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public static SVGPath drawFakeVoronoi(Projection2D proj, List<double[]> means) { CanvasSize viewport = proj.estimateViewport(); final SVGPath path = new SVGPath(); // Difference final double[] dirv = VMath.minus(means.get(1), means.get(0)); VMath.rotate90Equals(dirv); double[] dir = proj.fastProjectRelativeDataToRenderSpace(dirv); // Mean final double[] mean = VMath.plus(means.get(0), means.get(1)); VMath.timesEquals(mean, 0.5); double[] projmean = proj.fastProjectDataToRenderSpace(mean); double factor = viewport.continueToMargin(projmean, dir); path.moveTo(projmean[0] + factor * dir[0], projmean[1] + factor * dir[1]); // Inverse direction: dir[0] *= -1; dir[1] *= -1; factor = viewport.continueToMargin(projmean, dir); path.drawTo(projmean[0] + factor * dir[0], projmean[1] + factor * dir[1]); return path; }
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public void select(Segment segment, boolean addToSelection) { // abort if segment represents pairs inNone. Would select all segments... if(segment.isNone()) { return; } if(!addToSelection) { deselectAllSegments(); } // get selected segments if(segment.isUnpaired()) { // check if all segments are selected if(addToSelection) { boolean allSegmentsSelected = true; for(Segment other : segments.getPairedSegments(segment)) { if(!isSelected(other)) { allSegmentsSelected = false; break; } } // if all are selected, deselect all if(allSegmentsSelected) { deselectSegment(segment); return; } } if(isSelected(segment)) { deselectSegment(segment); } else { selectSegment(segment); } } else { // an object segment was selected if(isSelected(segment)) { deselectSegment(segment); } else { selectSegment(segment); } } }
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protected void deselectSegment(Segment segment) { if(segment.isUnpaired()) { ArrayList<Segment> remove = new ArrayList<>(); // remove all object segments associated with unpaired segment from // selection list for(Entry<Segment, Segment> entry : indirectSelections.entrySet()) { if(entry.getValue() == segment) { remove.add(entry.getKey()); } } for(Segment other : remove) { indirectSelections.remove(other); deselectSegment(other); } } else { // check if deselected object Segment has a unpaired segment highlighted Segment unpaired = indirectSelections.get(segment); if(unpaired != null) { // remove highlight deselectSegment(unpaired); } if(selectedSegments.remove(segment) && segment.getDBIDs() != null) { unselectedObjects.addDBIDs(segment.getDBIDs()); } } }
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protected void selectSegment(Segment segment) { if(segment.isUnpaired()) { // remember selected unpaired segment for(Segment other : segments.getPairedSegments(segment)) { indirectSelections.put(other, segment); selectSegment(other); } } else { if(!selectedSegments.contains(segment)) { selectedSegments.add(segment); if(segment.getDBIDs() != null) { unselectedObjects.removeDBIDs(segment.getDBIDs()); } } } }
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private boolean checkSupertypes(Class<?> cls) { for(Class<?> c : knownParameterizables) { if(c.isAssignableFrom(cls)) { return true; } } return false; }
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private State checkV3Parameterization(Class<?> cls, State state) throws NoClassDefFoundError { // check for a V3 Parameterizer class for(Class<?> inner : cls.getDeclaredClasses()) { if(AbstractParameterizer.class.isAssignableFrom(inner)) { try { Class<? extends AbstractParameterizer> pcls = inner.asSubclass(AbstractParameterizer.class); pcls.newInstance(); if(checkParameterizer(cls, pcls)) { if(state == State.INSTANTIABLE) { LOG.warning("More than one parameterization method in class " + cls.getName()); } state = State.INSTANTIABLE; } } catch(Exception|Error e) { LOG.verbose("Could not run Parameterizer: " + inner.getName() + ": " + e.getMessage()); // continue. Probably non-public } } } return state; }
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private State checkDefaultConstructor(Class<?> cls, State state) throws NoClassDefFoundError { try { cls.getConstructor(); return State.DEFAULT_INSTANTIABLE; } catch(Exception e) { // do nothing. } return state; }
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public static double logpdf(double x, double k, double theta, double shift) { x = (x - shift); if(x <= 0.) { return Double.NEGATIVE_INFINITY; } final double log1px = FastMath.log1p(x); return k * FastMath.log(theta) - GammaDistribution.logGamma(k) - (theta + 1.) * log1px + (k - 1) * FastMath.log(log1px); }
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protected void plotGray(SVGPlot plot, Element parent, double x, double y, double size) { Element marker = plot.svgCircle(x, y, size * .5); SVGUtil.setStyle(marker, SVGConstants.CSS_FILL_PROPERTY + ":" + greycolor); parent.appendChild(marker); }
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protected void plotUncolored(SVGPlot plot, Element parent, double x, double y, double size) { Element marker = plot.svgCircle(x, y, size * .5); SVGUtil.setStyle(marker, SVGConstants.CSS_FILL_PROPERTY + ":" + dotcolor); parent.appendChild(marker); }
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public int truePositives() { int tp = 0; for(int i = 0; i < confusion.length; i++) { tp += truePositives(i); } return tp; }
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public int trueNegatives(int classindex) { int tn = 0; for(int i = 0; i < confusion.length; i++) { for(int j = 0; j < confusion[i].length; j++) { if(i != classindex && j != classindex) { tn += confusion[i][j]; } } } return tn; }
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public int falsePositives(int classindex) { int fp = 0; for(int i = 0; i < confusion[classindex].length; i++) { if(i != classindex) { fp += confusion[classindex][i]; } } return fp; }
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public int falseNegatives(int classindex) { int fn = 0; for(int i = 0; i < confusion.length; i++) { if(i != classindex) { fn += confusion[i][classindex]; } } return fn; }
