本文整理了Java中htsjdk.samtools.util.Histogram.divideByHistogram()方法的一些代码示例，展示了Histogram.divideByHistogram()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Histogram.divideByHistogram()方法的具体详情如下：
包路径：htsjdk.samtools.util.Histogram
类名称：Histogram
方法名：divideByHistogram

Histogram.divideByHistogram介绍

[英]Immutable method that divides the current Histogram by an input Histogram and generates a new one Throws an exception if the bins don't match up exactly
[中]

代码示例

代码示例来源：origin: broadinstitute/picard

private void onComplete() {
  final double meanClustersPerTile = tileToClusterHistogram.getMeanBinSize();
  metrics.MEAN_CLUSTERS_PER_TILE = Math.round(meanClustersPerTile);
  metrics.SD_CLUSTERS_PER_TILE = Math.round(tileToClusterHistogram.getStandardDeviationBinSize(meanClustersPerTile));
  final double meanPfClustersPerTile = tileToPfClusterHistogram.getMeanBinSize();
  metrics.MEAN_PF_CLUSTERS_PER_TILE = Math.round(meanPfClustersPerTile);
  metrics.SD_PF_CLUSTERS_PER_TILE = Math.round(tileToPfClusterHistogram.getStandardDeviationBinSize(meanPfClustersPerTile));
  final DecimalFormat decFormat = new DecimalFormat("#.##");
  final Histogram<Integer> laneToPctPfClusterHistogram = tileToPfClusterHistogram.divideByHistogram(tileToClusterHistogram);
  final double meanPctPfClustersPerTile = laneToPctPfClusterHistogram.getMeanBinSize();
  metrics.MEAN_PCT_PF_CLUSTERS_PER_TILE = (Double.isNaN(meanPctPfClustersPerTile) ? 0 : Double.valueOf(decFormat.format(meanPctPfClustersPerTile * 100)));
  metrics.SD_PCT_PF_CLUSTERS_PER_TILE = Double.valueOf(decFormat.format(laneToPctPfClusterHistogram.getStandardDeviationBinSize(meanPctPfClustersPerTile) * 100));
  metrics.TOTAL_CLUSTERS = (long) this.tileToClusterHistogram.getSumOfValues();
  metrics.PF_CLUSTERS = (long) this.tileToPfClusterHistogram.getSumOfValues();
  final ReadStructure readStructure = new ReadStructure(READ_STRUCTURE);
  int templateBaseCountPerCluster = 0;
  for (int i = 0; i < readStructure.templates.length(); i++) {
    templateBaseCountPerCluster += readStructure.templates.get(i).length;
  }
  metrics.TOTAL_READS = metrics.TOTAL_CLUSTERS * readStructure.templates.length();
  metrics.PF_READS = metrics.PF_CLUSTERS * readStructure.templates.length();
  metrics.TOTAL_BASES = metrics.TOTAL_CLUSTERS * templateBaseCountPerCluster;
  metrics.PF_BASES = metrics.PF_CLUSTERS * templateBaseCountPerCluster;
}

代码示例来源：origin: com.github.broadinstitute/picard

private void onComplete() {
  final double meanClustersPerTile = tileToClusterHistogram.getMeanBinSize();
  metrics.MEAN_CLUSTERS_PER_TILE = Math.round(meanClustersPerTile);
  metrics.SD_CLUSTERS_PER_TILE = Math.round(tileToClusterHistogram.getStandardDeviationBinSize(meanClustersPerTile));
  final double meanPfClustersPerTile = tileToPfClusterHistogram.getMeanBinSize();
  metrics.MEAN_PF_CLUSTERS_PER_TILE = Math.round(meanPfClustersPerTile);
  metrics.SD_PF_CLUSTERS_PER_TILE = Math.round(tileToPfClusterHistogram.getStandardDeviationBinSize(meanPfClustersPerTile));
  final DecimalFormat decFormat = new DecimalFormat("#.##");
  final Histogram<Integer> laneToPctPfClusterHistogram = tileToPfClusterHistogram.divideByHistogram(tileToClusterHistogram);
  final double meanPctPfClustersPerTile = laneToPctPfClusterHistogram.getMeanBinSize();
  metrics.MEAN_PCT_PF_CLUSTERS_PER_TILE = (Double.isNaN(meanPctPfClustersPerTile) ? 0 : Double.valueOf(decFormat.format(meanPctPfClustersPerTile * 100)));
  metrics.SD_PCT_PF_CLUSTERS_PER_TILE = Double.valueOf(decFormat.format(laneToPctPfClusterHistogram.getStandardDeviationBinSize(meanPctPfClustersPerTile) * 100));
  metrics.TOTAL_CLUSTERS = (long) this.tileToClusterHistogram.getSumOfValues();
  metrics.PF_CLUSTERS = (long) this.tileToPfClusterHistogram.getSumOfValues();
  final ReadStructure readStructure = new ReadStructure(READ_STRUCTURE);
  int templateBaseCountPerCluster = 0;
  for (int i = 0; i < readStructure.templates.length(); i++) {
    templateBaseCountPerCluster += readStructure.templates.get(i).length;
  }
  metrics.TOTAL_READS = metrics.TOTAL_CLUSTERS * readStructure.templates.length();
  metrics.PF_READS = metrics.PF_CLUSTERS * readStructure.templates.length();
  metrics.TOTAL_BASES = metrics.TOTAL_CLUSTERS * templateBaseCountPerCluster;
  metrics.PF_BASES = metrics.PF_CLUSTERS * templateBaseCountPerCluster;
}