@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 testEmptyFeatureVector() {
Config config = ConfigFactory.parseString(makeConfig());
Transform transform = TransformFactory.createTransform(config, "test_cut");
FeatureVector featureVector = new FeatureVector();
transform.doTransform(featureVector);
assertTrue(featureVector.getStringFeatures() == null);
}
@Test
public void testTransformLowerBoundOnly() {
Config config = ConfigFactory.parseString(makeConfigWithLowerBoundOnly());
Transform transform = TransformFactory.createTransform(config, "test_cut");
FeatureVector featureVector = TransformTestingHelper.makeFeatureVector();
transform.doTransform(featureVector);
Map<String, Set<String>> stringFeatures = featureVector.getStringFeatures();
assertTrue(stringFeatures.size() == 1);
Map<String, Double> feat1 = featureVector.getFloatFeatures().get("loc");
assertEquals(2, feat1.size());
assertEquals(37.7, feat1.get("lat"), 0.1);
assertEquals(40.0, feat1.get("long"), 0.1);
assertNull(feat1.get("z"));
}
@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);
}
}
@Test
public void testTransformWithNewOutput() {
Config config = ConfigFactory.parseString(makeConfigWithOutput());
Transform transform = TransformFactory.createTransform(config, "test_cut");
FeatureVector featureVector = TransformTestingHelper.makeFeatureVector();
transform.doTransform(featureVector);
Map<String, Set<String>> stringFeatures = featureVector.getStringFeatures();
assertTrue(stringFeatures.size() == 1);
// original feature should not change
Map<String, Double> feat1 = featureVector.getFloatFeatures().get("loc");
assertEquals(3, feat1.size());
assertEquals(37.7, feat1.get("lat"), 0.1);
assertEquals(40.0, feat1.get("long"), 0.1);
assertEquals(-20, feat1.get("z"), 0.1);
// capped features are in a new feature family
assertTrue(featureVector.getFloatFeatures().containsKey("new_output"));
Map<String, Double> feat2 = featureVector.getFloatFeatures().get("new_output");
assertEquals(1, feat2.size());
assertEquals(37.7, feat2.get("lat"), 0.1);
assertNull(feat2.get("long"));
assertNull(feat2.get("z"));
}
