Examples with AnalogStatisticsQuantizer com.infiniteautomation.mango.quantize.AnalogStatisticsQuantizer used on opensource projects

Example 1 with AnalogStatisticsQuantizer

use of com.infiniteautomation.mango.quantize.AnalogStatisticsQuantizer in project ma-core-public by infiniteautomation.

the class StatisticsAggregatorTest method emptyStream.

@Test
public void emptyStream() {
    BucketCalculator bucketCalc = new TemporalAmountBucketCalculator(from, to, aggregatePeriod);
    List<NumericAggregate> aggregates = StatisticsAggregator.aggregate(Stream.empty(), new AnalogStatisticsQuantizer(bucketCalc)).collect(Collectors.toList());
    Assert.assertEquals(expectedAggregateValues, aggregates.size());
    for (var aggregate : aggregates) {
        assertEquals(0L, aggregate.getCount());
        assertEquals(Double.NaN, aggregate.getArithmeticMean(), 0.0D);
        assertEquals(Double.NaN, aggregate.getAverage(), 0.0D);
    }
}

Example 2 with AnalogStatisticsQuantizer

use of com.infiniteautomation.mango.quantize.AnalogStatisticsQuantizer in project ma-core-public by infiniteautomation.

the class StatisticsAggregatorTest method aggregateWithInitialValue.

@Test
public void aggregateWithInitialValue() {
    PointValueTime initialValue = new PointValueTime(1.0D, from.minusHours(1L).toInstant().toEpochMilli());
    PointValueGenerator generator = new ConstantPointValueGenerator(from.toInstant(), to.toInstant(), pollPeriod, new NumericValue(0.0D));
    var stream = generator.apply(new DataPointVO()).map(BatchPointValue::getValue);
    BucketCalculator bucketCalc = new TemporalAmountBucketCalculator(from, to, aggregatePeriod);
    List<NumericAggregate> aggregates = StatisticsAggregator.aggregate(Stream.concat(Stream.of(initialValue), stream), new AnalogStatisticsQuantizer(bucketCalc)).collect(Collectors.toList());
    Assert.assertEquals(expectedAggregateValues, aggregates.size());
    for (var aggregate : aggregates) {
        assertEquals(180L, aggregate.getCount());
        assertEquals(0.0D, aggregate.getArithmeticMean(), 0.0D);
        assertEquals(0.0D, aggregate.getArithmeticMean(), 0.0D);
    }
}

Example 3 with AnalogStatisticsQuantizer

use of com.infiniteautomation.mango.quantize.AnalogStatisticsQuantizer in project ma-core-public by infiniteautomation.

the class StatisticsAggregatorTest method initialValueOnly.

@Test
public void initialValueOnly() {
    PointValueTime initialValue = new PointValueTime(1.0D, from.minusHours(1L).toInstant().toEpochMilli());
    BucketCalculator bucketCalc = new TemporalAmountBucketCalculator(from, to, aggregatePeriod);
    List<NumericAggregate> aggregates = StatisticsAggregator.aggregate(Stream.of(initialValue), new AnalogStatisticsQuantizer(bucketCalc)).collect(Collectors.toList());
    Assert.assertEquals(expectedAggregateValues, aggregates.size());
    for (var aggregate : aggregates) {
        assertEquals(0L, aggregate.getCount());
        assertEquals(Double.NaN, aggregate.getArithmeticMean(), 0.0D);
        assertEquals(1.0D, aggregate.getAverage(), 0.0D);
    }
}

Example 4 with AnalogStatisticsQuantizer

use of com.infiniteautomation.mango.quantize.AnalogStatisticsQuantizer in project ma-core-public by infiniteautomation.

the class StatisticsAggregatorTest method aggregate.

@Test
public void aggregate() {
    PointValueGenerator generator = new ConstantPointValueGenerator(from.toInstant(), to.toInstant(), pollPeriod, new NumericValue(0.0D));
    var stream = generator.apply(new DataPointVO()).map(BatchPointValue::getValue);
    BucketCalculator bucketCalc = new TemporalAmountBucketCalculator(from, to, aggregatePeriod);
    List<NumericAggregate> aggregates = StatisticsAggregator.aggregate(stream, new AnalogStatisticsQuantizer(bucketCalc)).collect(Collectors.toList());
    Assert.assertEquals(expectedAggregateValues, aggregates.size());
    for (var aggregate : aggregates) {
        assertEquals(180L, aggregate.getCount());
        assertEquals(0.0D, aggregate.getArithmeticMean(), 0.0D);
        assertEquals(0.0D, aggregate.getArithmeticMean(), 0.0D);
    }
}

Example 5 with AnalogStatisticsQuantizer

use of com.infiniteautomation.mango.quantize.AnalogStatisticsQuantizer in project ma-core-public by infiniteautomation.

the class AggregateDao method aggregate.

/**
 * Aggregate a stream of raw point values into aggregate statistics. Mango statistics rely on knowing the initial
 * value of the point before the "from" time, you must include an initial start value in the stream (if one exists).
 * The timestamp of this start value should be less than the "from" time.
 *
 * @param point data point
 * @param from from time (inclusive)
 * @param to to time (exclusive)
 * @param pointValues stream of point values, must include a start value (at time < from) for accurate statistics
 * @param aggregationPeriod aggregation period (bucket/window size)
 * @return stream of aggregates
 */
default Stream<SeriesValueTime<AggregateValue>> aggregate(DataPointVO point, ZonedDateTime from, ZonedDateTime to, Stream<? extends PointValueTime> pointValues, TemporalAmount aggregationPeriod) {
    BucketCalculator bucketCalc = new TemporalAmountBucketCalculator(from, to, aggregationPeriod);
    AbstractPointValueTimeQuantizer<?> quantizer;
    switch(point.getPointLocator().getDataType()) {
        case BINARY:
        case MULTISTATE:
            quantizer = new StartsAndRuntimeListQuantizer(bucketCalc);
            break;
        case NUMERIC:
            quantizer = new AnalogStatisticsQuantizer(bucketCalc);
            break;
        case ALPHANUMERIC:
            quantizer = new ValueChangeCounterQuantizer(bucketCalc);
            break;
        default:
            throw new IllegalStateException("Unknown data type: " + point.getPointLocator().getDataType());
    }
    Stream<AggregateValue> aggregateStream = StatisticsAggregator.aggregate(pointValues, quantizer).filter(v -> v instanceof AggregateValue).map(v -> (AggregateValue) v);
    return aggregateStream.map(v -> new DefaultSeriesValueTime<>(point.getSeriesId(), v.getPeriodStartTime(), v));
}