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Posted to commits@datasketches.apache.org by le...@apache.org on 2024/03/26 21:57:46 UTC
(datasketches-java) branch extend_KS_to_kll created (now ce189132)
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leerho pushed a change to branch extend_KS_to_kll
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at ce189132 This extends the usability of the Kolmogorov-Smirnov test
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new ce189132 This extends the usability of the Kolmogorov-Smirnov test
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(datasketches-java) 01/01: This extends the usability of the Kolmogorov-Smirnov test
Posted by le...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
leerho pushed a commit to branch extend_KS_to_kll
in repository https://gitbox.apache.org/repos/asf/datasketches-java.git
commit ce189132f794c88898d322443ce2f4d7d704531f
Author: Lee Rhodes <le...@users.noreply.github.com>
AuthorDate: Tue Mar 26 14:57:32 2024 -0700
This extends the usability of the Kolmogorov-Smirnov test
from the Classic DoublesSketch to KllDoublesSketch and the
KllFloatsSketch.
In order to do this I needed to add "getNormalizedRankError(boolean) to
the root interface QuantilesAPI. All of the sketches (except REQ) had
this anyway. In REQ I just throw an unsupported operation exception,
because it makes no sense for REQ.
This also means the KolmogorovSmirnov class and its test move to the
"quantilescommon" package.
---
.../org/apache/datasketches/kll/KllSketch.java | 14 +-
.../datasketches/quantiles/DoublesSketch.java | 10 +-
.../apache/datasketches/quantiles/ItemsSketch.java | 8 +-
.../datasketches/quantiles/KolmogorovSmirnov.java | 114 -------
.../quantilescommon/KolmogorovSmirnov.java | 167 ++++++++++
.../datasketches/quantilescommon/QuantilesAPI.java | 11 +
.../org/apache/datasketches/req/ReqSketch.java | 9 +
.../quantiles/KolmogorovSmirnovTest.java | 148 ---------
.../quantilescommon/KolmogorovSmirnovTest.java | 355 +++++++++++++++++++++
9 files changed, 545 insertions(+), 291 deletions(-)
diff --git a/src/main/java/org/apache/datasketches/kll/KllSketch.java b/src/main/java/org/apache/datasketches/kll/KllSketch.java
index bbf269cb..2d7385f6 100644
--- a/src/main/java/org/apache/datasketches/kll/KllSketch.java
+++ b/src/main/java/org/apache/datasketches/kll/KllSketch.java
@@ -193,15 +193,7 @@ public abstract class KllSketch implements QuantilesAPI {
return KllHelper.getNormalizedRankError(k, pmf);
}
- /**
- * Gets the approximate rank error of this sketch normalized as a fraction between zero and one.
- * The epsilon returned is a best fit to 99 percent confidence empirically measured max error
- * in thousands of trials.
- * @param pmf if true, returns the "double-sided" normalized rank error for the getPMF() function.
- * Otherwise, it is the "single-sided" normalized rank error for all the other queries.
- * @return if pmf is true, returns the "double-sided" normalized rank error for the getPMF() function.
- * Otherwise, it is the "single-sided" normalized rank error for all the other queries.
- */
+ @Override
public final double getNormalizedRankError(final boolean pmf) {
return getNormalizedRankError(getMinK(), pmf);
}
@@ -279,10 +271,6 @@ public abstract class KllSketch implements QuantilesAPI {
*/
public abstract void merge(KllSketch other);
- /**
- * Returns human readable summary information about this sketch.
- * Used for debugging.
- */
@Override
public final String toString() {
return toString(false, false);
diff --git a/src/main/java/org/apache/datasketches/quantiles/DoublesSketch.java b/src/main/java/org/apache/datasketches/quantiles/DoublesSketch.java
index fd0698b8..1d148268 100644
--- a/src/main/java/org/apache/datasketches/quantiles/DoublesSketch.java
+++ b/src/main/java/org/apache/datasketches/quantiles/DoublesSketch.java
@@ -266,15 +266,7 @@ public abstract class DoublesSketch implements QuantilesDoublesAPI {
@Override
public abstract long getN();
- /**
- * Gets the approximate rank error of this sketch normalized as a fraction between zero and one.
- * The epsilon returned is a best fit to 99 percent confidence empirically measured max error
- * in thousands of trials.
- * @param pmf if true, returns the "double-sided" normalized rank error for the getPMF() function.
- * Otherwise, it is the "single-sided" normalized rank error for all the other queries.
- * @return if pmf is true, returns the normalized rank error for the getPMF() function.
