public void testMin() { try { EMPTY_STATS_VARARGS.min(); fail("Expected IllegalStateException"); } catch (IllegalStateException expected) { EMPTY_STATS_ITERABLE.min(); fail("Expected IllegalStateException"); } catch (IllegalStateException expected) { assertThat(ONE_VALUE_STATS.min()).isWithin(ALLOWED_ERROR).of(ONE_VALUE); assertThat(Stats.of(POSITIVE_INFINITY).min()).isPositiveInfinity(); assertThat(Stats.of(NEGATIVE_INFINITY).min()).isNegativeInfinity(); assertThat(Stats.of(NaN).min()).isNaN(); assertThat(TWO_VALUES_STATS.min()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MIN); assertThat(MANY_VALUES_STATS_VARARGS.min()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MIN); assertThat(MANY_VALUES_STATS_ITERABLE.min()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MIN); assertThat(MANY_VALUES_STATS_ITERATOR.min()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MIN); StatsAccumulator accumulator = new StatsAccumulator(); accumulator.addAll(values.asIterable()); double min = accumulator.snapshot().min(); if (values.hasAnyNaN()) { assertThat(min).named("min of " + values).isNaN(); assertThat(INTEGER_MANY_VALUES_STATS_VARARGS.min()) .isWithin(ALLOWED_ERROR) .of(INTEGER_MANY_VALUES_MIN); assertThat(INTEGER_MANY_VALUES_STATS_ITERABLE.min()) .isWithin(ALLOWED_ERROR)
/** * Adds the given statistics to the dataset, as if the individual values used to compute the * statistics had been added directly. */ public void addAll(Stats values) { if (values.count() == 0) { return; } if (count == 0) { count = values.count(); mean = values.mean(); sumOfSquaresOfDeltas = values.sumOfSquaresOfDeltas(); min = values.min(); max = values.max(); } else { count += values.count(); if (isFinite(mean) && isFinite(values.mean())) { // This is a generalized version of the calculation in add(double) above. double delta = values.mean() - mean; mean += delta * values.count() / count; sumOfSquaresOfDeltas += values.sumOfSquaresOfDeltas() + delta * (values.mean() - mean) * values.count(); } else { mean = calculateNewMeanNonFinite(mean, values.mean()); sumOfSquaresOfDeltas = NaN; } min = Math.min(min, values.min()); max = Math.max(max, values.max()); } }
public void testToString() { assertThat(EMPTY_STATS_VARARGS.toString()).isEqualTo("Stats{count=0}"); assertThat(MANY_VALUES_STATS_ITERABLE.toString()) .isEqualTo( "Stats{count=" + MANY_VALUES_STATS_ITERABLE.count() + ", mean=" + MANY_VALUES_STATS_ITERABLE.mean() + ", populationStandardDeviation=" + MANY_VALUES_STATS_ITERABLE.populationStandardDeviation() + ", min=" + MANY_VALUES_STATS_ITERABLE.min() + ", max=" + MANY_VALUES_STATS_ITERABLE.max() + "}"); }
/** * Adds the given statistics to the dataset, as if the individual values used to compute the * statistics had been added directly. */ public void addAll(Stats values) { if (values.count() == 0) { return; } if (count == 0) { count = values.count(); mean = values.mean(); sumOfSquaresOfDeltas = values.sumOfSquaresOfDeltas(); min = values.min(); max = values.max(); } else { count += values.count(); if (isFinite(mean) && isFinite(values.mean())) { // This is a generalized version of the calculation in add(double) above. double delta = values.mean() - mean; mean += delta * values.count() / count; sumOfSquaresOfDeltas += values.sumOfSquaresOfDeltas() + delta * (values.mean() - mean) * values.count(); } else { mean = calculateNewMeanNonFinite(mean, values.mean()); sumOfSquaresOfDeltas = NaN; } min = Math.min(min, values.min()); max = Math.max(max, values.max()); } }