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public int totalInstances() { int total = 0; for(int i = 0; i < confusion.length; i++) { for(int j = 0; j < confusion[i].length; j++) { total += confusion[i][j]; } } return total; }
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protected static <A> double[] computeDistances(NumberArrayAdapter<?, A> adapter, A data) { final int size = adapter.size(data); double[] dMatrix = new double[(size * (size + 1)) >> 1]; for(int i = 0, c = 0; i < size; i++) { for(int j = 0; j < i; j++) { double dx = adapter.getDouble(data, i) - adapter.getDouble(data, j); dMatrix[c++] = (dx < 0) ? -dx : dx; // Absolute difference. } c++; // Diagonal entry: zero } doubleCenterMatrix(dMatrix, size); return dMatrix; }
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public static void doubleCenterMatrix(double[] dMatrix, int size) { double[] rowMean = new double[size]; // row sum for(int i = 0, c = 0; i < size; i++) { for(int j = 0; j < i; j++) { double v = dMatrix[c++]; rowMean[i] += v; rowMean[j] += v; } assert (dMatrix[c] == 0.); c++; // Diagonal entry. Must be zero! } // Normalize averages: double matrixMean = 0.; for(int i = 0; i < size; i++) { matrixMean += rowMean[i]; rowMean[i] /= size; } matrixMean /= size * size; for(int o = 0, c = 0; o < size; o++) { // Including row mean! for(int p = 0; p <= o; p++) { dMatrix[c++] -= rowMean[o] + rowMean[p] - matrixMean; } } }
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public HyperBoundingBox determineAlphaMinMax(HyperBoundingBox interval) { final int dim = vec.getDimensionality(); if(interval.getDimensionality() != dim - 1) { throw new IllegalArgumentException("Interval needs to have dimensionality d=" + (dim - 1) + ", read: " + interval.getDimensionality()); } if(extremumType.equals(ExtremumType.CONSTANT)) { double[] centroid = SpatialUtil.centroid(interval); return new HyperBoundingBox(centroid, centroid); } double[] alpha_min = new double[dim - 1]; double[] alpha_max = new double[dim - 1]; if(SpatialUtil.contains(interval, alphaExtremum)) { if(extremumType.equals(ExtremumType.MINIMUM)) { alpha_min = alphaExtremum; for(int d = dim - 2; d >= 0; d--) { alpha_max[d] = determineAlphaMax(d, alpha_max, interval); } } else { alpha_max = alphaExtremum; for(int d = dim - 2; d >= 0; d--) { alpha_min[d] = determineAlphaMin(d, alpha_min, interval); } } } else { for(int d = dim - 2; d >= 0; d--) { alpha_min[d] = determineAlphaMin(d, alpha_min, interval); alpha_max[d] = determineAlphaMax(d, alpha_max, interval); } } return new HyperBoundingBox(alpha_min, alpha_max); }
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private ExtremumType extremumType(int n, double[] alpha_extreme, HyperBoundingBox interval) { // return the type of the global extremum if(n == alpha_extreme.length - 1) { return extremumType; } // create random alpha values double[] alpha_extreme_l = new double[alpha_extreme.length]; double[] alpha_extreme_r = new double[alpha_extreme.length]; double[] alpha_extreme_c = new double[alpha_extreme.length]; System.arraycopy(alpha_extreme, 0, alpha_extreme_l, 0, alpha_extreme.length); System.arraycopy(alpha_extreme, 0, alpha_extreme_r, 0, alpha_extreme.length); System.arraycopy(alpha_extreme, 0, alpha_extreme_c, 0, alpha_extreme.length); double[] centroid = SpatialUtil.centroid(interval); for(int i = 0; i < n; i++) { alpha_extreme_l[i] = centroid[i]; alpha_extreme_r[i] = centroid[i]; alpha_extreme_c[i] = centroid[i]; } double intervalLength = interval.getMax(n) - interval.getMin(n); alpha_extreme_l[n] = Math.random() * intervalLength + interval.getMin(n); alpha_extreme_r[n] = Math.random() * intervalLength + interval.getMin(n); double f_c = function(alpha_extreme_c); double f_l = function(alpha_extreme_l); double f_r = function(alpha_extreme_r); if(f_l < f_c) { if(f_r < f_c || Math.abs(f_r - f_c) < DELTA) { return ExtremumType.MAXIMUM; } } if(f_r < f_c) { if(f_l < f_c || Math.abs(f_l - f_c) < DELTA) { return ExtremumType.MAXIMUM; } } if(f_l > f_c) { if(f_r > f_c || Math.abs(f_r - f_c) < DELTA) { return ExtremumType.MINIMUM; } } if(f_r > f_c) { if(f_l > f_c || Math.abs(f_l - f_c) < DELTA) { return ExtremumType.MINIMUM; } } if(Math.abs(f_l - f_c) < DELTA && Math.abs(f_r - f_c) < DELTA) { return ExtremumType.CONSTANT; } throw new IllegalArgumentException("Houston, we have a problem!\n" + this + // "\nf_l " + f_l + "\nf_c " + f_c + "\nf_r " + f_r + "\np " + vec + // "\nalpha " + FormatUtil.format(alpha_extreme_c) + // "\nalpha_l " + FormatUtil.format(alpha_extreme_l) + // "\nalpha_r " + FormatUtil.format(alpha_extreme_r) + "\nn " + n); // + "box min " + FormatUtil.format(interval.getMin()) + "\n" // + "box max " + FormatUtil.format(interval.getMax()) + "\n" }
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private double determineAlphaMin(int n, double[] alpha_min, HyperBoundingBox interval) { double alpha_n = extremum_alpha_n(n, alpha_min); double lower = interval.getMin(n); double upper = interval.getMax(n); double[] alpha_extreme = new double[alpha_min.length]; System.arraycopy(alpha_min, n, alpha_extreme, n, alpha_extreme.length - n); alpha_extreme[n] = alpha_n; ExtremumType type = extremumType(n, alpha_extreme, interval); if(type.equals(ExtremumType.MINIMUM) || type.equals(ExtremumType.CONSTANT)) { // A) lower <= alpha_n <= upper if(lower <= alpha_n && alpha_n <= upper) { return alpha_n; } // B) alpha_n < upper else if(alpha_n < lower) { return lower; } // C) alpha_n > max else { if(alpha_n <= upper) { throw new IllegalStateException("Should never happen!"); } return upper; } } // extremum is maximum else { if(lower <= alpha_n && alpha_n <= upper) { // A1) min <= alpha_n <= max && alpha_n - min <= max - alpha_n if(alpha_n - lower <= upper - alpha_n) { return upper; } // A2) min <= alpha_n <= max && alpha_n - min > max - alpha_n else { return lower; } } // B) alpha_n < min else if(alpha_n < lower) { return upper; } // C) alpha_n > max else { if(alpha_n <= upper) { throw new IllegalStateException("Should never happen!"); } return lower; } } }
