public double likelihood() {
double c1 = 0.0;
double c3 = -1.0 / (double) Math.sqrt(2.0 * variance);
double sum = 0.0;
double cpart = -0.5 * Math.log(Math.sqrt(2.0 * Math.PI * variance));
for (int i = 0; i < data.size(); i++) {
for (int k = 0; k < channels.length; k++) {
c1 += cpart;
double pi = 0.0;
for (Integer t : transcripts.keySet()) {
if (transcripts.get(t).contains(i)) {
double gammai = gammas[t][k];
double dit = delta(i, t);
double pit = gammai * Math.exp(-lambda * dit);
pi += pit;
}
}
double zi = Math.log(pi);
double err = data.values(i)[channels[k]] - zi;
sum += (err * err);
}
}
return c1 + c3 * sum;
}
public double error() {
double sum = 0.0;
for (int i = 0; i < data.size(); i++) {
for (int k = 0; k < channels.length; k++) {
double pi = 0.0;
for (Integer t : transcripts.keySet()) {
if (transcripts.get(t).contains(i)) {
double gammai = gammas[t][k];
double dit = delta(i, t);
double pit = gammai * Math.exp(-lambda * dit);
pi += pit;
}
}
double zi = Math.log(pi);
double err = Math.abs(data.values(i)[channels[k]] - zi);
sum += err;
}
}
return sum;
}
public ClusterLikelihoods(
ClusterData d, Integer[] chs, int[] five, int[] three, double v, double l) {
data = d;
channels = chs.clone();
gammas = new double[five.length][channels.length];
for (int t = 0; t < gammas.length; t++) {
for (int i = 0; i < gammas[t].length; i++) {
gammas[t][i] = 1.0;
}
}
transcripts = new TreeMap<Integer, Set<Integer>>();
fiveprime = five;
threeprime = three;
if (fiveprime.length != threeprime.length) {
String msg = String.format("%d != %d", fiveprime.length, threeprime.length);
throw new IllegalArgumentException(msg);
}
variance = v;
lambda = l;
for (int t = 0; t < fiveprime.length; t++) {
transcripts.put(t, new TreeSet<Integer>());
}
for (int i = 0; i < data.size(); i++) {
int loc = data.location(i);
for (int t = 0; t < fiveprime.length; t++) {
if (fiveprime[t] <= loc && threeprime[t] >= loc) {
transcripts.get(t).add(i);
}
}
}
}