Java tutorial
/* * Copyright (c) 2013, Cloudera, Inc. All Rights Reserved. * * Cloudera, Inc. licenses this file to you under the Apache License, * Version 2.0 (the "License"). You may not use this file except in * compliance with the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * This software is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR * CONDITIONS OF ANY KIND, either express or implied. See the License for * the specific language governing permissions and limitations under the * License. */ package com.cloudera.oryx.kmeans.computation.local; import com.cloudera.oryx.kmeans.common.WeightedRealVector; import com.cloudera.oryx.kmeans.computation.cluster.KSketchIndex; import org.apache.commons.math3.linear.RealVector; import java.util.List; import java.util.concurrent.Callable; public final class AssignmentRun implements Callable<List<WeightedRealVector>> { private final KSketchIndex index; //private final RandomGenerator random; private final int foldId; private final List<RealVector> vecs; public AssignmentRun(KSketchIndex index, int foldId, List<RealVector> vecs) { this.index = index; //this.random = random; this.foldId = foldId; this.vecs = vecs; } @Override public List<WeightedRealVector> call() { long[] cnts = new long[index.getPointCounts()[foldId]]; for (RealVector v : vecs) { cnts[index.getDistance(v, foldId, true).getClosestCenterId()]++; } return index.getWeightedVectorsForFold(foldId, cnts); } }