化为适当的值
var matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\X.mat");
var input = matReader.ReadMatrix();
var reader2 = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_smooth_31.mat");
var expected = reader2.ReadMatrix();
var actual = target.Process((Matrix)input, RIPP.Lib.MathLib.VectorType.Row);
var writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_smooth_31_my.mat");
writer.WriteMatrix <double>(actual, "dd");
writer.Close();
target = new SavitzkyGolay(21);
actual = target.Process((Matrix)input, RIPP.Lib.MathLib.VectorType.Row);
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_smooth_21_my.mat");
writer.WriteMatrix <double>(actual, "dd");
writer.Close();
// Assert.Inconclusive("验证此测试方法的正确性。");
}
public void CanWriteMatrices()
{
Matrix mat1 = new DenseMatrix(5, 3);
for (var i = 0; i < mat1.ColumnCount; i++)
{
mat1[i, i] = i + .1f;
}
Matrix mat2 = new DenseMatrix(4, 5);
for (var i = 0; i < mat2.RowCount; i++)
{
mat2[i, i] = i + .1f;
}
Matrix mat3 = new SparseMatrix(5, 4);
for (var i = 0; i < mat3.ColumnCount; i++)
{
mat3[i, i] = i + .1f;
}
Matrix mat4 = new SparseMatrix(3, 5);
for (var i = 0; i < mat4.RowCount; i++)
{
mat4[i, i] = i + .1f;
}
var write = new[] { mat1, mat2, mat3, mat4 };
var names = new[] { "mat1", "dense_matrix_2", "s1", "sparse2" };
if (File.Exists("test.mat"))
{
File.Delete("test.mat");
}
var writer = new MatlabMatrixWriter("test.mat");
writer.WriteMatrices(write, names);
writer.Dispose();
var reader = new MatlabMatrixReader("test.mat");
var read = reader.ReadMatrices(names);
Assert.AreEqual(write.Length, read.Count);
for (var i = 0; i < write.Length; i++)
{
var w = write[i];
var r = read[names[i]];
Assert.AreEqual(w.RowCount, r.RowCount);
Assert.AreEqual(w.ColumnCount, r.ColumnCount);
Assert.IsTrue(w.Equals(r));
}
}
public void CanReadNamedSparseMatrix()
{
var dmr = new MatlabMatrixReader("./data/Matlab/sparse-small.mat");
var matrix = dmr.ReadMatrix("S");
Assert.AreEqual(100, matrix.RowCount);
Assert.AreEqual(100, matrix.ColumnCount);
Assert.AreEqual(typeof(SparseMatrix), matrix.GetType());
AssertHelpers.AlmostEqual(17.6385090630805f, matrix.FrobeniusNorm(), 6);
}
public void CanWriteDoubleMatrices()
{
var mat1 = new LinearAlgebra.Double.DenseMatrix(5, 3);
for (var i = 0; i < mat1.ColumnCount; i++)
{
mat1[i, i] = i + .1;
}
var mat2 = new LinearAlgebra.Double.DenseMatrix(4, 5);
for (var i = 0; i < mat2.RowCount; i++)
{
mat2[i, i] = i + .1;
}
var mat3 = new LinearAlgebra.Double.SparseMatrix(5, 4);
mat3[0, 0] = 1.1;
mat3[0, 2] = 2.2;
mat3[4, 3] = 3.3;
var mat4 = new LinearAlgebra.Double.SparseMatrix(3, 5);
mat4[0, 0] = 1.1;
mat4[0, 2] = 2.2;
mat4[2, 4] = 3.3;
var write = new LinearAlgebra.Double.Matrix[] { mat1, mat2, mat3, mat4 };
var names = new[] { "mat1", "dense_matrix_2", "s1", "sparse2" };
if (File.Exists("testd.mat"))
{
File.Delete("testd.mat");
}
var writer = new MatlabMatrixWriter("testd.mat");
writer.WriteMatrices(write, names);
writer.Dispose();
var reader = new MatlabMatrixReader <double>("testd.mat");
var read = reader.ReadMatrices(names);
Assert.AreEqual(write.Length, read.Count);
for (var i = 0; i < write.Length; i++)
{
var w = write[i];
var r = read[names[i]];
Assert.AreEqual(w.RowCount, r.RowCount);
Assert.AreEqual(w.ColumnCount, r.ColumnCount);
Assert.IsTrue(w.Equals(r));
}
}
