l_ai_knowledge/internal/application/service/metric/mrr_test.go

73 lines
1.4 KiB
Go

package metric
import (
"testing"
"knowlege-lsxd/internal/types"
)
func TestMRRMetric_Compute(t *testing.T) {
tests := []struct {
name string
input *types.MetricInput
expected float64
}{
{
name: "perfect match - first position",
input: &types.MetricInput{
RetrievalGT: [][]int{{1, 2}},
RetrievalIDs: []int{1, 2, 3},
},
// RR = 1/1 = 1.0
expected: 1.0,
},
{
name: "match at second position",
input: &types.MetricInput{
RetrievalGT: [][]int{{1, 2}},
RetrievalIDs: []int{3, 1, 2},
},
// RR = 1/2 = 0.5
expected: 0.5,
},
{
name: "no match",
input: &types.MetricInput{
RetrievalGT: [][]int{{1, 2}},
RetrievalIDs: []int{3, 4},
},
expected: 0.0,
},
{
name: "multiple queries",
input: &types.MetricInput{
RetrievalGT: [][]int{
{1, 2}, // RR = 1/1 = 1.0
{3, 4}, // RR = 1/2 = 0.5
},
RetrievalIDs: []int{1, 3, 2, 4},
},
// MRR = (1.0 + 0.5)/2 = 0.75
expected: 0.75,
},
{
name: "empty ground truth",
input: &types.MetricInput{
RetrievalGT: [][]int{},
RetrievalIDs: []int{1, 2},
},
expected: 0.0,
},
}
metric := NewMRRMetric()
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got := metric.Compute(tt.input)
if !almostEqual(got, tt.expected, 1e-6) {
t.Errorf("Compute() = %v, want %v", got, tt.expected)
}
})
}
}