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elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/VoronoiDraw.java
VoronoiDraw.drawFakeVoronoi
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; }
java
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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Fake Voronoi diagram. For two means only @param proj Projection @param means Mean vectors @return SVG path
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/VoronoiDraw.java#L150-L170
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/pairsegments/SegmentsStylingPolicy.java
SegmentsStylingPolicy.select
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); } } }
java
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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Adds or removes the given segment to the selection. Depending on the clustering and cluster selected and the addToSelection option given, the current selection will be modified. This method is called by clicking on a segment and ring and the CTRL-button status. Adding selections does only work on the same clustering and cluster, else a new selection will be added. @param segment the selected element representing a segment ring (specific clustering) @param addToSelection flag for adding segment to current selection
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/pairsegments/SegmentsStylingPolicy.java#L191-L234
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/pairsegments/SegmentsStylingPolicy.java
SegmentsStylingPolicy.deselectSegment
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()); } } }
java
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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Deselect a segment @param segment Segment to deselect
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/pairsegments/SegmentsStylingPolicy.java#L250-L277
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/pairsegments/SegmentsStylingPolicy.java
SegmentsStylingPolicy.selectSegment
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()); } } } }
java
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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Select a segment @param segment Segment to select
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/pairsegments/SegmentsStylingPolicy.java#L284-L300
train
elki-project/elki
elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/application/internal/CheckParameterizables.java
CheckParameterizables.checkSupertypes
private boolean checkSupertypes(Class<?> cls) { for(Class<?> c : knownParameterizables) { if(c.isAssignableFrom(cls)) { return true; } } return false; }
java
private boolean checkSupertypes(Class<?> cls) { for(Class<?> c : knownParameterizables) { if(c.isAssignableFrom(cls)) { return true; } } return false; }
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Check all supertypes of a class. @param cls Class to check. @return {@code true} when at least one supertype is a known parameterizable type.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/application/internal/CheckParameterizables.java#L158-L165
train
elki-project/elki
elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/application/internal/CheckParameterizables.java
CheckParameterizables.checkV3Parameterization
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; }
java
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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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/application/internal/CheckParameterizables.java#L180-L201
train
elki-project/elki
elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/application/internal/CheckParameterizables.java
CheckParameterizables.checkDefaultConstructor
private State checkDefaultConstructor(Class<?> cls, State state) throws NoClassDefFoundError { try { cls.getConstructor(); return State.DEFAULT_INSTANTIABLE; } catch(Exception e) { // do nothing. } return state; }
java
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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Check for a default constructor.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/application/internal/CheckParameterizables.java#L204-L213
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/LogGammaDistribution.java
LogGammaDistribution.logpdf
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); }
java
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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LogGamma distribution logPDF @param x query value @param k Alpha @param theta Theta = 1 / Beta @return log probability density
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/distribution/LogGammaDistribution.java#L205-L212
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/style/marker/PrettyMarkers.java
PrettyMarkers.plotGray
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); }
java
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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Plot a replacement marker when an object is to be plotted as "disabled", usually gray. @param plot Plot to draw to @param parent Parent element @param x X position @param y Y position @param size Size
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/style/marker/PrettyMarkers.java#L251-L255
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/style/marker/PrettyMarkers.java
PrettyMarkers.plotUncolored
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); }
java
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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Plot a replacement marker when no color is set; usually black @param plot Plot to draw to @param parent Parent element @param x X position @param y Y position @param size Size
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/style/marker/PrettyMarkers.java#L266-L270
train
elki-project/elki
elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java
ConfusionMatrix.truePositives
public int truePositives() { int tp = 0; for(int i = 0; i < confusion.length; i++) { tp += truePositives(i); } return tp; }
java
public int truePositives() { int tp = 0; for(int i = 0; i < confusion.length; i++) { tp += truePositives(i); } return tp; }
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The number of correctly classified instances. @return the number of correctly classified instances
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java#L151-L157
train
elki-project/elki
elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java
ConfusionMatrix.trueNegatives
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; }