public void CanReadFirstMatrix()
{
var dmr = new MatlabMatrixReader("./data/Matlab/A.mat");
var matrix = dmr.ReadMatrix();
Assert.AreEqual(100, matrix.RowCount);
Assert.AreEqual(100, matrix.ColumnCount);
Assert.AreEqual(typeof(DenseMatrix), matrix.GetType());
AssertHelpers.AlmostEqual(100.108979553704, matrix.FrobeniusNorm(), 5);
}
public void CanReadNamedMatrix()
{
var dmr = new MatlabMatrixReader("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices(new[] { "Ad" });
Assert.AreEqual(1, matrices.Length);
Assert.AreEqual(100, matrices[0].RowCount);
Assert.AreEqual(100, matrices[0].ColumnCount);
AssertHelpers.AlmostEqual(100.431635988639f, matrices[0].FrobeniusNorm(), 6);
Assert.AreEqual(typeof(DenseMatrix), matrices[0].GetType());
}
public void CanReadAllMatrices()
{
var dmr = new MatlabMatrixReader("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices();
Assert.AreEqual(30, matrices.Length);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(DenseMatrix), matrix.GetType());
}
}
public void CanReadNonComplex32NamedSparseMatrix()
{
var dmr = new MatlabMatrixReader <Complex32>("./data/Matlab/sparse-small.mat");
var matrix = dmr.ReadMatrix("S");
Assert.AreEqual(100, matrix.RowCount);
Assert.AreEqual(100, matrix.ColumnCount);
Assert.AreEqual(typeof(LinearAlgebra.Complex32.SparseMatrix), matrix.GetType());
AssertHelpers.AlmostEqual(17.6385090630805, matrix.FrobeniusNorm().Real, 6);
}
public void CanReadNamedMatrices()
{
var dmr = new MatlabMatrixReader("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices(new[] { "Ad", "Au64" });
Assert.AreEqual(2, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(DenseMatrix), matrix.Value.GetType());
}
}
public void CanReadAllMatrices()
{
var dmr = new MatlabMatrixReader<double>("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices();
Assert.AreEqual(30, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(LinearAlgebra.Double.DenseMatrix), matrix.Value.GetType());
}
}
public void CanReadNamedSparseMatrix()
{
var dmr = new MatlabMatrixReader("./data/Matlab/sparse-small.mat");
var matrix = dmr.ReadMatrix("S");
Assert.AreEqual(100, matrix.RowCount);
Assert.AreEqual(100, matrix.ColumnCount);
Assert.AreEqual(typeof(SparseMatrix), matrix.GetType());
AssertHelpers.AlmostEqual(17.6385090630805f, matrix.FrobeniusNorm(), 6);
}
public void CanReadNonComplexFirstMatrix()
{
var dmr = new MatlabMatrixReader <Complex>("./data/Matlab/A.mat");
var matrix = dmr.ReadMatrix();
Assert.AreEqual(100, matrix.RowCount);
Assert.AreEqual(100, matrix.ColumnCount);
Assert.AreEqual(typeof(LinearAlgebra.Complex.DenseMatrix), matrix.GetType());
AssertHelpers.AlmostEqual(100.108979553704, matrix.FrobeniusNorm(), 13);
}
public void CanReadFirstMatrix()
{
var dmr = new MatlabMatrixReader("./data/Matlab/A.mat");
var matrix = dmr.ReadMatrix();
Assert.AreEqual(100, matrix.RowCount);
Assert.AreEqual(100, matrix.ColumnCount);
Assert.AreEqual(typeof(DenseMatrix), matrix.GetType());
AssertHelpers.AlmostEqual(100.108979553704f, matrix.FrobeniusNorm(), 6);
}
public void CanReadNonComplexAllMatrices()
{
var dmr = new MatlabMatrixReader("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices();
Assert.AreEqual(30, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(DenseMatrix), matrix.Value.GetType());
}
}
public void CanReadNamedMatrices()
{