- * Otherwise, it is the "single-sided" normalized rank error for all the other queries.
- */
+ @Override
public double getNormalizedRankError(final boolean pmf) {
return getNormalizedRankError(k_, pmf);
}
diff --git a/src/main/java/org/apache/datasketches/quantiles/ItemsSketch.java b/src/main/java/org/apache/datasketches/quantiles/ItemsSketch.java
index 13aee81e..9361c6cd 100644
--- a/src/main/java/org/apache/datasketches/quantiles/ItemsSketch.java
+++ b/src/main/java/org/apache/datasketches/quantiles/ItemsSketch.java
@@ -361,13 +361,7 @@ public final class ItemsSketch<T> implements QuantilesGenericAPI<T> {
return n_;
}
- /**
- * Gets the approximate rank error of this sketch normalized as a fraction between zero and one.
- * @param pmf if true, returns the "double-sided" normalized rank error for the getPMF() function.
- * Otherwise, it is the "single-sided" normalized rank error for all the other queries.
- * @return if pmf is true, returns the normalized rank error for the getPMF() function.
- * Otherwise, it is the "single-sided" normalized rank error for all the other queries.
- */
+ @Override
public double getNormalizedRankError(final boolean pmf) {
return getNormalizedRankError(k_, pmf);
}
diff --git a/src/main/java/org/apache/datasketches/quantiles/KolmogorovSmirnov.java b/src/main/java/org/apache/datasketches/quantiles/KolmogorovSmirnov.java
deleted file mode 100644
index 6b8079ea..00000000
--- a/src/main/java/org/apache/datasketches/quantiles/KolmogorovSmirnov.java
+++ /dev/null
@@ -1,114 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing,
- * software distributed under the License is distributed on an
- * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
- * KIND, either express or implied. See the License for the
- * specific language governing permissions and limitations
- * under the License.
- */
-
-package org.apache.datasketches.quantiles;
-
-import org.apache.datasketches.quantilescommon.DoublesSketchSortedView;
-
-/**
- * Kolmogorov-Smirnov Test
- * See <a href="https://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test">Kolmogorov–Smirnov Test</a>
- */
-final class KolmogorovSmirnov {
-
- //TODO This KS test will have to be redesigned to accommodate REQ sketches.
-
- /**
- * Computes the raw delta area between two quantile sketches for the
- * <i>kolmogorovSmirnovTest(DoublesSketch, DoublesSketch, double)</i>
- * method.
- * @param sketch1 Input DoubleSketch 1
- * @param sketch2 Input DoubleSketch 2
- * @return the raw delta area between two quantile sketches
- */
- public static double computeKSDelta(final DoublesSketch sketch1, final DoublesSketch sketch2) {
- final DoublesSketchSortedView p = sketch1.getSortedView();
- final DoublesSketchSortedView q = sketch2.getSortedView();
-
- final double[] pSamplesArr = p.getQuantiles();
- final double[] qSamplesArr = q.getQuantiles();
- final long[] pCumWtsArr = p.getCumulativeWeights();
- final long[] qCumWtsArr = q.getCumulativeWeights();
- final int pSamplesArrLen = pSamplesArr.length;
- final int qSamplesArrLen = qSamplesArr.length;
-
- final double n1 = sketch1.getN();
- final double n2 = sketch2.getN();
-
- double deltaHeight = 0;
- int i = 0;
- int j = 0;
-
- while ((i < pSamplesArrLen - 1) && (j < qSamplesArrLen - 1)) {
- deltaHeight = Math.max(deltaHeight, Math.abs(pCumWtsArr[i] / n1 - qCumWtsArr[j] / n2));
- if (pSamplesArr[i] < qSamplesArr[j]) {
- i++;
- } else if (qSamplesArr[j] < pSamplesArr[i]) {
- j++;
- } else {
- i++;
- j++;
- }
- }
-
- deltaHeight = Math.max(deltaHeight, Math.abs(pCumWtsArr[i] / n1 - qCumWtsArr[j] / n2));
- return deltaHeight;
- }
-
- /**
- * Computes the adjusted delta height threshold for the
- * <i>kolmogorovSmirnovTest(DoublesSketch, DoublesSketch, double)</i>
- * method.
- * This adjusts the computed threshold by the error epsilons of the two given sketches.
- * @param sketch1 Input DoubleSketch 1
- * @param sketch2 Input DoubleSketch 2
- * @param tgtPvalue Target p-value. Typically .001 to .1, e.g., .05.
- * @return the adjusted threshold to be compared with the raw delta area.
