[阶段8] 新增每日数据模块；趋势改为全指标并列 + 周期聚合

每日数据（新页面 /daily）:
- 按活动/能量/心率/压力/睡眠/血氧呼吸/训练七组，列出全部 40 项指标
- 日期选择器 + 前后一天翻页；"只显示有数据的指标"开关
- 附当天的运动记录明细
- 标题处显示当天记录到多少项，缺数据一目了然

趋势（重写）:
- 15 组指标全部并列展示，不再一次只能看一个
- 标签可逐个隐藏/显示，选择存入 localStorage（每次刷新都重置的
  选择算不上偏好）；提供全选/全不选
- 两级筛选：范围（一月/一季/半年/一年/两年）× 周期（每天/每 7 天/
  每月/每季度）。周期选项按范围过滤，避免出现"近一月按季度聚合"
- 所有图表共用同一份聚合结果，一行筛选器统摄全部图表

聚合口径（lib/aggregate.ts）:
- 无论累计型还是速率型指标，一律折算为"周期内日均"，这样 30 天的
  月份和 31 天的月份不会仅因日历差 3%
- 周按最新一天往回切，而不是按自然周一 —— 否则开头会出现一个半空
  的桶，看起来像低谷，其实只是窗口起点
- 累计型指标的统计标签写作"日均"而非"平均"，读者不必猜口径

fix(viz): 聚合后柱形/面积图掩盖了变化
- 柱形与面积都以延展量编码大小，必须从 0 起；而一年的月均步数都在
  9,590~12,701 之间，画出来几乎一样高，恰恰看不见要看的变化
- 聚合视图改用折线：折线编码位置而非延展量，非零轴是正当的。
  改后 y 轴自动落在 9350~12750，走势清晰可读

fix(health): 运动记录按日期筛选时 500
- get_activities 复用了按 date 列过滤的子句，但 activities 表只有
  start_time，报 "Unknown column 'date'"。此前唯一的调用方不传
  日期，所以一直没暴露，每日数据页一传就炸
- 上界改用次日零点的开区间：SQLite 按字符串比较，而存储的分隔符
  可能是 'T'(0x54) 也可能是空格(0x20)，写成 "end 23:59:59" 会让
  当天 18:30 的记录排在上界之后而被排除在自己那天之外

tests (+6, 共 305): 运动记录的单日范围、上下界闭合、仅起点/仅终点、
不传范围返回全部、端点级验证

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

client/src/lib/aggregate.ts

@@ -0,0 +1,126 @@
+import { HealthDay } from '../services/api';
+
+export type Granularity = 'day' | 'week' | 'month' | 'quarter' | 'year';
+
+export const GRANULARITIES: Array<{ id: Granularity; label: string; days: number }> = [
+  { id: 'day', label: '每天', days: 1 },
+  { id: 'week', label: '每 7 天', days: 7 },
+  { id: 'month', label: '每月', days: 30 },
+  { id: 'quarter', label: '每季度', days: 91 },
+  { id: 'year', label: '每年', days: 365 },
+];
+
+/**
+ * Which metrics are counts that accumulate over a day, and which are rates or
+ * levels that only make sense as an average.
+ *
+ * The distinction matters once days are bucketed: summing a week of step
+ * counts is meaningful, summing a week of resting heart rates is nonsense.
+ * Both are still reported *per day* so buckets of different length stay
+ * comparable — a 30-day month and a 31-day month should not differ by 3%
+ * purely because of the calendar.
+ */
+const CUMULATIVE = new Set([
+  'steps', 'distanceMeters', 'caloriesBurned', 'activeCalories', 'bmrCalories',
+  'floorsAscended', 'floorsDescended', 'intensityMinutes',
+  'sedentarySeconds', 'activeSeconds',
+]);
+
+export function isCumulative(key: string) {
+  return CUMULATIVE.has(key);
+}
+
+function startOfBucket(date: Date, g: Granularity, anchor: Date): Date {
+  const d = new Date(date);
+  d.setHours(0, 0, 0, 0);
+  if (g === 'day') return d;
+  if (g === 'month') return new Date(d.getFullYear(), d.getMonth(), 1);
+  if (g === 'quarter') {
+    return new Date(d.getFullYear(), Math.floor(d.getMonth() / 3) * 3, 1);
+  }
+  if (g === 'year') return new Date(d.getFullYear(), 0, 1);
+  // Weeks are counted back from the newest day rather than from a calendar
+  // Monday, so "每 7 天" always means the last 7 days, the 7 before that, and
+  // so on — a half-empty leading bucket would read as a slump that is really
+  // just where the window happened to start.
+  const diffDays = Math.floor((anchor.getTime() - d.getTime()) / 86400000);
+  const bucket = new Date(anchor);
+  bucket.setHours(0, 0, 0, 0);
+  bucket.setDate(bucket.getDate() - Math.floor(diffDays / 7) * 7 - 6);
+  return bucket;
+}
+
+function labelFor(start: Date, g: Granularity): string {
+  const mm = String(start.getMonth() + 1).padStart(2, '0');
+  const dd = String(start.getDate()).padStart(2, '0');
+  if (g === 'day') return `${mm}-${dd}`;
+  if (g === 'week') return `${mm}-${dd}`;
+  if (g === 'month') return `${start.getFullYear()}-${mm}`;
+  if (g === 'quarter') return `${start.getFullYear()} Q${Math.floor(start.getMonth() / 3) + 1}`;
+  return String(start.getFullYear());
+}
+
+export interface Bucket {
+  key: string;
+  label: string;
+  start: string;
+  end: string;
+  /** Days in the bucket that carried at least one value. */
+  days: number;
+  values: Record<string, number | null>;
+}
+
+/**
+ * Group days into buckets and reduce each metric to a per-day figure.
+ *
+ * Every metric — cumulative or not — comes out as a daily average, so the
+ * y-axis keeps the same unit and meaning whichever granularity is selected.
+ */
+export function aggregate(
+  days: HealthDay[],
+  granularity: Granularity,
+  keys: string[]
+): Bucket[] {
+  if (days.length === 0) return [];
+
+  const anchor = new Date(days[days.length - 1].date);
+  anchor.setHours(0, 0, 0, 0);
+
+  const groups = new Map<string, { start: Date; rows: HealthDay[] }>();
+  for (const row of days) {
+    const start = startOfBucket(new Date(row.date), granularity, anchor);
+    const key = start.toISOString().slice(0, 10);
+    if (!groups.has(key)) groups.set(key, { start, rows: [] });
+    groups.get(key)!.rows.push(row);
+  }
+
+  return [...groups.entries()]
+    .sort(([a], [b]) => a.localeCompare(b))
+    .map(([key, { start, rows }]) => {
+      const values: Record<string, number | null> = {};
+      for (const metric of keys) {
+        const present = rows
+          .map((r) => (r as any)[metric])
+          .filter((v): v is number => typeof v === 'number');
+        values[metric] = present.length
+          ? present.reduce((a, b) => a + b, 0) / present.length
+          : null;
+      }
+      return {
+        key,
+        label: labelFor(start, granularity),
+        start: rows[0].date,
+        end: rows[rows.length - 1].date,
+        days: rows.length,
+        values,
+      };
+    });
+}
+
+/** Pick the coarsest granularity that keeps a window readable. */
+export function suggestGranularity(dayCount: number): Granularity {
+  if (dayCount <= 31) return 'day';
+  if (dayCount <= 120) return 'week';
+  if (dayCount <= 400) return 'month';
+  return 'quarter';
+}