com.google.common.io.ByteSink#com.carrotsearch.hppc.DoubleArrayList源码实例Demo

public static TimeSeries readSampleSubsequence(File dataset) throws IOException {
  try (BufferedReader br = new BufferedReader(new FileReader(dataset))) {
    DoubleArrayList data = new DoubleArrayList();
    String line = null;
    while ((line = br.readLine()) != null) {
      line = line.trim();
      String[] values = line.split("[ \\t]");
      if (values.length > 0) {
        for (String value : values) {
          try {
            value = value.trim();
            if (isNonEmptyColumn(value)) {
              data.add(Double.parseDouble(value));
            }
          } catch (NumberFormatException nfe) {
            // Parse-Exception ignored
          }
        }
      }
    }
    return new TimeSeries(data.toArray());
  }
}
 

public static TimeSeries[] readSamplesQuerySeries(File dataset) throws IOException {
  List<TimeSeries> samples = new ArrayList<>();
  try (BufferedReader br = new BufferedReader(new FileReader(dataset))) {
    String line = null;
    while ((line = br.readLine()) != null) {
      DoubleArrayList data = new DoubleArrayList();
      line = line.trim();
      String[] values = line.split("[ \\t]");
      if (values.length > 0) {
        for (String value : values) {
          try {
            value = value.trim();
            if (isNonEmptyColumn(value)) {
              data.add(Double.parseDouble(value));
            }
          } catch (NumberFormatException nfe) {
            // Parse-Exception ignored
          }
        }
        samples.add(new TimeSeries(data.toArray()));
      }
    }
  }
  return samples.toArray(new TimeSeries[]{});
}
 

protected void addAverages(EvaluationResultContainer subTaskResults, EvaluationResultContainer results) {
    Map<String, DoubleArrayList> mapping = createNameValueMapping(subTaskResults.getResults());
    DoubleArrayList values;
    int subTaskCount = subTaskResults.getResults().size();
    double sum;
    for (String name : mapping.keySet()) {
        values = mapping.get(name);
        if (values.elementsCount == subTaskCount) {
            sum = 0;
            for (int i = 0; i < values.elementsCount; ++i) {
                sum += values.buffer[i];
            }
            results.addResult(new DoubleEvaluationResult(name, sum / subTaskCount));
        }
    }
}
 

@Override
public double summarize(double[] values, double[] weights) {
    if (values.length == 0) {
        throw new IllegalArgumentException(
                "The given array has to have at least one element to determine the modus.");
    }
    DoubleArrayList weightedValues = new DoubleArrayList(values.length);
    for (int i = 0; i < values.length; ++i) {
        if (!Double.isNaN(values[i])) {
            weightedValues.add(weights[i] * values[i]);
        }
    }
    if (weightedValues.size() == 0) {
        return 0;
    }
    double weightedValuesAsArray[] = weightedValues.toArray();
    Arrays.sort(weightedValuesAsArray);
    if ((weightedValuesAsArray.length & 1) > 0) {
        return weightedValuesAsArray[weightedValuesAsArray.length / 2];
    } else {
        return (weightedValuesAsArray[weightedValuesAsArray.length / 2] + weightedValuesAsArray[(weightedValuesAsArray.length / 2) - 1]) / 2.0;
    }
}
 

private Map<String, DoubleArrayList> createNameValueMapping(List<EvaluationResult> results) {
    Map<String, DoubleArrayList> mapping = new HashMap<String, DoubleArrayList>();
    for (EvaluationResult result : results) {
        addToMapping(mapping, result);
    }
    return mapping;
}
 

private static double[] readArray(File file) throws IOException {
  final Iterable<String> lines = GZIPByteSource.fromCompressed(
      Files.asByteSource(file)).asCharSource(Charsets.UTF_8).readLines();

  final DoubleArrayList ret = new DoubleArrayList();
  for (final String line : lines) {
    ret.add(100.0 * Double.parseDouble(line));
  }
  return ret.toArray();
}
 