- */
- public static double computeKSThreshold(final DoublesSketch sketch1,
- final DoublesSketch sketch2,
- final double tgtPvalue) {
- final double r1 = sketch1.getNumRetained();
- final double r2 = sketch2.getNumRetained();
- final double alpha = tgtPvalue;
- final double alphaFactor = Math.sqrt(-0.5 * Math.log(0.5 * alpha));
- final double deltaAreaThreshold = alphaFactor * Math.sqrt((r1 + r2) / (r1 * r2));
- final double eps1 = sketch1.getNormalizedRankError(false);
- final double eps2 = sketch2.getNormalizedRankError(false);
- return deltaAreaThreshold + eps1 + eps2;
- }
-
- /**
- * Performs the Kolmogorov-Smirnov Test between two quantiles sketches.
- * Note: if the given sketches have insufficient data or if the sketch sizes are too small,
- * this will return false.
- * @param sketch1 Input DoubleSketch 1
- * @param sketch2 Input DoubleSketch 2
- * @param tgtPvalue Target p-value. Typically .001 to .1, e.g., .05.
- * @return Boolean indicating whether we can reject the null hypothesis (that the sketches
- * reflect the same underlying distribution) using the provided tgtPValue.
- */
- public static boolean kolmogorovSmirnovTest(final DoublesSketch sketch1,
- final DoublesSketch sketch2, final double tgtPvalue) {
- final double delta = computeKSDelta(sketch1, sketch2);
- final double thresh = computeKSThreshold(sketch1, sketch2, tgtPvalue);
- return delta > thresh;
- }
-
-}
diff --git a/src/main/java/org/apache/datasketches/quantilescommon/KolmogorovSmirnov.java b/src/main/java/org/apache/datasketches/quantilescommon/KolmogorovSmirnov.java
new file mode 100644
index 00000000..2856cff0
--- /dev/null
+++ b/src/main/java/org/apache/datasketches/quantilescommon/KolmogorovSmirnov.java
@@ -0,0 +1,167 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.datasketches.quantilescommon;
+
+import static org.apache.datasketches.quantilescommon.QuantilesAPI.UNSUPPORTED_MSG;
+
+import org.apache.datasketches.req.ReqSketch;
+
+/**
+ * Kolmogorov-Smirnov Test
+ * See <a href="https://en.wikipedia.org/wiki/Kolmogorov-Smirnov_test">Kolmogorov–Smirnov Test</a>
+ */
+public final class KolmogorovSmirnov {
+
+ /**
+ * Computes the raw delta between two QuantilesDoublesAPI sketches for the <i>kolmogorovSmirnovTest(...)</i> method.
+ * @param sketch1 first Input QuantilesDoublesAPI
+ * @param sketch2 second Input QuantilesDoublesAPI
+ * @return the raw delta area between two QuantilesDoublesAPI sketches
+ */
+ public static double computeKSDelta(final QuantilesDoublesAPI sketch1, final QuantilesDoublesAPI sketch2) {
+ final DoublesSortedView p = sketch1.getSortedView();
+ final DoublesSortedView q = sketch2.getSortedView();
+
+ final double[] pSamplesArr = p.getQuantiles();
+ final double[] qSamplesArr = q.getQuantiles();
+ final long[] pCumWtsArr = p.getCumulativeWeights();
+ final long[] qCumWtsArr = q.getCumulativeWeights();
+ final int pSamplesArrLen = pSamplesArr.length;
+ final int qSamplesArrLen = qSamplesArr.length;
+
+ final double n1 = sketch1.getN();
+ final double n2 = sketch2.getN();
+
+ double deltaHeight = 0;
+ int i = 0;
+ int j = 0;
+
+ while ((i < pSamplesArrLen - 1) && (j < qSamplesArrLen - 1)) {
+ deltaHeight = Math.max(deltaHeight, Math.abs(pCumWtsArr[i] / n1 - qCumWtsArr[j] / n2));
+ if (pSamplesArr[i] < qSamplesArr[j]) {
+ i++;
+ } else if (qSamplesArr[j] < pSamplesArr[i]) {
+ j++;
+ } else {
+ i++;
+ j++;
+ }
+ }
+
+ deltaHeight = Math.max(deltaHeight, Math.abs(pCumWtsArr[i] / n1 - qCumWtsArr[j] / n2));
+ return deltaHeight;
+ }
+
+ /**
+ * Computes the raw delta between two QuantilesFloatsAPI sketches for the <i>kolmogorovSmirnovTest(...)</i> method.
+ * method.
