public String toCSV() {
if (dataset == null) {
return "";
}
String out =
"Experiment name: "
+ this.context.getExpContext().getExperimentName()
+ "\nRaw data dir: "
+ this.context.getExpContext().getRawDir()
+ "\n"
+ region
+ "\n";
int nr = dataset.getSeriesCount();
for (int s = 0; s < nr; s++) {
out += dataset.getSeriesKey(s);
if (s + 1 < nr) {
out += ", ";
} else {
out += "\n";
}
}
if (nr > 0) {
for (int f = 0; f < dataset.getItemCount(0); f++) {
double x = dataset.getXValue(0, f);
out += x + ",";
for (int s = 0; s < nr; s++) {
if (s < dataset.getSeriesCount() && f < dataset.getItemCount(s)) {
out += dataset.getY(s, f);
if (s + 1 < nr) {
out += ", ";
} else {
out += "\n";
}
} else out += "\n";
}
}
}
return out;
}
// See McClelland 1991 for details.
// given two phonemes and some parameters, returns which of the two phonemes is most active
// according to the rule.
// result is of the form: model_input phon1 win/lose phon2 win/lose
// winner=1, loser=0.
public String runningAverageMetricReport(
String phon1, String phon2, String input, double lambda, double init, String[] labels) {
int p1_idx = -1, p2_idx = -1;
for (int i = 0; i < labels.length; i++) {
if (labels[i].equals(phon1)) p1_idx = i;
if (labels[i].equals(phon2)) p2_idx = i;
}
// case: one or both of the phonemes was not found in the array of labels.
if (p1_idx == -1 || p2_idx == -1) return "";
double p1_val = init, p2_val = init;
int length = Math.min(data.getItemCount(p1_idx), data.getItemCount(p2_idx));
for (int i = 0; i < length; i++) {
p1_val = (lambda * data.getY(p1_idx, i).doubleValue()) + ((1 - lambda) * p1_val);
p2_val = (lambda * data.getY(p2_idx, i).doubleValue()) + ((1 - lambda) * p2_val);
}
String result = input + "\t";
result += phon1 + "\t";
if (p1_val > p2_val) result += "1\t";
else result += "0\t";
result += phon2 + "\t";
if (p2_val > p1_val) result += "1\t";
else result += "0\t";
return result;
}