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public static double sinusProduct(int start, int end, double[] alpha) { double result = 1; for(int j = start; j < end; j++) { result *= FastMath.sin(alpha[j]); } return result; }
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private void determineGlobalExtremum() { alphaExtremum = new double[vec.getDimensionality() - 1]; for(int n = alphaExtremum.length - 1; n >= 0; n--) { alphaExtremum[n] = extremum_alpha_n(n, alphaExtremum); if(Double.isNaN(alphaExtremum[n])) { throw new IllegalStateException("Houston, we have a problem!\n" + this + "\n" + vec + "\n" + FormatUtil.format(alphaExtremum)); } } determineGlobalExtremumType(); }
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private void determineGlobalExtremumType() { final double f = function(alphaExtremum); // create random alpha values double[] alpha_1 = new double[alphaExtremum.length]; double[] alpha_2 = new double[alphaExtremum.length]; for(int i = 0; i < alphaExtremum.length; i++) { alpha_1[i] = Math.random() * Math.PI; alpha_2[i] = Math.random() * Math.PI; } // look if f1 and f2 are less, greater or equal to f double f1 = function(alpha_1); double f2 = function(alpha_2); if(f1 < f && f2 < f) { extremumType = ExtremumType.MAXIMUM; } else if(f1 > f && f2 > f) { extremumType = ExtremumType.MINIMUM; } else if(Math.abs(f1 - f) < DELTA && Math.abs(f2 - f) < DELTA) { extremumType = ExtremumType.CONSTANT; } else { throw new IllegalStateException("Houston, we have a problem:" + "\n" + this + "\nextremum at " + FormatUtil.format(alphaExtremum) + "\nf " + f + "\nf1 " + f1 + "\nf2 " + f2); } }
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public void setParameters(Parameterization config) { TrackParameters track = new TrackParameters(config); configureStep(track); // update parameter table { parameterTable.setEnabled(false); parameterTable.clear(); for(TrackedParameter pair : track.getAllParameters()) { parameterTable.addParameter(pair.getOwner(), pair.getParameter(), track); } // parameters.updateFromTrackParameters(track); parameterTable.revalidate(); parameterTable.setEnabled(true); } // Update status and notify observers updateStatus(); firePanelUpdated(); }
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protected void reportErrors(Parameterization config) { StringBuilder buf = new StringBuilder(); for(ParameterException e : config.getErrors()) { if(e instanceof UnspecifiedParameterException) { continue; } buf.append(e.getMessage()).append(FormatUtil.NEWLINE); } if(buf.length() > 0) { LOG.warning("Configuration errors:" + FormatUtil.NEWLINE + FormatUtil.NEWLINE + buf.toString()); } // config.clearErrors(); }
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public boolean canRun() { Status status = getStatus(); return Status.STATUS_READY.equals(status) || Status.STATUS_COMPLETE.equals(status); }
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public SVGPath lineTo(double x, double y) { return append(PATH_LINE_TO).append(x).append(y); }
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public SVGPath relativeLineTo(double x, double y) { return append(PATH_LINE_TO_RELATIVE).append(x).append(y); }
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public SVGPath moveTo(double x, double y) { return append(PATH_MOVE).append(x).append(y); }
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public SVGPath relativeMoveTo(double x, double y) { return append(PATH_MOVE_RELATIVE).append(x).append(y); }
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public SVGPath smoothQuadTo(double x, double y) { return append(PATH_SMOOTH_QUAD_TO).append(x).append(y); }
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public SVGPath relativeSmoothQuadTo(double x, double y) { return append(PATH_SMOOTH_QUAD_TO_RELATIVE).append(x).append(y); }
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private SVGPath append(char action) { assert lastaction != 0 || action == PATH_MOVE : "Paths must begin with a move to the initial position!"; if(lastaction != action) { buf.append(action); lastaction = action; } return this; }
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private SVGPath append(double x) { if(!Double.isFinite(x)) { throw new IllegalArgumentException("Cannot draw an infinite/NaN position."); } if(x >= 0) { final int l = buf.length(); if(l > 0) { char c = buf.charAt(l - 1); assert c != 'e' && c != 'E' : "Invalid exponential in path"; if(c >= '0' && c <= '9') buf.append(' '); } } buf.append(SVGUtil.FMT.format(x)); return this; }
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public SVGPath close() { assert lastaction != 0 : "Paths must begin with a move to the initial position!"; if(lastaction != PATH_CLOSE) { buf.append(' ').append(PATH_CLOSE); lastaction = PATH_CLOSE; } return this; }
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public Element makeElement(SVGPlot plot) { Element elem = plot.svgElement(SVGConstants.SVG_PATH_TAG); elem.setAttribute(SVGConstants.SVG_D_ATTRIBUTE, buf.toString()); return elem; }
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public void setParameters(Parameterization config) { // Clear errors after each step, so they don't consider themselves failed // because of earlier errors. logTab.setParameters(config); // config.clearErrors(); inputTab.setParameters(config); // config.clearErrors(); algTab.setParameters(config); // config.clearErrors(); evalTab.setParameters(config); // config.clearErrors(); outTab.setParameters(config); // config.clearErrors(); }
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public ArrayList<String> serializeParameters() { ListParameterization params = new ListParameterization(); logTab.appendParameters(params); inputTab.appendParameters(params); algTab.appendParameters(params); evalTab.appendParameters(params); outTab.appendParameters(params); return params.serialize(); }