+ * @param sketch1 first Input QuantilesFloatsAPI sketch
+ * @param sketch2 second Input QuantilesFloatsAPI sketch
+ * @return the raw delta area between two QuantilesFloatsAPI sketches
+ */
+ public static double computeKSDelta(final QuantilesFloatsAPI sketch1, final QuantilesFloatsAPI sketch2) {
+ final FloatsSortedView p = sketch1.getSortedView();
+ final FloatsSortedView q = sketch2.getSortedView();
+
+ final float[] pSamplesArr = p.getQuantiles();
+ final float[] qSamplesArr = q.getQuantiles();
+ final long[] pCumWtsArr = p.getCumulativeWeights();
+ final long[] qCumWtsArr = q.getCumulativeWeights();
+ final int pSamplesArrLen = pSamplesArr.length;
+ final int qSamplesArrLen = qSamplesArr.length;
+
+ final double n1 = sketch1.getN();
+ final double n2 = sketch2.getN();
+
+ double deltaHeight = 0;
+ int i = 0;
+ int j = 0;
+
+ while ((i < pSamplesArrLen - 1) && (j < qSamplesArrLen - 1)) {
+ deltaHeight = Math.max(deltaHeight, Math.abs(pCumWtsArr[i] / n1 - qCumWtsArr[j] / n2));
+ if (pSamplesArr[i] < qSamplesArr[j]) {
+ i++;
+ } else if (qSamplesArr[j] < pSamplesArr[i]) {
+ j++;
+ } else {
+ i++;
+ j++;
+ }
+ }
+
+ deltaHeight = Math.max(deltaHeight, Math.abs(pCumWtsArr[i] / n1 - qCumWtsArr[j] / n2));
+ return deltaHeight;
+ }
+
+ /**
+ * Computes the adjusted delta height threshold for the <i>kolmogorovSmirnovTest(...)</i> method.
+ * This adjusts the computed threshold by the error epsilons of the two given sketches.
+ * The two sketches must be of the same primitive type, double or float.
+ * This will not work with the REQ sketch.
+ * @param sketch1 first Input QuantilesAPI sketch
+ * @param sketch2 second Input QuantilesAPI sketch
+ * @param tgtPvalue Target p-value. Typically .001 to .1, e.g., .05.
+ * @return the adjusted threshold to be compared with the raw delta area.
+ */
+ public static double computeKSThreshold(final QuantilesAPI sketch1,
+ final QuantilesAPI sketch2,
+ final double tgtPvalue) {
+ final double r1 = sketch1.getNumRetained();
+ final double r2 = sketch2.getNumRetained();
+ final double alpha = tgtPvalue;
+ final double alphaFactor = Math.sqrt(-0.5 * Math.log(0.5 * alpha));
+ final double deltaAreaThreshold = alphaFactor * Math.sqrt((r1 + r2) / (r1 * r2));
+ final double eps1 = sketch1.getNormalizedRankError(false);
+ final double eps2 = sketch2.getNormalizedRankError(false);
+ return deltaAreaThreshold + eps1 + eps2;
+ }
+
+ /**
+ * Performs the Kolmogorov-Smirnov Test between two QuantilesAPI sketches.
+ * Note: if the given sketches have insufficient data or if the sketch sizes are too small,
+ * this will return false. The two sketches must be of the same primitive type, double or float.
+ * This will not work with the REQ sketch.
+ * @param sketch1 first Input QuantilesAPI
+ * @param sketch2 second Input QuantilesAPI
+ * @param tgtPvalue Target p-value. Typically .001 to .1, e.g., .05.
+ * @return Boolean indicating whether we can reject the null hypothesis (that the sketches
+ * reflect the same underlying distribution) using the provided tgtPValue.
