@Test
public void testBasics_1() {
// Simple domain mapping
Assert.assertArrayEquals(a(0, 1, 2, 3), Utils.mapping(a(0, 1, 2, 3)));
Assert.assertArrayEquals(a(0, 1, 2, -1, 3), Utils.mapping(a(0, 1, 2, 4)));
Assert.assertArrayEquals(a(0, -1, 1), Utils.mapping(a(-1, 1)));
Assert.assertArrayEquals(a(0, -1, 1, -1, 2), Utils.mapping(a(-1, 1, 3)));
}
@Test
public void testBasics_2() {
Assert.assertArrayEquals(
a(2, 30, 400, 5000), Utils.compose(Utils.mapping(a(0, 1, 2, 3)), a(2, 30, 400, 5000)));
Assert.assertArrayEquals(
a(2, 30, 400, -1, 5000), Utils.compose(Utils.mapping(a(0, 1, 2, 4)), a(2, 30, 400, 5000)));
Assert.assertArrayEquals(
a(2, -1, 30), Utils.compose(Utils.mapping(a(-1, 1)), a(2, 30, 400, 5000)));
Assert.assertArrayEquals(
a(2, -1, 30, -1, 400), Utils.compose(Utils.mapping(a(-1, 1, 3)), a(2, 30, 400, 5000)));
}
void testModelAdaptation(String train, String test, PrepData dprep, boolean exactAdaptation) {
DRFModel model = null;
Frame frTest = null;
Frame frTrain = null;
Key trainKey = Key.make("train.hex");
Key testKey = Key.make("test.hex");
Frame[] frAdapted = null;
try {
// Prepare a simple model
frTrain = parseFrame(trainKey, train);
model = runDRF(frTrain, dprep);
// Load test dataset - test data contains input columns matching train data,
// BUT each input requires adaptation. Moreover, test data contains additional columns
// containing correct value mapping.
frTest = parseFrame(testKey, test);
Assert.assertEquals(
"TEST CONF ERROR: The test dataset should contain 2*<number of input columns>+1!",
2 * (frTrain.numCols() - 1) + 1,
frTest.numCols());
// Adapt test dataset
frAdapted = model.adapt(frTest, exactAdaptation); // do/do not perform translation to enums
Assert.assertEquals("Adapt method should return two frames", 2, frAdapted.length);
Assert.assertEquals(
"Test expects that all columns in test dataset has to be adapted",
dprep.needAdaptation(frTrain),
frAdapted[1].numCols());
// Compare vectors
Frame adaptedFrame = frAdapted[0];
// System.err.println(frTest.toStringAll());
// System.err.println(adaptedFrame.toStringAll());
for (int av = 0; av < frTrain.numCols() - 1; av++) {
int ev = av + frTrain.numCols();
Vec actV = adaptedFrame.vecs()[av];
Vec expV = frTest.vecs()[ev];
Assert.assertEquals(
"Different number of rows in test vectors", expV.length(), actV.length());
for (long r = 0; r < expV.length(); r++) {
if (expV.isNA(r))
Assert.assertTrue(
"Badly adapted vector - expected NA! Col: " + av + ", row: " + r, actV.isNA(r));
else {
Assert.assertTrue(
"Badly adapted vector - expected value but get NA! Col: " + av + ", row: " + r,
!actV.isNA(r));
Assert.assertEquals(
"Badly adapted vector - wrong values! Col: " + av + ", row: " + r,
expV.at8(r),
actV.at8(r));
}
}
}
} finally {
// Test cleanup
if (model != null) UKV.remove(model._selfKey);
if (frTrain != null) frTrain.remove();
UKV.remove(trainKey);
if (frTest != null) frTest.remove();
UKV.remove(testKey);
// Remove adapted vectors which were saved into KV-store, rest of vectors are remove by
// frTest.remove()
if (frAdapted != null) frAdapted[1].remove();
}
}