public void applyUncalled() {
Progress progress = new Progress(uncalled.size(), 50);
while (!uncalled.isEmpty()) {
List<FunType> uncalledDup = new ArrayList<>(uncalled);
for (FunType cl : uncalledDup) {
progress.tick();
Call.apply(cl, null, null, null, null, null, null);
}
}
}
private Map<String, Double> getExpressionPvals(
Set<String> targets, boolean[] set1, boolean[] set2) {
Map<String, Double> map = new HashMap<String, Double>();
Histogram2D h = new Histogram2D(0.2);
System.out.println("targets = " + targets.size());
Progress prg = new Progress(targets.size());
for (String sym : targets) {
prg.tick();
if (expMan.getNonZeroRatio(sym) == 0) continue;
double pval = calcDiffPval(sym, set1, set2, true);
if (Double.isNaN(pval)) continue;
if (pval == 0) pval = 1E-11;
double pPerm = calcDiffPval(sym, set1, set2, false);
if (pPerm == 0) pPerm = 1E-5;
h.count(-Math.log(pval), -Math.log(pPerm));
// pval = 0 is not real and it is not compatible with fisher's combined probability.
// below is a better approximation.
// if (pval == 0)
// {
// pval = 1E-11;
// }
map.put(sym, pval);
}
Histogram2DPlot p = new Histogram2DPlot(h);
p.setLines(Arrays.asList(new double[] {1, 0}));
p.setVisible(true);
return map;
}
@Nullable
private Type parseAndResolve(String file) {
try {
Node ast = getAstForFile(file);
if (ast == null) {
failedToParse.add(file);
return null;
} else {
Type type = Node.transformExpr(ast, globaltable);
if (!loadedFiles.contains(file)) {
loadedFiles.add(file);
loadingProgress.tick();
}
return type;
}
} catch (OutOfMemoryError e) {
if (astCache != null) {
astCache.clear();
}
System.gc();
return null;
}
}
