Examples of org.apache.commons.math.stat.descriptive.DescriptiveStatistics

Package org.apache.commons.math.stat.descriptive

Examples of org.apache.commons.math.stat.descriptive.DescriptiveStatistics

org.apache.commons.math.stat.descriptive.DescriptiveStatistics
Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data. The {@link #getWindowSize() windowSize}property sets a limit on the number of values that can be stored in the dataset. The default value, INFINITE_WINDOW, puts no limit on the size of the dataset. This value should be used with caution, as the backing store will grow without bound in this case. For very large datasets, {@link SummaryStatistics}, which does not store the dataset, should be used instead of this class. If windowSize is not INFINITE_WINDOW and more values are added than can be stored in the dataset, new values are added in a "rolling" manner, with new values replacing the "oldest" values in the dataset.
Note: this class is not threadsafe. Use {@link SynchronizedDescriptiveStatistics} if concurrent access from multiplethreads is required.
@version $Revision: 1054186 $ $Date: 2011-01-01 03:28:46 +0100 (sam. 01 janv. 2011) $

    this( task, -1, time );
  }
  
  public Result(Task task, double memory, double time) {
    this.task = task;
    this.memory = new DescriptiveStatistics();
    this.memory.addValue(memory);
    this.time = new DescriptiveStatistics();
    this.time.addValue(time);
  }

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    for (int size = 1; size <= maxsize; size *= 2) {
      double[] mems = new double[1+dens];
      int index2 = 0;
      int last = -1;
      for (double density = 1; density >= mindensity; density /= 2) {
        DescriptiveStatistics stats = new DescriptiveStatistics();


        int steps = (int) Math.max(1, Math.floor(density * size));
        int step = (int) Math.max(1, size / steps);
        if (step == last)
          break;
        for (int i = 0; i < 30; i++) {
          stats.addValue(insertTime(type, size, step)
              / (double) steps);
        }


        mems[index2++] = stats.getMean();
        last = step;
        System.out.println(type + " d: " + size + " D: " + density
            + " step: " + step + " = " + stats.getMean());
      }
      out[index++] = mems;
    }
    return out;
  }

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    for (VectorType type : VectorType.values()) {
      double[][] times = inesertTimes(type);
      double[] means = new double[dims];
      DescriptiveStatistics[] stats = new DescriptiveStatistics[dims];
      for(int i = 0; i < dims; i++) {
        stats[i] = new DescriptiveStatistics();
        for(int j = 0; j < dens; j++) {
          stats[i].addValue(times[i][j]);
        }
        means[i] = stats[i].getMean();
      }

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      if (!warmup)
         System.out.printf("%s %s %s %s%n", padString("Function Impl", 25), padString("String keys", 18), padString("Byte array keys", 18), padString("Object keys", 18));


      for (HashFunction f : functions) {
         long oRes = 0, sRes = 0, bRes = 0;
         DescriptiveStatistics oStats = new DescriptiveStatistics();
         DescriptiveStatistics sStats = new DescriptiveStatistics();
         DescriptiveStatistics bStats = new DescriptiveStatistics();


         long st = System.currentTimeMillis();
         for (Object o : objectKeys) captureStats(f.hash(o.hashCode()), oStats);
         oRes = System.currentTimeMillis() - st;


         st = System.currentTimeMillis();
         for (String s : stringKeys) captureStats(f.hash(s), sStats);
         sRes = System.currentTimeMillis() - st;


         st = System.currentTimeMillis();
         for (byte[] b : byteArrayKeys) captureStats(f.hash(b), bStats);
         bRes = System.currentTimeMillis() - st;


         if (!warmup) {
            System.out.printf("%s %s %s %s%n",
                    padString(f.functionName(), 25),
                    padString(prettyPrintTime(sRes), 18),
                    padString(prettyPrintTime(bRes), 18),
                    padString(prettyPrintTime(oRes), 18)
            );
            System.out.printf("%s %s %s %s%n",
                    padString("  mean", 25),
                    padDouble(sStats.getMean()),
                    padDouble(bStats.getMean()),
                    padDouble(oStats.getMean())
            );
            System.out.printf("%s %s %s %s%n",
                    padString("  median", 25),
                    padDouble(sStats.getPercentile(50.0)),
                    padDouble(bStats.getPercentile(50.0)),
                    padDouble(oStats.getPercentile(50.0))
            );
            System.out.printf("%s %s %s %s%n",
                    padString("  deviation", 25),
                    padDouble(sStats.getStandardDeviation()),
                    padDouble(bStats.getStandardDeviation()),
                    padDouble(oStats.getStandardDeviation())
            );


