//
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// http://numerics.mathdotnet.com
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using System;
using System.Collections.Generic;
using MathNet.Numerics.LinearAlgebra;
using MathNet.Numerics.LinearAlgebra.Single;
using NUnit.Framework;
namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
{
///
/// Sparse matrix tests.
///
public class SparseMatrixTests : MatrixTests
{
///
/// Creates a matrix for the given number of rows and columns.
///
/// The number of rows.
/// The number of columns.
/// A matrix with the given dimensions.
protected override Matrix CreateMatrix(int rows, int columns)
{
return new SparseMatrix(rows, columns);
}
///
/// Creates a matrix from a 2D array.
///
/// The 2D array to create this matrix from.
/// A matrix with the given values.
protected override Matrix CreateMatrix(float[,] data)
{
return SparseMatrix.OfArray(data);
}
///
/// Creates a vector of the given size.
///
/// The size of the vector to create.
///
/// The new vector.
protected override Vector CreateVector(int size)
{
return new SparseVector(size);
}
///
/// Creates a vector from an array.
///
/// The array to create this vector from.
/// The new vector.
protected override Vector CreateVector(float[] data)
{
return SparseVector.OfEnumerable(data);
}
///
/// Can create a matrix form array.
///
[Test]
public void CanCreateMatrixFrom1DArray()
{
var testData = new Dictionary>
{
{"Singular3x3", SparseMatrix.OfColumnMajor(3, 3, new float[] {1, 1, 1, 1, 1, 1, 2, 2, 2})},
{"Square3x3", SparseMatrix.OfColumnMajor(3, 3, new[] {-1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f, -3.3f, 2.2f, 6.6f})},
{"Square4x4", SparseMatrix.OfColumnMajor(4, 4, new[] {-1.1f, 0.0f, 1.0f, -4.4f, -2.2f, 1.1f, 2.1f, 5.5f, -3.3f, 2.2f, 6.2f, 6.6f, -4.4f, 3.3f, 4.3f, -7.7f})},
{"Tall3x2", SparseMatrix.OfColumnMajor(3, 2, new[] {-1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f})},
{"Wide2x3", SparseMatrix.OfColumnMajor(2, 3, new[] {-1.1f, 0.0f, -2.2f, 1.1f, -3.3f, 2.2f})}
};
foreach (var name in testData.Keys)
{
Assert.AreEqual(TestMatrices[name], testData[name]);
}
}
///
/// Matrix from array is a copy.
///
[Test]
public void MatrixFrom1DArrayIsCopy()
{
// Sparse Matrix copies values from float[], but no remember reference.
var data = new float[] {1, 1, 1, 1, 1, 1, 2, 2, 2};
var matrix = SparseMatrix.OfColumnMajor(3, 3, data);
matrix[0, 0] = 10.0f;
Assert.AreNotEqual(10.0f, data[0]);
}
///
/// Matrix from two-dimensional array is a copy.
///
[Test]
public void MatrixFrom2DArrayIsCopy()
{
var matrix = SparseMatrix.OfArray(TestData2D["Singular3x3"]);
matrix[0, 0] = 10.0f;
Assert.AreEqual(1.0f, TestData2D["Singular3x3"][0, 0]);
}
///
/// Can create a matrix from two-dimensional array.
///
/// Matrix name.
[TestCase("Singular3x3")]
[TestCase("Singular4x4")]
[TestCase("Square3x3")]
[TestCase("Square4x4")]
[TestCase("Tall3x2")]
[TestCase("Wide2x3")]
public void CanCreateMatrixFrom2DArray(string name)
{
var matrix = SparseMatrix.OfArray(TestData2D[name]);
for (var i = 0; i < TestData2D[name].GetLength(0); i++)
{
for (var j = 0; j < TestData2D[name].GetLength(1); j++)
{
Assert.AreEqual(TestData2D[name][i, j], matrix[i, j]);
}
}
}
///
/// Can create an identity matrix.
///
[Test]
public void CanCreateIdentity()
{
var matrix = SparseMatrix.Identity(5);
for (var i = 0; i < matrix.RowCount; i++)
{
for (var j = 0; j < matrix.ColumnCount; j++)
{
Assert.AreEqual(i == j ? 1.0f : 0.0f, matrix[i, j]);
}
}
}
///
/// Identity with wrong order throws ArgumentOutOfRangeException.
