Blob summary_test.go
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package tdigest import ( "math" "math/rand" "sort" "testing" ) func TestBasics(t *testing.T) { s := newSummary(2) err := s.Add(1, 1) if err != nil { t.Errorf("Failed to add simple item") } if s.Add(math.NaN(), 1) == nil { t.Errorf("Adding math.NaN() shouldn't be allowed") } if s.Add(1, 0) == nil { t.Errorf("Adding count=0 shouldn't be allowed") } } func checkSorted(s *summary, t *testing.T) { if !sort.Float64sAreSorted(s.means) { t.Fatalf("Keys are not sorted! %v", s.means) } } func TestCore(t *testing.T) { testData := make(map[float64]uint64) const maxDataSize = 10000 s := newSummary(maxDataSize) checkSorted(s, t) if s.Len() != 0 { t.Errorf("Initial size should be zero regardless of capacity. Got %d", s.Len()) } // construct a summary made of unique items only for i := 0; i < maxDataSize; i++ { k := rand.Float64() v := rand.Uint64() _, exists := testData[k] if !exists { _ = s.Add(k, v) testData[k] = v } } checkSorted(s, t) if s.Len() != len(testData) { t.Errorf("Got Len() == %d. Expected %d", s.Len(), len(testData)) } for k, v := range testData { i := s.findIndex(k) if i == s.Len() { t.Errorf("Couldn't find previously added key on summary") continue } if s.means[i] != k || s.counts[i] != v { t.Errorf("Wanted to find {%.4f,%d}, but found {%.4f,%d} instead", k, v, s.means[i], s.counts[i]) } } } func TestSetAtNeverBreaksSorting(t *testing.T) { s := newSummary(10) for _, i := range []float64{10, 10, 10, 10, 10} { _ = s.Add(i, 1) } s.setAt(0, 30, 1) checkSorted(s, t) s.setAt(s.Len()-1, 0, 1) checkSorted(s, t) s.setAt(3, 10.1, 1) checkSorted(s, t) s.setAt(3, 9.9, 1) checkSorted(s, t) } func TestForEach(t *testing.T) { s := newSummary(10) for _, i := range []uint64{1, 2, 3, 4, 5, 6} { _ = s.Add(float64(i), i*10) } c := 0 s.ForEach(func(mean float64, count uint64) bool { c++ return false }) if c != 1 { t.Errorf("ForEach must exit early if the closure returns false") } var tot uint64 s.ForEach(func(mean float64, count uint64) bool { tot += count return true }) if tot != 210 { t.Errorf("ForEach must walk through the whole data if it always returns true") } } func TestFloorSum(t *testing.T) { s := newSummary(100) var total uint64 for i := 0; i < 100; i++ { count := uint64(rand.Intn(10)) + 1 _ = s.Add(rand.Float64(), count) total += count } idx, _ := s.FloorSum(-1) if idx != -1 { t.Errorf("Expected no centroid to satisfy -1 but got index=%d", idx) } for i := float64(0); i < float64(total)+10; i++ { node, _ := s.FloorSum(i) if s.HeadSum(node) > i { t.Errorf("headSum(%d)=%.0f (>%.0f)", node, s.HeadSum(node), i) } if node+1 < s.Len() && s.HeadSum(node+1) <= i { t.Errorf("headSum(%d)=%.0f (>%.0f)", node+1, s.HeadSum(node+1), i) } } } func TestFloor(t *testing.T) { s := newSummary(200) for i := float64(0); i < 101; i++ { _ = s.Add(i/2.0, 1) } if s.Floor(-30) != -1 { t.Errorf("Shouldn't have found a floor index. Got %d", s.Floor(-30)) } for i := 0; i < s.Len(); i++ { m := s.means[i] f := s.means[s.Floor(m+0.1)] if m != f { t.Errorf("Erm, %.4f != %.4f", m, f) } } } func TestAdjustLeftRight(t *testing.T) { keys := []float64{1, 2, 3, 4, 9, 5, 6, 7, 8} counts := []uint64{1, 2, 3, 4, 9, 5, 6, 7, 8} s := summary{means: keys, counts: counts} s.adjustRight(4) if !sort.Float64sAreSorted(s.means) || s.counts[4] != 5 { t.Errorf("adjustRight should have fixed the keys/counts state. %v %v", s.means, s.counts) } keys = []float64{1, 2, 3, 4, 0, 5, 6, 7, 8} counts = []uint64{1, 2, 3, 4, 0, 5, 6, 7, 8} s = summary{means: keys, counts: counts} s.adjustLeft(4) if !sort.Float64sAreSorted(s.means) || s.counts[4] != 4 { t.Errorf("adjustLeft should have fixed the keys/counts state. %v %v", s.means, s.counts) } } |