java
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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The number of true negatives of the specified class. @param classindex the index of the class to retrieve the true negatives for @return the number of true negatives of the specified class
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java#L192-L202
train
elki-project/elki
elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java
ConfusionMatrix.falsePositives
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; }
java
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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The false positives for the specified class. @param classindex the index of the class to retrieve the false positives for @return the false positives for the specified class
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java#L212-L220
train
elki-project/elki
elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java
ConfusionMatrix.falseNegatives
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; }
java
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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The false negatives for the specified class. @param classindex the index of the class to retrieve the false negatives for @return the false negatives for the specified class
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java#L230-L238
train
elki-project/elki
elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java
ConfusionMatrix.totalInstances
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; }
java
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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The total number of instances covered by this confusion matrix. @return the total number of instances covered by this confusion matrix
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-classification/src/main/java/de/lmu/ifi/dbs/elki/evaluation/classification/ConfusionMatrix.java#L246-L254
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/DistanceCorrelationDependenceMeasure.java
DistanceCorrelationDependenceMeasure.computeDistances
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; }
java
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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Compute the double-centered delta matrix. @param adapter Data adapter @param data Input data @return Double-centered delta matrix.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/DistanceCorrelationDependenceMeasure.java#L121-L133
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/DistanceCorrelationDependenceMeasure.java
DistanceCorrelationDependenceMeasure.doubleCenterMatrix
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; } } }
java
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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Computes the distance variance matrix of one axis. @param dMatrix distance matrix of the axis @param size Dimensionality
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/statistics/dependence/DistanceCorrelationDependenceMeasure.java#L141-L167
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java
ParameterizationFunction.determineAlphaMinMax
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); }
java
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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Determines the alpha values where this function has a minumum and maximum value in the given interval. @param interval the hyper bounding box defining the interval @return he alpha values where this function has a minumum and maximum value in the given interval
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java#L118-L154
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java
ParameterizationFunction.extremumType
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" }
java
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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Returns the type of the extremum at the specified alpha values. @param n the index until the alpha values are computed @param alpha_extreme the already computed alpha values @param interval the hyper bounding box defining the interval in which the extremum occurs @return the type of the extremum at the specified alpha_values
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java#L165-L228
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java
ParameterizationFunction.determineAlphaMin
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; } } }
java
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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Determines the n-th alpha value where this function has a minimum in the specified interval. @param n the index of the alpha value to be determined @param alpha_min the already computed alpha values @param interval the hyper bounding box defining the interval @return the n-th alpha value where this function has a minimum in the specified interval
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java#L240-L291
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java
ParameterizationFunction.sinusProduct
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; }
java
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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Computes the product of all sinus values of the specified angles from start to end index. @param start the index to start @param end the index to end @param alpha the array of angles @return the product of all sinus values of the specified angles from start to end index
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java#L428-L434
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java
ParameterizationFunction.determineGlobalExtremum
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(); }
java
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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Determines the global extremum of this parameterization function.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java#L439-L449
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java
ParameterizationFunction.determineGlobalExtremumType
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); } }
java
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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Determines the type of the global extremum.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/correlation/cash/ParameterizationFunction.java#L454-L481
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/panels/ParameterTabPanel.java