///
/// The size of the square matrix
[TestCase(0)]
[TestCase(-1)]
public void IdentityWithWrongOrderThrowsArgumentOutOfRangeException(int order)
{
Assert.Throws(() => SparseMatrix.Identity(order));
}
///
/// Can create a large sparse matrix
///
[Test]
public void CanCreateLargeSparseMatrix()
{
var matrix = new SparseMatrix(500, 1000);
var nonzero = 0;
var rnd = new System.Random();
for (var i = 0; i < matrix.RowCount; i++)
{
for (var j = 0; j < matrix.ColumnCount; j++)
{
var value = rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10);
if (value != 0)
{
nonzero++;
}
matrix[i, j] = value;
}
}
Assert.AreEqual(matrix.NonZerosCount, nonzero);
}
///
/// Test whether order matters when adding sparse matrices.
///
[Test]
public void CanAddSparseMatricesBothWays()
{
var m1 = new SparseMatrix(1, 3);
var m2 = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
var sum1 = m1 + m2;
var sum2 = m2 + m1;
Assert.IsTrue(sum1.Equals(m2));
Assert.IsTrue(sum1.Equals(sum2));
var sparseResult = new SparseMatrix(1, 3);
sparseResult.Add(m2, sparseResult);
Assert.IsTrue(sparseResult.Equals(sum1));
sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
sparseResult.Add(m1, sparseResult);
Assert.IsTrue(sparseResult.Equals(sum1));
sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
m1.Add(sparseResult, sparseResult);
Assert.IsTrue(sparseResult.Equals(sum1));
sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
sparseResult.Add(sparseResult, sparseResult);
Assert.IsTrue(sparseResult.Equals(2*sum1));
var denseResult = new DenseMatrix(1, 3);
denseResult.Add(m2, denseResult);
Assert.IsTrue(denseResult.Equals(sum1));
denseResult = DenseMatrix.OfArray(new float[,] {{0, 1, 1}});
denseResult.Add(m1, denseResult);
Assert.IsTrue(denseResult.Equals(sum1));
var m3 = DenseMatrix.OfArray(new float[,] {{0, 1, 1}});
var sum3 = m1 + m3;
var sum4 = m3 + m1;
Assert.IsTrue(sum3.Equals(m3));
Assert.IsTrue(sum3.Equals(sum4));
}
///
/// Test whether order matters when subtracting sparse matrices.
///
[Test]
public void CanSubtractSparseMatricesBothWays()
{
var m1 = new SparseMatrix(1, 3);
var m2 = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
var diff1 = m1 - m2;
var diff2 = m2 - m1;
Assert.IsTrue(diff1.Equals(m2.Negate()));
Assert.IsTrue(diff1.Equals(diff2.Negate()));
var sparseResult = new SparseMatrix(1, 3);
sparseResult.Subtract(m2, sparseResult);
Assert.IsTrue(sparseResult.Equals(diff1));
sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
sparseResult.Subtract(m1, sparseResult);
Assert.IsTrue(sparseResult.Equals(diff2));
sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
m1.Subtract(sparseResult, sparseResult);
Assert.IsTrue(sparseResult.Equals(diff1));
sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
sparseResult.Subtract(sparseResult, sparseResult);
Assert.IsTrue(sparseResult.Equals(0*diff1));
var denseResult = new DenseMatrix(1, 3);
denseResult.Subtract(m2, denseResult);
Assert.IsTrue(denseResult.Equals(diff1));
denseResult = DenseMatrix.OfArray(new float[,] {{0, 1, 1}});
denseResult.Subtract(m1, denseResult);
Assert.IsTrue(denseResult.Equals(diff2));
var m3 = DenseMatrix.OfArray(new float[,] {{0, 1, 1}});
var diff3 = m1 - m3;
var diff4 = m3 - m1;
Assert.IsTrue(diff3.Equals(m3.Negate()));
Assert.IsTrue(diff3.Equals(diff4.Negate()));
}
///
/// Test whether we can create a large sparse matrix
///
[Test]
public void CanCreateLargeMatrix()
{
const int Order = 1000000;
var matrix = new SparseMatrix(Order);
Assert.AreEqual(Order, matrix.RowCount);
Assert.AreEqual(Order, matrix.ColumnCount);
Assert.DoesNotThrow(() => matrix[0, 0] = 1);
}
}
}