use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class CreateData method saveCompoundMolecules.
@SuppressWarnings("null")
private void saveCompoundMolecules(MemoryPeakResults results) {
if (idToCompound == null) {
return;
}
final MemoryPeakResults[] set = new MemoryPeakResults[compoundNames.size()];
for (int i = 0; i < set.length; i++) {
set[i] = copyMemoryPeakResults("Compound " + (i + 1) + ", " + compoundNames.get(i));
}
final PeakResult[] peakResults = results.toArray();
// Sort using the ID
Arrays.sort(peakResults, new Comparator<PeakResult>() {
@Override
public int compare(PeakResult o1, PeakResult o2) {
return o1.getId() - o2.getId();
}
});
MemoryPeakResults currentResults = null;
final FrameCounter counter = new FrameCounter(-1);
for (final PeakResult p : peakResults) {
if (counter.advance(p.getId())) {
currentResults = set[idToCompound.get(p.getId())];
}
currentResults.add(p);
}
for (int i = 0; i < set.length; i++) {
set[i].end();
}
}
use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class Filter method filterSubset.
/**
* Filter the results.
*
* <p>Input PeakResults must be allocated a score for true positive, false positive, true negative
* and false negative (accessed via the object property get methods). The filter is run and
* results that pass accumulate scores for true positive and false positive, otherwise the scores
* are accumulated for true negative and false negative. The simplest scoring scheme is to mark
* valid results as tp=fn=1 and fp=tn=0 and invalid results the opposite.
*
* <p>The number of failures before each peak is stored in the origX property of the PeakResult.
*
* @param results the results
* @param score If not null will be populated with the fraction score [ tp, fp, tn, fn, p, n ]
* @return the filtered results
*/
public MemoryPeakResults filterSubset(MemoryPeakResults results, double[] score) {
final MemoryPeakResults newResults = new MemoryPeakResults();
final FrameCounter counter = new FrameCounter();
newResults.copySettings(results);
setup(results);
final double[] s = new double[4];
final Counter p = new Counter();
results.forEach((PeakResultProcedure) peak -> {
counter.advanceAndReset(peak.getFrame());
final boolean isPositive = accept(peak);
if (isPositive) {
peak.setOrigX(counter.getCount());
counter.reset();
newResults.add(peak);
} else {
counter.increment();
}
if (isPositive) {
p.increment();
s[TP] += peak.getTruePositiveScore();
s[FP] += peak.getFalsePositiveScore();
} else {
s[FN] += peak.getFalseNegativeScore();
s[TN] += peak.getTrueNegativeScore();
}
});
end();
if (score != null && score.length > 5) {
score[0] = s[TP];
score[1] = s[FP];
score[2] = s[TN];
score[3] = s[FN];
score[4] = p.getCount();
score[5] = (double) results.size() - p.getCount();
}
return newResults;
}
use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class Filter method filterSubset.
/**
* Filter the results.
*
* <p>Input PeakResults must be allocated a score for true positive, false positive, true negative
* and false negative (accessed via the object property get methods). The filter is run and
* results that pass accumulate scores for true positive and false positive, otherwise the scores
* are accumulated for true negative and false negative. The simplest scoring scheme is to mark
* valid results as tp=fn=1 and fp=tn=0 and invalid results the opposite.
*
* <p>The number of consecutive rejections are counted per frame. When the configured number of
* failures is reached all remaining results for the frame are rejected. This assumes the results
* are ordered by the frame.
*
* <p>The number of failures before each peak is stored in the origX property of the PeakResult.
*
* @param results the results
* @param failures the number of failures to allow per frame before all peaks are rejected
* @param score If not null will be populated with the fraction score [ tp, fp, tn, fn, p, n ]
* @return the filtered results
*/
public MemoryPeakResults filterSubset(MemoryPeakResults results, final int failures, double[] score) {
final MemoryPeakResults newResults = new MemoryPeakResults();
final FrameCounter counter = new FrameCounter();
newResults.copySettings(results);
setup(results);
final double[] s = new double[4];
results.forEach((PeakResultProcedure) peak -> {
counter.advanceAndReset(peak.getFrame());
final boolean isPositive;
if (counter.getCount() > failures) {
isPositive = false;
} else {
isPositive = accept(peak);
}
if (isPositive) {
peak.setOrigX(counter.getCount());
counter.reset();
newResults.add(peak);
} else {
counter.increment();
}
if (isPositive) {
s[TP] += peak.getTruePositiveScore();
s[FP] += peak.getFalsePositiveScore();
} else {
s[FN] += peak.getFalseNegativeScore();
s[TN] += peak.getTrueNegativeScore();
}
});
end();
if (score != null && score.length > 5) {
score[0] = s[TP];
score[1] = s[FP];
score[2] = s[TN];
score[3] = s[FN];
score[4] = newResults.size();
score[5] = (double) results.size() - newResults.size();
}
return newResults;
}
use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class Filter method fractionScore2.
