Examples with DataException uk.ac.sussex.gdsc.core.data.DataException used on opensource projects

Example 6 with DataException

use of uk.ac.sussex.gdsc.core.data.DataException in project GDSC-SMLM by aherbert.

the class TranslateResults method run.

@Override
public void run(String arg) {
    SmlmUsageTracker.recordPlugin(this.getClass(), arg);
    if (MemoryPeakResults.isMemoryEmpty()) {
        IJ.error(TITLE, "There are no fitting results in memory");
        return;
    }
    final TranslateResultsSettings.Builder settings = SettingsManager.readTranslateResultsSettings(0).toBuilder();
    // Show a dialog allowing the results set to be filtered
    final ExtendedGenericDialog gd = new ExtendedGenericDialog(TITLE);
    gd.addMessage("Select a dataset to translate");
    ResultsManager.addInput(gd, settings.getInputOption(), InputSource.MEMORY);
    gd.addNumericField("x", settings.getDx(), 3);
    gd.addNumericField("y", settings.getDy(), 3);
    gd.addNumericField("z", settings.getDz(), 3);
    gd.addChoice("Distance_unit", SettingsManager.getDistanceUnitNames(), settings.getDistanceUnitValue());
    gd.addHelp(HelpUrls.getUrl("translate-results"));
    gd.showDialog();
    if (gd.wasCanceled()) {
        return;
    }
    settings.setInputOption(ResultsManager.getInputSource(gd));
    settings.setDx(gd.getNextNumber());
    settings.setDy(gd.getNextNumber());
    settings.setDz(gd.getNextNumber());
    settings.setDistanceUnitValue(gd.getNextChoiceIndex());
    SettingsManager.writeSettings(settings);
    final MemoryPeakResults results = ResultsManager.loadInputResults(settings.getInputOption(), false, null, null);
    if (MemoryPeakResults.isEmpty(results)) {
        IJ.error(TITLE, "No results could be loaded");
        return;
    }
    TypeConverter<DistanceUnit> converter;
    try {
        converter = results.getDistanceConverter(settings.getDistanceUnit());
    } catch (final DataException ex) {
        IJ.error(TITLE, "Unit conversion error: " + ex.getMessage());
        return;
    }
    final float x = (float) converter.convertBack(settings.getDx());
    final float y = (float) converter.convertBack(settings.getDy());
    final float z = (float) converter.convertBack(settings.getDz());
    // Reset the 2D bounds
    if (x != 0 || y != 0) {
        results.setBounds(null);
    }
    results.forEach((PeakResultProcedure) peakResult -> {
        final float[] params = peakResult.getParameters();
        params[PeakResult.X] += x;
        params[PeakResult.Y] += y;
        params[PeakResult.Z] += z;
    });
}

Example 7 with DataException

use of uk.ac.sussex.gdsc.core.data.DataException in project GDSC-SMLM by aherbert.

the class TrackPopulationAnalysis method getTracks.

/**
 * Gets the tracks. Each track has contiguous frames and the length is enough to fit
 * {@code minTrackLength} overlapping windows of the specified size:
 *
 * <pre>
 * length >= window + minTrackLength - 1
 * </pre>
 *
 * @param combinedResults the combined results
 * @param window the window size
 * @param minTrackLength the minimum track length (assumed to be {@code >= 1})
 * @return the tracks
 */
private static List<Trace> getTracks(List<MemoryPeakResults> combinedResults, int window, int minTrackLength) {
    final LocalList<Trace> tracks = new LocalList<>();
    final Statistics stats = new Statistics();
    final int minSize = window + Math.max(minTrackLength, 1) - 1;
    combinedResults.forEach(results -> {
        final int start = tracks.size();
        // Sort by id then frame
        results = results.copy();
        results.sort(IdFramePeakResultComparator.INSTANCE);
        final int size = results.size();
        // Skip IDs not associated with clustering
        int index = 0;
        while (index < size && results.get(index).getId() < 1) {
            index++;
        }
        // Initialise current id and frame
        int id = results.get(index).getId() - 1;
        int frame = results.get(index).getFrame();
        Trace track = new Trace();
        for (; index < size; index++) {
            final PeakResult result = results.get(index);
            // Same ID and contiguous frames
            if (result.getId() != id || result.getFrame() != frame + 1) {
                addTrack(minSize, tracks, track);
                track = new Trace();
            }
            id = result.getId();
            frame = result.getFrame();
            track.add(result);
        }
        addTrack(minSize, tracks, track);
        stats.reset();
        for (int i = start; i < tracks.size(); i++) {
            stats.add(tracks.unsafeGet(i).size());
        }
        final StringBuilder sb = new StringBuilder(256);
        TextUtils.formatTo(sb, "%s tracks=%d, length=%s +/- %s", results.getName(), stats.getN(), MathUtils.rounded(stats.getMean(), 3), MathUtils.rounded(stats.getStandardDeviation(), 3));
        // Limit of diffusion coefficient from the localisation precision.
        // Just use the entire dataset for simplicity (i.e. not the tracks of min length).
        final PrecisionResultProcedure pp = new PrecisionResultProcedure(results);
        try {
            pp.getPrecision();
            final Mean mean = new Mean();
            for (final double p : pp.precisions) {
                mean.add(p);
            }
            // 2nDt = MSD (n = number of dimensions)
            // D = MSD / 2nt
            final CalibrationReader reader = results.getCalibrationReader();
            final double t = reader.getExposureTime() / 1000.0;
            // Assume computed in nm. Convert to um.
            final double x = mean.getMean() / 1000;
            final double d = x * x / (2 * t);
            TextUtils.formatTo(sb, ", precision=%s nm, D limit=%s um^2/s", MathUtils.rounded(x * 1000, 4), MathUtils.rounded(d, 4));
        } catch (final DataException ex) {
        // No precision
        }
        IJ.log(sb.toString());
    });
    return tracks;
}

