public static void testGet(Matrix m) {
int rows = m.rows();
int cols = m.columns();
for (int trials = 0; trials < 100; ++trials) {
int i = (int) (rows * Math.random());
int j = (int) (cols * Math.random());
double v = m.get(i, j);
double r = Math.random();
m.set(i, j, r);
m.set(i, j, v);
assertEquals(v, m.get(i, j), 0.01);
}
}
@Test
public void testNonSquareMatrix() {
int[][] testInput = {
{6, 0, 5},
{0, 1, 1},
{1, 5, 0},
{0, 1, 0},
{1, 5, 7},
{1, 1, 1}
};
double[][] testOutput = {{}};
double error = .00001;
Matrix inputMatrix = new YaleSparseMatrix(6, 3);
for (int row = 0; row < 6; ++row)
for (int col = 0; col < 3; ++col) inputMatrix.set(row, col, testInput[row][col]);
Transform transform = new TfIdfTransform();
Matrix outputMatrix = transform.transform(inputMatrix);
for (int row = 0; row < 6; ++row) {
for (int col = 0; col < 3; ++col) System.out.println(outputMatrix.get(row, col));
// assertEquals(testOutput[row][col],
// outputMatrix.get(row, col), error);
}
}
@Test
public void testSparseListMatrix() {
List<SparseDoubleVector> vectors = new ArrayList<SparseDoubleVector>();
for (double[] values : VALUES) vectors.add(new CompactSparseVector(values));
Matrix m = new ListMatrix<SparseDoubleVector>(vectors);
assertEquals(VALUES.length, m.rows());
assertEquals(VALUES[0].length, m.columns());
for (int r = 0; r < m.rows(); ++r)
for (int c = 0; c < m.columns(); ++c) assertEquals(VALUES[r][c], m.get(r, c), .0001);
m.set(0, 0, 0);
assertEquals(0, vectors.get(0).get(0), .0001);
for (int r = 0; r < m.rows(); ++r) assertEquals(vectors.get(r), m.getRowVector(r));
}
@Test
public void testMatrixTransformSize() {
int[][] testInput = {
{0, 0, 0, 0, 1, 1, 2, 4, 5, 0},
{0, 1, 1, 2, 0, 1, 5, 2, 8, 10},
{1, 5, 0, 0, 1, 0, 6, 3, 7, 9},
{0, 1, 0, 1, 0, 1, 2, 0, 3, 0},
{1, 5, 7, 0, 0, 1, 6, 10, 2, 45},
{1, 1, 1, 1, 1, 1, 1, 1, 1, 1}
};
double[][] testOutput = {
{
0.00000, 0.00000, 0.00000, 0.00000, 0.17028, 0.10217, 0.04644, 0.10217, 0.09824, 0.00000,
},
{
0.00000, 0.00810, 0.01171, 0.05268, 0.00000, 0.02107, 0.02395, 0.01054, 0.03242, 0.01621,
},
{
0.07438, 0.08582, 0.00000, 0.00000, 0.07438, 0.00000, 0.06086, 0.03347, 0.06008, 0.03090,
},
{
0.00000, 0.03929, 0.00000, 0.12771, 0.00000, 0.10217, 0.04644, 0.00000, 0.05894, 0.00000,
},
{
0.03512, 0.04052, 0.08195, 0.00000, 0.00000, 0.02107, 0.02873, 0.05268, 0.00810, 0.07294,
},
{
-0.03177, -0.00733, -0.01059, -0.02383, -0.03177, -0.01906, -0.00433, -0.00477, -0.00367,
-0.00147,
}
};
double error = .00001;
Matrix inputMatrix = new YaleSparseMatrix(6, 10);
for (int row = 0; row < 6; ++row)
for (int col = 0; col < 10; ++col) inputMatrix.set(row, col, testInput[row][col]);
Transform transform = new TfIdfTransform();
Matrix outputMatrix = transform.transform(inputMatrix);
for (int row = 0; row < 6; ++row) {
for (int col = 0; col < 10; ++col)
assertEquals(testOutput[row][col], outputMatrix.get(row, col), error);
}
}
