/** Test a column matrix. */
@Test
public void testSmallDeviations() {
System.out.println("testSmallDeviations");
// run nearest point test by making small deviations (del) to lattice points.
int iters = 10;
Random r = new Random();
double del = 0.0001;
for (int t = 0; t < iters; t++) {
int n = r.nextInt(10) + 5;
LatticeAndNearestPointAlgorithm lattice = new AnstarSorted(n - 1);
Matrix G = lattice.getGeneratorMatrix();
Babai babai = new Babai();
babai.setLattice(lattice);
// System.out.println("G is " + G.getRowDimension() + " by " + G.getColumnDimension());
double[] x = new double[G.getRowDimension()];
double[] xdel = new double[G.getRowDimension()];
double[] u = VectorFunctions.randomIntegerVector(n, 1000);
// System.out.println("u is length " + u.length + ", x is length" + x.length);
VectorFunctions.matrixMultVector(G, u, x);
for (int i = 0; i < x.length; i++) {
xdel[i] = x[i] + r.nextGaussian() * del;
}
babai.nearestPoint(xdel);
double dist = VectorFunctions.distance_between(babai.getLatticePoint(), x);
System.out.println(dist);
assertEquals(true, dist < 0.00001);
}
}
/** Test a column matrix. */
@Test
public void testBeatsOrEqualsBabai() {
System.out.println("testBeatsOrEqualsBabai");
// run nearest point test by making small deviations (del) to lattice points.
int iters = 100;
Random r = new Random();
double del = 1000.0;
for (int t = 0; t < iters; t++) {
int n = r.nextInt(100) + 5;
Lattice lattice = new GeneralLattice(Matrix.random(n, n));
Matrix G = lattice.getGeneratorMatrix();
Mbest instance = new Mbest(lattice, n);
Babai babai = new Babai(lattice);
// System.out.println("G is " + G.getRowDimension() + " by " + G.getColumnDimension());
double[] x = new double[G.getRowDimension()];
double[] xdel = new double[G.getRowDimension()];
double[] u = new double[n];
for (int i = 0; i < n; i++) {
u[i] = r.nextDouble();
}
VectorFunctions.matrixMultVector(G, u, xdel);
instance.nearestPoint(xdel);
babai.nearestPoint(xdel);
double instdist = VectorFunctions.distance_between2(instance.getLatticePoint(), xdel);
double babaidist = VectorFunctions.distance_between2(babai.getLatticePoint(), xdel);
System.out.println(babaidist + ", " + instdist);
// System.out.println(VectorFunctions.print(babai.getIndex()));
assertTrue(instdist <= babaidist);
}
}
@Test
public void testDisambiguate() {
System.out.println("testDisambiguate");
double[] p1 = {1.3, -2.1};
int m = p1.length - 1;
AmbiguityRemover instance = new AmbiguityRemover(m);
p1 = instance.disambiguate(p1);
double[] y1 = {0.3, -0.1};
assertTrue(VectorFunctions.distance_between2(p1, y1) < 0.000001);
double[] p2 = {1.3, -2.1, 2.6};
m = p2.length - 1;
instance = new AmbiguityRemover(m);
p2 = instance.disambiguate(p2);
double[] y2 = {0.3, 0.4, 0.1};
assertTrue(VectorFunctions.distance_between2(p2, y2) < 0.000001);
}
@Override
public final double[] closestPoint(double[] y) {
if (n != y.length - 1) throw new RuntimeException("y is the wrong length");
Anstar.project(y, y);
VectorFunctions.round(y, u);
double m = VectorFunctions.sum(u);
for (int i = 0; i < n + 1; i++) {
z[i].value = Math.signum(m) * (y[i] - u[i]);
z[i].index = i;
}
Arrays.sort(z);
for (int i = 0; i < Math.abs(m); i++) u[z[i].index] -= Math.signum(m);
return u;
}
/** Test of FloydRivestSelect method, of class FastSelection. */
@Test
public void FloydRivestSelect() {
System.out.println("FloydRivestSelect");
int iters = 100;
Random r = new Random();
for (int j = 1; j < iters; j++) {
double[] A = VectorFunctions.randomGaussian(iters * 10);
int L = 0;
int R = A.length - 1;
int K = r.nextInt(A.length);
double result = FastSelection.FloydRivestSelect(L, R, K, A);
// assertEquals(expResult, result);
for (int i = 0; i < K; i++) {
assertTrue(A[i] <= A[K]);
}
for (int i = K + 1; i < A.length; i++) {
assertTrue(A[i] >= A[K]);
}
}
for (int j = 1; j < iters; j++) {
double[] A = VectorFunctions.randomGaussian(iters * 10);
Double[] Ac = new Double[A.length];