public void testEquivalentStreams() { // For datasets of many double values created from an array, we test many combinations of finite // and non-finite values: for (ManyValues values : ALL_MANY_VALUES) { double[] array = values.asArray(); Stats stats = Stats.of(array); // instance methods on Stats vs on instance methods on DoubleStream assertThat(stats.count()).isEqualTo(stream(array).count()); assertEquivalent(stats.mean(), stream(array).average().getAsDouble()); assertEquivalent(stats.sum(), stream(array).sum()); assertEquivalent(stats.max(), stream(array).max().getAsDouble()); assertEquivalent(stats.min(), stream(array).min().getAsDouble()); // static method on Stats vs on instance method on DoubleStream assertEquivalent(Stats.meanOf(array), stream(array).average().getAsDouble()); // instance methods on Stats vs instance methods on DoubleSummaryStatistics DoubleSummaryStatistics streamStats = stream(array).summaryStatistics(); assertThat(stats.count()).isEqualTo(streamStats.getCount()); assertEquivalent(stats.mean(), streamStats.getAverage()); assertEquivalent(stats.sum(), streamStats.getSum()); assertEquivalent(stats.max(), streamStats.getMax()); assertEquivalent(stats.min(), streamStats.getMin()); } }
/** * Adds the given statistics to the dataset, as if the individual values used to compute the * statistics had been added directly. */ public void addAll(Stats values) { if (values.count() == 0) { return; } if (count == 0) { count = values.count(); mean = values.mean(); sumOfSquaresOfDeltas = values.sumOfSquaresOfDeltas(); min = values.min(); max = values.max(); } else { count += values.count(); if (isFinite(mean) && isFinite(values.mean())) { // This is a generalized version of the calculation in add(double) above. double delta = values.mean() - mean; mean += delta * values.count() / count; sumOfSquaresOfDeltas += values.sumOfSquaresOfDeltas() + delta * (values.mean() - mean) * values.count(); } else { mean = calculateNewMeanNonFinite(mean, values.mean()); sumOfSquaresOfDeltas = NaN; } min = Math.min(min, values.min()); max = Math.max(max, values.max()); } }
actualStats.min(); fail("Expected IllegalStateException"); } catch (IllegalStateException expected) { assertThat(actualStats.mean()).isWithin(ALLOWED_ERROR).of(expectedStats.mean()); assertThat(actualStats.populationVariance()).isWithin(0.0).of(0.0); assertThat(actualStats.min()).isWithin(ALLOWED_ERROR).of(expectedStats.min()); assertThat(actualStats.max()).isWithin(ALLOWED_ERROR).of(expectedStats.max()); } else { .isWithin(ALLOWED_ERROR) .of(expectedStats.populationVariance()); assertThat(actualStats.min()).isWithin(ALLOWED_ERROR).of(expectedStats.min()); assertThat(actualStats.max()).isWithin(ALLOWED_ERROR).of(expectedStats.max());
public void testMin() { try { EMPTY_STATS_VARARGS.min(); fail("Expected IllegalStateException"); } catch (IllegalStateException expected) { EMPTY_STATS_ITERABLE.min(); fail("Expected IllegalStateException"); } catch (IllegalStateException expected) { assertThat(ONE_VALUE_STATS.min()).isWithin(ALLOWED_ERROR).of(ONE_VALUE); assertThat(Stats.of(POSITIVE_INFINITY).min()).isPositiveInfinity(); assertThat(Stats.of(NEGATIVE_INFINITY).min()).isNegativeInfinity(); assertThat(Stats.of(NaN).min()).isNaN(); assertThat(TWO_VALUES_STATS.min()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MIN); assertThat(MANY_VALUES_STATS_VARARGS.min()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MIN); assertThat(MANY_VALUES_STATS_ITERABLE.min()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MIN); assertThat(MANY_VALUES_STATS_ITERATOR.min()).isWithin(ALLOWED_ERROR).of(MANY_VALUES_MIN); StatsAccumulator accumulator = new StatsAccumulator(); accumulator.addAll(values.asIterable()); double min = accumulator.snapshot().min(); if (values.hasAnyNaN()) { assertThat(min).named("min of " + values).isNaN(); assertThat(INTEGER_MANY_VALUES_STATS_VARARGS.min()) .isWithin(ALLOWED_ERROR) .of(INTEGER_MANY_VALUES_MIN); assertThat(INTEGER_MANY_VALUES_STATS_ITERABLE.min()) .isWithin(ALLOWED_ERROR)
