feat: 修复 AI 风险语义并隔离 Mock 数据

server-go/internal/service/risk_test.go

@@ -1,43 +1,120 @@
 package service
 
-import "testing"
+import (
+	"math"
+	"testing"
+)
 
-func f(v float64) *float64 { return &v }
+func ptr(v float64) *float64 { return &v }
 
 func TestComputeRiskScoreWeights(t *testing.T) {
-	// 全 1：0.5*1 + 0.2*1 + 0.15*1 + 0.15*1 = 1 → 100
-	if s := ComputeRiskScore(RiskInput{AI: 1, Env: 1, Stage: 1, Uniformity: 1}); s != 100 {
-		t.Errorf("全 1 应得 100，实际 %.2f", s)
+	got := ComputeRiskScore(RiskInput{AI: ptr(1), Env: ptr(1), Stage: ptr(1), Uniformity: ptr(1)})
+	if got.Score != 100 {
+		t.Errorf("全 1 应得 100，实际 %.2f", got.Score)
 	}
-	// 仅 AI 置信度 1：0.5*1 = 0.5 → 50
-	if s := ComputeRiskScore(RiskInput{AI: 1}); s != 50 {
-		t.Errorf("仅 AI=1 应得 50，实际 %.2f", s)
+	if len(got.Missing) != 0 {
+		t.Errorf("全组件可用时不应有 missing，实际 %v", got.Missing)
 	}
-	// 0.5*0.8 + 0.2*0.5 = 0.5
-	if s := ComputeRiskScore(RiskInput{AI: 0.8, Env: 0.5}); s != 50 {
-		t.Errorf("0.8/0.5 应得 50，实际 %.2f", s)
+	if got.Components["aiAbnormalProbability"] == nil || got.Components["uniformity"] == nil {
+		t.Errorf("全组件可用时 components 不应为 null: %v", got.Components)
+	}
+}
+
+func TestComputeRiskScoreNormalizesMissingComponents(t *testing.T) {
+	got := ComputeRiskScore(RiskInput{AI: ptr(1)})
+	if got.Score != 100 {
+		t.Errorf("仅 AI=1 归一化后应得 100，实际 %.2f", got.Score)
+	}
+	if len(got.Missing) != 3 {
+		t.Errorf("missing 应为 environment/stage/uniformity，实际 %v", got.Missing)
+	}
+	if got.Components["environment"] != nil {
+		t.Error("缺失 environment 应序列化为 null")
+	}
+}
+
+func TestHealthyHighConfidenceDoesNotIncreaseRisk(t *testing.T) {
+	got := AbnormalProbability([]AIDetection{{ClassName: "healthy", Confidence: .95}})
+	if got != 0 {
+		t.Fatalf("healthy 高置信度不应产生异常概率，实际 %v", got)
+	}
+	assessment := ComputeRiskScore(RiskInput{AI: ptr(got)})
+	if assessment.Score != 0 {
+		t.Fatalf("healthy 高置信度风险分应为 0，实际 %.2f", assessment.Score)
+	}
+}
+
+func TestSickHighConfidenceIncreasesRisk(t *testing.T) {
+	got := AbnormalProbability([]AIDetection{{ClassName: "sick", Confidence: .9}})
+	if got != .9 {
+		t.Fatalf("sick 高置信度异常概率应为 0.9，实际 %v", got)
+	}
+	assessment := ComputeRiskScore(RiskInput{AI: ptr(got)})
+	if assessment.Score != 90 {
+		t.Fatalf("仅 AI=0.9 归一化后风险分应为 90，实际 %.2f", assessment.Score)
+	}
+}
+
+func TestAbnormalProbabilityIgnoresUnknown(t *testing.T) {
+	if got := AbnormalProbability([]AIDetection{{ClassName: "unknown", Confidence: .9}}); got != 0 {
+		t.Errorf("unknown 不应贡献异常概率，实际 %v", got)
+	}
+}
+
+func TestComputeRiskScoreMissingAll(t *testing.T) {
+	got := ComputeRiskScore(RiskInput{})
+	if got.Score != 0 {
+		t.Errorf("无任何组件时分数应为 0，实际 %.2f", got.Score)
+	}
+	if got.Confidence != "unknown" {
+		t.Errorf("无 AI 组件时 confidence 应为 unknown，实际 %s", got.Confidence)
+	}
+	if len(got.Missing) != 4 {
+		t.Errorf("missing 应为 4 项，实际 %v", got.Missing)
 	}
 }
 
