Initial commit of akmon project

2026-01-20 08:04:15 +08:00
commit 77a2bab985
1309 changed files with 343305 additions and 0 deletions
--- a/uts/utils/chartDataUtils.uts
+++ b/uts/utils/chartDataUtils.uts
@@ -0,0 +1,482 @@
+/**
+ * 健康数据图表处理工具
+ * 提供将原始健康数据转换为ak-charts显示格式的功能
+ */
+
+import type { HealthData } from '../../uni_modules/ak-sbsrv/utssdk/interface.uts'
+import type { ChartOption, ChartType } from '../../uni_modules/ak-charts/interface.uts'
+
+type MultiMetricBucket = {
+  heart?: number[]
+  spo2?: number[]
+  speed?: number[]
+  steps?: number[]
+}
+
+// Re-export ChartOption for use in other modules
+export type { ChartOption, ChartType }
+
+/**
+ * 心率数据处理配置
+ */
+export type HeartRateChartConfig = {
+  maxPoints?: number; // 最大显示点数，默认50
+  frequency?: number; // 数据频率控制，每N个点取一个，默认1（全部）
+  color?: string; // 图表颜色，默认'#FF6384'
+}
+
+/**
+ * 血氧数据处理配置
+ */
+export type Spo2ChartConfig = {
+  maxPoints?: number; // 最大显示点数，默认50
+  frequency?: number; // 数据频率控制，默认1
+  color?: string; // 图表颜色，默认'#36A2EB'
+}
+
+/**
+ * 步数数据处理配置
+ */
+export type StepsChartConfig = {
+  maxPoints?: number; // 最大显示点数，默认50
+  frequency?: number; // 数据频率控制，默认1
+  color?: string; // 图表颜色，默认'#FFCE56'
+}
+
+/**
+ * 处理心率数据为图表格式
+ * @param healthDataArray 健康数据数组
+ * @param config 配置选项
+ * @returns ChartOption对象
+ */
+export function processHeartRateData(
+  healthDataArray: HealthData[],
+  config: HeartRateChartConfig = {}
+): ChartOption {
+  const {
+    maxPoints = 100, // 增加到100个点
+    frequency = 1,
+    color = '#FF6384'
+  } = config
+
+  // 兼容性：如果传入frequency作为时间间隔（1或5秒），则使用时间分桶
+  // frequency字段 legacy 用法仍然支持按索引采样
+  const freq = frequency
+  const useBucket = freq >= 1 && freq <= 10
+
+  if (!useBucket) {
+    // legacy 行为：按索引采样
+    const heartRateData = healthDataArray
+      .filter(data => data.type === 'heart' && data.heartRate != null)
+      .filter((_, index) => index % frequency === 0)
+      .slice(-maxPoints)
+
+    const data = heartRateData.map(item => item.heartRate!)
+    const labels = heartRateData.map((_, index) => ((index + 1) % 10 === 0 ? `${index + 1}` : ''))
+    return { type: 'line' as ChartType, data, labels, color }
+  }
+
+  // 使用时间分桶（默认1s或5s）: 将心率按时间区间取最大值
+  const intervalSeconds = Math.max(1, Math.floor(freq))
+  const intervalMs = intervalSeconds * 1000
+  const buckets = new Map<number, number[]>()
+  for (let i = 0; i < healthDataArray.length; i++) {
+    const d = healthDataArray[i]
+    if (d.type !== 'heart' || d.heartRate == null) continue
+    const timestamp = d.timestamp
+    const ts = (timestamp == null) ? Date.now() : (typeof timestamp === 'number' ? timestamp : new Date(timestamp as string).getTime())
+    const key = Math.floor(ts / intervalMs) * intervalMs
+    if (!buckets.has(key)) buckets.set(key, [])
+    const heartRateValue = d.heartRate != null ? Number.parseFloat(d.heartRate.toString()) : 0
+    buckets.get(key)!.push(heartRateValue)
+  }
+
+  // 按时间排序并只取最新maxPoints
+  const keys: number[] = []
+  buckets.forEach((_, key) => { keys.push(key) })
+  keys.sort((a, b) => a - b)
+  const slicedKeys = keys.slice(-maxPoints)
+
+  const data: number[] = []
+  const labels: string[] = []
+  for (let i = 0; i < slicedKeys.length; i++) {
+    const key = slicedKeys[i]
+      const arr = (buckets.get(key) != null) ? buckets.get(key)! : []
+  let maxValue = NaN
+    for (let j = 0; j < arr.length; j++) {
+        const num = arr[j] as number
+      if (isNaN(num)) continue
+      if (isNaN(maxValue) || num > maxValue) {
+        maxValue = num
+      }
+    }
+    data.push(maxValue)
+    const labelDate = new Date(key)
+    const ss = labelDate.getSeconds().toString().padStart(2, '0')
+    const mm = labelDate.getMinutes().toString().padStart(2, '0')
+    labels.push(`${mm}:${ss}`)
+  }
+  return { type: 'line' as ChartType, data, labels, color }
+}
+
+/**
+ * 处理血氧数据为图表格式
+ * @param healthDataArray 健康数据数组
+ * @param config 配置选项
+ * @returns ChartOption对象
+ */
+export function processSpo2Data(
+  healthDataArray: HealthData[],
+  config: Spo2ChartConfig = {}
+): ChartOption {
+  const {
+    maxPoints = 100, // 增加到100个点
+    frequency = 1,
+    color = '#36A2EB'
+  } = config
+  // 使用时间分桶（如果frequency为秒级1或5）取区间内最大值（或最后值）
+  const freq = frequency
+  const useBucket = freq >= 1 && freq <= 10
+  if (!useBucket) {
+    const spo2Data = healthDataArray
+      .filter(data => data.type === 'spo2' && data.spo2 != null)
+      .filter((_, index) => index % frequency === 0)
+      .slice(-maxPoints)
+    const data = spo2Data.map(item => item.spo2!)
