Examples with PeakResultPoint uk.ac.sussex.gdsc.smlm.results.PeakResultPoint used on opensource projects

Example 1 with PeakResultPoint

use of uk.ac.sussex.gdsc.smlm.results.PeakResultPoint in project GDSC-SMLM by aherbert.

the class ResultsMatchCalculator method savePairs.

private void savePairs(MemoryPeakResults results1, MemoryPeakResults results2, List<PointPair> allMatches) {
    if (!settings.savePairs) {
        return;
    }
    // Get the directory
    final String directory = ImageJUtils.getDirectory("Pairs_directory", settings.pairsDirectory);
    if (directory == null) {
        return;
    }
    settings.pairsDirectory = directory;
    final double[] distanceThresholds = getDistances(settings.distanceThreshold, settings.increments, settings.delta);
    // Create output files for each distance band
    final PeakResults[] output1 = new PeakResults[distanceThresholds.length];
    final PeakResults[] output2 = new PeakResults[distanceThresholds.length];
    double high = 0;
    for (int i = 0; i < distanceThresholds.length; i++) {
        final double low = high;
        high = distanceThresholds[i];
        output1[i] = createFilePeakResults(directory, 1, results1, low, high);
        output2[i] = createFilePeakResults(directory, 2, results2, low, high);
    }
    // Square the thresholds
    SimpleArrayUtils.apply(distanceThresholds, v -> v * v);
    final double[] pairDistances = getPairDistances(allMatches);
    int index = 0;
    for (final PointPair pair : allMatches) {
        final int insert = search(distanceThresholds, pairDistances[index++]);
        if (insert != -1) {
            final PeakResult r1 = ((PeakResultPoint) pair.getPoint1()).getPeakResult();
            final PeakResult r2 = ((PeakResultPoint) pair.getPoint2()).getPeakResult();
            output1[insert].add(r1);
            output2[insert].add(r2);
        }
    }
    for (int i = 0; i < output1.length; i++) {
        output1[i].end();
        output2[i].end();
    }
}

Example 2 with PeakResultPoint

use of uk.ac.sussex.gdsc.smlm.results.PeakResultPoint in project GDSC-SMLM by aherbert.

the class ResultsMatchCalculator method showResults.

@SuppressWarnings("null")
private void showResults(MemoryPeakResults results1, MemoryPeakResults results2, final List<PointPair> allMatches, int n1, int n2, final boolean doIdAnalysis1, final boolean doIdAnalysis2, TextWindow resultsWindow) {
    if (!settings.showTable) {
        return;
    }
    // Output the results
    Consumer<String> output;
    if (resultsWindow != null) {
        output = resultsWindow::append;
    } else {
        // Headless mode
        output = IJ::log;
        if (writeHeader.get()) {
            writeHeader.set(false);
            IJ.log(createResultsHeader(settings.idAnalysis));
        }
    }
    // We have the results for the largest distance.
    // Now reduce the distance threshold and recalculate the results
    final double[] distanceThresholds = getDistances(settings.distanceThreshold, settings.increments, settings.delta);
    final double[] pairDistances = getPairDistances(allMatches);
    // Re-use storage for the ID analysis
    TIntHashSet id1 = null;
    TIntHashSet id2 = null;
    TIntHashSet matchId1 = null;
    TIntHashSet matchId2 = null;
    final boolean doIdAnalysis = doIdAnalysis1 || doIdAnalysis2;
    if (doIdAnalysis) {
        if (doIdAnalysis1) {
            id1 = getIds(results1);
            matchId1 = new TIntHashSet(id1.size());
        }
        if (doIdAnalysis2) {
            id2 = getIds(results2);
            matchId2 = new TIntHashSet(id2.size());
        }
    }
    final StringBuilder sb = new StringBuilder();
    for (final double distanceThreshold : distanceThresholds) {
        double rms = 0;
        int tp2 = 0;
        final double d2 = distanceThreshold * distanceThreshold;
        for (final double d : pairDistances) {
            if (d <= d2) {
                rms += d;
                tp2++;
            }
        }
        // All non-true positives must be added to the false totals.
        final int fp2 = n2 - tp2;
        final int fn2 = n1 - tp2;
        // RMSD to be the root mean square deviation in a single dimension so divide by 2.
        // (This assumes 2D Euclidean distances.)
        final MatchResult result = new MatchResult(tp2, fp2, fn2, Math.sqrt(MathUtils.div0(rms / 2, tp2)));
        MatchResult idResult1 = null;
        MatchResult idResult2 = null;
        if (doIdAnalysis) {
            if (doIdAnalysis1) {
                matchId1.clear();
            }
            if (doIdAnalysis2) {
                matchId2.clear();
            }
            int index = 0;
            for (final PointPair pair : allMatches) {
                if (pairDistances[index++] <= d2) {
                    if (doIdAnalysis1) {
                        matchId1.add(((PeakResultPoint) pair.getPoint1()).getPeakResult().getId());
                    }
                    if (doIdAnalysis2) {
                        matchId2.add(((PeakResultPoint) pair.getPoint2()).getPeakResult().getId());
                    }
                }
            }
            // => Only the recall will be valid: tp / (tp + fn)
            if (doIdAnalysis1) {
                idResult1 = new MatchResult(matchId1.size(), 0, id1.size() - matchId1.size(), 0);
            }
            if (doIdAnalysis2) {
                idResult2 = new MatchResult(matchId2.size(), 0, id2.size() - matchId2.size(), 0);
            }
        }
        addResult(sb, settings.inputOption1, settings.inputOption2, distanceThreshold, result, idResult1, idResult2);
        output.accept(sb.toString());
    }
}