            System.out.printf("%s %s %s %s%n",
                    padString("  variance", 25),
                    padDouble(sStats.getVariance()),
                    padDouble(bStats.getVariance()),
                    padDouble(oStats.getVariance())
            );
         }
      }
   }

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    public void beforeIteration(ResultNode node) {
    }


    public void beforeNode(ResultNode node) {
        for(Alternative a : alternatives) {
            statisticsMap.put(a.getName(), new DescriptiveStatistics());
        }


    }

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                concurrencyLevels = Arrays.asList(1);
            }


            for (Integer concurrency: concurrencyLevels) {
                // Run the test
                DescriptiveStatistics statistics = runTest(concurrency);
                if (statistics.getN() > 0) {
                    System.out.format(
                            "%-28.28s  %6d  %6.0f  %6.0f  %6.0f  %6.0f  %6.0f  %6d%n",
                            fixture.toString(),
                            concurrency,
                            statistics.getMin(),
                            statistics.getPercentile(10.0),
                            statistics.getPercentile(50.0),
                            statistics.getPercentile(90.0),
                            statistics.getMax(),
                            statistics.getN());
                    if (out != null) {
                        out.format(
                                "%-28.28s, %6d, %6.0f, %6.0f, %6.0f, %6.0f, %6.0f, %6d%n",
                                fixture.toString(),
                                concurrency,
                                statistics.getMin(),
                                statistics.getPercentile(10.0),
                                statistics.getPercentile(50.0),
                                statistics.getPercentile(90.0),
                                statistics.getMax(),
                                statistics.getN());
                    }
                }


            }
        } finally {

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            return stats.get(benchmark);
        }


        public void out() {
            for (Entry<ScalabilityBenchmark, DescriptiveStatistics> entry : stats.entrySet()) {
                DescriptiveStatistics statistics = entry.getValue();
                ScalabilityBenchmark benchmark = entry.getKey();


                System.out
                        .format(
                                "# %-26.26s       min     10%%     50%%     90%%     max       N%n",
                                benchmark.toString());
                if (out != null) {
                    out.format(
                            "# %-26.26s       min     10%%     50%%     90%%     max       N%n",
                            benchmark.toString());
                }


                System.out.format(
                        "%-30.30s  %6.0f  %6.0f  %6.0f  %6.0f  %6.0f  %6d%n",
                        fixture.toString(),
                        statistics.getMin(),
                        statistics.getPercentile(10.0),
                        statistics.getPercentile(50.0),
                        statistics.getPercentile(90.0),
                        statistics.getMax(),
                        statistics.getN());


                if (out != null) {
                    out.format(
                            "%-30.30s  %-6.0f  %-6.0f  %-6.0f  %-6.0f  %-6.0f  %-6d%n",
                            fixture.toString(),
                            statistics.getMin(),
                            statistics.getPercentile(10.0),
                            statistics.getPercentile(50.0),
                            statistics.getPercentile(90.0),
                            statistics.getMax(),
                            statistics.getN());
                }


                StringBuilder header = new StringBuilder();
                header.append("\t# %-26.26s");
                for (String increment : INCREMENTS) {
                    header.append("\t");
                    header.append(increment);
                }
                header.append("%n");
                System.out.format(header.toString(), "Iterations/Load");


                StringBuffer format = new StringBuffer();
                format.append("%-30.30s");
                System.out.format(format.toString(), "\t" + "Time (ms)");
                if (out != null) {
                    out.format(format.toString(), "\t" + "Time (ms)");
                }


                for (int idx = 0; idx < INCREMENTS.size(); idx++) {
                    format = new StringBuffer();
                    format.append("\t");
                    format.append("%-7.0f");
                    System.out.format(format.toString(), statistics.getValues()[idx]);
                    if (out != null) {
                        out.format(format.toString(), statistics.getValues()[idx]);
                    }
                }
                System.out.format("%n");
            }
        }