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public static void main(final String[] args) { GUIUtil.logUncaughtExceptions(LOG); GUIUtil.setLookAndFeel(); OutputStep.setDefaultHandlerVisualizer(); javax.swing.SwingUtilities.invokeLater(new Runnable() { @Override public void run() { try { final MultiStepGUI gui = new MultiStepGUI(); gui.run(); if(args != null && args.length > 0) { gui.setParameters(new SerializedParameterization(args)); } else { gui.setParameters(new SerializedParameterization()); } } catch(Exception | Error e) { // Restore error handler, as the GUI is likely broken. LoggingConfiguration.replaceDefaultHandler(new CLISmartHandler()); LOG.exception(e); } } }); }
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protected static boolean match(Object ref, Object test) { if(ref == null) { return false; } // Cheap and fast, may hold for class labels! if(ref == test) { return true; } if(ref instanceof LabelList && test instanceof LabelList) { final LabelList lref = (LabelList) ref; final LabelList ltest = (LabelList) test; final int s1 = lref.size(), s2 = ltest.size(); if(s1 == 0 || s2 == 0) { return false; } for(int i = 0; i < s1; i++) { String l1 = lref.get(i); if(l1 == null) { continue; } for(int j = 0; j < s2; j++) { if(l1.equals(ltest.get(j))) { return true; } } } } // Fallback to equality, e.g. on class labels return ref.equals(test); }
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private void findMatches(ModifiableDBIDs posn, Relation<?> lrelation, Object label) { posn.clear(); for(DBIDIter ri = lrelation.iterDBIDs(); ri.valid(); ri.advance()) { if(match(label, lrelation.get(ri))) { posn.add(ri); } } }
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private void computeDistances(ModifiableDoubleDBIDList nlist, DBIDIter query, final DistanceQuery<O> distQuery, Relation<O> relation) { nlist.clear(); O qo = relation.get(query); for(DBIDIter ri = relation.iterDBIDs(); ri.valid(); ri.advance()) { if(!includeSelf && DBIDUtil.equal(ri, query)) { continue; } double dist = distQuery.distance(qo, ri); if(dist != dist) { /* NaN */ dist = Double.POSITIVE_INFINITY; } nlist.add(dist, ri); } nlist.sort(); }
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private PrintStream newStream(String name) throws IOException { if(LOG.isDebuggingFiner()) { LOG.debugFiner("Requested stream: " + name); } // Ensure the directory exists: if(!basename.exists()) { basename.mkdirs(); } String fn = basename.getAbsolutePath() + File.separator + name + EXTENSION; fn = usegzip ? fn + GZIP_EXTENSION : fn; OutputStream os = new FileOutputStream(fn); if(usegzip) { // wrap into gzip stream. os = new GZIPOutputStream(os); } PrintStream res = new PrintStream(os); if(LOG.isDebuggingFiner()) { LOG.debugFiner("Opened new output stream:" + fn); } // cache. return res; }
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protected <N extends Page & Externalizable> PageFile<N> makePageFile(Class<N> cls) { @SuppressWarnings("unchecked") final PageFileFactory<N> castFactory = (PageFileFactory<N>) pageFileFactory; return castFactory.newPageFile(cls); }
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public static boolean isAngularDistance(AbstractMaterializeKNNPreprocessor<?> kNN) { DistanceFunction<?> distanceFunction = kNN.getDistanceQuery().getDistanceFunction(); return CosineDistanceFunction.class.isInstance(distanceFunction) // || ArcCosineDistanceFunction.class.isInstance(distanceFunction); }
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public static Element drawCosine(SVGPlot svgp, Projection2D proj, NumberVector mid, double angle) { // Project origin double[] pointOfOrigin = proj.fastProjectDataToRenderSpace(new double[proj.getInputDimensionality()]); // direction of the selected Point double[] selPoint = proj.fastProjectDataToRenderSpace(mid); double[] range1, range2; { // Rotation plane: double[] pm = mid.toArray(); // Compute relative vectors double[] p1 = minusEquals(proj.fastProjectRenderToDataSpace(selPoint[0] + 10, selPoint[1]), pm); double[] p2 = minusEquals(proj.fastProjectRenderToDataSpace(selPoint[0], selPoint[1] + 10), pm); // Scale p1 and p2 to unit length: timesEquals(p1, 1. / euclideanLength(p1)); timesEquals(p2, 1. / euclideanLength(p2)); if(Math.abs(scalarProduct(p1, p2)) > 1E-10) { LoggingUtil.warning("Projection does not seem to be orthogonal?"); } // Project onto p1, p2: double l1 = scalarProduct(pm, p1), l2 = scalarProduct(pm, p2); // Rotate projection by + and - angle // Using sin(-x) = -sin(x) and cos(-x)=cos(x) final DoubleWrapper tmp = new DoubleWrapper(); // To return cosine final double sangle = FastMath.sinAndCos(angle, tmp), cangle = tmp.value; double r11 = +cangle * l1 - sangle * l2, r12 = +sangle * l1 + cangle * l2; double r21 = +cangle * l1 + sangle * l2, r22 = -sangle * l1 + cangle * l2; // Build rotated vectors - remove projected component, add rotated // component: double[] r1 = plusTimesEquals(plusTimes(pm, p1, -l1 + r11), p2, -l2 + r12); double[] r2 = plusTimesEquals(plusTimes(pm, p1, -l1 + r21), p2, -l2 + r22); // Project to render space: range1 = proj.fastProjectDataToRenderSpace(r1); range2 = proj.fastProjectDataToRenderSpace(r2); } // Continue lines to viewport. { CanvasSize viewport = proj.estimateViewport(); minusEquals(range1, pointOfOrigin); plusEquals(timesEquals(range1, viewport.continueToMargin(pointOfOrigin, range1)), pointOfOrigin); minusEquals(range2, pointOfOrigin); plusEquals(timesEquals(range2, viewport.continueToMargin(pointOfOrigin, range2)), pointOfOrigin); // Go backwards into the other direction - the origin might not be in the // viewport! double[] start1 = minus(pointOfOrigin, range1); plusEquals(timesEquals(start1, viewport.continueToMargin(range1, start1)), range1); double[] start2 = minus(pointOfOrigin, range2); plusEquals(timesEquals(start2, viewport.continueToMargin(range2, start2)), range2); // TODO: add filled variant? return new SVGPath().moveTo(start1).lineTo(range1).moveTo(start2).lineTo(range2).makeElement(svgp); } }