Example 3 with PeakResultPoint

use of uk.ac.sussex.gdsc.smlm.results.PeakResultPoint in project GDSC-SMLM by aherbert.

the class ClassificationMatchCalculator method getTimepoints.

/**
 * Merge the time points from each map into a single sorted list of unique time points.
 *
 * @param actualCoordinates the actual coordinates
 * @param predictedCoordinates the predicted coordinates
 * @return a list of time points
 */
private static int[] getTimepoints(TIntObjectHashMap<List<PeakResultPoint>> actualCoordinates, TIntObjectHashMap<List<PeakResultPoint>> predictedCoordinates) {
    // Do inline to avoid materialising the keys arrays
    final TIntHashSet hashset = new TIntHashSet(Math.max(actualCoordinates.size(), predictedCoordinates.size()));
    final TIntProcedure p = value -> {
        hashset.add(value);
        return true;
    };
    actualCoordinates.forEachKey(p);
    predictedCoordinates.forEachKey(p);
    final int[] set = hashset.toArray();
    Arrays.sort(set);
    return set;
}

Example 4 with PeakResultPoint

use of uk.ac.sussex.gdsc.smlm.results.PeakResultPoint in project GDSC-SMLM by aherbert.

the class ClassificationMatchCalculator method getCoordinates.

/**
 * Build a map between the peak id (time point) and a list of coordinates that pass the filter.
 *
 * @param results the results
 * @param test the test
 * @return the coordinates
 */
public static TIntObjectHashMap<List<PeakResultPoint>> getCoordinates(MemoryPeakResults results, Predicate<PeakResult> test) {
    final TIntObjectHashMap<List<PeakResultPoint>> coords = new TIntObjectHashMap<>();
    if (results.size() > 0) {
        // Do not use HashMap directly to build the coords object since there
        // will be many calls to getEntry(). Instead sort the results and use
        // a new list for each time point
        results.sort();
        // Create list
        final LocalList<PeakResultPoint> tmpCoords = new LocalList<>();
        // Add the results for each frame
        final FrameCounter counter = results.newFrameCounter();
        results.forEach(DistanceUnit.PIXEL, (XyzrResultProcedure) (x, y, z, r) -> {
            if (counter.advance(r.getFrame()) && !tmpCoords.isEmpty()) {
                coords.put(counter.previousFrame(), tmpCoords.copy());
                tmpCoords.clear();
            }
            if (test.test(r)) {
                tmpCoords.add(new PeakResultPoint(r.getFrame(), x, y, z, r));
            }
        });
        if (!tmpCoords.isEmpty()) {
            coords.put(counter.currentFrame(), tmpCoords.copy());
        }
    }
    return coords;
}

Example 5 with PeakResultPoint

use of uk.ac.sussex.gdsc.smlm.results.PeakResultPoint in project GDSC-SMLM by aherbert.

the class ResultsMatchCalculator method runCompareCoordinates.