+ */
+ public static boolean kolmogorovSmirnovTest(final QuantilesAPI sketch1,
+ final QuantilesAPI sketch2, final double tgtPvalue) {
+
+ final double delta = isDoubleType(sketch1, sketch2)
+ ? computeKSDelta((QuantilesDoublesAPI)sketch1, (QuantilesDoublesAPI)sketch2)
+ : computeKSDelta((QuantilesFloatsAPI)sketch1, (QuantilesFloatsAPI)sketch2);
+ final double thresh = computeKSThreshold(sketch1, sketch2, tgtPvalue);
+ return delta > thresh;
+ }
+
+ private static boolean isDoubleType(final Object sk1, final Object sk2) {
+ if (sk1 instanceof ReqSketch || sk2 instanceof ReqSketch) {
+ throw new UnsupportedOperationException(UNSUPPORTED_MSG);
+ }
+ final boolean isDbl = (sk1 instanceof QuantilesDoublesAPI && sk2 instanceof QuantilesDoublesAPI);
+ final boolean isFlt = (sk1 instanceof QuantilesFloatsAPI && sk2 instanceof QuantilesFloatsAPI);
+ if (isDbl ^ isFlt) { return isDbl; }
+ else { throw new UnsupportedOperationException(UNSUPPORTED_MSG); }
+ }
+
+}
diff --git a/src/main/java/org/apache/datasketches/quantilescommon/QuantilesAPI.java b/src/main/java/org/apache/datasketches/quantilescommon/QuantilesAPI.java
index f433519e..0d02d2ec 100644
--- a/src/main/java/org/apache/datasketches/quantilescommon/QuantilesAPI.java
+++ b/src/main/java/org/apache/datasketches/quantilescommon/QuantilesAPI.java
@@ -225,6 +225,17 @@ public interface QuantilesAPI {
*/
long getN();
+ /**
+ * Gets the approximate rank error of this sketch normalized as a fraction between zero and one.
+ * The epsilon returned is a best fit to 99 percent confidence empirically measured max error
+ * in thousands of trials.
+ * @param pmf if true, returns the "double-sided" normalized rank error for the getPMF() function.
+ * Otherwise, it is the "single-sided" normalized rank error for all the other queries.
+ * @return if pmf is true, returns the "double-sided" normalized rank error for the getPMF() function.
+ * Otherwise, it is the "single-sided" normalized rank error for all the other queries.
+ */
+ double getNormalizedRankError(boolean pmf);
+
/**
* Gets the number of quantiles retained by the sketch.
* @return the number of quantiles retained by the sketch
diff --git a/src/main/java/org/apache/datasketches/req/ReqSketch.java b/src/main/java/org/apache/datasketches/req/ReqSketch.java
index 347b3aaf..7e19be1d 100644
--- a/src/main/java/org/apache/datasketches/req/ReqSketch.java
+++ b/src/main/java/org/apache/datasketches/req/ReqSketch.java
@@ -235,6 +235,15 @@ public final class ReqSketch extends BaseReqSketch {
return totalN;
}
+ @Override
+ /**
+ * This is an unsupported operation for this sketch
+ */
+ public double getNormalizedRankError(final boolean pmf) {
+ throw new UnsupportedOperationException(UNSUPPORTED_MSG);
+
+ }
+
@Override
public double[] getPMF(final float[] splitPoints, final QuantileSearchCriteria searchCrit) {
if (isEmpty()) { throw new IllegalArgumentException(QuantilesAPI.EMPTY_MSG); }
diff --git a/src/test/java/org/apache/datasketches/quantiles/KolmogorovSmirnovTest.java b/src/test/java/org/apache/datasketches/quantiles/KolmogorovSmirnovTest.java
deleted file mode 100644
index fd8e4f71..00000000
--- a/src/test/java/org/apache/datasketches/quantiles/KolmogorovSmirnovTest.java
+++ /dev/null
@@ -1,148 +0,0 @@
-/*
- * Licensed to the Apache Software Foundation (ASF) under one
- * or more contributor license agreements. See the NOTICE file
- * distributed with this work for additional information
- * regarding copyright ownership. The ASF licenses this file
- * to you under the Apache License, Version 2.0 (the
- * "License"); you may not use this file except in compliance
- * with the License. You may obtain a copy of the License at
- *
- * http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing,
- * software distributed under the License is distributed on an
- * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
- * KIND, either express or implied. See the License for the
- * specific language governing permissions and limitations
- * under the License.
