content: /**
   * Licensed to the Apache Software Foundation (ASF) under one or more
   * contributor license agreements.  See the NOTICE file distributed with
   * this work for additional information regarding copyright ownership.
   * The ASF 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
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License 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 org.apache.bigtop.datagenerators.samplers.samplers;
  
  import java.util.List;
  import java.util.Random;
  
  import org.apache.bigtop.datagenerators.samplers.SeedFactory;
  import org.apache.commons.lang3.tuple.Pair;
  
  import com.google.common.collect.ImmutableList;
  
  public class BoundedMultiModalGaussianSampler implements Sampler<Double>
  {
  	ImmutableList<Pair<Double, Double>> distributions;
  
  	double min;
  	double max;
  	Random rng;
  
  	public BoundedMultiModalGaussianSampler(List<Pair<Double, Double>> distributions, double min, double max, SeedFactory seedFactory)
  	{
  		rng = new Random(seedFactory.getNextSeed());
  		this.distributions = ImmutableList.copyOf(distributions);
  
  		this.min = min;
  		this.max = max;
  	}
  
  	public Double sample()
  	{
  		while(true)
  		{
  			int idx = rng.nextInt(distributions.size());
  
  			double mean = distributions.get(idx).getLeft();
  			double std = distributions.get(idx).getRight();
  
  			double value = mean + rng.nextGaussian() * std;
  
  			if (value >= this.min && value <= this.max)
  			{
  				return value;
  			}
  		}
  	}
  
  }
  