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public void splitupNoSort(ArrayModifiableDBIDs ind, int begin, int end, int dim, Random rand) { final int nele = end - begin; dim = dim % projectedPoints.length;// choose a projection of points DoubleDataStore tpro = projectedPoints[dim]; // save set such that used for density or neighborhood computation // sets should be roughly minSplitSize if(nele > minSplitSize * (1 - sizeTolerance) && nele < minSplitSize * (1 + sizeTolerance)) { // sort set, since need median element later ind.sort(begin, end, new DataStoreUtil.AscendingByDoubleDataStore(tpro)); splitsets.add(DBIDUtil.newArray(ind.slice(begin, end))); } // compute splitting element // do not store set or even sort set, since it is too large if(nele > minSplitSize) { // splits can be performed either by distance (between min,maxCoord) or by // picking a point randomly(picking index of point) // outcome is similar // int minInd splitByDistance(ind, nele, tpro); int minInd = splitRandomly(ind, begin, end, tpro, rand); // split set recursively // position used for splitting the projected points into two // sets used for recursive splitting int splitpos = minInd + 1; splitupNoSort(ind, begin, splitpos, dim + 1, rand); splitupNoSort(ind, splitpos, end, dim + 1, rand); } }
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public int splitRandomly(ArrayModifiableDBIDs ind, int begin, int end, DoubleDataStore tpro, Random rand) { final int nele = end - begin; DBIDArrayIter it = ind.iter(); // pick random splitting element based on position double rs = tpro.doubleValue(it.seek(begin + rand.nextInt(nele))); int minInd = begin, maxInd = end - 1; // permute elements such that all points smaller than the splitting // element are on the right and the others on the left in the array while(minInd < maxInd) { double currEle = tpro.doubleValue(it.seek(minInd)); if(currEle > rs) { while(minInd < maxInd && tpro.doubleValue(it.seek(maxInd)) > rs) { maxInd--; } if(minInd == maxInd) { break; } ind.swap(minInd, maxInd); maxInd--; } minInd++; } // if all elements are the same split in the middle if(minInd == end - 1) { minInd = (begin + end) >>> 1; } return minInd; }
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public int splitByDistance(ArrayModifiableDBIDs ind, int begin, int end, DoubleDataStore tpro, Random rand) { DBIDArrayIter it = ind.iter(); // pick random splitting point based on distance double rmin = Double.MAX_VALUE * .5, rmax = -Double.MAX_VALUE * .5; int minInd = begin, maxInd = end - 1; for(it.seek(begin); it.getOffset() < end; it.advance()) { double currEle = tpro.doubleValue(it); rmin = Math.min(currEle, rmin); rmax = Math.max(currEle, rmax); } if(rmin != rmax) { // if not all elements are the same double rs = rmin + rand.nextDouble() * (rmax - rmin); // permute elements such that all points smaller than the splitting // element are on the right and the others on the left in the array while(minInd < maxInd) { double currEle = tpro.doubleValue(it.seek(minInd)); if(currEle > rs) { while(minInd < maxInd && tpro.doubleValue(it.seek(maxInd)) > rs) { maxInd--; } if(minInd == maxInd) { break; } ind.swap(minInd, maxInd); maxInd--; } minInd++; } } else { // if all elements are the same split in the middle minInd = (begin + end) >>> 1; } return minInd; }
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public DataStore<? extends DBIDs> getNeighs() { final DBIDs ids = points.getDBIDs(); // init lists WritableDataStore<ModifiableDBIDs> neighs = DataStoreUtil.makeStorage(ids, DataStoreFactory.HINT_HOT, ModifiableDBIDs.class); for(DBIDIter it = ids.iter(); it.valid(); it.advance()) { neighs.put(it, DBIDUtil.newHashSet()); } FiniteProgress splitp = LOG.isVerbose() ? new FiniteProgress("Processing splits for neighborhoods", splitsets.size(), LOG) : null; // go through all sets Iterator<ArrayDBIDs> it1 = splitsets.iterator(); DBIDVar v = DBIDUtil.newVar(); while(it1.hasNext()) { ArrayDBIDs pinSet = it1.next(); final int indoff = pinSet.size() >> 1; // middle point of projection pinSet.assignVar(indoff, v); // add all points as neighbors to middle point neighs.get(v).addDBIDs(pinSet); // and the the middle point to all other points in set for(DBIDIter it = pinSet.iter(); it.valid(); it.advance()) { neighs.get(it).add(v); } LOG.incrementProcessed(splitp); } LOG.ensureCompleted(splitp); return neighs; }
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public DoubleDataStore computeAverageDistInSet() { WritableDoubleDataStore davg = DataStoreUtil.makeDoubleStorage(points.getDBIDs(), DataStoreFactory.HINT_HOT); WritableIntegerDataStore nDists = DataStoreUtil.makeIntegerStorage(points.getDBIDs(), DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_TEMP); FiniteProgress splitp = LOG.isVerbose() ? new FiniteProgress("Processing splits for density estimation", splitsets.size(), LOG) : null; DBIDVar v = DBIDUtil.newVar(); for(Iterator<ArrayDBIDs> it1 = splitsets.iterator(); it1.hasNext();) { ArrayDBIDs pinSet = it1.next(); final int len = pinSet.size(); final int indoff = len >> 1; pinSet.assignVar(indoff, v); V midpoint = points.get(v); for(DBIDArrayIter it = pinSet.iter(); it.getOffset() < len; it.advance()) { if(DBIDUtil.equal(it, v)) { continue; } double dist = EuclideanDistanceFunction.STATIC.distance(points.get(it), midpoint); ++distanceComputations; davg.increment(v, dist); nDists.increment(v, 1); davg.increment(it, dist); nDists.increment(it, 1); } LOG.incrementProcessed(splitp); } LOG.ensureCompleted(splitp); for(DBIDIter it = points.getDBIDs().iter(); it.valid(); it.advance()) { // it might be that a point does not occur for a certain size of a // projection (likely if do few projections, in this case there is no avg // distance) int count = nDists.intValue(it); double val = (count == 0) ? FastOPTICS.UNDEFINED_DISTANCE : (davg.doubleValue(it) / count); davg.put(it, val); } nDists.destroy(); // No longer needed after normalization return davg; }
