package service

import (
	"math"
	"testing"
)

func ptr(v float64) *float64 { return &v }

func TestComputeRiskScoreWeights(t *testing.T) {
	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)
	}
	if len(got.Missing) != 0 {
		t.Errorf("全组件可用时不应有 missing，实际 %v", got.Missing)
	}
	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) {
	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 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",
		30.5: "yellow",
		60:   "yellow",
		61:   "orange",
		80:   "orange",
		81:   "red",
		100:  "red",
	}
	for score, want := range cases {
		if got := RiskLevel(score); got != want {
			t.Errorf("RiskLevel(%.1f) = %s, want %s", score, got, want)
		}
	}
}

func TestStageCoefficientMapping(t *testing.T) {
	if StageCoefficient("pupa") <= 0 {
		t.Error("蛹期应有风险系数")
	}
	if StageCoefficient("") != 0 {
		t.Error("空阶段应为 0")
	}
	if StageCoefficient("unknown") != 0 {
		t.Error("未知阶段应为 0")
	}
	if StageCoefficient("pupa") <= StageCoefficient("egg") {
		t.Error("蛹期系数应高于卵期")
	}
}

func TestEnvCoefficientRules(t *testing.T) {
	// 湿度 >=80 → 高（真菌病）
	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(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(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(ptr(25), ptr(60)); c != 0 {
		t.Errorf("舒适环境应为 0，实际 %.2f", c)
	}
	// 缺数据 → 0
	if c := EnvCoefficient(nil, nil); c != 0 {
		t.Errorf("无数据应为 0，实际 %.2f", c)
	}
}