ParameterTabPanel.setParameters
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(); }
java
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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Do the actual setParameters invocation. @param config Parameterization
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/panels/ParameterTabPanel.java#L191-L212
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/panels/ParameterTabPanel.java
ParameterTabPanel.reportErrors
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(); }
java
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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Report errors in a single error log record. @param config Parameterization
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/panels/ParameterTabPanel.java#L228-L240
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/panels/ParameterTabPanel.java
ParameterTabPanel.canRun
public boolean canRun() { Status status = getStatus(); return Status.STATUS_READY.equals(status) || Status.STATUS_COMPLETE.equals(status); }
java
public boolean canRun() { Status status = getStatus(); return Status.STATUS_READY.equals(status) || Status.STATUS_COMPLETE.equals(status); }
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Test if this tab is ready-to-run @return can-run status
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/panels/ParameterTabPanel.java#L294-L297
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.lineTo
public SVGPath lineTo(double x, double y) { return append(PATH_LINE_TO).append(x).append(y); }
java
public SVGPath lineTo(double x, double y) { return append(PATH_LINE_TO).append(x).append(y); }
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Draw a line to the given coordinates. @param x new coordinates @param y new coordinates @return path object, for compact syntax.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L229-L231
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.relativeLineTo
public SVGPath relativeLineTo(double x, double y) { return append(PATH_LINE_TO_RELATIVE).append(x).append(y); }
java
public SVGPath relativeLineTo(double x, double y) { return append(PATH_LINE_TO_RELATIVE).append(x).append(y); }
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Draw a line to the given relative coordinates. @param x relative coordinates @param y relative coordinates @return path object, for compact syntax.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L250-L252
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.moveTo
public SVGPath moveTo(double x, double y) { return append(PATH_MOVE).append(x).append(y); }
java
public SVGPath moveTo(double x, double y) { return append(PATH_MOVE).append(x).append(y); }
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Move to the given coordinates. @param x new coordinates @param y new coordinates @return path object, for compact syntax.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L311-L313
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.relativeMoveTo
public SVGPath relativeMoveTo(double x, double y) { return append(PATH_MOVE_RELATIVE).append(x).append(y); }
java
public SVGPath relativeMoveTo(double x, double y) { return append(PATH_MOVE_RELATIVE).append(x).append(y); }
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Move to the given relative coordinates. @param x new coordinates @param y new coordinates @return path object, for compact syntax.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L332-L334
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.smoothQuadTo
public SVGPath smoothQuadTo(double x, double y) { return append(PATH_SMOOTH_QUAD_TO).append(x).append(y); }
java
public SVGPath smoothQuadTo(double x, double y) { return append(PATH_SMOOTH_QUAD_TO).append(x).append(y); }
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Smooth quadratic Bezier line to the given coordinates. @param x new coordinates @param y new coordinates @return path object, for compact syntax.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L503-L505
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.relativeSmoothQuadTo
public SVGPath relativeSmoothQuadTo(double x, double y) { return append(PATH_SMOOTH_QUAD_TO_RELATIVE).append(x).append(y); }
java
public SVGPath relativeSmoothQuadTo(double x, double y) { return append(PATH_SMOOTH_QUAD_TO_RELATIVE).append(x).append(y); }
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Smooth quadratic Bezier line to the given relative coordinates. @param x new coordinates @param y new coordinates @return path object, for compact syntax.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L524-L526
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.append
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; }
java
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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Append an action to the current path. @param action Current action
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L627-L634
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.append
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; }
java
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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Append a value to the current path. @param x coordinate.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L641-L656
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.close
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; }
java
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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Close the path. @return path object, for compact syntax.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L663-L670
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java
SVGPath.makeElement
public Element makeElement(SVGPlot plot) { Element elem = plot.svgElement(SVGConstants.SVG_PATH_TAG); elem.setAttribute(SVGConstants.SVG_D_ATTRIBUTE, buf.toString()); return elem; }
java
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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Turn the path buffer into an SVG element. @param plot Plot context (= element factory) @return SVG Element
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/svg/SVGPath.java#L678-L682
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/MultiStepGUI.java
MultiStepGUI.setParameters
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(); }
java
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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Set the parameters. @param config Parameterization