var dmr = new MatlabMatrixReader("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices(new[] { "Ad", "Au64" });
Assert.AreEqual(2, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(DenseMatrix), matrix.Value.GetType());
}
}
public void CanReadAllMatrices()
{
var dmr = new MatlabMatrixReader <double>("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices();
Assert.AreEqual(30, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(LinearAlgebra.Double.DenseMatrix), matrix.Value.GetType());
}
}
public void CanReadNamedMatrix()
{
var dmr = new MatlabMatrixReader("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices(new[] { "Ad" });
Assert.AreEqual(1, matrices.Count);
var ad = matrices["Ad"];
Assert.AreEqual(100, ad.RowCount);
Assert.AreEqual(100, ad.ColumnCount);
AssertHelpers.AlmostEqual(100.431635988639f, ad.FrobeniusNorm(), 6);
Assert.AreEqual(typeof(DenseMatrix), ad.GetType());
}
public void CanReadSparseComplexAllMatrices()
{
var dmr = new MatlabMatrixReader("./data/Matlab/sparse_complex.mat");
var matrices = dmr.ReadMatrices();
Assert.AreEqual(3, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(SparseMatrix), matrix.Value.GetType());
}
var a = matrices["sa"];
Assert.AreEqual(100, a.RowCount);
Assert.AreEqual(100, a.ColumnCount);
AssertHelpers.AlmostEqual(13.223654390985379, a.L2Norm(), 15);
}
public void CanReadComplexAllMatrices()
{
var dmr = new MatlabMatrixReader("./data/Matlab/complex.mat");
var matrices = dmr.ReadMatrices();
Assert.AreEqual(3, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(DenseMatrix), matrix.Value.GetType());
}
var a = matrices["a"];
Assert.AreEqual(100, a.RowCount);
Assert.AreEqual(100, a.ColumnCount);
AssertHelpers.AlmostEqual(27.232498979698409, a.L2Norm(), 15);
}
public void CanReadComplexAllMatrices()
{
var dmr = new MatlabMatrixReader("./data/Matlab/complex.mat");
var matrices = dmr.ReadMatrices();
Assert.AreEqual(3, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(DenseMatrix), matrix.Value.GetType());
}
var a = matrices["a"];
Assert.AreEqual(100, a.RowCount);
Assert.AreEqual(100, a.ColumnCount);
AssertHelpers.AlmostEqual(27.232498979698409, a.L2Norm().Real, 6);
}
public void CanReadSparseComplexAllMatrices()
{
var dmr = new MatlabMatrixReader("./data/Matlab/sparse_complex.mat");
var matrices = dmr.ReadMatrices();
Assert.AreEqual(3, matrices.Count);
foreach (var matrix in matrices)
{
Assert.AreEqual(typeof(SparseMatrix), matrix.Value.GetType());
}
var a = matrices["sa"];
Assert.AreEqual(100, a.RowCount);
Assert.AreEqual(100, a.ColumnCount);
AssertHelpers.AlmostEqual(13.223654390985379, a.L2Norm().Real, 7);
}
// [TestMethod()]
public void MSCTest()
{
// int winSize = 5; // TODO: 初始化为适当的值
var target = new MSC(); // TODO: 初始化为适当的值
var matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\X.mat");
var input = matReader.ReadMatrix();
var actual = target.Process((Matrix)input, RIPP.Lib.MathLib.VectorType.Row);
var writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_msc_my.mat");
writer.WriteMatrix <double>(actual, "dd");
writer.Close();
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_msc_my_m.mat");
writer.WriteMatrix <double>(target.Mean.ToRowMatrix(), "m");
writer.Close();
//测试按列来
var input2 = input.Transpose();
var target2 = new MSC();
actual = target2.Process((Matrix)input2, RIPP.Lib.MathLib.VectorType.Column);