/**
* Filter the results and return the performance score. Allows benchmarking the filter by marking
* the results as true or false.
*
* <p>Input PeakResults must be allocated a score for true positive, false positive, true negative
* and false negative (accessed via the object property get methods). The filter is run and
* results that pass accumulate scores for true positive and false positive, otherwise the scores
* are accumulated for true negative and false negative. The simplest scoring scheme is to mark
* valid results as tp=fn=1 and fp=tn=0 and invalid results the opposite.
*
* <p>The number of consecutive rejections are counted per frame. When the configured number of
* failures is reached all remaining results for the frame are rejected. This assumes the results
* are ordered by the frame.
*
* <p>Note that this method is to be used to score a set of results that may have been extracted
* from a larger set since the number of consecutive failures before each peak are expected to be
* stored in the origY property. Set this to zero and the results should be identical to
* {@link #fractionScore(List, int)}.
*
* @param resultsList a list of results to analyse
* @param failures the number of failures to allow per frame before all peaks are rejected
* @return the score
*/
public FractionClassificationResult fractionScore2(List<MemoryPeakResults> resultsList, final int failures) {
final double[] s = new double[4];
final Counter p = new Counter();
int negatives = 0;
for (final MemoryPeakResults peakResults : resultsList) {
setup(peakResults);
final FrameCounter counter = new FrameCounter();
peakResults.forEach((PeakResultProcedure) peak -> {
counter.advanceAndReset(peak.getFrame());
counter.increment(peak.getOrigY());
final boolean isPositive;
if (counter.getCount() > failures) {
isPositive = false;
} else {
isPositive = accept(peak);
}
if (isPositive) {
counter.reset();
} else {
counter.increment();
}
if (isPositive) {
p.increment();
s[TP] += peak.getTruePositiveScore();
s[FP] += peak.getFalsePositiveScore();
} else {
s[FN] += peak.getFalseNegativeScore();
s[TN] += peak.getTrueNegativeScore();
}
});
negatives += peakResults.size();
end();
}
negatives -= p.getCount();
return new FractionClassificationResult(s[TP], s[FP], s[TN], s[FN], p.getCount(), negatives);
}
use of uk.ac.sussex.gdsc.smlm.results.count.FrameCounter in project GDSC-SMLM by aherbert.
the class Filter method filterSubset2.
/**
* Filter the results.
*
* <p>Input PeakResults must be allocated a score for true positive, false positive, true negative
* and false negative (accessed via the object property get methods). The filter is run and
* results that pass accumulate scores for true positive and false positive, otherwise the scores
* are accumulated for true negative and false negative. The simplest scoring scheme is to mark
* valid results as tp=fn=1 and fp=tn=0 and invalid results the opposite.
*
* <p>The number of consecutive rejections are counted per frame. When the configured number of
* failures is reached all remaining results for the frame are rejected. This assumes the results
* are ordered by the frame.
*
* <p>Note that this method is to be used to score a set of results that may have been extracted
* from a larger set since the number of consecutive failures before each peak are expected to be
* stored in the origY property. Set this to zero and the results should be identical to
* {@link #filterSubset(MemoryPeakResults, int, double[])}.
*
* <p>The number of failures before each peak is stored in the origX property of the PeakResult.
*
* @param results the results
* @param failures the number of failures to allow per frame before all peaks are rejected
* @param score If not null will be populated with the fraction score [ tp, fp, tn, fn, p, n ]
* @return the filtered results
*/
public MemoryPeakResults filterSubset2(MemoryPeakResults results, final int failures, double[] score) {
final MemoryPeakResults newResults = new MemoryPeakResults();
final FrameCounter counter = new FrameCounter();
newResults.copySettings(results);
setup(results);
final double[] s = new double[4];
results.forEach((PeakResultProcedure) peak -> {
counter.advanceAndReset(peak.getFrame());
counter.increment(peak.getOrigY());
final boolean isPositive;
if (counter.getCount() > failures) {
isPositive = false;
} else {
isPositive = accept(peak);
}
if (isPositive) {
peak.setOrigX(counter.getCount());
counter.reset();
newResults.add(peak);
} else {
counter.increment();
}
if (isPositive) {
s[TP] += peak.getTruePositiveScore();
s[FP] += peak.getFalsePositiveScore();
} else {
s[FN] += peak.getFalseNegativeScore();
s[TN] += peak.getTrueNegativeScore();
}
});
end();
if (score != null && score.length > 5) {
score[0] = s[TP];
score[1] = s[FP];
score[2] = s[TN];
score[3] = s[FN];
score[4] = newResults.size();
score[5] = (double) results.size() - newResults.size();
}
return newResults;
}
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