Example 8 with DataException

use of uk.ac.sussex.gdsc.core.data.DataException in project GDSC-SMLM by aherbert.

the class PoissonCalculatorTest method canComputeLogLikelihoodRatio.

private static void canComputeLogLikelihoodRatio(RandomSeed seed, BaseNonLinearFunction nlf) {
    logger.log(TestLogUtils.getRecord(LOG_LEVEL, nlf.name));
    final int n = maxx * maxx;
    final double[] a = new double[] { 1 };
    // Simulate Poisson process
    nlf.initialise(a);
    final UniformRandomProvider rng = RngUtils.create(seed.getSeed());
    final double[] x = new double[n];
    final double[] u = new double[n];
    for (int i = 0; i < n; i++) {
        u[i] = nlf.eval(i);
        if (u[i] > 0) {
            x[i] = GdscSmlmTestUtils.createPoissonSampler(rng, u[i]).sample();
        }
    }
    final DoubleDoubleBiPredicate predicate = TestHelper.doublesAreClose(1e-10, 0);
    double ll = PoissonCalculator.logLikelihood(u, x);
    final double mll = PoissonCalculator.maximumLogLikelihood(x);
    double llr = -2 * (ll - mll);
    double llr2 = PoissonCalculator.logLikelihoodRatio(u, x);
    logger.log(TestLogUtils.getRecord(LOG_LEVEL, "llr=%f, llr2=%f", llr, llr2));
    TestAssertions.assertTest(llr, llr2, predicate, "Log-likelihood ratio");
    final double[] op = new double[x.length];
    for (int i = 0; i < n; i++) {
        op[i] = PoissonCalculator.maximumLikelihood(x[i]);
    }
    // TestSettings.setLogLevel(uk.ac.sussex.gdsc.smlm.TestLog.Level.FINE);
    final int df = n - 1;
    final ChiSquaredDistributionTable table = ChiSquaredDistributionTable.createUpperTailed(0.05, df);
    final ChiSquaredDistributionTable table2 = ChiSquaredDistributionTable.createUpperTailed(0.001, df);
    if (logger.isLoggable(LOG_LEVEL)) {
        logger.log(TestLogUtils.getRecord(LOG_LEVEL, "Chi2 = %f (q=%.3f), %f (q=%.3f)  %f %b  %f", table.getCrititalValue(df), table.getSignificanceValue(), table2.getCrititalValue(df), table2.getSignificanceValue(), ChiSquaredDistributionTable.computeQValue(24, 2), ChiSquaredDistributionTable.createUpperTailed(0.05, 2).reject(24, 2), ChiSquaredDistributionTable.getChiSquared(1e-6, 2)));
    }
    final TDoubleArrayList list = new TDoubleArrayList();
    final int imin = 5;
    final int imax = 15;
    for (int i = imin; i <= imax; i++) {
        a[0] = (double) i / 10;
        nlf.initialise(a);
        for (int j = 0; j < n; j++) {
            u[j] = nlf.eval(j);
        }
        ll = PoissonCalculator.logLikelihood(u, x);
        list.add(ll);
        llr = PoissonCalculator.logLikelihoodRatio(u, x);
        BigDecimal product = new BigDecimal(1);
        double ll2 = 0;
        for (int j = 0; j < n; j++) {
            final double p1 = PoissonCalculator.likelihood(u[j], x[j]);
            ll2 += Math.log(p1);
            final double ratio = p1 / op[j];
            product = product.multiply(new BigDecimal(ratio));
        }
        llr2 = -2 * Math.log(product.doubleValue());
        final double p = ChiSquaredDistributionTable.computePValue(llr, df);
        final double q = ChiSquaredDistributionTable.computeQValue(llr, df);
        logger.log(TestLogUtils.getRecord(LOG_LEVEL, "a=%f, ll=%f, ll2=%f, llr=%f, llr2=%f, product=%s, p=%f, q=%f " + "(reject=%b @ %.3f, reject=%b @ %.3f)", a[0], ll, ll2, llr, llr2, product.round(new MathContext(4)).toString(), p, q, table.reject(llr, df), table.getSignificanceValue(), table2.reject(llr, df), table2.getSignificanceValue()));
        // too small to store in a double.
        if (product.doubleValue() > 0) {
            TestAssertions.assertTest(ll, ll2, predicate, "Log-likelihood");
            TestAssertions.assertTest(llr, llr2, predicate, "Log-likelihood ratio");
        }
    }
    // Find max using quadratic fit
    final double[] data = list.toArray();
    int index = SimpleArrayUtils.findMaxIndex(data);
    final double maxa = (double) (imin + index) / 10;
    double fita = maxa;
    try {
        if (index == 0) {
            index++;
        }
        if (index == data.length - 1) {
            index--;
        }
        final int i1 = index - 1;
        final int i2 = index;
        final int i3 = index + 1;
        fita = QuadraticUtils.findMinMax((double) (imin + i1) / 10, data[i1], (double) (imin + i2) / 10, data[i2], (double) (imin + i3) / 10, data[i3]);
    } catch (final DataException ex) {
    // Ignore
    }
    // Allow a tolerance as the random data may alter the p-value computation.
    // Should allow it to be less than 2 increment either side of the answer.
    logger.log(TestLogUtils.getRecord(LOG_LEVEL, "max fit = %g => %g", maxa, fita));
    Assertions.assertEquals(1, fita, 0.199, "max");
}