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public boolean containedIn(SparseNumberVector bv) { int i1 = this.iter(), i2 = bv.iter(); while(this.iterValid(i1)) { if(!bv.iterValid(i2)) { return false; } int d1 = this.iterDim(i1), d2 = bv.iterDim(i2); if(d1 < d2) { return false; // Missing } if(d1 == d2) { if(bv.iterDoubleValue(i2) == 0.) { return false; } i1 = this.iterAdvance(i1); } i2 = bv.iterAdvance(i2); } return true; }
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public static long[] toBitset(Itemset i, long[] bits) { for(int it = i.iter(); i.iterValid(it); it = i.iterAdvance(it)) { BitsUtil.setI(bits, i.iterDim(it)); } return bits; }
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protected static int compareLexicographical(Itemset a, Itemset o) { int i1 = a.iter(), i2 = o.iter(); while(a.iterValid(i1) && o.iterValid(i2)) { int v1 = a.iterDim(i1), v2 = o.iterDim(i2); if(v1 < v2) { return -1; } if(v2 < v1) { return +1; } i1 = a.iterAdvance(i1); i2 = o.iterAdvance(i2); } return a.iterValid(i1) ? 1 : o.iterValid(i2) ? -1 : 0; }
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public final StringBuilder appendTo(StringBuilder buf, VectorFieldTypeInformation<BitVector> meta) { appendItemsTo(buf, meta); return buf.append(": ").append(support); }
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public StringBuilder appendItemsTo(StringBuilder buf, VectorFieldTypeInformation<BitVector> meta) { int it = this.iter(); if(this.iterValid(it)) { while(true) { int v = this.iterDim(it); String lbl = (meta != null) ? meta.getLabel(v) : null; if(lbl == null) { buf.append(v); } else { buf.append(lbl); } it = this.iterAdvance(it); if(!this.iterValid(it)) { break; } buf.append(", "); } } return buf; }
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@Override public double getWeight(double distance, double max, double stddev) { if(max <= 0) { return 1.0; } double relativedistance = distance / max; // -2.303 is log(.1) to suit the intended range of 1.0-0.1 return FastMath.exp(-2.3025850929940455 * relativedistance * relativedistance); }
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@Override public void writePage(int pageID, P page) { if (page.isDirty()) { try { countWrite(); byte[] array = pageToByteArray(page); file.getRecordBuffer(pageID).put(array); page.setDirty(false); } catch (IOException e) { throw new RuntimeException(e); } } }
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private byte[] pageToByteArray(P page) { try { if (page == null) { ByteArrayOutputStream baos = new ByteArrayOutputStream(); ObjectOutputStream oos = new ObjectOutputStream(baos); oos.writeInt(EMPTY_PAGE); oos.close(); baos.close(); byte[] array = baos.toByteArray(); byte[] result = new byte[pageSize]; System.arraycopy(array, 0, result, 0, array.length); return result; } else { ByteArrayOutputStream baos = new ByteArrayOutputStream(); ObjectOutputStream oos = new ObjectOutputStream(baos); oos.writeInt(FILLED_PAGE); oos.writeObject(page); oos.close(); baos.close(); byte[] array = baos.toByteArray(); if (array.length > this.pageSize) { throw new IllegalArgumentException("Size of page " + page + " is greater than specified" + " pagesize: " + array.length + " > " + pageSize); } else if (array.length == this.pageSize) { return array; } else { byte[] result = new byte[pageSize]; System.arraycopy(array, 0, result, 0, array.length); return result; } } } catch (IOException e) { throw new RuntimeException("IOException occurred! ", e); } }
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public static SinCosTable make(int steps) { if ((steps & 0x3) == 0) { return new QuarterTable(steps); } if ((steps & 0x1) == 0) { return new HalfTable(steps); } return new FullTable(steps); }
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@Override protected void process(DBIDRef id, ArrayDBIDs ids, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m) { clinkstep3(id, it, n, pi, lambda, m); clinkstep4567(id, ids, it, n, pi, lambda, m); clinkstep8(id, it, n, pi, lambda, m); }
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private void clinkstep8(DBIDRef id, DBIDArrayIter it, int n, WritableDBIDDataStore pi, WritableDoubleDataStore lambda, WritableDoubleDataStore m) { DBIDVar p_i = DBIDUtil.newVar(), pp_i = DBIDUtil.newVar(); for(it.seek(0); it.getOffset() < n; it.advance()) { p_i.from(pi, it); // p_i = pi[i] pp_i.from(pi, p_i); // pp_i = pi[pi[i]] if(DBIDUtil.equal(pp_i, id) && lambda.doubleValue(it) >= lambda.doubleValue(p_i)) { pi.putDBID(it, id); } } }
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public static int levenshteinDistance(String o1, String o2) { // Let o1 be the shorter one: if(o1.length() > o2.length()) { return levenshteinDistance(o2, o1); } final int l1 = o1.length(), l2 = o2.length(); // Exploit that Java caches the hash code of strings: if(l1 == l2 && o1.hashCode() == o2.hashCode() && o1.equals(o2)) { return 0; } // Determine prefix and postfix lengths: final int prefix = prefixLen(o1, o2); if(prefix == l1 || prefix == l2) { return Math.abs(l1 - l2); } final int postfix = postfixLen(o1, o2, prefix); return // Prefix and postfix are a complete object: (prefix + postfix == l1 || prefix + postfix == l2) ? Math.abs(l1 - l2) : // // Exactly one char difference optimization: (l1 == l2 && prefix + postfix + 1 == l1) ? 1 : // // Default case, compute levenshteinDistance(o1, o2, prefix, postfix); }
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private static int prefixLen(String o1, String o2) { final int l1 = o1.length(), l2 = o2.length(), l = l1 < l2 ? l1 : l2; int prefix = 0; while(prefix < l && (o1.charAt(prefix) == o2.charAt(prefix))) { prefix++; } return prefix; }
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private static int postfixLen(String o1, String o2, int prefix) { int postfix = 0; int p1 = o1.length(), p2 = o2.length(); while(p1 > prefix && p2 > prefix && (o1.charAt(--p1) == o2.charAt(--p2))) { ++postfix; } return postfix; }