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_msc_myColumn.mat");
writer.WriteMatrix <double>(actual, "dColumn");
writer.Close();
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_msc_my_mColumn.mat");
writer.WriteMatrix <double>(target.Mean.ToRowMatrix(), "mColumn");
writer.Close();
//
var target3 = new MSC();
actual = target3.ProcessForPrediction((Matrix)input, RIPP.Lib.MathLib.VectorType.Row, target.Mean);
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_msc_my_ForPrediction.mat");
writer.WriteMatrix <double>(actual, "dd");
writer.Close();
// Assert.Inconclusive("验证此测试方法的正确性。");
}
//[TestMethod]
public void AtScaleTest()
{
var target = new AtScale(); // TODO: 初始化为适当的值
var matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\X.mat");
var input = matReader.ReadMatrix();
var actual = target.Process((Matrix)input, RIPP.Lib.MathLib.VectorType.Row);
var writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_atscale_my.mat");
writer.WriteMatrix <double>(actual, "dd");
writer.Close();
var o2 = target.Process((Matrix)input.Transpose(), RIPP.Lib.MathLib.VectorType.Column);
var writer2 = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_atscale_my2.mat");
writer2.WriteMatrix <double>(o2, "dd2");
writer.Close();
}
//[TestMethod()]
public void DetrendTest()
{
// int winSize = 5; // TODO: 初始化为适当的值
var target = new Detrend(); // TODO: 初始化为适当的值
var matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\X.mat");
var input = matReader.ReadMatrix();
var actual = target.Process((Matrix)input, RIPP.Lib.MathLib.VectorType.Row);
var writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_detrend_my.mat");
writer.WriteMatrix <double>(actual, "dd");
writer.Close();
var dd2 = target.Process((Matrix)input.Transpose(), RIPP.Lib.MathLib.VectorType.Column);
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_detrend_myColumn.mat");
writer.WriteMatrix <double>(actual, "dd2");
writer.Close();
}
//
//编写测试时，还可使用以下特性:
//
//使用 ClassInitialize 在运行类中的第一个测试前先运行代码
//[ClassInitialize()]
//public static void MyClassInitialize(TestContext testContext)
//{
//}
//
//使用 ClassCleanup 在运行完类中的所有测试后再运行代码
//[ClassCleanup()]
//public static void MyClassCleanup()
//{
//}
//
//使用 TestInitialize 在运行每个测试前先运行代码
//[TestInitialize()]
//public void MyTestInitialize()
//{
//}
//
//使用 TestCleanup 在运行完每个测试后运行代码
//[TestCleanup()]
//public void MyTestCleanup()
//{
//}
//
#endregion
/// <summary>
///Compute 的测试
///</summary>
// [TestMethod()]
public void Deriate1Test()
{
int winSize = 5; // TODO: 初始化为适当的值
Deriate1 target = new Deriate1(winSize); // TODO: 初始化为适当的值
var matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\X.mat");
var input = matReader.ReadMatrix();
var reader2 = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_deriate1_5.mat");
var expected = reader2.ReadMatrix();
var actual = target.Process((Matrix)input, RIPP.Lib.MathLib.VectorType.Row);
var writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_deriate1_5_my.mat");
writer.WriteMatrix <double>(actual, "dd");
writer.Close();
//Assert.Inconclusive("验证此测试方法的正确性。");
}
// [TestMethod()]
public void NormPathLengthTest()
{
var target = new NormPathLength(); // TODO: 初始化为适当的值
var matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\X.mat");
var input = matReader.ReadMatrix();