Example 9 with DataException

use of uk.ac.sussex.gdsc.core.data.DataException in project GDSC-SMLM by aherbert.

the class ScmosLikelihoodWrapperTest method canComputePValue.

private static void canComputePValue(RandomSeed seed, BaseNonLinearFunction nlf) {
    logger.log(TestLogUtils.getRecord(Level.INFO, nlf.name));
    final int n = maxx * maxx;
    final double[] a = new double[] { 1 };
    // Simulate sCMOS camera
    nlf.initialise(a);
    final SCcmosLikelihoodWrapperTestData testData = (SCcmosLikelihoodWrapperTestData) dataCache.computeIfAbsent(seed, ScmosLikelihoodWrapperTest::createData);
    final float[] var = testData.var;
    final float[] g = testData.gain;
    final float[] o = testData.offset;
    final float[] sd = testData.sd;
    final UniformRandomProvider r = RngUtils.create(seed.getSeed());
    final SharedStateContinuousSampler gs = SamplerUtils.createGaussianSampler(r, 0, 1);
    final double[] k = SimpleArrayUtils.newArray(n, 0, 1.0);
    for (int i = 0; i < n; i++) {
        double mean = nlf.eval(i);
        if (mean > 0) {
            mean = GdscSmlmTestUtils.createPoissonSampler(r, mean).sample();
        }
        k[i] = mean * g[i] + o[i] + gs.sample() * sd[i];
    }
    final ScmosLikelihoodWrapper f = new ScmosLikelihoodWrapper(nlf, a, k, n, var, g, o);
    final double oll = f.computeObservedLikelihood();
    double oll2 = 0;
    final double[] op = new double[n];
    for (int j = 0; j < n; j++) {
        op[j] = ScmosLikelihoodWrapper.likelihood((k[j] - o[j]) / g[j], var[j], g[j], o[j], k[j]);
        oll2 -= Math.log(op[j]);
    }
    logger.log(TestLogUtils.getRecord(Level.INFO, "oll=%f, oll2=%f", oll, oll2));
    final DoubleDoubleBiPredicate predicate = TestHelper.doublesAreClose(1e-10, 0);
    TestAssertions.assertTest(oll2, oll, predicate, "Observed Log-likelihood");
    final TDoubleArrayList list = new TDoubleArrayList();
    final int imin = 5;
    final int imax = 15;
    for (int i = imin; i <= imax; i++) {
        a[0] = (double) i / 10;
        final double ll = f.likelihood(a);
        list.add(ll);
        final double llr = f.computeLogLikelihoodRatio(ll);
        BigDecimal product = new BigDecimal(1);
        double ll2 = 0;
        for (int j = 0; j < n; j++) {
            final double p1 = ScmosLikelihoodWrapper.likelihood(nlf.eval(j), var[j], g[j], o[j], k[j]);
            ll2 -= Math.log(p1);
            final double ratio = p1 / op[j];
            product = product.multiply(new BigDecimal(ratio));
        }
        final double llr2 = -2 * Math.log(product.doubleValue());
        final double q = f.computeQValue(ll);
        logger.log(TestLogUtils.getRecord(Level.INFO, "a=%f, ll=%f, ll2=%f, llr=%f, llr2=%f, product=%s, p=%f", a[0], ll, ll2, llr, llr2, product.round(new MathContext(4)).toString(), q));
        // too small to store in a double.
        if (product.doubleValue() > 0) {
            TestAssertions.assertTest(llr, llr2, predicate, "Log-likelihood");
        }
    }
    // Find min using quadratic fit
    final double[] data = list.toArray();
    int index = SimpleArrayUtils.findMinIndex(data);
    final double mina = (double) (imin + index) / 10;
    double fita = mina;
    try {
        if (index == 0) {
            index++;
        }
        if (index == data.length - 1) {
            index--;
        }
        final int i1 = index - 1;
        final int i2 = index;
        final int i3 = index + 1;
        fita = QuadraticUtils.findMinMax((double) (imin + i1) / 10, data[i1], (double) (imin + i2) / 10, data[i2], (double) (imin + i3) / 10, data[i3]);
    } catch (final DataException ex) {
    // Ignore
    }
    // Allow a tolerance as the random data may alter the p-value computation.
    // Should allow it to be less than 2 increment either side of the answer.
    logger.log(TestLogUtils.getRecord(Level.INFO, "min fit = %g => %g", mina, fita));
    Assertions.assertEquals(1, fita, 0.199, "min");
}