- */
-
-package org.apache.datasketches.quantiles;
-
-import static org.testng.Assert.assertEquals;
-import static org.testng.Assert.assertFalse;
-import static org.testng.Assert.assertTrue;
-
-import java.util.Random;
-
-import org.testng.annotations.Test;
-
-public class KolmogorovSmirnovTest {
-
- @Test
- public void checkDisjointDistribution() {
- final int k = 256;
- final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
- final UpdateDoublesSketch s2 = DoublesSketch.builder().setK(k).build();
-
- final Random rand = new Random(1);
-
- final int n = (3 * k) - 1;
- for (int i = 0; i < n; ++i) {
- final double x = rand.nextGaussian();
- s1.update(x + 500);
- s2.update(x);
- }
- //assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s2), 1.0, 1E-6);
- println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s2));
- }
-
- @Test
- public void checkIdenticalDistribution() {
- final int k = 256;
- final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
-
- final Random rand = new Random(1);
-
- final int n = (3 * k) - 1;
- for (int i = 0; i < n; ++i) {
- final double x = rand.nextGaussian();
- s1.update(x);
- }
-
- assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s1), 0.0, 0.0);
- println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s1));
- }
-
-
- @Test
- public void checkSameDistributionDifferentSketches() {
- final int k = 256;
- final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
- final UpdateDoublesSketch s2 = DoublesSketch.builder().setK(k).build();
-
- final Random rand = new Random(1);
-
- final int n = (3 * k) - 1;
- for (int i = 0; i < n; ++i) {
- final double x = rand.nextGaussian();
- s1.update(x);
- s2.update(x);
- }
-
- assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s2), 0, .01);
- println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s2));
- }
-
- @Test
- public void mediumResolution() {
- final int k = 2048;
- final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
- final UpdateDoublesSketch s2 = DoublesSketch.builder().setK(k).build();
- final double tgtPvalue = .05;
-
- final Random rand = new Random(1);
-
- final int n = (3 * k) - 1;
- for (int i = 0; i < n; ++i) {
- final double x = rand.nextGaussian();
- s1.update(x + .05);
- s2.update(x);
- }
-
- double D = KolmogorovSmirnov.computeKSDelta(s1, s2);
- double thresh = KolmogorovSmirnov.computeKSThreshold(s1, s2, tgtPvalue);
- final boolean reject = KolmogorovSmirnov.kolmogorovSmirnovTest(s1, s2, tgtPvalue);
- println("pVal = " + tgtPvalue + "\nK = " + k + "\nD = " + D + "\nTh = " + thresh
- + "\nNull Hypoth Rejected = " + reject);
- assertFalse(reject);
- }
-
- @Test
- public void highResolution() {
- final int k = 8192;
- final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
- final UpdateDoublesSketch s2 = DoublesSketch.builder().setK(k).build();
- final double tgtPvalue = .05;
-
- final Random rand = new Random(1);
-
- final int n = (3 * k) - 1;
- for (int i = 0; i < n; ++i) {
- final double x = rand.nextGaussian();
- s1.update(x + .05);
- s2.update(x);
- }
-
- double D = KolmogorovSmirnov.computeKSDelta(s1, s2);
- double thresh = KolmogorovSmirnov.computeKSThreshold(s1, s2, tgtPvalue);
- final boolean reject = KolmogorovSmirnov.kolmogorovSmirnovTest(s1, s2, tgtPvalue);
- println("pVal = " + tgtPvalue + "\nK = " + k + "\nD = " + D + "\nTh = " + thresh
- + "\nNull Hypoth Rejected = " + reject);
- assertTrue(reject);
- }
-
-
- @Test
- public void printlnTest() {
- println("PRINTING: "+this.getClass().getName());
- }
-
- /**
- * @param s value to print
- */
- static void println(String s) {
- //System.out.println(s); //disable here
- }
-
-}
diff --git a/src/test/java/org/apache/datasketches/quantilescommon/KolmogorovSmirnovTest.java b/src/test/java/org/apache/datasketches/quantilescommon/KolmogorovSmirnovTest.java
new file mode 100644
index 00000000..eeb005cc
--- /dev/null
+++ b/src/test/java/org/apache/datasketches/quantilescommon/KolmogorovSmirnovTest.java
@@ -0,0 +1,355 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.datasketches.quantilescommon;
+
+import static org.testng.Assert.assertEquals;
+import static org.testng.Assert.assertFalse;
+import static org.testng.Assert.assertTrue;
+
+import java.util.Random;
+
+import org.apache.datasketches.kll.KllDoublesSketch;
+import org.apache.datasketches.kll.KllFloatsSketch;
+import org.apache.datasketches.kll.KllSketch;
+import org.apache.datasketches.quantiles.DoublesSketch;
+import org.apache.datasketches.quantiles.UpdateDoublesSketch;