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    @Test
    public void testMultiplePositions()
            throws Exception
    {
        DescriptiveStatistics stats = new DescriptiveStatistics();


        for (int i = 0; i < 500; ++i) {
            int uniques = ThreadLocalRandom.current().nextInt(20000) + 1;


            List<Object> values = createRandomSample(uniques, (int) (uniques * 1.5));


            long actual = estimateGroupByCount(values);
            double error = (actual - uniques) * 1.0 / uniques;


            stats.addValue(error);
        }


        assertLessThan(stats.getMean(), 1.0e-2);
        assertLessThan(Math.abs(stats.getStandardDeviation() - ApproximateCountDistinctAggregation.getStandardError()), 1.0e-2);
    }

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    @Test
    public void testTableSampleBernoulli()
            throws Exception
    {
        DescriptiveStatistics stats = new DescriptiveStatistics();


        int total = computeExpected("SELECT orderkey FROM orders", ImmutableList.of(SINGLE_LONG)).getMaterializedTuples().size();


        for (int i = 0; i < 100; i++) {
            List<MaterializedTuple> values = computeActual("SELECT orderkey FROM ORDERS TABLESAMPLE BERNOULLI (50)").getMaterializedTuples();


            assertEquals(values.size(), ImmutableSet.copyOf(values).size(), "TABLESAMPLE produced duplicate rows");
            stats.addValue(values.size() * 1.0 / total);
        }


        double mean = stats.getGeometricMean();
        assertTrue(mean > 0.45 && mean < 0.55, format("Expected mean sampling rate to be ~0.5, but was %s", mean));
    }

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      if (!warmup)
         System.out.printf("%s %s %s %s%n", padString("Function Impl", 25), padString("String keys", 18), padString("Byte array keys", 18), padString("Object keys", 18));


      for (HashFunction f : functions) {
         long oRes = 0, sRes = 0, bRes = 0;
         DescriptiveStatistics oStats = new DescriptiveStatistics();
         DescriptiveStatistics sStats = new DescriptiveStatistics();
         DescriptiveStatistics bStats = new DescriptiveStatistics();


         long st = System.currentTimeMillis();
         for (Object o : objectKeys) captureStats(f.hash(o.hashCode()), oStats);
         oRes = System.currentTimeMillis() - st;


         st = System.currentTimeMillis();
         for (String s : stringKeys) captureStats(f.hash(s), sStats);
         sRes = System.currentTimeMillis() - st;


         st = System.currentTimeMillis();
         for (byte[] b : byteArrayKeys) captureStats(f.hash(b), bStats);
         bRes = System.currentTimeMillis() - st;


         if (!warmup) {
            System.out.printf("%s %s %s %s%n",
                    padString(f.functionName(), 25),
                    padString(prettyPrintTime(sRes), 18),
                    padString(prettyPrintTime(bRes), 18),
                    padString(prettyPrintTime(oRes), 18)
            );
            System.out.printf("%s %s %s %s%n",
                    padString("  mean", 25),
                    padDouble(sStats.getMean()),
                    padDouble(bStats.getMean()),
                    padDouble(oStats.getMean())
            );
            System.out.printf("%s %s %s %s%n",
                    padString("  median", 25),
                    padDouble(sStats.getPercentile(50.0)),
                    padDouble(bStats.getPercentile(50.0)),
                    padDouble(oStats.getPercentile(50.0))
            );
            System.out.printf("%s %s %s %s%n",
                    padString("  deviation", 25),
                    padDouble(sStats.getStandardDeviation()),
                    padDouble(bStats.getStandardDeviation()),
                    padDouble(oStats.getStandardDeviation())
            );


            System.out.printf("%s %s %s %s%n",
                    padString("  variance", 25),
                    padDouble(sStats.getVariance()),
                    padDouble(bStats.getVariance()),
                    padDouble(oStats.getVariance())
            );
         }
      }
   }

View Full Code Here

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