Fix example function names, stabilize tests, and relax floating-point comparisons

CHANGELOG.md

@@ -9,7 +9,11 @@ The format is based on Keep a Changelog and this project adheres to Semantic Ver
 - pkg.go.dev Examples: `ExampleNewKDTreeFromDim_Insert`, `ExampleKDTree_TiesBehavior`, `ExampleKDTree_Radius_none`.
 - Lint: enable `errcheck` in `.golangci.yml` with test-file exclusion to reduce noise.
 - CI: enable module cache in `actions/setup-go` to speed up workflows.
-- Docs: README cross-link to Performance page and add a concise “Choosing a metric” tip section.
+
+### Fixed
+- go vet failures in examples due to misnamed `Example*` functions; renamed to avoid referencing non-existent methods and identifiers.
+- Stabilized `ExampleKDTree_Nearest` to avoid a tie case; adjusted query and expected output.
+- Relaxed floating-point equality in `TestWeightedCosineDistance_Basics` to use an epsilon, avoiding spurious failures on some toolchains.
 
 ## [0.3.0] - 2025-11-03
 ### Added

examples_test.go

@@ -40,9 +40,9 @@ func ExampleKDTree_Nearest() {
 		{ID: "y", Coords: []float64{2, 0}, Value: 2},
 	}
 	tr, _ := poindexter.NewKDTree(pts, poindexter.WithMetric(poindexter.EuclideanDistance{}))
-	p, d, ok := tr.Nearest([]float64{1, 0})
+	p, d, ok := tr.Nearest([]float64{1.4, 0})
 	fmt.Printf("ok=%v id=%s d=%.1f", ok, p.ID, d)
-	// Output: ok=true id=y d=1.0
+	// Output: ok=true id=y d=0.6
 }
 
 func ExampleKDTree_KNearest() {
@@ -69,7 +69,7 @@ func ExampleKDTree_Radius() {
 	// Output: 2 a b
 }
 
-func ExampleKDTree_InsertDeleteByID() {
+func ExampleKDTree_DeleteByID() {
 	pts := []poindexter.KDPoint[string]{
 		{ID: "A", Coords: []float64{0}, Value: "a"},
 	}
@@ -204,7 +204,7 @@ func ExampleBuild4DWithStats() {
 	// Output: 4
 }
 
-func ExampleNewKDTreeFromDim_Insert() {
+func ExampleNewKDTreeFromDim() {
 	// Construct an empty 2D tree, insert a point, then query.
 	tr, _ := poindexter.NewKDTreeFromDim[string](2)
 	tr.Insert(poindexter.KDPoint[string]{ID: "A", Coords: []float64{0.1, 0.2}, Value: "alpha"})
@@ -213,7 +213,7 @@ func ExampleNewKDTreeFromDim_Insert() {
 	// Output: ok=true id=A dim=2 len=1
 }
 
-func ExampleKDTree_TiesBehavior() {
+func Example_tiesBehavior() {
 	// Two points equidistant from the query; tie ordering is arbitrary,
 	// but distances are equal.
 	pts := []poindexter.KDPoint[int]{

kdtree_nd_test.go

@@ -47,8 +47,9 @@ func TestWeightedCosineDistance_Basics(t *testing.T) {
 	a := []float64{1, 0}
 	b := []float64{1, 0}
 	d := w.Distance(a, b)
-	if d != 0 {
+	// allow tiny floating-point noise
-		t.Fatalf("expected 0, got %v", d)
+	if d > 1e-12 {
+		t.Fatalf("expected ~0, got %v", d)
 	}
 	// orthogonal remains ~1 regardless of weights for these axes
 	b = []float64{0, 3}