var actual = target.Process((Matrix)input, RIPP.Lib.MathLib.VectorType.Row);
var writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_normpathlength_my.mat");
writer.WriteMatrix <double>(actual, "dd");
writer.Close();
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_normpathlength_mx_my.mat");
writer.WriteMatrix <double>(target.Mean.ToColumnMatrix(), "mxmy");
writer.Close();
var Scale = target.Scale.ToColumnMatrix().Clone();
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\filter\out_normpathlength_sd_my.mat");
writer.WriteMatrix <double>(Scale, "sdmy");
writer.Close();
}
public void CanReadFloatNamedMatrix()
{
var dmr = new MatlabMatrixReader<float>("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices(new[] { "Ad" });
Assert.AreEqual(1, matrices.Count);
var ad = matrices["Ad"];
Assert.AreEqual(100, ad.RowCount);
Assert.AreEqual(100, ad.ColumnCount);
AssertHelpers.AlmostEqual(100.431635988639f, ad.FrobeniusNorm(), 6);
Assert.AreEqual(typeof(LinearAlgebra.Single.DenseMatrix), ad.GetType());
}
public void CanReadNonComplex32FirstMatrix()
{
var dmr = new MatlabMatrixReader<Complex32>("./data/Matlab/A.mat");
var matrix = dmr.ReadMatrix();
Assert.AreEqual(100, matrix.RowCount);
Assert.AreEqual(100, matrix.ColumnCount);
Assert.AreEqual(typeof(LinearAlgebra.Complex32.DenseMatrix), matrix.GetType());
AssertHelpers.AlmostEqual(100.108979553704, matrix.FrobeniusNorm(), 6);
}
public void CanReadNonComplexNamedMatrix()
{
var dmr = new MatlabMatrixReader("./data/Matlab/collection.mat");
var matrices = dmr.ReadMatrices(new[] { "Ad" });
Assert.AreEqual(1, matrices.Count);
var ad = matrices["Ad"];
Assert.AreEqual(100, ad.RowCount);
Assert.AreEqual(100, ad.ColumnCount);
AssertHelpers.AlmostEqual(100.431635988639, ad.FrobeniusNorm(), 13);
Assert.AreEqual(typeof(DenseMatrix), ad.GetType());
}
// [TestMethod]
public void SpectraFitTest()
{
var matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\cx.mat");
var cx = matReader.ReadMatrix();
matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\vx.mat");
var vx = matReader.ReadMatrix();
var f1 = new Sgdiff();
f1.P = 2;
var cx1 = f1.Process((Matrix)cx);
var writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\fit\cx1.mat");
writer.WriteMatrix <double>(cx1, "cx1");
writer.Close();
var f2 = new SavitzkyGolay(5);
var cx2 = f2.Process((Matrix)cx1);
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\fit\cx2.mat");
writer.WriteMatrix <double>(cx2, "cx2");
writer.Close();
var f3 = new VarRegionManu();
f3.Xaxis = new DenseVector(cx.RowCount);
for (int i = 1; i <= cx.RowCount; i++)
{
f3.Xaxis[i - 1] = i;
}
var a = f3.Argus;
a["Xaxis"].Value = f3.Xaxis;
f3.XaxisRegion = new System.Collections.Generic.List <RegionPoint>();
f3.XaxisRegion.Add(new RegionPoint(131, 314));
f3.XaxisRegion.Add(new RegionPoint(468, 677));
a["XaxisRegion"].Value = f3.XaxisRegion;
f3.Argus = a;
var lst = new System.Collections.Generic.List <Vector>();
for (int i = 0; i < cx2.ColumnCount; i++)
{
lst.Add(f3.VarProcess((Vector)cx2.Column(i)));
}
var cx3 = new DenseMatrix(lst[0].Count, cx2.ColumnCount);
for (int i = 0; i < cx2.ColumnCount; i++)
{
cx3.SetColumn(i, lst[i]);
}
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\fit\cx3.mat");
writer.WriteMatrix <double>(cx3, "cx3");
writer.Close();
var f4 = new NormPathLength();