Example 10 with DataException

use of uk.ac.sussex.gdsc.core.data.DataException in project GDSC-SMLM by aherbert.

the class CreateFilters method processElement.

private int processElement(StringWriter sw, Node node) throws TransformerFactoryConfigurationError {
    // Get entire element as a string
    final String xmlString = uk.ac.sussex.gdsc.core.utils.XmlUtils.getString(node, false);
    ArrayList<StringBuilder> out = new ArrayList<>();
    // Process through the XML appending to the current output.
    final String[] tokens = xmlString.split("\\s+");
    for (final String token : tokens) {
        // Any attributes with enumerations should be expanded.
        final Matcher match = pattern.matcher(token);
        if (match.find()) {
            final String prefix = " " + match.group(1) + "=\"";
            // Use Big Decimal for the enumeration to preserve the precision of the input text
            // (i.e. using doubles for an enumeration can lose precision and fail to correctly
            // enumerate)
            BigDecimal min;
            BigDecimal max;
            BigDecimal inc;
            try {
                min = new BigDecimal(match.group(2));
                max = new BigDecimal(match.group(3));
                inc = new BigDecimal(match.group(4));
                if (min.compareTo(max) > 0 || inc.compareTo(BigDecimal.ZERO) <= 0) {
                    throw new DataException("Invalid 'min:max:increment' attribute: " + token);
                }
            } catch (final NumberFormatException ex) {
                throw new DataException("Invalid 'min:max:increment' attribute: " + token, ex);
            }
            final String suffix = "\"" + match.group(5);
            // Enumerate the attribute
            final ArrayList<String> attributeText = new ArrayList<>();
            for (BigDecimal bd = min; bd.compareTo(max) <= 0; bd = bd.add(inc)) {
                attributeText.add(prefix + bd.toString() + suffix);
            }
            // Add to the current output
            final ArrayList<StringBuilder> out2 = new ArrayList<>(out.size() * attributeText.size());
            if (enumerateEarly) {
                // Enumerate earlier attributes first
                for (final String text : attributeText) {
                    for (final StringBuilder sb : out) {
                        out2.add(new StringBuilder(sb.toString()).append(text));
                    }
                }
            } else {
                // Enumerate later attributes first
                for (final StringBuilder sb : out) {
                    final String current = sb.toString();
                    for (final String text : attributeText) {
                        out2.add(new StringBuilder(current).append(text));
                    }
                }
            }
            out = out2;
        } else if (out.isEmpty()) {
            out.add(new StringBuilder(token));
        } else {
            for (final StringBuilder sb : out) {
                sb.append(" ").append(token);
            }
        }
    }
    if (!out.isEmpty()) {
        sw.write("<FilterSet name=\"");
        sw.write(getName(out.get(0)));
        sw.write("\"><filters class=\"linked-list\">");
        for (final StringBuilder sb : out) {
            sw.write(sb.toString());
        }
        sw.write("</filters></FilterSet>");
    }
    return out.size();
}