Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics.addValue()

Package org.apache.commons.math3.stat.descriptive

Class org.apache.commons.math3.stat.descriptive.DescriptiveStatistics

Examples of org.apache.commons.math3.stat.descriptive.DescriptiveStatistics.addValue()

org.apache.commons.math3.stat.descriptive.DescriptiveStatistics.addValue()
Adds the value to the dataset. If the dataset is at the maximum size (i.e., the number of stored elements equals the currently configured windowSize), the first (oldest) element in the dataset is discarded to make room for the new value. @param v the value to be added


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


            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));
    }

View Full Code Here


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


        for (int i = 0; i < 100; i++) {
            List<MaterializedRow> values = computeActual("SELECT orderkey FROM ORDERS TABLESAMPLE POISSONIZED (50)").getMaterializedRows();
            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));
    }

View Full Code Here


        long total = (long) computeExpected("SELECT COUNT(*) FROM orders", ImmutableList.of(BIGINT)).getMaterializedRows().get(0).getField(0);


        for (int i = 0; i < 100; i++) {
            long value = (long) computeActual("SELECT COUNT(*) FROM orders TABLESAMPLE POISSONIZED (50) RESCALED").getMaterializedRows().get(0).getField(0);
            stats.addValue(value * 1.0 / total);
        }


        double mean = stats.getGeometricMean();
        assertTrue(mean > 0.90 && mean < 1.1, format("Expected sample to be rescaled to ~1.0, but was %s", mean));
        assertTrue(stats.getVariance() > 0, "Samples all had the exact same size");

View Full Code Here

            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);
    }

View Full Code Here

            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);
    }

View Full Code Here

        double standardizedSample[] = StatUtils.normalize(sample);


        DescriptiveStatistics stats = new DescriptiveStatistics();
        // Add the data from the array
        for (int i = 0; i < length; i++) {
            stats.addValue(standardizedSample[i]);
        }
        // the calculations do have a limited precision    
        double distance = 1E-10;
        // check the mean an standard deviation
        Assert.assertEquals(0.0, stats.getMean(), distance);

View Full Code Here

            
            // Record deviations from "true" beta
            double dist = olsBeta.getDistance(b);
            olsBetaStats.addValue(dist * dist);
            dist = glsBeta.getDistance(b);
            glsBetaStats.addValue(dist * dist);
            
        }
        
        // Verify that GLS is on average more efficient, lower variance
        assert(olsBetaStats.getMean() > 1.5 * glsBetaStats.getMean());

View Full Code Here


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


            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));
    }

View Full Code Here


        long total = (long) computeExpected("SELECT COUNT(*) FROM orders", ImmutableList.of(BIGINT)).getMaterializedRows().get(0).getField(0);


        for (int i = 0; i < 100; i++) {
            String value = (String) computeActual("SELECT COUNT(*) FROM orders TABLESAMPLE POISSONIZED (50) APPROXIMATE AT 95 CONFIDENCE").getMaterializedRows().get(0).getField(0);
            stats.addValue(Long.parseLong(value.split(" ")[0]) * 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));
    }

View Full Code Here


        long total = (long) computeExpected("SELECT COUNT(*) FROM orders", ImmutableList.of(BIGINT)).getMaterializedRows().get(0).getField(0);


        for (int i = 0; i < 100; i++) {
            String value = (String) computeActual("SELECT COUNT(*) FROM orders TABLESAMPLE POISSONIZED (50) RESCALED APPROXIMATE AT 95 CONFIDENCE").getMaterializedRows().get(0).getField(0);
            stats.addValue(Long.parseLong(value.split(" ")[0]) * 1.0 / total);
        }


        double mean = stats.getGeometricMean();
        assertTrue(mean > 0.90 && mean < 1.1, format("Expected sample to be rescaled to ~1.0, but was %s", mean));
        assertTrue(stats.getVariance() > 0, "Samples all had the exact same size");

View Full Code Here

0 1 2 3 4 5 6 7 8 9

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.