public virtual Matrix <double> Jacobian(Vector <double> x)
{
var output = new LinearAlgebra.Double.DenseMatrix(this.ItemDimension, this.ParameterDimension);
this.JacobianbyRef(x, output);
return(output);
}
public virtual Matrix <double> ItemHessian(Vector <double> x, int itemIndex)
{
var output = new LinearAlgebra.Double.DenseMatrix(this.ParameterDimension, this.ParameterDimension);
this.ItemHessianByRef(x, itemIndex, output);
return(output);
}
public virtual void SsqHessianByRef(Vector <double> x, Matrix <double> output)
{
if (output.RowCount != this.ParameterDimension || output.ColumnCount != this.ParameterDimension)
{
throw new ArgumentException($"Output matrix must match parameter dimension of function; expected {this.ParameterDimension}x{this.ParameterDimension}, got {output.RowCount}x{output.ColumnCount}.");
}
for (int ii = 0; ii < this.ParameterDimension; ++ii)
{
for (int jj = 0; jj < this.ParameterDimension; ++jj)
{
output[ii, jj] = 0.0;
}
}
var tmp_grad = new LinearAlgebra.Double.DenseVector(this.ParameterDimension);
var tmp_hess = new LinearAlgebra.Double.DenseMatrix(this.ParameterDimension, this.ParameterDimension);
double tmp_value = 0.0;
for (int ii = 0; ii < this.ItemDimension; ++ii)
{
tmp_value = this.ItemValue(x, ii);
this.ItemGradientByRef(x, ii, tmp_grad);
this.ItemHessianByRef(x, ii, tmp_hess);
for (int jj = 0; jj < this.ParameterDimension; ++jj)
{
for (int kk = 0; kk < this.ParameterDimension; ++kk)
{
var increment = 2 * (tmp_value * tmp_hess[jj, kk] + tmp_grad[jj] * tmp_grad[kk]);
output[jj, kk] += increment;
}
}
}
}
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 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));
}
}