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/MultiStepGUI.java#L203-L216
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/MultiStepGUI.java
MultiStepGUI.serializeParameters
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(); }
java
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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Get the serialized parameters @return Serialized parameters
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/MultiStepGUI.java#L223-L231
train
elki-project/elki
elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/MultiStepGUI.java
MultiStepGUI.main
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); } } }); }
java
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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Main method that just spawns the UI. @param args command line parameters
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-gui-minigui/src/main/java/de/lmu/ifi/dbs/elki/gui/multistep/MultiStepGUI.java#L244-L269
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/statistics/EvaluateRetrievalPerformance.java
EvaluateRetrievalPerformance.match
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); }
java
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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Test whether two relation agree. @param ref Reference object @param test Test object @return {@code true} if the objects match
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/statistics/EvaluateRetrievalPerformance.java#L189-L218
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/statistics/EvaluateRetrievalPerformance.java
EvaluateRetrievalPerformance.findMatches
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); } } }
java
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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Find all matching objects. @param posn Output set. @param lrelation Label relation @param label Query object label
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/statistics/EvaluateRetrievalPerformance.java#L227-L234
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/statistics/EvaluateRetrievalPerformance.java
EvaluateRetrievalPerformance.computeDistances
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(); }
java
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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Compute the distances to the neighbor objects. @param nlist Neighbor list (output) @param query Query object @param distQuery Distance function @param relation Data relation
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/algorithm/statistics/EvaluateRetrievalPerformance.java#L244-L258
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/result/textwriter/MultipleFilesOutput.java
MultipleFilesOutput.newStream
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; }
java
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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Open a new stream of the given name @param name file name (which will be appended to the base name) @return stream object for the given name @throws IOException
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/result/textwriter/MultipleFilesOutput.java#L91-L112
train
elki-project/elki
elki-index/src/main/java/de/lmu/ifi/dbs/elki/index/PagedIndexFactory.java
PagedIndexFactory.makePageFile
protected <N extends Page & Externalizable> PageFile<N> makePageFile(Class<N> cls) { @SuppressWarnings("unchecked") final PageFileFactory<N> castFactory = (PageFileFactory<N>) pageFileFactory; return castFactory.newPageFile(cls); }
java
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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Make the page file for this index. @param <N> page type @param cls Class information @return Page file
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-index/src/main/java/de/lmu/ifi/dbs/elki/index/PagedIndexFactory.java#L71-L75
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/scatterplot/selection/DistanceFunctionVisualization.java
DistanceFunctionVisualization.isAngularDistance
public static boolean isAngularDistance(AbstractMaterializeKNNPreprocessor<?> kNN) { DistanceFunction<?> distanceFunction = kNN.getDistanceQuery().getDistanceFunction(); return CosineDistanceFunction.class.isInstance(distanceFunction) // || ArcCosineDistanceFunction.class.isInstance(distanceFunction); }
java
public static boolean isAngularDistance(AbstractMaterializeKNNPreprocessor<?> kNN) { DistanceFunction<?> distanceFunction = kNN.getDistanceQuery().getDistanceFunction(); return CosineDistanceFunction.class.isInstance(distanceFunction) // || ArcCosineDistanceFunction.class.isInstance(distanceFunction); }
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Test whether the given preprocessor used an angular distance function @param kNN kNN preprocessor @return true when angular
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/scatterplot/selection/DistanceFunctionVisualization.java#L131-L135
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/scatterplot/selection/DistanceFunctionVisualization.java
DistanceFunctionVisualization.drawCosine
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); } }
java
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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Visualizes Cosine and ArcCosine distance functions @param svgp SVG Plot @param proj Visualization projection @param mid mean vector @param angle Opening angle in radians @return path element
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/visualizers/scatterplot/selection/DistanceFunctionVisualization.java#L146-L200
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java
RandomProjectedNeighborsAndDensities.splitupNoSort
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); } }
java
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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Recursively splits entire point set until the set is below a threshold @param ind points that are in the current set @param begin Interval begin in the ind array @param end Interval end in the ind array @param dim depth of projection (how many times point set has been split already) @param rand Random generator
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java#L246-L276
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java
RandomProjectedNeighborsAndDensities.splitRandomly
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; }
java
