public void CanCreateMatrixNormal(int n, int p)
{
var matrixM = Matrix<double>.Build.Random(n, p, 1);
var matrixV = Matrix<double>.Build.RandomPositiveDefinite(n, 1);
var matrixK = Matrix<double>.Build.RandomPositiveDefinite(p, 1);
var d = new MatrixNormal(matrixM, matrixV, matrixK);
for (var i = 0; i < matrixM.RowCount; i++)
{
for (var j = 0; j < matrixM.ColumnCount; j++)
{
Assert.AreEqual(matrixM[i, j], d.Mean[i, j]);
}
}
for (var i = 0; i < matrixV.RowCount; i++)
{
for (var j = 0; j < matrixV.ColumnCount; j++)
{
Assert.AreEqual(matrixV[i, j], d.RowCovariance[i, j]);
}
}
for (var i = 0; i < matrixK.RowCount; i++)
{
for (var j = 0; j < matrixK.ColumnCount; j++)
{
Assert.AreEqual(matrixK[i, j], d.ColumnCovariance[i, j]);
}
}
}
public void CanSample(int n, int p)
{
var d = new MatrixNormal(Matrix<double>.Build.Random(n, p, 1), Matrix<double>.Build.RandomPositiveDefinite(n, 1), Matrix<double>.Build.RandomPositiveDefinite(p, 1));
d.Sample();
}
public void ValidateDensity()
{
const int Rows = 2;
const int Cols = 2;
var m = Matrix<double>.Build.Dense(Rows, Cols);
m[0, 0] = 0.156065579983862;
m[0, 1] = -0.568039841576594;
m[1, 0] = -0.806288628097313;
m[1, 1] = -1.20004405005077;
var v = Matrix<double>.Build.Dense(Rows, Rows);
v[0, 0] = 0.674457817054746;
v[0, 1] = 0.878930403442185;
v[1, 0] = 0.878930403442185;
v[1, 1] = 1.76277498368061;
var k = Matrix<double>.Build.Dense(Cols, Cols);
k[0, 0] = 0.674457817054746;
k[0, 1] = 0.878930403442185;
k[1, 0] = 0.878930403442185;
k[1, 1] = 1.76277498368061;
var d = new MatrixNormal(m, v, k);
var x = Matrix<double>.Build.Dense(Rows, Cols);
x[0, 0] = 2;
x[0, 1] = 2;
AssertHelpers.AlmostEqualRelative(0.00015682927366491211, d.Density(x), 16);
}
public void ValidateNonsquareDensity()
{
const int Rows = 2;
const int Cols = 1;
var m = Matrix<double>.Build.Dense(Rows, Cols);
m[0, 0] = 0.156065579983862;
m[1, 0] = -0.806288628097313;
var v = Matrix<double>.Build.Dense(Rows, Rows);
v[0, 0] = 0.674457817054746;
v[0, 1] = 0.878930403442185;
v[1, 0] = 0.878930403442185;
v[1, 1] = 1.76277498368061;
var k = Matrix<double>.Build.Dense(Cols, Cols);
k[0, 0] = 0.674457817054746;
var d = new MatrixNormal(m, v, k);
var x = Matrix<double>.Build.Dense(Rows, Cols);
x[0, 0] = 2;
x[1, 0] = 1.5;
AssertHelpers.AlmostEqualRelative(0.008613384131384546, d.Density(x), 12);
}
public void CanGetK(int n, int p)
{
var matrixK = Matrix<double>.Build.RandomPositiveDefinite(p, 1);
var d = new MatrixNormal(Matrix<double>.Build.Random(n, p, 1), Matrix<double>.Build.RandomPositiveDefinite(n, 1), matrixK);
for (var i = 0; i < matrixK.RowCount; i++)
{
for (var j = 0; j < matrixK.ColumnCount; j++)
{
Assert.AreEqual(matrixK[i, j], d.ColumnCovariance[i, j]);
}
}
}
public void CanGetM(int n, int p)
{
var matrixM = Matrix<double>.Build.Random(n, p, 1);
var d = new MatrixNormal(matrixM, Matrix<double>.Build.RandomPositiveDefinite(n, 1), Matrix<double>.Build.RandomPositiveDefinite(p, 1));
for (var i = 0; i < matrixM.RowCount; i++)
{
for (var j = 0; j < matrixM.ColumnCount; j++)
{
Assert.AreEqual(matrixM[i, j], d.Mean[i, j]);
}
}
}
public void ValidateToString()
{
const int N = 2;
const int P = 5;
var d = new MatrixNormal(Matrix<double>.Build.Random(N, P, 1), Matrix<double>.Build.RandomPositiveDefinite(N, 1), Matrix<double>.Build.RandomPositiveDefinite(P, 1));
Assert.AreEqual("MatrixNormal(Rows = 2, Columns = 5)", d.ToString());
}
public void HasRandomSourceEvenAfterSetToNull()
{
const int N = 2;
const int P = 3;
var d = new MatrixNormal(Matrix<double>.Build.Random(N, P, 1), Matrix<double>.Build.RandomPositiveDefinite(N, 1), Matrix<double>.Build.RandomPositiveDefinite(P, 1));
Assert.DoesNotThrow(() => d.RandomSource = null);
Assert.IsNotNull(d.RandomSource);
}
public void HasRandomSource()
{
const int N = 2;
const int P = 3;
var d = new MatrixNormal(Matrix<double>.Build.Random(N, P, 1), Matrix<double>.Build.RandomPositiveDefinite(N, 1), Matrix<double>.Build.RandomPositiveDefinite(P, 1));
Assert.IsNotNull(d.RandomSource);
}
