Interpolate merging digest percentiles by centroid weight

pyckle · Jun 13, 2018 · 08f3679 · 08f3679
1 parent b2d0bd2
commit 08f3679
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Showing 2 changed files with 47 additions and 8 deletions.
diff --git a/core/src/main/java/com/tdunning/math/stats/MergingDigest.java b/core/src/main/java/com/tdunning/math/stats/MergingDigest.java
@@ -678,7 +678,9 @@ public double quantile(double q) {
         // at the boundaries, we return min or max
         if (index < weight[0] / 2) {
             assert weight[0] > 0;
-            return min + 2 * index / weight[0] * (mean[0] - min);
+            double z1 = (index / totalWeight) * weight[0];
+            double z2 = ((weight[0] / 2 - index) / totalWeight) * getWeightForMinOrMax(weight[0]);
+            return weightedAverage(min, z2, mean[0], z1);
         }
 
         // in between we interpolate between centroids
@@ -687,8 +689,8 @@ public double quantile(double q) {
             double dw = (weight[i] + weight[i + 1]) / 2;
             if (weightSoFar + dw > index) {
                 // centroids i and i+1 bracket our current point
-                double z1 = index - weightSoFar;
-                double z2 = weightSoFar + dw - index;
+                double z1 = ((index - weightSoFar) / totalWeight) * weight[i + 1];
+                double z2 = ((weightSoFar + dw - index) / totalWeight) * weight[i];
                 return weightedAverage(mean[i], z2, mean[i + 1], z1);
             }
             weightSoFar += dw;
@@ -698,11 +700,28 @@ public double quantile(double q) {
 
         // weightSoFar = totalWeight - weight[n-1]/2 (very nearly)
         // so we interpolate out to max value ever seen
-        double z1 = index - totalWeight - weight[n - 1] / 2.0;
-        double z2 = weight[n - 1] / 2 - z1;
+        double z1 = ((totalWeight - index) / totalWeight) * weight[n - 1];
+        double z2 = (weight[n - 1] / 2 - z1) * getWeightForMinOrMax(weight[n - 1]);
         return weightedAverage(mean[n - 1], z1, max, z2);
     }
 
+    private double getWeightForMinOrMax(double maxWeight) {
+        return Math.min(maxWeight, centroidScaleToQuantile(1 / compression));
+    }
+
+    /**
+     * Takes a centroid scale (the centroid number) and returns the ideal
+     * starting percentile for it.
+     *
+     * @param centroidNumber the number of the centroid
+     * @return the ideal starting percentile for this centroid
+     */
+    private double centroidScaleToQuantile(double centroidNumber) {
+        double k = centroidNumber / compression;
+        double sinePrecalc = Math.sin((k*Math.PI)/2);
+        return sinePrecalc * sinePrecalc;
+    }
+
     @Override
     public int centroidCount() {
         return lastUsedCell;

diff --git a/core/src/test/java/com/tdunning/math/stats/MergingDigestTest.java b/core/src/test/java/com/tdunning/math/stats/MergingDigestTest.java
@@ -122,7 +122,7 @@ public void printQuantiles() throws FileNotFoundException {
         td.setMinMax(0, 10);
         td.add(1);
         td.add(2);
-        td.add(5, 2);
+        td.add(5);
         td.add(6);
         td.add(9);
         td.add(10);
@@ -132,7 +132,7 @@ public void printQuantiles() throws FileNotFoundException {
 
             quantiles.printf("x,q\n");
             cdfs.printf("x,q\n");
-            for (double q = 0; q < 1; q += 1e-3) {
+            for (double q = 1.0 / 12.0; q < 1; q += 1e-3) {
                 double x = td.quantile(q);
                 quantiles.printf("%.3f,%.3f\n", x, q);
 
@@ -145,7 +145,27 @@ public void printQuantiles() throws FileNotFoundException {
             }
         }
 
-        assertEquals(2.0 / 7, td.cdf(3), 1e-9);
+        assertEquals(0.25 + 1.0/18.0, td.cdf(3), 1e-9);
+    }
+
+    @Test
+    public void testCloseTo1QuantileBigWeights() {
+        MergingDigest td = new MergingDigest(200);
+        td.add(1, 1);
+        td.add(2, 100);
+        td.setMinMax(0, 1000);
+        final double quantile = td.quantile(.999);
+        assertTrue("Quantile val incorrect: " + quantile, quantile < 101);
+    }
+
+    @Test
+    public void testCloseToZeroQuantileBigWeights() {
+        MergingDigest td = new MergingDigest(200);
+        td.add(1000, 100);
+        td.add(1001, 1);
+        td.setMinMax(0, 1002);
+        final double quantile = td.quantile(.001);
+        assertTrue("Quantile val incorrect: " + quantile, quantile > 999);
     }
 
     @Override