@SuppressWarnings("null")
private void runCompareCoordinates(MemoryPeakResults results1, MemoryPeakResults results2) {
    final boolean requirePairs = settings.showPairs || settings.isSaveClassifications();
    final boolean saveMatched = settings.isSaveMatched();
    final boolean saveUnmatched = settings.isSaveUnmatched();
    final TextFilePeakResults fileResults = createFilePeakResults(results2);
    final List<PointPair> allMatches = new LinkedList<>();
    final List<PointPair> pairs = (requirePairs) ? new LinkedList<>() : null;
    final double maxDistance = settings.distanceThreshold + settings.increments * settings.delta;
    // Divide the results into time points
    final TIntObjectHashMap<List<Coordinate>> actualCoordinates = getCoordinates(results1, settings.coordinateMethod1);
    final TIntObjectHashMap<List<Coordinate>> predictedCoordinates = getCoordinates(results2, settings.coordinateMethod2);
    int n1 = 0;
    int n2 = 0;
    // Process each time point
    for (final int t : getTimepoints(actualCoordinates, predictedCoordinates)) {
        final Coordinate[] actual = getCoordinates(actualCoordinates, t);
        final Coordinate[] predicted = getCoordinates(predictedCoordinates, t);
        final List<Coordinate> tp = null;
        List<Coordinate> fp = null;
        List<Coordinate> fn = null;
        final List<PointPair> matches = new LinkedList<>();
        if (requirePairs) {
            fp = new LinkedList<>();
            fn = new LinkedList<>();
        }
        MatchCalculator.analyseResults2D(actual, predicted, maxDistance, tp, fp, fn, matches);
        // Aggregate
        n1 += actual.length;
        n2 += predicted.length;
        allMatches.addAll(matches);
        if (settings.showPairs) {
            pairs.addAll(matches);
            for (final Coordinate c : fn) {
                pairs.add(new PointPair(c, null));
            }
            for (final Coordinate c : fp) {
                pairs.add(new PointPair(null, c));
            }
        }
        if (fileResults != null) {
            // Matches are marked in the original value with 1 for true, 0 for false
            if (saveMatched) {
                for (final PointPair pair : matches) {
                    PeakResult result = ((PeakResultPoint) pair.getPoint2()).getPeakResult();
                    result = result.copy();
                    result.setOrigValue(1);
                    fileResults.add(result);
                }
            }
            if (saveUnmatched) {
                for (final Coordinate c : fp) {
                    PeakResult result = ((PeakResultPoint) c).getPeakResult();
                    result = result.copy();
                    result.setOrigValue(0);
                    fileResults.add(result);
                }
            }
        }
    }
    if (fileResults != null) {
        fileResults.end();
    }
    final boolean doIdAnalysis1 = settings.idAnalysis && haveIds(results1);
    final boolean doIdAnalysis2 = settings.idAnalysis && haveIds(results2);
    // Create output.
    // This supports headless mode with just the results table
    // or graphical mode with a results table and pairs window.
    final boolean headless = java.awt.GraphicsEnvironment.isHeadless();
    TextWindow resultsWindow = null;
    if (!headless) {
        resultsWindow = (settings.showTable) ? createResultsWindow(doIdAnalysis1 || doIdAnalysis2) : null;
        showPairs(results1, pairs, resultsWindow);
    }
    showResults(results1, results2, allMatches, n1, n2, doIdAnalysis1, doIdAnalysis2, resultsWindow);
    savePairs(results1, results2, allMatches);
}