for (int i = 0; i < A.length; i++) Ac[i] = new Double(A[i]);
int L = 0;
int R = A.length - 1;
int K = r.nextInt(A.length);
FastSelection.FloydRivestSelect(L, R, K, Ac);
// assertEquals(expResult, result);
for (int i = 0; i < K; i++) {
assertTrue(Ac[i].compareTo(Ac[K]) <= 0);
}
for (int i = K + 1; i < A.length; i++) {
assertTrue(Ac[i].compareTo(Ac[K]) >= 0);
}
}
}
/** Test of setSize method, of class AmbiguityRemover. */
@Test
public void testNextColumn() {
System.out.println("testNextColumn");
double[] c = VectorFunctions.eVector(0, 1);
// System.out.println("c = " + VectorFunctions.print(c));
c = AmbiguityRemover.getNextColumn(c);
// System.out.println("c = " + VectorFunctions.print(c));
double[] y1 = {0, 1};
assertTrue(VectorFunctions.distance_between2(c, y1) < 0.000001);
c = AmbiguityRemover.getNextColumn(c);
// System.out.println("c = " + VectorFunctions.print(c));
double[] y2 = {0, 1.0 / 2.0, 1.0 / 2.0};
assertTrue(VectorFunctions.distance_between2(c, y2) < 0.000001);
c = AmbiguityRemover.getNextColumn(c);
// System.out.println("c = " + VectorFunctions.print(c));
double[] y3 = {0, 1.0 / 3.0, 1.0 / 2.0, 1.0 / 6};
assertTrue(VectorFunctions.distance_between2(c, y3) < 0.000001);
}
public double getCRB() {
double p = h / var;
AllPAMSymbolGenerator gen = new AllPAMSymbolGenerator();
double bestcrb = Double.NEGATIVE_INFINITY;
double[] d = new double[T];
for (int i = 0; i < Math.pow(M, T); i++) {
double[] nextsym = gen.getNext();
// System.out.println(nextsym.length);
for (int j = 0; j < T; j++) {
d[j] = x[j] - nextsym[j];
}
double magd2 = VectorFunctions.sum2(d);
if (magd2 > 0.5) {
double std = VectorFunctions.dot(x, d);
double crb = var / (magx2 - p * std * std / Math.expm1(p * magd2));
if (crb > bestcrb) bestcrb = crb;
}
}
return bestcrb;
}
/** Babai's algorithm should work perfectly for Zn. This tests that it does. */
@Test
public void returnsCorrectForZn() {
System.out.println("returnsCorrectForZn");
double[] y = {1.1, 2.2, 3.9, -4.1, -100.49};
Babai babai = new Babai();
// construc the integer lattice
Zn lattice = new Zn(y.length);
babai.setLattice(lattice);
lattice.nearestPoint(y);
double[] xtrue = lattice.getLatticePoint();
double[] utrue = lattice.getIndex();
babai.nearestPoint(y);
double[] xtest = babai.getLatticePoint();
double[] utest = babai.getIndex();
System.out.println(VectorFunctions.print(xtrue));
System.out.println(VectorFunctions.print(xtest));
assertTrue(VectorFunctions.distance_between(utest, utrue) < 0.00001);
assertTrue(VectorFunctions.distance_between(xtest, xtrue) < 0.00001);
assertTrue(VectorFunctions.distance_between(utest, xtrue) < 0.00001);
assertTrue(VectorFunctions.distance_between(xtest, utrue) < 0.00001);
}
@Before
public void setUp() {
int length = 1500;
double[] A = VectorFunctions.randomGaussian(length);
Vector<Double> Ac = new Vector<Double>();
for (int i = 0; i < A.length; i++) Ac.add(A[i]);
Random r = new Random();
k = r.nextInt(A.length);
elem = (Double) instance.select(k, Ac);
System.out.println("k = " + k + ", elem = " + elem);
}
/** Test of generateReceivedSignal method, of class simulator.qam.FadingNoisyQAM. */
public void testGenerateReceivedSignal() {
System.out.println("generateReceivedSignal");
FadingNoisyQAM instance = new FadingNoisyQAM();
double[] xr = {1.0, 2.0, -2.0};
double[] xi = {1.0, -3.0, 1.0};
instance.setChannel(-0.4326, -1.6656);
RealRandomVariable noise = new pubsim.distributions.UniformNoise(0.0, 0.0);
instance.setNoiseGenerator(noise);
instance.setTransmittedSignal(xr, xi);
double[] expr = {1.2330, -5.8620, 2.5308};
double[] expi = {-2.0982, -2.0334, 2.8986};
instance.generateReceivedSignal();
System.out.println(VectorFunctions.print(instance.getInphase()));
System.out.println(VectorFunctions.print(instance.getQuadrature()));
assertEquals(true, VectorFunctions.distance_between(expr, instance.getInphase()) < 0.00001);
assertEquals(true, VectorFunctions.distance_between(expi, instance.getQuadrature()) < 0.00001);
}