+import org.testng.annotations.Test;
+
+public class KolmogorovSmirnovTest {
+
+ @Test
+ public void checkDisjointDistributionClassicDoubles() {
+ final int k = 256;
+ final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
+ final UpdateDoublesSketch s2 = DoublesSketch.builder().setK(k).build();
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x + 500);
+ s2.update(x);
+ }
+ final double delta = DoublesSketch.getNormalizedRankError(k, false);
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s2));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s2), 1.0, delta);
+ }
+
+ @Test
+ public void checkDisjointDistributionKllDoubles() {
+ final int k = 256;
+ final KllDoublesSketch s1 = KllDoublesSketch.newHeapInstance(k);
+ final KllDoublesSketch s2 = KllDoublesSketch.newHeapInstance(k);
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x + 500);
+ s2.update(x);
+ }
+ final double delta = KllSketch.getNormalizedRankError(k, false);
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s2));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s2), 1.0, delta);
+ }
+
+ @Test
+ public void checkDisjointDistributionKllFloats() {
+ final int k = 256;
+ final KllFloatsSketch s1 = KllFloatsSketch.newHeapInstance(k);
+ final KllFloatsSketch s2 = KllFloatsSketch.newHeapInstance(k);
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final float x = (float)rand.nextGaussian();
+ s1.update(x + 500);
+ s2.update(x);
+ }
+ final double delta = KllSketch.getNormalizedRankError(k, false);
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s2));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s2), 1.0, delta);
+ }
+
+ @Test
+ public void checkIdenticalDistributionClassicDoubles() {
+ final int k = 256;
+ final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x);
+ }
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s1));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s1), 0.0, 0.0);
+ }
+
+ @Test
+ public void checkIdenticalDistributionKllDoubles() {
+ final int k = 256;
+ final KllDoublesSketch s1 = KllDoublesSketch.newHeapInstance(k);
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x);
+ }
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s1));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s1), 0.0, 0.0);
+ }
+
+ @Test
+ public void checkIdenticalDistributionKllFloats() {
+ final int k = 256;
+ final KllFloatsSketch s1 = KllFloatsSketch.newHeapInstance(k);
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final float x = (float)rand.nextGaussian();
+ s1.update(x);
+ }
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s1));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s1), 0.0, 0.0);
+ }
+
+ @Test
+ public void checkSameDistributionDifferentClassicDoublesSketches() {
+ final int k = 256;
+ final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
+ final UpdateDoublesSketch s2 = DoublesSketch.builder().setK(k).build();
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x);
+ s2.update(x);
+ }
+ final double delta = DoublesSketch.getNormalizedRankError(k, false);
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s2));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s2), 0, delta);
+ }
+
+ @Test
+ public void checkSameDistributionDifferentKllDoublesSketches() {
+ final int k = 256;
+ final KllDoublesSketch s1 = KllDoublesSketch.newHeapInstance(k);
+ final KllDoublesSketch s2 = KllDoublesSketch.newHeapInstance(k);
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x);
+ s2.update(x);
+ }
+ final double delta = KllSketch.getNormalizedRankError(k, false);
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s2));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s2), 0, delta);
+ }
+
+ @Test
+ public void checkSameDistributionDifferentKllFloatsSketches() {
+ final int k = 256;
+ final KllFloatsSketch s1 = KllFloatsSketch.newHeapInstance(k);
+ final KllFloatsSketch s2 = KllFloatsSketch.newHeapInstance(k);
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final float x = (float)rand.nextGaussian();
+ s1.update(x);
+ s2.update(x);
+ }
+ final double delta = KllSketch.getNormalizedRankError(k, false);
+ println("D = " + KolmogorovSmirnov.computeKSDelta(s1, s2));
+ assertEquals(KolmogorovSmirnov.computeKSDelta(s1, s2), 0, delta);
+ }
+
+ @Test
+ public void mediumResolutionClassicDoubles() {
+ final int k = 2048;
+ final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
+ final UpdateDoublesSketch s2 = DoublesSketch.builder().setK(k).build();