+    const labels = spo2Data.map((_, index) => ((index + 1) % 10 === 0 ? `${index + 1}` : ''))
+    return { type: 'line' as ChartType, data, labels, color }
+  }
+
+  const intervalSeconds = Math.max(1, Math.floor(freq))
+  const intervalMs = intervalSeconds * 1000
+  const buckets = new Map<number, number[]>()
+  for (let i = 0; i < healthDataArray.length; i++) {
+    const d = healthDataArray[i]
+    if (d.type !== 'spo2' || d.spo2 == null) continue
+    const timestamp = d.timestamp
+    const ts = (timestamp == null) ? Date.now() : (typeof timestamp === 'number' ? timestamp : new Date(timestamp as string).getTime())
+    const key = Math.floor(ts / intervalMs) * intervalMs
+    if (!buckets.has(key)) buckets.set(key, [])
+    const spo2Value = d.spo2 != null ? Number.parseFloat(d.spo2.toString()) : 0
+    buckets.get(key)!.push(spo2Value)
+  }
+  const keys: number[] = []
+  buckets.forEach((_, key) => { keys.push(key) })
+  keys.sort((a, b) => a - b)
+  const slicedKeys = keys.slice(-maxPoints)
+
+  const data: number[] = []
+  const labels: string[] = []
+  for (let i = 0; i < slicedKeys.length; i++) {
+    const key = slicedKeys[i]
+      const bucketValue = buckets.get(key)
+      const arr = (bucketValue != null) ? bucketValue : []
+  let maxValue = NaN
+    for (let j = 0; j < arr.length; j++) {
+        const num = arr[j] as number
+      if (isNaN(num)) continue
+      if (isNaN(maxValue) || num > maxValue) {
+        maxValue = num
+      }
+    }
+    data.push(maxValue)
+    const labelDate = new Date(key)
+    const ss = labelDate.getSeconds().toString().padStart(2, '0')
+    const mm = labelDate.getMinutes().toString().padStart(2, '0')
+    labels.push(`${mm}:${ss}`)
+  }
+  return { type: 'line' as ChartType, data, labels, color }
+}
+
+/**
+ * 处理步数数据为图表格式
+ * @param healthDataArray 健康数据数组
+ * @param config 配置选项
+ * @returns ChartOption对象
+ */
+export function processStepsData(
+  healthDataArray: HealthData[],
+  config: StepsChartConfig = {}
+): ChartOption {
+  const {
+    maxPoints = 100, // 增加到100个点
+    frequency = 1,
+    color = '#FFCE56'
+  } = config
+  // 步数通常以累计值或增量形式出现，按时间区间取最后一个值（或累加）
+  const freq = frequency
+  const useBucket = freq >= 1 && freq <= 10
+  if (!useBucket) {
+    const stepsData = healthDataArray
+      .filter(data => data.type === 'steps' && data.steps != null)
+      .filter((_, index) => index % frequency === 0)
+      .slice(-maxPoints)
+    const data = stepsData.map(item => item.steps!)