var cx4 = f4.Process(cx3);
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\fit\cx4.mat");
writer.WriteMatrix <double>(cx4, "cx4");
writer.Close();
matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\fit\mcx4.mat");
cx4 = (Matrix)matReader.ReadMatrix();
var fitr = new DenseMatrix(cx4.ColumnCount - 1, cx4.ColumnCount);
for (int i = 0; i < cx4.ColumnCount; i++)
{
var subm = new DenseMatrix(cx4.RowCount, cx4.ColumnCount - 1);
int tag = 0;
for (int k = 0; k < cx4.ColumnCount; k++)
{
if (k == i)
{
continue;
}
subm.SetColumn(tag, cx4.Column(k));
tag++;
}
var fr = SpectraFit.Fit((Matrix)subm, (Vector)cx4.Column(i));
fitr.SetColumn(i, fr);
}
writer = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\fit\fitr.mat");
writer.WriteMatrix <double>(fitr, "fitr");
writer.Close();
}
//[TestMethod]
public void PLS1Test()
{
var matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\x.mat");
var X = matReader.ReadMatrix();
matReader = new MatlabMatrixReader <double>(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\y.mat");
var Y = matReader.ReadMatrix().Row(0);
var pls = new PLS1SubModel();
pls.MaxFactor = 10;
pls.Train((Matrix)X, (Vector)Y);
var writer2 = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\out_pls_Weights.mat");
writer2.WriteMatrix <double>(pls.Weights, "w");
writer2.Close();
writer2 = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\out_pls_Loads.mat");
writer2.WriteMatrix <double>(pls.Loads, "l");
writer2.Close();
writer2 = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\out_pls_Scores.mat");
writer2.WriteMatrix <double>(pls.Scores, "s");
writer2.Close();
writer2 = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\out_pls_Score_Length.mat");
writer2.WriteMatrix <double>(pls.Score_Length.ToRowMatrix(), "sle");
writer2.Close();
writer2 = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\out_pls_Bias.mat");
writer2.WriteMatrix <double>(pls.Bias.ToColumnMatrix(), "Bias");
writer2.Close();
//var yLast = new DenseMatrix(pls.MaxFactor, X.ColumnCount);
//for (int i = 0; i < X.ColumnCount; i++)
//{
// yLast.SetColumn(i, pls.Predict((Vector)X.Column(i)).YLast);
//}
//writer2 = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\out_pls_yLast.mat");
//writer2.WriteMatrix<double>(yLast, "yLast");
//writer2.Close();
//CV
var lst = new List <PLS1SubResult>();
for (int i = 0; i < X.ColumnCount; i++)
{
var x = new DenseMatrix(X.RowCount, X.ColumnCount - 1);
var y = new DenseVector(X.ColumnCount - 1);
int c = 0;
for (int k = 0; k < X.ColumnCount; k++)
{
if (i == k)
{
continue;
}
x.SetColumn(c, X.Column(k));
y[c] = Y[k];
c++;
}
var z = X.Column(i);
pls = new PLS1SubModel();
pls.MaxFactor = 10;
pls.Train((Matrix)x, (Vector)y);
lst.Add(pls.Predict((Vector)z));
}
var YLast = new DenseMatrix(X.ColumnCount, 10);
for (int i = 0; i < lst.Count; i++)
{
YLast.SetRow(i, lst[i].YLast);
}
writer2 = new MatlabMatrixWriter(@"F:\3506\15chemometrics\RIPP_DEMO\src\RIPP\testdata\pls\out_pls_yLast.mat");
writer2.WriteMatrix <double>(YLast, "yLast");
writer2.Close();
}
public void CanClearSubMatrixEx()
{
var dmr = new MatlabMatrixReader("./data/Matlab/sparse-small.mat");
var matrix = dmr.ReadMatrix("S");
var matrix2 = matrix.Clone();
// Zero the 40th row
for (int column = 0; column < matrix.ColumnCount; column++)
{
matrix.At(39, column, 0.0);