private void writeArray(DoubleArrayList numbers, File file) throws IOException {
  final ByteSink sink = GZIPByteSink.gzipCompress(Files.asByteSink(file));
  final PrintWriter out = new PrintWriter(sink.asCharSink(Charsets.UTF_8).openBufferedStream());
  for (final DoubleCursor cursor : numbers) {
    out.println(cursor.value);
  }
  out.close();
  ;
}
 

public static double[] readGoldStandard(String file) throws IOException {
    List<String> lines = FileUtils.readLines(new File(file));

    DoubleArrayList ratings = new DoubleArrayList();
    for (String line : lines) {
        try {
            ratings.add(Double.parseDouble(line));
        } catch (NumberFormatException e) {
            throw new IOException("Error while reading gold standard.", e);
        }
    }
    return ratings.toArray();
}
 

public CustomDoubleNumericDocValuesField(String  name, double value) {
    super(name);
    values = new DoubleArrayList();
    add(value);
}
 

private void writeSamplesScoringBreakdown(String modeName,
    Collection<BrokenDownSummaryConfusionMatrix<Symbol>> data,
    File outputFile, File rawDir) throws IOException {
  final StringBuilder sb = new StringBuilder();

  sb.append("BREAKDOWN BY ").append(modeName).append("\n");

  for (final Map.Entry<String, Collection<Symbol>> FMeasureSymbol : F_MEASURES_TO_PRINT.asMap()
      .entrySet()) {
    final Multimap<String, FMeasureCounts> fMeasuresToPrint = toFMeasures(data, FMeasureSymbol);

    final ImmutableMap.Builder<String, PercentileComputer.Percentiles> precisionPercentiles =
        ImmutableMap.builder();
    final ImmutableMap.Builder<String, PercentileComputer.Percentiles> recallPercentiles =
        ImmutableMap.builder();
    final ImmutableMap.Builder<String, PercentileComputer.Percentiles> fPercentiles =
        ImmutableMap.builder();

    final PercentileComputer nistComputer = PercentileComputer.nistPercentileComputer();

    for (final Map.Entry<String, Collection<FMeasureCounts>> entry : fMeasuresToPrint.asMap()
        .entrySet()) {
      final DoubleArrayList precisions = new DoubleArrayList(entry.getValue().size());
      final DoubleArrayList recalls = new DoubleArrayList(entry.getValue().size());
      final DoubleArrayList fs = new DoubleArrayList(entry.getValue().size());

      for (final FMeasureCounts counts : entry.getValue()) {
        precisions.add((double) counts.precision());
        recalls.add((double) counts.recall());
        fs.add((double) counts.F1());
      }

      final String rawPrefix = entry.getKey() + "_" + FMeasureSymbol.getKey();
      writeArray(precisions, new File(rawDir, rawPrefix + ".precisions.txt"));
      writeArray(recalls, new File(rawDir, rawPrefix + ".recalls.txt"));
      writeArray(fs, new File(rawDir, rawPrefix + ".fs.txt"));
      precisionPercentiles.put(entry.getKey(),
          nistComputer.calculatePercentilesAdoptingData(precisions.toArray()));
      recallPercentiles.put(entry.getKey(),
          nistComputer.calculatePercentilesAdoptingData(recalls.toArray()));
      fPercentiles.put(entry.getKey(),
          nistComputer.calculatePercentilesAdoptingData(fs.toArray()));
    }

    dumpPercentilesForMetric("Precision", precisionPercentiles.build(), FMeasureSymbol, sb);
    dumpPercentilesForMetric("Recall", recallPercentiles.build(), FMeasureSymbol, sb);
    dumpPercentilesForMetric("F1", fPercentiles.build(), FMeasureSymbol, sb);
  }

  Files.asCharSink(outputFile, Charsets.UTF_8).write(sb.toString());
}