 func TestComputeRiskScoreClamps(t *testing.T) {
-	if s := ComputeRiskScore(RiskInput{AI: 2, Env: 2, Stage: 2, Uniformity: 2}); s > 100 {
-		t.Errorf("应钳制到 100，实际 %.2f", s)
+	got := ComputeRiskScore(RiskInput{AI: ptr(2), Env: ptr(2), Stage: ptr(2), Uniformity: ptr(2)})
+	if got.Score > 100 {
+		t.Errorf("应钳制到 100，实际 %.2f", got.Score)
 	}
-	if s := ComputeRiskScore(RiskInput{AI: -1}); s < 0 {
-		t.Errorf("应钳制到 0，实际 %.2f", s)
+	if got := ComputeRiskScore(RiskInput{AI: ptr(-1)}).Score; got < 0 {
+		t.Errorf("应钳制到 0，实际 %.2f", got)
+	}
+}
+
+func TestRiskConfidenceLowMediumUnknown(t *testing.T) {
+	if got := RiskConfidence(RiskInput{}); got != "unknown" {
+		t.Errorf("无 AI 应为 unknown，实际 %s", got)
+	}
+	if got := RiskConfidence(RiskInput{AI: ptr(0.2)}); got != "low" {
+		t.Errorf("低异常概率应为 low，实际 %s", got)
+	}
+	if got := RiskConfidence(RiskInput{AI: ptr(0.9)}); got != "medium" {
+		t.Errorf("高异常概率当前最多应为 medium，实际 %s", got)
+	}
+}
+
+func TestComputeRiskScoreBoundaryUsesWeightNormalization(t *testing.T) {
+	// 0.5*0.8 + 0.2*0.5 的可用权重为 0.7：0.5/0.7 = 71.43
+	got := ComputeRiskScore(RiskInput{AI: ptr(0.8), Env: ptr(0.5)})
+	want := 50.0 / 0.7
+	if math.Abs(got.Score-want) > 0.01 {
+		t.Errorf("归一化应得 %.2f，实际 %.2f", want, got.Score)
 	}
 }
 
 func TestRiskLevelBoundaries(t *testing.T) {
 	cases := map[float64]string{
-		0:   "green",
-		30:  "green",
+		0:    "green",
+		30:   "green",
 		30.5: "yellow",
-		60:  "yellow",
-		61:  "orange",
-		80:  "orange",
-		81:  "red",
-		100: "red",
+		60:   "yellow",
+		61:   "orange",
+		80:   "orange",
+		81:   "red",
+		100:  "red",
 	}
 	for score, want := range cases {
 		if got := RiskLevel(score); got != want {
@@ -63,19 +140,19 @@ func TestStageCoefficientMapping(t *testing.T) {
 
 func TestEnvCoefficientRules(t *testing.T) {
 	// 湿度 >=80 → 高（真菌病）
-	if c := EnvCoefficient(f(25), f(85)); c < 0.7 {
+	if c := EnvCoefficient(ptr(25), ptr(85)); c < 0.7 {
 		t.Errorf("湿度 85 应 ≥0.7，实际 %.2f", c)
 	}
 	// 湿度 75-80 → 中
-	if c := EnvCoefficient(f(25), f(78)); c < 0.3 {
+	if c := EnvCoefficient(ptr(25), ptr(78)); c < 0.3 {
 		t.Errorf("湿度 78 应 ≥0.3，实际 %.2f", c)
 	}
 	// 温度突变 >30 → 中（核型多角体病诱发）
-	if c := EnvCoefficient(f(32), f(60)); c < 0.3 {
+	if c := EnvCoefficient(ptr(32), ptr(60)); c < 0.3 {
 		t.Errorf("温度 32 应 ≥0.3，实际 %.2f", c)
 	}
 	// 舒适环境 → 0
-	if c := EnvCoefficient(f(25), f(60)); c != 0 {
+	if c := EnvCoefficient(ptr(25), ptr(60)); c != 0 {
 		t.Errorf("舒适环境应为 0，实际 %.2f", c)
 	}
 	// 缺数据 → 0