}
matrix2.ClearRow(39);
// Zero the 4th column
for (int row = 0; row < matrix.RowCount; row++)
{
matrix.At(row, 3, 0.0);
}
matrix2.ClearColumn(3);
// Zero submatrix rows 20..30 columns 8..10
for (int row = 19; row <= 29; row++)
{
for (int column = 7; column <= 9; column++)
{
matrix.At(row, column, 0.0);
}
}
matrix2.ClearSubMatrix(19, 11, 7, 3);
Assert.That(matrix2.Equals(matrix), Is.True);
}
public void CanReadNonComplex32NamedSparseMatrix()
{
var dmr = new MatlabMatrixReader<Complex32>("./data/Matlab/sparse-small.mat");
var matrix = dmr.ReadMatrix("S");
Assert.AreEqual(100, matrix.RowCount);
Assert.AreEqual(100, matrix.ColumnCount);
Assert.AreEqual(typeof(LinearAlgebra.Complex32.SparseMatrix), matrix.GetType());
AssertHelpers.AlmostEqual(17.6385090630805, matrix.FrobeniusNorm().Real, 6);
}
public void CanWriteMatrices()
{
Matrix mat1 = new DenseMatrix(5, 3);
for (var i = 0; i < mat1.ColumnCount; i++)
{
mat1[i, i] = new Complex32(i + .1f, i + .1f);
}
Matrix mat2 = new DenseMatrix(4, 5);
for (var i = 0; i < mat2.RowCount; i++)
{
mat2[i, i] = new Complex32(i + .1f, i + .1f);
}
Matrix mat3 = new SparseMatrix(5, 4);
for (var i = 0; i < mat3.ColumnCount; i++)
{
mat3[i, i] = new Complex32(i + .1f, i + .1f);
}
Matrix mat4 = new SparseMatrix(3, 5);
for (var i = 0; i < mat4.RowCount; i++)
{
mat4[i, i] = new Complex32(i + .1f, i + .1f);
}
var write = new[] { mat1, mat2, mat3, mat4 };
var names = new[] { "mat1", "dense_matrix_2", "s1", "sparse2" };
if (File.Exists("test.mat"))
{
File.Delete("test.mat");
}
var writer = new MatlabMatrixWriter("test.mat");
writer.WriteMatrices(write, names);
writer.Dispose();
var reader = new MatlabMatrixReader("test.mat");
var read = reader.ReadMatrices(names);
Assert.AreEqual(write.Length, read.Count);
for (var i = 0; i < write.Length; i++)
{
var w = write[i];
var r = read[names[i]];
Assert.AreEqual(w.RowCount, r.RowCount);
Assert.AreEqual(w.ColumnCount, r.ColumnCount);
Assert.IsTrue(w.Equals(r));
}
}
public void CanWriteComplex32Matrices()
{
var mat1 = new LinearAlgebra.Complex32.DenseMatrix(5, 3);
for (var i = 0; i < mat1.ColumnCount; i++)
{
mat1[i, i] = new Complex32(i + .1f, i + .1f);
}
var mat2 = new LinearAlgebra.Complex32.DenseMatrix(4, 5);
for (var i = 0; i < mat2.RowCount; i++)
{
mat2[i, i] = new Complex32(i + .1f, i + .1f);
}
var mat3 = new LinearAlgebra.Complex32.SparseMatrix(5, 4);
mat3[0, 0] = new Complex32(1.1f, 1.1f);
mat3[0, 2] = new Complex32(2.2f, 2.2f);
mat3[4, 3] = new Complex32(3.3f, 3.3f);
var mat4 = new LinearAlgebra.Complex32.SparseMatrix(3, 5);
mat4[0, 0] = new Complex32(1.1f, 1.1f);
mat4[0, 2] = new Complex32(2.2f, 2.2f);
mat4[2, 4] = new Complex32(3.3f, 3.3f);
var write = new LinearAlgebra.Complex32.Matrix[] { mat1, mat2, mat3, mat4 };
var names = new[] { "mat1", "dense_matrix_2", "s1", "sparse2" };
if (File.Exists("testc.mat"))
{
File.Delete("testc.mat");
}
var writer = new MatlabMatrixWriter("testc.mat");
writer.WriteMatrices(write, names);
writer.Dispose();
var reader = new MatlabMatrixReader<Complex32>("testc.mat");
var read = reader.ReadMatrices(names);
Assert.AreEqual(write.Length, read.Count);
for (var i = 0; i < write.Length; i++)
{
var w = write[i];
var r = read[names[i]];
Assert.AreEqual(w.RowCount, r.RowCount);
Assert.AreEqual(w.ColumnCount, r.ColumnCount);
Assert.IsTrue(w.Equals(r));
}
}