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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Split the data set randomly. @param ind Object index @param begin Interval begin @param end Interval end @param tpro Projection @param rand Random generator @return Splitting point
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java#L288-L315
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java
RandomProjectedNeighborsAndDensities.splitByDistance
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; }
java
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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Split the data set by distances. @param ind Object index @param begin Interval begin @param end Interval end @param tpro Projection @param rand Random generator @return Splitting point
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java#L327-L363
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java
RandomProjectedNeighborsAndDensities.getNeighs
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; }
java
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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Compute list of neighbors for each point from sets resulting from projection @return list of neighbors for each point
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java#L371-L399
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java
RandomProjectedNeighborsAndDensities.computeAverageDistInSet
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; }
java
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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Compute for each point a density estimate as inverse of average distance to a point in a projected set @return for each point average distance to point in a set
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/index/preprocessed/fastoptics/RandomProjectedNeighborsAndDensities.java#L407-L442
train
elki-project/elki
elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java
Itemset.containedIn
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; }
java
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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Test whether the itemset is contained in a bit vector. @param bv Bit vector @return {@code true} when the itemset is contained in this vector.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java#L65-L84
train
elki-project/elki
elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java
Itemset.toBitset
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; }
java
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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Get the items. @param i Itemset @param bits Output bitset (must be zeros) @return Output bitset
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java#L100-L105
train
elki-project/elki
elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java
Itemset.compareLexicographical
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; }
java
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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Robust compare using the iterators, lexicographical only! Note: This does NOT take length into account. @param o Other itemset. @return Comparison result.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java#L195-L209
train
elki-project/elki
elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java
Itemset.appendTo
public final StringBuilder appendTo(StringBuilder buf, VectorFieldTypeInformation<BitVector> meta) { appendItemsTo(buf, meta); return buf.append(": ").append(support); }
java
public final StringBuilder appendTo(StringBuilder buf, VectorFieldTypeInformation<BitVector> meta) { appendItemsTo(buf, meta); return buf.append(": ").append(support); }
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Append items and support to a string buffer. @param buf Buffer @param meta Relation metadata (for labels) @return String buffer for chaining.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java#L223-L226
train
elki-project/elki
elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java
Itemset.appendItemsTo
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; }
java
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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Only append the items to a string buffer. @param buf Buffer @param meta Relation metadata (for labels) @return String buffer for chaining.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-itemsets/src/main/java/de/lmu/ifi/dbs/elki/algorithm/itemsetmining/Itemset.java#L235-L255
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/weightfunctions/GaussWeight.java
GaussWeight.getWeight
@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); }
java
@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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Get Gaussian weight. stddev is not used, scaled using max.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/pca/weightfunctions/GaussWeight.java#L36-L44
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/persistent/OnDiskArrayPageFile.java
OnDiskArrayPageFile.writePage
@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); } } }
java
@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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Write page to disk. @param pageID page id @param page the page which has to be written to disk
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/persistent/OnDiskArrayPageFile.java#L144-L156
train
elki-project/elki
elki/src/main/java/de/lmu/ifi/dbs/elki/persistent/OnDiskArrayPageFile.java
OnDiskArrayPageFile.pageToByteArray
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); } }
java
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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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki/src/main/java/de/lmu/ifi/dbs/elki/persistent/OnDiskArrayPageFile.java#L213-L248
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/SinCosTable.java
SinCosTable.make
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); }
java
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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Make a table for the given number of steps. For step numbers divisible by 4, an optimized implementation will be used. @param steps Number of steps @return Table
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/SinCosTable.java#L295-L303
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/CLINK.java
CLINK.process
@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); }
java
