@Override public SparseDoubleFV concatenate(List<SparseDoubleFV> ins) { SparseDoubleArray [] insValues = new SparseDoubleArray[ins.size()]; for (int i=0; i<ins.size(); i++) insValues[i] = ins.get(i).values; SparseDoubleArray vals = values.concatenate(insValues); return new SparseDoubleFV(vals); }
@Override public SparseDoubleFV newInstance() { return new SparseDoubleFV(length()); } }
@Override public SparseDoubleFV concatenate(SparseDoubleFV... ins) { SparseDoubleArray [] insValues = new SparseDoubleArray[ins.length]; for (int i=0; i<ins.length; i++) insValues[i] = ins[i].values; SparseDoubleArray vals = values.concatenate(insValues); return new SparseDoubleFV(vals); }
@Override public SparseDoubleFV newInstance() { return new SparseDoubleFV(length()); } }
@Override public SparseDoubleFV concatenate(SparseDoubleFV... ins) { SparseDoubleArray [] insValues = new SparseDoubleArray[ins.length]; for (int i=0; i<ins.length; i++) insValues[i] = ins[i].values; SparseDoubleArray vals = values.concatenate(insValues); return new SparseDoubleFV(vals); }
@Override public SparseDoubleFV concatenate(List<SparseDoubleFV> ins) { SparseDoubleArray [] insValues = new SparseDoubleArray[ins.size()]; for (int i=0; i<ins.size(); i++) insValues[i] = ins.get(i).values; SparseDoubleArray vals = values.concatenate(insValues); return new SparseDoubleFV(vals); }
@Override public SparseDoubleFV aggregateVectors(List<? extends ArrayFeatureVector<DATATYPE>> features) { final SparseDoubleFV fv = new SparseDoubleFV(assigner.size()); for (final ArrayFeatureVector<DATATYPE> f : features) { final IndependentPair<int[], DISTANCE> a = assigner.assignWeighted(f.values); increment(fv, a); } return fv; }
@Override public SparseDoubleFV aggregateVectors(List<? extends ArrayFeatureVector<DATATYPE>> features) { final SparseDoubleFV fv = new SparseDoubleFV(assigner.size()); for (final ArrayFeatureVector<DATATYPE> f : features) { final IndependentPair<int[], DISTANCE> a = assigner.assignWeighted(f.values); increment(fv, a); } return fv; }
/** * Aggregate the given features into a vector. * * @param features * the features to aggregate * @return the aggregated vector */ public SparseDoubleFV aggregateVectorsRaw(List<DATATYPE> features) { final SparseDoubleFV fv = new SparseDoubleFV(assigner.size()); for (final DATATYPE f : features) { final IndependentPair<int[], DISTANCE> a = assigner.assignWeighted(f); increment(fv, a); } return fv; }
/** * Aggregate the given features into a vector. * * @param features * the features to aggregate * @return the aggregated vector */ public SparseDoubleFV aggregateVectorsRaw(List<DATATYPE> features) { final SparseDoubleFV fv = new SparseDoubleFV(assigner.size()); for (final DATATYPE f : features) { final IndependentPair<int[], DISTANCE> a = assigner.assignWeighted(f); increment(fv, a); } return fv; }
@Override public SparseDoubleFV aggregate(List<? extends LocalFeature<?, ? extends ArrayFeatureVector<DATATYPE>>> features) { final SparseDoubleFV fv = new SparseDoubleFV(assigner.size()); for (final LocalFeature<?, ? extends ArrayFeatureVector<DATATYPE>> f : features) { final IndependentPair<int[], DISTANCE> a = assigner.assignWeighted(f.getFeatureVector().values); increment(fv, a); } return fv; }
@Override public SparseDoubleFV aggregate(List<? extends LocalFeature<?, ? extends ArrayFeatureVector<DATATYPE>>> features) { final SparseDoubleFV fv = new SparseDoubleFV(assigner.size()); for (final LocalFeature<?, ? extends ArrayFeatureVector<DATATYPE>> f : features) { final IndependentPair<int[], DISTANCE> a = assigner.assignWeighted(f.getFeatureVector().values); increment(fv, a); } return fv; }