leerho commented on code in PR #535: URL: https://github.com/apache/datasketches-java/pull/535#discussion_r1541395138
########## 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) { Review Comment: Fixed. -- This is an automated message from the Apache Git Service. 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