@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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CLINK main loop, based on the SLINK main loop. @param id Current object @param ids All objects @param it Array iterator @param n Last object to process at this run @param pi Parent @param lambda Height @param m Distance
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/CLINK.java#L89-L94
train
elki-project/elki
elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/CLINK.java
CLINK.clinkstep8
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); } } }
java
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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Update hierarchy. @param id Current object @param it Iterator @param n Last object to process @param pi Parent data store @param lambda Height data store @param m Distance data store
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-clustering/src/main/java/de/lmu/ifi/dbs/elki/algorithm/clustering/hierarchical/CLINK.java#L195-L204
train
elki-project/elki
elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/strings/LevenshteinDistanceFunction.java
LevenshteinDistanceFunction.levenshteinDistance
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); }
java
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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Levenshtein distance for two strings. @param o1 First string @param o2 Second string @return Levenshtein distance
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/strings/LevenshteinDistanceFunction.java#L84-L106
train
elki-project/elki
elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/strings/LevenshteinDistanceFunction.java
LevenshteinDistanceFunction.prefixLen
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; }
java
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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Compute the length of the prefix. @param o1 First string @param o2 Second string @return Prefix length
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/strings/LevenshteinDistanceFunction.java#L115-L122
train
elki-project/elki
elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/strings/LevenshteinDistanceFunction.java
LevenshteinDistanceFunction.postfixLen
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; }
java
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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Compute the postfix length. @param o1 First object @param o2 Second object @param prefix Known prefix length @return Postfix length
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/strings/LevenshteinDistanceFunction.java#L132-L139
train
elki-project/elki
elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/strings/LevenshteinDistanceFunction.java
LevenshteinDistanceFunction.levenshteinDistance
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)]; }
java
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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Compute the Levenshtein distance, except for prefix and postfix. @param o1 First object @param o2 Second object @param prefix Prefix length @param postfix Postfix length @return Levenshtein distance
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/strings/LevenshteinDistanceFunction.java#L150-L167
train
elki-project/elki
elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/range/ParseIntRanges.java
ParseIntRanges.nextSep
private static int nextSep(String str, int start) { int next = str.indexOf(',', start); return next == -1 ? str.length() : next; }
java
private static int nextSep(String str, int start) { int next = str.indexOf(',', start); return next == -1 ? str.length() : next; }
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Find the next separator. TODO: allow other separators, too? @param str String @param start Starting position @return Next separator position, or end of string.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/datastructures/range/ParseIntRanges.java#L168-L171
train
elki-project/elki
elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/colorhistogram/HSBHistogramQuadraticDistanceFunction.java
HSBHistogramQuadraticDistanceFunction.computeWeightMatrix
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; }
java
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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Compute the weight matrix for HSB similarity. @param quanth H bins @param quants S bins @param quantb B bins @return Weight matrix
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-distance/src/main/java/de/lmu/ifi/dbs/elki/distance/distancefunction/colorhistogram/HSBHistogramQuadraticDistanceFunction.java#L74-L100
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.plus
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; }
java
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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Computes component-wise v1 + v2 for vectors. @param v1 first vector @param v2 second vector @return the sum v1 + v2
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L138-L145
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.plusEquals
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; }
java
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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Computes component-wise v1 = v1 + v2, overwriting the vector v1. @param v1 first vector (overwritten) @param v2 second vector @return v1 = v1 + v2
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L207-L213
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.plus
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; }
java
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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Computes component-wise v1 + s1. @param v1 vector to add to @param s1 constant value to add @return v1 + s1
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L274-L280
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.plusEquals
public static double[] plusEquals(final double[] v1, final double s1) { for(int i = 0; i < v1.length; i++) { v1[i] += s1; } return v1; }
java
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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Computes component-wise v1 = v1 + s1, overwriting the vector v1. @param v1 vector to add to (overwritten) @param s1 constant value to add @return Modified vector
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L290-L295
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.minus
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; }
java