+ final double tgtPvalue = .05;
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x + .05);
+ s2.update(x);
+ }
+
+ double D = KolmogorovSmirnov.computeKSDelta(s1, s2);
+ double thresh = KolmogorovSmirnov.computeKSThreshold(s1, s2, tgtPvalue);
+ final boolean reject = KolmogorovSmirnov.kolmogorovSmirnovTest(s1, s2, tgtPvalue);
+ println("pVal = " + tgtPvalue + "\nK = " + k + "\nD = " + D + "\nTh = " + thresh
+ + "\nNull Hypoth Rejected = " + reject);
+ assertFalse(reject);
+ }
+
+ @Test
+ public void mediumResolutionKllDoubles() {
+ final int k = 2048;
+ final KllDoublesSketch s1 = KllDoublesSketch.newHeapInstance(k);
+ final KllDoublesSketch s2 = KllDoublesSketch.newHeapInstance(k);
+ final double tgtPvalue = .05;
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x + .05);
+ s2.update(x);
+ }
+
+ double D = KolmogorovSmirnov.computeKSDelta(s1, s2);
+ double thresh = KolmogorovSmirnov.computeKSThreshold(s1, s2, tgtPvalue);
+ final boolean reject = KolmogorovSmirnov.kolmogorovSmirnovTest(s1, s2, tgtPvalue);
+ println("pVal = " + tgtPvalue + "\nK = " + k + "\nD = " + D + "\nTh = " + thresh
+ + "\nNull Hypoth Rejected = " + reject);
+ assertFalse(reject);
+ }
+
+ @Test
+ public void mediumResolutionKllFloats() {
+ final int k = 2048;
+ final KllFloatsSketch s1 = KllFloatsSketch.newHeapInstance(k);
+ final KllFloatsSketch s2 = KllFloatsSketch.newHeapInstance(k);
+ final double tgtPvalue = .05;
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final float x = (float)rand.nextGaussian();
+ s1.update(x + .05F);
+ s2.update(x);
+ }
+
+ double D = KolmogorovSmirnov.computeKSDelta(s1, s2);
+ double thresh = KolmogorovSmirnov.computeKSThreshold(s1, s2, tgtPvalue);
+ final boolean reject = KolmogorovSmirnov.kolmogorovSmirnovTest(s1, s2, tgtPvalue);
+ println("pVal = " + tgtPvalue + "\nK = " + k + "\nD = " + D + "\nTh = " + thresh
+ + "\nNull Hypoth Rejected = " + reject);
+ assertFalse(reject);
+ }
+
+ @Test
+ public void highResolutionClassicDoubles() {
+ final int k = 8192;
+ final UpdateDoublesSketch s1 = DoublesSketch.builder().setK(k).build();
+ final UpdateDoublesSketch s2 = DoublesSketch.builder().setK(k).build();
+ final double tgtPvalue = .05;
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x + .05);
+ s2.update(x);
+ }
+
+ double D = KolmogorovSmirnov.computeKSDelta(s1, s2);
+ double thresh = KolmogorovSmirnov.computeKSThreshold(s1, s2, tgtPvalue);
+ final boolean reject = KolmogorovSmirnov.kolmogorovSmirnovTest(s1, s2, tgtPvalue);
+ println("pVal = " + tgtPvalue + "\nK = " + k + "\nD = " + D + "\nTh = " + thresh
+ + "\nNull Hypoth Rejected = " + reject);
+ assertTrue(reject);
+ }
+
+ @Test
+ public void highResolutionKllDoubles() {
+ final int k = 8192;
+ final KllDoublesSketch s1 = KllDoublesSketch.newHeapInstance(k);
+ final KllDoublesSketch s2 = KllDoublesSketch.newHeapInstance(k);
+ final double tgtPvalue = .05;
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final double x = rand.nextGaussian();
+ s1.update(x + .05);
+ s2.update(x);
+ }
+
+ double D = KolmogorovSmirnov.computeKSDelta(s1, s2);
+ double thresh = KolmogorovSmirnov.computeKSThreshold(s1, s2, tgtPvalue);
+ final boolean reject = KolmogorovSmirnov.kolmogorovSmirnovTest(s1, s2, tgtPvalue);
+ println("pVal = " + tgtPvalue + "\nK = " + k + "\nD = " + D + "\nTh = " + thresh
+ + "\nNull Hypoth Rejected = " + reject);
+ assertTrue(reject);
+ }
+
+ @Test
+ public void highResolutionKllFloats() {
+ final int k = 8192;
+ final KllFloatsSketch s1 = KllFloatsSketch.newHeapInstance(k);
+ final KllFloatsSketch s2 = KllFloatsSketch.newHeapInstance(k);
+ final double tgtPvalue = .05;
+
+ final Random rand = new Random(1);
+
+ final int n = (3 * k) - 1;
+ for (int i = 0; i < n; ++i) {
+ final float x = (float)rand.nextGaussian();
+ s1.update(x + .05F);
+ s2.update(x);
+ }
+
+ double D = KolmogorovSmirnov.computeKSDelta(s1, s2);
+ double thresh = KolmogorovSmirnov.computeKSThreshold(s1, s2, tgtPvalue);
+ final boolean reject = KolmogorovSmirnov.kolmogorovSmirnovTest(s1, s2, tgtPvalue);
+ println("pVal = " + tgtPvalue + "\nK = " + k + "\nD = " + D + "\nTh = " + thresh
+ + "\nNull Hypoth Rejected = " + reject);
+ assertTrue(reject);
+ }
+
+ @Test
+ public void printlnTest() {
+ println("PRINTING: "+this.getClass().getName());
+ }
+
+ /**
+ * @param s value to print
+ */
+ static void println(String s) {
+ //System.out.println(s); //disable here
+ }
+
+}
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