feat(stats): #10 第②层 —— 统计页按设备过滤(per-device 本地日曲线)

镜像账户级时区曲线到「按设备」:
- migration 000018 `usage_device_hourly`(每设备 UTC 小时桶,稀疏)。
- ReportUsage deviceID>0 时加 AccumulateDeviceHourly;NodeStore 接口+impl+mock。
- usage.Store.DeviceHourlyRange(JOIN devices 校验归属+解析 uuid→id);UsageCurve
  增 deviceUUID 形参:空=账户级,非空=该设备本地日曲线(分桶逻辑复用)。
- /v1/usage?device=<uuid>;客户端 account_api.usage(device)、usageProvider key 改
  记录 (days,device)、stats_page 接 statsDeviceProvider → 选设备即重取该设备曲线。
测试:per-device 曲线隔离+归属校验(A的设备不进B)、UsageCurve(deviceUUID)、
migration v18、客户端 widget(选设备→/v1/usage 带 device=)。全量 go/flutter 绿。

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

server/internal/usage/service.go

@@ -53,7 +53,8 @@ type UsagePoint struct {
 // It reads UTC hourly buckets (usage_hourly) and re-aggregates by local calendar
 // day, so "today" matches the user's local date regardless of server timezone
 // (fixes "29号却显示28号数据"). offsetMin out of ±14h falls back to 0 (UTC).
-func (svc *Service) UsageCurve(ctx context.Context, userID int64, days, offsetMin int) ([]UsagePoint, *apierr.Error) {
+// deviceUUID == "" → account-level curve; non-empty → that device's curve only.
+func (svc *Service) UsageCurve(ctx context.Context, userID int64, days, offsetMin int, deviceUUID string) ([]UsagePoint, *apierr.Error) {
 	if days < 1 {
 		days = 7
 	}
@@ -73,7 +74,13 @@ func (svc *Service) UsageCurve(ctx context.Context, userID int64, days, offsetMi
 	fromHour := fromLocal.UTC().Unix() / 3600
 	toHour := now.Unix() / 3600
 
-	rows, err := svc.store.HourlyRange(ctx, userID, fromHour, toHour)
+	var rows []HourBucket
+	var err error
+	if deviceUUID == "" {
+		rows, err = svc.store.HourlyRange(ctx, userID, fromHour, toHour)
+	} else {
+		rows, err = svc.store.DeviceHourlyRange(ctx, userID, deviceUUID, fromHour, toHour)
+	}
 	if err != nil {
 		return nil, apierr.ErrInternal
 	}