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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Computes component-wise v1 - v2. @param v1 first vector @param v2 the vector to be subtracted from this vector @return v1 - v2
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L304-L311
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.minusEquals
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; }
java
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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Computes component-wise v1 = v1 - v2, overwriting the vector v1. @param v1 vector @param v2 another vector @return v1 = v1 - v2
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L373-L379
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.minus
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; }
java
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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Subtract component-wise v1 - s1. @param v1 original vector @param s1 Value to subtract @return v1 - s1
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L440-L446
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.minusEquals
public static double[] minusEquals(final double[] v1, final double s1) { for(int i = 0; i < v1.length; i++) { v1[i] -= s1; } return v1; }
java
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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Subtract component-wise in-place v1 = v1 - s1, overwriting the vector v1. @param v1 original vector @param s1 Value to subtract @return v1 = v1 - s1
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L456-L461
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.sum
public static double sum(final double[] v1) { double acc = 0.; for(int row = 0; row < v1.length; row++) { acc += v1[row]; } return acc; }
java
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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Sum of the vector components. @param v1 vector @return sum of this vector
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L653-L659
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.argmax
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; }
java
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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Find the maximum value. @param v Vector @return Position of maximum
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L692-L704
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.normalize
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; }
java
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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Normalizes v1 to the length of 1.0. @param v1 vector @return normalized copy of v1
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L712-L721
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.normalizeEquals
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; }
java
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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Normalizes v1 to the length of 1.0 in place. @param v1 vector (overwritten) @return normalized v1
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L729-L737
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.clear
public static void clear(final double[][] m) { for(int i = 0; i < m.length; i++) { Arrays.fill(m[i], 0.0); } }
java
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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Reset the matrix to 0. @param m Matrix
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L774-L778
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.rotate90Equals
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; }
java
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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Rotate the two-dimensional vector by 90 degrees. @param v1 first vector @return modified v1, rotated by 90 degrees
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L786-L792
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.diagonal
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; }
java
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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Returns a quadratic matrix consisting of zeros and of the given values on the diagonal. @param v1 the values on the diagonal @return the resulting matrix
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L843-L850
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.copy
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; }
java
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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Make a deep copy of a matrix. @param m1 Input matrix @return a new matrix containing the same values as this matrix
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L858-L865
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.getCol
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; }
java
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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Get a column from a matrix as vector. @param m1 Matrix to extract the column from @param col Column number @return Column
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L1091-L1097
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.getDiagonal
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; }
java
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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getDiagonal returns array of diagonal-elements. @param m1 Input matrix @return values on the diagonal of the Matrix
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L1555-L1562
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.normalizeColumns
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; } } } }
java
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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Normalizes the columns of this matrix to length of 1.0. Note: if a column has length 0, it will remain unmodified. @param m1 Input matrix
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L1571-L1586
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.appendColumns
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; }
java
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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Returns a matrix which consists of this matrix and the specified columns. @param m1 Input matrix @param m2 the columns to be appended @return the new matrix with the appended columns
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L1595-L1612
