use of com.srotya.sidewinder.core.functions.windowed.ReducingWindowedAggregator in project sidewinder by srotya.
the class TestChainFunction method testTwoFunctions.
@Test
public void testTwoFunctions() throws Exception {
Series series = new Series("cpu", "test", Arrays.asList(new Tag("t", "1"), new Tag("t", "2")));
List<DataPoint> dps = new ArrayList<>();
long baseTs = 1486617103629L;
for (int i = 0; i < 4; i++) {
dps.add(new DataPoint(baseTs + 30_000 * i, 1));
}
series.setDataPoints(dps);
series.setFp(false);
List<Series> seriesList = Arrays.asList(series);
ChainFunction cf = new ChainFunction();
ReducingWindowedAggregator rwa = new WindowedMean();
rwa.init(new Object[] { 70, "smean" });
ReducingWindowedAggregator rwa2 = new WindowedMean();
rwa2.init(new Object[] { 200, "smean" });
cf.init(new Function[] { rwa, rwa2 });
List<Series> apply = cf.apply(seriesList);
List<DataPoint> result = apply.get(0).getDataPoints();
assertEquals(1, result.size());
assertEquals(1, result.get(0).getLongValue());
}
use of com.srotya.sidewinder.core.functions.windowed.ReducingWindowedAggregator in project sidewinder by srotya.
the class TestWindowedFunctions method testDerivativeAggregator.
@Test
public void testDerivativeAggregator() throws Exception {
double[] values = { 1.1, 2.2, 3.3, 4.4 };
List<DataPoint> dps = new ArrayList<>();
long ts = 1486617103629L;
for (int i = 0; i < values.length; i++) {
double d = values[i];
ts = ts + (30_000);
dps.add(MiscUtils.buildDataPoint(ts, d));
}
ReducingWindowedAggregator rwa = new DerivativeFunction();
rwa.init(new Object[] { 70, "smean" });
Series series = new Series();
series.setDataPoints(dps);
series.setFp(true);
List<DataPoint> result = rwa.apply(series).getDataPoints();
// 1.65 and 3.85
assertEquals(1, result.size());
assertEquals(0.00003666666667 * 1000, result.get(0).getValue(), 0.01);
System.out.println(result.get(0).getValue() * 1000 + "\t" + ts);
}
use of com.srotya.sidewinder.core.functions.windowed.ReducingWindowedAggregator in project sidewinder by srotya.
the class TestWindowedFunctions method testWindowedMean.
@Test
public void testWindowedMean() throws Exception {
double[] values = { 1.1, 2.2, 3.3, 4.4 };
List<DataPoint> dps = new ArrayList<>();
long ts = 1486617103629L;
for (int i = 0; i < values.length; i++) {
double d = values[i];
ts = ts + (30_000);
dps.add(MiscUtils.buildDataPoint(ts, d));
}
ReducingWindowedAggregator rwa = new WindowedMean();
rwa.init(new Object[] { 70, "smean" });
Series series = new Series();
series.setDataPoints(dps);
series.setFp(true);
List<DataPoint> result = rwa.apply(series).getDataPoints();
assertEquals(2, result.size());
assertEquals(1.1, result.get(0).getValue(), 0);
assertEquals(3.3, result.get(1).getValue(), 0.001);
}
use of com.srotya.sidewinder.core.functions.windowed.ReducingWindowedAggregator in project sidewinder by srotya.
the class TestWindowedFunctions method testWindowedFirst.
@Test
public void testWindowedFirst() throws Exception {
double[] values = { 1.1, 3.3, 2.2, 4.4 };
List<DataPoint> dps = new ArrayList<>();
long ts = 1486617103629L;
for (int i = 0; i < values.length; i++) {
double d = values[i];
ts = ts + (30_000);
dps.add(MiscUtils.buildDataPoint(ts, d));
}
ReducingWindowedAggregator rwa = new WindowedFirst();
rwa.init(new Object[] { 70, "smean" });
Series series = new Series();
series.setDataPoints(dps);
series.setFp(true);
List<DataPoint> result = rwa.apply(series).getDataPoints();
assertEquals(2, result.size());
assertEquals(1.1, result.get(0).getValue(), 0);
assertEquals(3.3, result.get(1).getValue(), 0);
}
use of com.srotya.sidewinder.core.functions.windowed.ReducingWindowedAggregator in project sidewinder by srotya.
the class TestWindowedFunctions method testDerivativeAggregator2.
@Test
public void testDerivativeAggregator2() throws Exception {
long[] values = { 1, 4, 1, 4, 1 };
List<DataPoint> dps = new ArrayList<>();
long ts = 1486617103629L;
for (int i = 0; i < values.length; i++) {
long d = values[i];
ts = ts + (10_000);
dps.add(MiscUtils.buildDataPoint(ts, d));
}
ReducingWindowedAggregator rwa = new DerivativeFunction();
rwa.init(new Object[] { 20, "smean" });
Series series = new Series();
series.setDataPoints(dps);
series.setFp(false);
Series result = rwa.apply(series);
assertEquals(1, result.getDataPoints().size());
assertEquals(false, result.isFp());
assertEquals(0, result.getDataPoints().get(0).getValue() * 1000, 0.01);
System.out.println(result.getDataPoints().get(0).getValue() * 1000 + "\t" + ts);
}
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