Merge pull request #3 from geniussportsgroup/develop

Develop

percentile_test.go

@@ -0,0 +1,75 @@
+package treaps
+
+import (
+	"github.com/stretchr/testify/assert"
+	"math/rand"
+	"testing"
+)
+
+// This example shows how to get the some percentiles of a sample of a million of random heights
+
+// The following type simulate the representation of the height of a person
+type Sample struct {
+	id     int // id of person
+	height int // height in millimeters
+}
+
+const N = int(1e7)
+
+func createSamples(n int) *Treap {
+
+	set := NewTreap(func(i1, i2 interface{}) bool {
+		p1, ok := i1.(*Sample)
+		if !ok {
+			panic("First parameter is not of type *Sample")
+		}
+		p2, ok := i2.(*Sample)
+		if !ok {
+			panic("Second parameter is not of type *Sample")
+		}
+		return p1.height < p2.height
+	})
+
+	// we will generate 1e6 samples of random heights according to a normal dist with mean 1600 mm
+	// and standard deviation of 400 mm/
+	// Pay attention to the fact that heights can be repeat. So we must use InsertDup
+	for id := 0; id < n; id++ {
+		set.InsertDup(&Sample{
+			id:     id,
+			height: int(rand.NormFloat64()*400 + 1600),
+		})
+	}
+
+	return set
+}
+
+func TestExample_99Percentiles(t *testing.T) {
+
+	set := createSamples(N)
+
+	posOfPercentile99 := int((set.Size() * 99) / 100) // index of first item belonging to 99 percentile
+
+	// we have two ways for getting the samples included in the 99 percentile
+
+	percentile99Size := set.Size() - posOfPercentile99
+
+	// First we can use the method choose(i) for getting all the samples. This way has complexity
+	// O(n log(N)) where n is the n ~ 0.01*N and N is the number of samples, which definitely is faster
+	// than O(N log N) in time and O(N) in space if you take the elements and sort them
+	p99Slice := make([]Sample, 0)
+	for i := posOfPercentile99; i < set.Size(); i++ {
+		samplePtr := set.Choose(i)
+		p99Slice = append(p99Slice, *samplePtr.(*Sample))
+	}
+
+	// The second method is just to extract the whole percentile from the set, with the eventual
+	// disadvantage that the set is modified, but with the advantage that the set is gotten in O(log n)
+	p99 := set.ExtractRange(posOfPercentile99, set.Size()-1)
+
+	assert.Equal(t, percentile99Size, p99.Size())
+	assert.Equal(t, N-p99.Size(), set.Size())
+
+	for i, it := 0, NewIterator(p99); i < len(p99Slice); i, it = i+1, it.Next() {
+		assert.Equal(t, p99Slice[i].id, it.GetCurr().(*Sample).id)
+	}
+}

simple_example_test.go

@@ -0,0 +1 @@
+package treaps