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.orthonormalize
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; }
java
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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Returns an orthonormalization of this matrix. @param m1 Input matrix @return the orthonormalized matrix
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L1620-L1639
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.inverse
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(); }
java
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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Matrix inverse or pseudoinverse @param A matrix to invert @return inverse(A) if A is square, pseudoinverse otherwise.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L1673-L1678
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.almostEquals
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; }
java
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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Compare two matrices with a delta parameter to take numerical errors into account. @param m1 Input matrix @param m2 other matrix to compare with @param maxdelta maximum delta allowed @return true if delta smaller than maximum
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L1771-L1788
train
elki-project/elki
elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java
VMath.angle
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.; }
java
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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Compute the cosine of the angle between two vectors, where the smaller angle between those vectors is viewed. @param v1 first vector @param v2 second vector @return cosine of the smaller angle
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-math/src/main/java/de/lmu/ifi/dbs/elki/math/linearalgebra/VMath.java#L1830-L1852
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/gui/SelectionTableWindow.java
SelectionTableWindow.updateFromSelection
protected void updateFromSelection() { DBIDSelection sel = context.getSelection(); if(sel != null) { this.dbids = DBIDUtil.newArray(sel.getSelectedIds()); this.dbids.sort(); } else { this.dbids = DBIDUtil.newArray(); } }
java
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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Update our selection
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/gui/SelectionTableWindow.java#L188-L197
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/DataStoreEvent.java
DataStoreEvent.insertionEvent
public static DataStoreEvent insertionEvent(DBIDs inserts) { return new DataStoreEvent(inserts, DBIDUtil.EMPTYDBIDS, DBIDUtil.EMPTYDBIDS); }
java
public static DataStoreEvent insertionEvent(DBIDs inserts) { return new DataStoreEvent(inserts, DBIDUtil.EMPTYDBIDS, DBIDUtil.EMPTYDBIDS); }
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Insertion event. @param inserts Insertions @return Event
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/DataStoreEvent.java#L73-L75
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/DataStoreEvent.java
DataStoreEvent.removalEvent
public static DataStoreEvent removalEvent(DBIDs removals) { return new DataStoreEvent(DBIDUtil.EMPTYDBIDS, removals, DBIDUtil.EMPTYDBIDS); }
java
public static DataStoreEvent removalEvent(DBIDs removals) { return new DataStoreEvent(DBIDUtil.EMPTYDBIDS, removals, DBIDUtil.EMPTYDBIDS); }
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Removal event. @param removals Removal @return Event
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/DataStoreEvent.java#L83-L85
train
elki-project/elki
elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/DataStoreEvent.java
DataStoreEvent.updateEvent
public static DataStoreEvent updateEvent(DBIDs updates) { return new DataStoreEvent(DBIDUtil.EMPTYDBIDS, DBIDUtil.EMPTYDBIDS, updates); }
java
public static DataStoreEvent updateEvent(DBIDs updates) { return new DataStoreEvent(DBIDUtil.EMPTYDBIDS, DBIDUtil.EMPTYDBIDS, updates); }
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Update event. @param updates Updates @return Event
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-dbids/src/main/java/de/lmu/ifi/dbs/elki/database/datastore/DataStoreEvent.java#L93-L95
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/gui/detail/DetailView.java
DetailView.instantiateVisualization
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; }
java
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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Instantiate a visualization. @param task Task to instantiate @return Visualization
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/gui/detail/DetailView.java#L226-L243
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/gui/detail/DetailView.java
DetailView.destroy
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(); }
java
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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Cleanup function. To remove listeners.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/gui/detail/DetailView.java#L248-L258
train
elki-project/elki
addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/gui/detail/DetailView.java
DetailView.lazyRefresh
private void lazyRefresh() { Runnable pr = new Runnable() { @Override public void run() { if(pendingRefresh.compareAndSet(this, null)) { refresh(); } } }; pendingRefresh.set(pr); scheduleUpdate(pr); }
java
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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Trigger a refresh.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/addons/batikvis/src/main/java/de/lmu/ifi/dbs/elki/visualization/gui/detail/DetailView.java#L288-L299
train
elki-project/elki
elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/BufferedLineReader.java
BufferedLineReader.nextLine
public boolean nextLine() throws IOException { while(reader.readLine(buf.delete(0, buf.length()))) { ++lineNumber; if(lengthWithoutLinefeed(buf) > 0) { return true; } } return false; }
java
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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Read the next line. @return {@code true} if another line was read successfully. @throws IOException on IO errors.
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b54673327e76198ecd4c8a2a901021f1a9174498
https://github.com/elki-project/elki/blob/b54673327e76198ecd4c8a2a901021f1a9174498/elki-core-util/src/main/java/de/lmu/ifi/dbs/elki/utilities/io/BufferedLineReader.java#L160-L168
train