Examples with DirectFilter gdsc.smlm.results.filter.DirectFilter used on opensource projects

Example 16 with DirectFilter

use of gdsc.smlm.results.filter.DirectFilter in project GDSC-SMLM by aherbert.

the class BenchmarkFilterAnalysis method findOptimum.

public SearchResult<FilterScore> findOptimum(double[][] points) {
    ga_iteration++;
    SimpleFilterScore max = es_optimum;
    final FilterScoreResult[] scoreResults = scoreFilters(setStrength(new FilterSet(searchSpaceToFilters(points))), false);
    if (scoreResults == null)
        return null;
    for (int index = 0; index < scoreResults.length; index++) {
        final FilterScoreResult scoreResult = scoreResults[index];
        final SimpleFilterScore result = new SimpleFilterScore(scoreResult, true, scoreResult.criteria >= minCriteria);
        if (result.compareTo(max) < 0) {
            max = result;
        }
    }
    es_optimum = max;
    // Add the best filter to the table
    // This filter may not have been part of the scored subset so use the entire results set for reporting
    DirectFilter filter = max.r.filter;
    FractionClassificationResult r = scoreFilter(filter, minimalFilter, ga_resultsList, coordinateStore);
    final StringBuilder text = createResult(filter, r);
    add(text, ga_iteration);
    gaWindow.append(text.toString());
    return new SearchResult<FilterScore>(filter.getParameters(), max);
}

Example 17 with DirectFilter

use of gdsc.smlm.results.filter.DirectFilter in project GDSC-SMLM by aherbert.

the class BenchmarkFilterAnalysis method reportResults.

private ComplexFilterScore reportResults(boolean newResults, List<ComplexFilterScore> filters) {
    if (filters.isEmpty()) {
        IJ.log("Warning: No filters pass the criteria");
        return null;
    }
    getCoordinateStore();
    Collections.sort(filters);
    FractionClassificationResult topFilterClassificationResult = null;
    ArrayList<FractionalAssignment[]> topFilterResults = null;
    String topFilterSummary = null;
    if (showSummaryTable || saveTemplate) {
        createSummaryWindow();
        int n = 0;
        final double range = (summaryDepth / simulationParameters.a) * 0.5;
        int np = 0;
        for (double depth : depthStats) {
            if (Math.abs(depth) < range)
                np++;
        }
        for (ComplexFilterScore fs : filters) {
            final ArrayList<FractionalAssignment[]> list = new ArrayList<FractionalAssignment[]>(resultsList.length);
            final FractionClassificationResult r = scoreFilter(fs.getFilter(), minimalFilter, resultsList, list, coordinateStore);
            final StringBuilder sb = createResult(fs.getFilter(), r);
            if (topFilterResults == null) {
                topFilterResults = list;
                topFilterClassificationResult = r;
            }
            // Show the recall at the specified depth. Sum the distance and signal factor of all scored spots.
            int scored = 0;
            double tp = 0, d = 0, sf = 0, rmsd = 0;
            SimpleRegression regression = new SimpleRegression(false);
            for (FractionalAssignment[] assignments : list) {
                if (assignments == null)
                    continue;
                for (int i = 0; i < assignments.length; i++) {
                    final CustomFractionalAssignment c = (CustomFractionalAssignment) assignments[i];
                    if (Math.abs(c.peak.error) <= range)
                        tp += c.getScore();
                    d += c.d;
                    sf += c.getSignalFactor();
                    rmsd += c.d * c.d;
                    regression.addData(c.peakResult.getSignal(), c.peak.getSignal());
                }
                scored += assignments.length;
            }
            final double slope = regression.getSlope();
            sb.append('\t');
            sb.append(Utils.rounded((double) tp / np)).append('\t');
            sb.append(Utils.rounded(d / scored)).append('\t');
            sb.append(Utils.rounded(sf / scored)).append('\t');
            sb.append(Utils.rounded(Math.sqrt(rmsd / scored))).append('\t');
            sb.append(Utils.rounded(slope)).append('\t');
            if (fs.atLimit() != null)
                sb.append(fs.atLimit());
            String text = sb.toString();
            if (topFilterSummary == null) {
                topFilterSummary = text;
                if (!showSummaryTable)
                    break;
            }
            if (fs.time != 0) {
                sb.append('\t');
                sb.append(fs.algorithm);
                sb.append('\t');
                sb.append(org.apache.commons.lang3.time.DurationFormatUtils.formatDurationHMS(fs.time));
            } else
                sb.append("\t\t");
            if (fs.paramTime != 0) {
                sb.append('\t');
                sb.append(fs.getParamAlgorithm());
                sb.append('\t');
                sb.append(org.apache.commons.lang3.time.DurationFormatUtils.formatDurationHMS(fs.paramTime));
            } else
                sb.append("\t\t");
            text = sb.toString();
            if (isHeadless)
                IJ.log(text);
            else
                summaryWindow.append(text);
            n++;
            if (summaryTopN > 0 && n >= summaryTopN)
                break;
        }
        // Add a spacer to the summary table if we have multiple results
        if (n > 1 && showSummaryTable) {
            if (isHeadless)
                IJ.log("");
            else
                summaryWindow.append("");
        }
    }
    DirectFilter bestFilter = filters.get(0).getFilter();
    if (saveBestFilter)
        saveFilter(bestFilter);
    if (topFilterClassificationResult == null) {
        topFilterResults = new ArrayList<FractionalAssignment[]>(resultsList.length);
        topFilterClassificationResult = scoreFilter(bestFilter, minimalFilter, resultsList, topFilterResults, coordinateStore);
    }
    if (newResults || scores.isEmpty()) {
        scores.add(new FilterResult(failCount, residualsThreshold, duplicateDistance, filters.get(0)));
    }
    if (saveTemplate)
        saveTemplate(topFilterSummary);
    showPlots();
    calculateSensitivity();
    topFilterResults = depthAnalysis(topFilterResults, bestFilter);
    topFilterResults = scoreAnalysis(topFilterResults, bestFilter);
    componentAnalysis(topFilterClassificationResult, filters.get(0));
    PreprocessedPeakResult[] filterResults = null;
    if (isShowOverlay())
        filterResults = showOverlay(topFilterResults, bestFilter);
    saveResults(filterResults, bestFilter);
    wo.tile();
    return filters.get(0);
}