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public static int levenshteinDistance(String o1, String o2, int prefix, int postfix) { final int l1 = o1.length(), l2 = o2.length(); // Buffer, interleaved. Even and odd values are our rows. int[] buf = new int[(l2 + 1 - (prefix + postfix)) << 1]; // Initial "row", on even positions for(int j = 0; j < buf.length; j += 2) { buf[j] = j >> 1; } int inter = 1; // Interleaving offset for(int i = prefix, e1 = l1 - postfix; i < e1; i++, inter ^= 1) { final char chr = o1.charAt(i); buf[inter] = i + 1 - prefix; // First entry for(int c = 2 + inter, p = 3 - inter, j = prefix; c < buf.length; c += 2, p += 2) { buf[c] = min(buf[p] + 1, buf[c - 2] + 1, buf[p - 2] + ((chr == o2.charAt(j++)) ? 0 : 1)); } } return buf[buf.length - 2 + (inter ^ 1)]; }
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private static int nextSep(String str, int start) { int next = str.indexOf(',', start); return next == -1 ? str.length() : next; }
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public static double[][] computeWeightMatrix(final int quanth, final int quants, final int quantb) { final int dim = quanth * quants * quantb; final DoubleWrapper tmp = new DoubleWrapper(); // To return cosine assert (dim > 0); final double[][] m = new double[dim][dim]; for(int x = 0; x < dim; x++) { final int hx = x / (quantb * quants); final int sx = (x / quantb) % quants; final int bx = x % quantb; for(int y = x; y < dim; y++) { final int hy = y / (quantb * quants); final int sy = (y / quantb) % quants; final int by = y % quantb; final double shx = FastMath.sinAndCos((hx + .5) / quanth * MathUtil.TWOPI, tmp); final double chx = tmp.value; final double shy = FastMath.sinAndCos((hy + .5) / quanth * MathUtil.TWOPI, tmp); final double chy = tmp.value; final double cos = chx * (sx + .5) / quants - chy * (sy + .5) / quants; final double sin = shx * (sx + .5) / quants - shy * (sy + .5) / quants; final double db = (bx - by) / (double) quantb; final double val = 1. - FastMath.sqrt((db * db + sin * sin + cos * cos) / 5); m[x][y] = m[y][x] = val; } } return m; }
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public static double[] plus(final double[] v1, final double[] v2) { assert v1.length == v2.length : ERR_VEC_DIMENSIONS; final double[] result = new double[v1.length]; for(int i = 0; i < result.length; i++) { result[i] = v1[i] + v2[i]; } return result; }
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public static double[] plusEquals(final double[] v1, final double[] v2) { assert v1.length == v2.length : ERR_VEC_DIMENSIONS; for(int i = 0; i < v1.length; i++) { v1[i] += v2[i]; } return v1; }
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public static double[] plus(final double[] v1, final double s1) { final double[] result = new double[v1.length]; for(int i = 0; i < result.length; i++) { result[i] = v1[i] + s1; } return result; }
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public static double[] plusEquals(final double[] v1, final double s1) { for(int i = 0; i < v1.length; i++) { v1[i] += s1; } return v1; }
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public static double[] minus(final double[] v1, final double[] v2) { assert v1.length == v2.length : ERR_VEC_DIMENSIONS; final double[] sub = new double[v1.length]; for(int i = 0; i < v1.length; i++) { sub[i] = v1[i] - v2[i]; } return sub; }
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public static double[] minusEquals(final double[] v1, final double[] v2) { assert v1.length == v2.length : ERR_VEC_DIMENSIONS; for(int i = 0; i < v1.length; i++) { v1[i] -= v2[i]; } return v1; }
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public static double[] minus(final double[] v1, final double s1) { final double[] result = new double[v1.length]; for(int i = 0; i < v1.length; i++) { result[i] = v1[i] - s1; } return result; }
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public static double[] minusEquals(final double[] v1, final double s1) { for(int i = 0; i < v1.length; i++) { v1[i] -= s1; } return v1; }
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public static double sum(final double[] v1) { double acc = 0.; for(int row = 0; row < v1.length; row++) { acc += v1[row]; } return acc; }
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public static int argmax(double[] v) { assert (v.length > 0); int maxIndex = 0; double currentMax = v[0]; for(int i = 1; i < v.length; i++) { final double x = v[i]; if(x > currentMax) { maxIndex = i; currentMax = x; } } return maxIndex; }
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public static double[] normalize(final double[] v1) { final double norm = 1. / euclideanLength(v1); double[] re = new double[v1.length]; if(norm < Double.POSITIVE_INFINITY) { for(int row = 0; row < v1.length; row++) { re[row] = v1[row] * norm; } } return re; }
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public static double[] normalizeEquals(final double[] v1) { final double norm = 1. / euclideanLength(v1); if(norm < Double.POSITIVE_INFINITY) { for(int row = 0; row < v1.length; row++) { v1[row] *= norm; } } return v1; }
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public static void clear(final double[][] m) { for(int i = 0; i < m.length; i++) { Arrays.fill(m[i], 0.0); } }
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public static double[] rotate90Equals(final double[] v1) { assert v1.length == 2 : "rotate90Equals is only valid for 2d vectors."; final double temp = v1[0]; v1[0] = v1[1]; v1[1] = -temp; return v1; }
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public static double[][] diagonal(final double[] v1) { final int dim = v1.length; final double[][] result = new double[dim][dim]; for(int i = 0; i < dim; i++) { result[i][i] = v1[i]; } return result; }
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public static double[][] copy(final double[][] m1) { final int rowdim = m1.length, coldim = getColumnDimensionality(m1); final double[][] X = new double[rowdim][coldim]; for(int i = 0; i < rowdim; i++) { System.arraycopy(m1[i], 0, X[i], 0, coldim); } return X; }