/** * Adds the given statistics to the dataset, as if the individual values used to compute the * statistics had been added directly. */ public void addAll(Stats values) { if (values.count() == 0) { return; } if (count == 0) { count = values.count(); mean = values.mean(); sumOfSquaresOfDeltas = values.sumOfSquaresOfDeltas(); min = values.min(); max = values.max(); } else { count += values.count(); if (isFinite(mean) && isFinite(values.mean())) { // This is a generalized version of the calculation in add(double) above. double delta = values.mean() - mean; mean += delta * values.count() / count; sumOfSquaresOfDeltas += values.sumOfSquaresOfDeltas() + delta * (values.mean() - mean) * values.count(); } else { mean = calculateNewMeanNonFinite(mean, values.mean()); sumOfSquaresOfDeltas = NaN; } min = Math.min(min, values.min()); max = Math.max(max, values.max()); } }
/** * Adds the given statistics to the dataset, as if the individual values used to compute the * statistics had been added directly. */ public void addAll(Stats values) { if (values.count() == 0) { return; } if (count == 0) { count = values.count(); mean = values.mean(); sumOfSquaresOfDeltas = values.sumOfSquaresOfDeltas(); min = values.min(); max = values.max(); } else { count += values.count(); if (isFinite(mean) && isFinite(values.mean())) { // This is a generalized version of the calculation in add(double) above. double delta = values.mean() - mean; mean += delta * values.count() / count; sumOfSquaresOfDeltas += values.sumOfSquaresOfDeltas() + delta * (values.mean() - mean) * values.count(); } else { mean = calculateNewMeanNonFinite(mean, values.mean()); sumOfSquaresOfDeltas = NaN; } min = Math.min(min, values.min()); max = Math.max(max, values.max()); } }
public void testToString() { assertThat(EMPTY_STATS_VARARGS.toString()).isEqualTo("Stats{count=0}"); assertThat(MANY_VALUES_STATS_ITERABLE.toString()) .isEqualTo( "Stats{count=" + MANY_VALUES_STATS_ITERABLE.count() + ", mean=" + MANY_VALUES_STATS_ITERABLE.mean() + ", populationStandardDeviation=" + MANY_VALUES_STATS_ITERABLE.populationStandardDeviation() + ", min=" + MANY_VALUES_STATS_ITERABLE.min() + ", max=" + MANY_VALUES_STATS_ITERABLE.max() + "}"); }
public void testEquivalentStreams() { // For datasets of many double values created from an array, we test many combinations of finite // and non-finite values: for (ManyValues values : ALL_MANY_VALUES) { double[] array = values.asArray(); Stats stats = Stats.of(array); // instance methods on Stats vs on instance methods on DoubleStream assertThat(stats.count()).isEqualTo(stream(array).count()); assertEquivalent(stats.mean(), stream(array).average().getAsDouble()); assertEquivalent(stats.sum(), stream(array).sum()); assertEquivalent(stats.max(), stream(array).max().getAsDouble()); assertEquivalent(stats.min(), stream(array).min().getAsDouble()); // static method on Stats vs on instance method on DoubleStream assertEquivalent(Stats.meanOf(array), stream(array).average().getAsDouble()); // instance methods on Stats vs instance methods on DoubleSummaryStatistics DoubleSummaryStatistics streamStats = stream(array).summaryStatistics(); assertThat(stats.count()).isEqualTo(streamStats.getCount()); assertEquivalent(stats.mean(), streamStats.getAverage()); assertEquivalent(stats.sum(), streamStats.getSum()); assertEquivalent(stats.max(), streamStats.getMax()); assertEquivalent(stats.min(), streamStats.getMin()); } }
actualStats.min(); fail("Expected IllegalStateException"); } catch (IllegalStateException expected) { assertThat(actualStats.mean()).isWithin(ALLOWED_ERROR).of(expectedStats.mean()); assertThat(actualStats.populationVariance()).isWithin(0.0).of(0.0); assertThat(actualStats.min()).isWithin(ALLOWED_ERROR).of(expectedStats.min()); assertThat(actualStats.max()).isWithin(ALLOWED_ERROR).of(expectedStats.max()); } else { .isWithin(ALLOWED_ERROR) .of(expectedStats.populationVariance()); assertThat(actualStats.min()).isWithin(ALLOWED_ERROR).of(expectedStats.min()); assertThat(actualStats.max()).isWithin(ALLOWED_ERROR).of(expectedStats.max());