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public static double[] getCol(double[][] m1, int col) { double[] ret = new double[m1.length]; for(int i = 0; i < ret.length; i++) { ret[i] = m1[i][col]; } return ret; }
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public static double[] getDiagonal(final double[][] m1) { final int dim = Math.min(getColumnDimensionality(m1), m1.length); final double[] diagonal = new double[dim]; for(int i = 0; i < dim; i++) { diagonal[i] = m1[i][i]; } return diagonal; }
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public static void normalizeColumns(final double[][] m1) { final int columndimension = getColumnDimensionality(m1); for(int col = 0; col < columndimension; col++) { double norm = 0.0; for(int row = 0; row < m1.length; row++) { final double v = m1[row][col]; norm += v * v; } if(norm > 0) { norm = FastMath.sqrt(norm); for(int row = 0; row < m1.length; row++) { m1[row][col] /= norm; } } } }
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public static double[][] appendColumns(final double[][] m1, final double[][] m2) { final int columndimension = getColumnDimensionality(m1); final int ccolumndimension = getColumnDimensionality(m2); assert m1.length == m2.length : "m.getRowDimension() != column.getRowDimension()"; final int rcolumndimension = columndimension + ccolumndimension; final double[][] result = new double[m1.length][rcolumndimension]; for(int i = 0; i < rcolumndimension; i++) { // FIXME: optimize - excess copying! if(i < columndimension) { setCol(result, i, getCol(m1, i)); } else { setCol(result, i, getCol(m2, i - columndimension)); } } return result; }
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public static double[][] orthonormalize(final double[][] m1) { final int columndimension = getColumnDimensionality(m1); final double[][] v = copy(m1); // FIXME: optimize - excess copying! for(int i = 1; i < columndimension; i++) { final double[] u_i = getCol(m1, i); final double[] sum = new double[m1.length]; for(int j = 0; j < i; j++) { final double[] v_j = getCol(v, j); final double scalar = scalarProduct(u_i, v_j) / scalarProduct(v_j, v_j); plusEquals(sum, times(v_j, scalar)); } final double[] v_i = minus(u_i, sum); setCol(v, i, v_i); } normalizeColumns(v); return v; }
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public static double[][] inverse(double[][] A) { final int rows = A.length, cols = A[0].length; return rows == cols // ? (new LUDecomposition(A, rows, cols)).inverse() // : (new QRDecomposition(A, rows, cols)).inverse(); }
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public static boolean almostEquals(final double[] m1, final double[] m2, final double maxdelta) { if(m1 == m2) { return true; } if(m1 == null || m2 == null) { return false; } final int rowdim = m1.length; if(rowdim != m2.length) { return false; } for(int i = 0; i < rowdim; i++) { if(Math.abs(m1[i] - m2[i]) > maxdelta) { return false; } } return true; }
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public static double angle(double[] v1, double[] v2) { final int mindim = (v1.length <= v2.length) ? v1.length : v2.length; // Essentially, we want to compute this: // v1.transposeTimes(v2) / (v1.euclideanLength() * v2.euclideanLength()); // We can just compute all three in parallel. double s = 0, e1 = 0, e2 = 0; for(int k = 0; k < mindim; k++) { final double r1 = v1[k], r2 = v2[k]; s += r1 * r2; e1 += r1 * r1; e2 += r2 * r2; } for(int k = mindim; k < v1.length; k++) { final double r1 = v1[k]; e1 += r1 * r1; } for(int k = mindim; k < v2.length; k++) { final double r2 = v2[k]; e2 += r2 * r2; } double a = FastMath.sqrt((s / e1) * (s / e2)); return (a < 1.) ? a : 1.; }
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protected void updateFromSelection() { DBIDSelection sel = context.getSelection(); if(sel != null) { this.dbids = DBIDUtil.newArray(sel.getSelectedIds()); this.dbids.sort(); } else { this.dbids = DBIDUtil.newArray(); } }
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public static DataStoreEvent insertionEvent(DBIDs inserts) { return new DataStoreEvent(inserts, DBIDUtil.EMPTYDBIDS, DBIDUtil.EMPTYDBIDS); }
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public static DataStoreEvent removalEvent(DBIDs removals) { return new DataStoreEvent(DBIDUtil.EMPTYDBIDS, removals, DBIDUtil.EMPTYDBIDS); }
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public static DataStoreEvent updateEvent(DBIDs updates) { return new DataStoreEvent(DBIDUtil.EMPTYDBIDS, DBIDUtil.EMPTYDBIDS, updates); }
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private Visualization instantiateVisualization(VisualizationTask task) { try { Visualization v = task.getFactory().makeVisualization(context, task, this, width, height, item.proj); if(task.has(RenderFlag.NO_EXPORT)) { v.getLayer().setAttribute(NO_EXPORT_ATTRIBUTE, NO_EXPORT_ATTRIBUTE); } return v; } catch(Exception e) { if(LOG.isDebugging()) { LOG.warning("Visualizer " + task.getFactory().getClass().getName() + " failed.", e); } else { LOG.warning("Visualizer " + task.getFactory().getClass().getName() + " failed - enable debugging to see details: " + e.toString()); } } return null; }
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public void destroy() { context.removeVisualizationListener(this); context.removeResultListener(this); for(Entry<VisualizationTask, Visualization> v : taskmap.entrySet()) { Visualization vis = v.getValue(); if(vis != null) { vis.destroy(); } } taskmap.clear(); }
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private void lazyRefresh() { Runnable pr = new Runnable() { @Override public void run() { if(pendingRefresh.compareAndSet(this, null)) { refresh(); } } }; pendingRefresh.set(pr); scheduleUpdate(pr); }
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public boolean nextLine() throws IOException { while(reader.readLine(buf.delete(0, buf.length()))) { ++lineNumber; if(lengthWithoutLinefeed(buf) > 0) { return true; } } return false; }
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