+    const labels = stepsData.map((_, index) => ((index + 1) % 10 === 0 ? `${index + 1}` : ''))
+    return { type: 'bar' as ChartType, data, labels, color }
+  }
+
+  const intervalSeconds = Math.max(1, Math.floor(freq))
+  const intervalMs = intervalSeconds * 1000
+  const buckets = new Map<number, number[]>()
+  for (let i = 0; i < healthDataArray.length; i++) {
+    const d = healthDataArray[i]
+    if (d.type !== 'steps' || d.steps == null) continue
+      const ts = (d.timestamp == null) ? Date.now() : (typeof d.timestamp === 'number' ? d.timestamp : new Date(d.timestamp as string).getTime())
+    const key = Math.floor(ts / intervalMs) * intervalMs
+    if (!buckets.has(key)) buckets.set(key, [])
+    const stepsValue = d.steps != null ? Number.parseFloat(d.steps.toString()) : 0
+    buckets.get(key)!.push(stepsValue)
+  }
+  const keys: number[] = []
+  buckets.forEach((_, key) => { keys.push(key) })
+  keys.sort((a, b) => a - b)
+  const slicedKeys = keys.slice(-maxPoints)
+
+  const data: number[] = []
+  const labels: string[] = []
+  for (let i = 0; i < slicedKeys.length; i++) {
+    const key = slicedKeys[i]
+      const bucketValue = buckets.get(key)
+      const arr = (bucketValue != null) ? bucketValue : []
+  let lastValue = NaN
+    if (arr.length > 0) {
+        const candidate = Number.parseFloat(arr[arr.length - 1].toString())
+  lastValue = isNaN(candidate) ? NaN : candidate
+    }
+    data.push(lastValue)
+    const labelDate = new Date(key)
+    const ss = labelDate.getSeconds().toString().padStart(2, '0')
+    const mm = labelDate.getMinutes().toString().padStart(2, '0')
+    labels.push(`${mm}:${ss}`)
+  }
+  return { type: 'bar' as ChartType, data, labels, color }
+}
+
+/**
+ * 创建对齐的多指标图表数据（心率、血氧、速度、步数）
+ * 返回一个数组，包含每个指标对应的 ChartOption，且 labels 保持一致
+ */
+export function processMultiMetricCharts(
+  healthDataArray: HealthData[],
+  intervalSeconds: number = 1,
+  maxPoints: number = 100,
+  metrics: ('heart' | 'spo2' | 'steps' | 'speed')[] = ['heart', 'spo2', 'steps']
+): ChartOption[] {
+  const intervalMs = Math.max(1, intervalSeconds) * 1000
+  const buckets = new Map<number, MultiMetricBucket>()
+
+  for (let i = 0; i < healthDataArray.length; i++) {
+    const d = healthDataArray[i]
+    const ts = (d.timestamp == null) ? Date.now() : (typeof d.timestamp === 'number' ? d.timestamp : new Date(d.timestamp).getTime())
+    const key = Math.floor(ts / intervalMs) * intervalMs
+    if (!buckets.has(key)) buckets.set(key, {})
+    const entry = buckets.get(key)!
+    if (d.type === 'heart' && d.heartRate != null) {
+      if (!entry.heart) entry.heart = []
+      const heartRateValue = d.heartRate != null ? Number.parseFloat(d.heartRate.toString()) : 0
+      entry.heart.push(heartRateValue)
+    }
+    if (d.type === 'spo2' && d.spo2 != null) {
+      if (!entry.spo2) entry.spo2 = []
+      const spo2Value = d.spo2 != null ? Number.parseFloat(d.spo2.toString()) : 0
+      entry.spo2.push(spo2Value)
+    }
+    if ((d.type === 'speed' || d.type === 'heart') && (d as any).speed != null) {
+      if (!entry.speed) entry.speed = []
+      const speedValue = (d as any).speed != null ? Number.parseFloat((d as any).speed.toString()) : 0
+      entry.speed.push(speedValue)
+    }
+    if (d.type === 'steps' && d.steps != null) {
+      if (!entry.steps) entry.steps = []
+      const stepsValue = d.steps != null ? Number.parseFloat(d.steps.toString()) : 0
+      entry.steps.push(stepsValue)
+    }
+  }
+
+  const keys: number[] = []
+  buckets.forEach((_, key) => { keys.push(key) })
+  keys.sort((a, b) => a - b)
+  const slicedKeys = keys.slice(-maxPoints)
+  const labels: string[] = []
+  for (let i = 0; i < slicedKeys.length; i++) {
+    const key = slicedKeys[i]
+    const labelDate = new Date(key)
+    const ss = labelDate.getSeconds().toString().padStart(2, '0')
+    const mm = labelDate.getMinutes().toString().padStart(2, '0')
+    labels.push(`${mm}:${ss}`)
+  }
+
+  const results: ChartOption[] = []
+  if (metrics.includes('heart')) {
+    const data: number[] = []
+    for (let i = 0; i < slicedKeys.length; i++) {
+      const key = slicedKeys[i]
+      const bucketValue = buckets.get(key)
+      const arr = (bucketValue?.heart != null) ? bucketValue.heart : []
+  let maxValue = NaN
+      for (let j = 0; j < arr.length; j++) {
+        const num = Number.parseFloat(arr[j].toString())
+        if (isNaN(num)) continue
+        if (isNaN(maxValue) || num > maxValue) {
+          maxValue = num
+        }
+      }
+      data.push(maxValue)
+    }
+    results.push({ type: 'line' as ChartType, data, labels, color: '#FF6B6B' })
+  }
+  if (metrics.includes('spo2')) {
+    const data: number[] = []
+    for (let i = 0; i < slicedKeys.length; i++) {
+      const key = slicedKeys[i]
+      const bucketValue = buckets.get(key)
+      const arr = (bucketValue?.spo2 != null) ? bucketValue.spo2 : []
+  let maxValue = NaN
+      for (let j = 0; j < arr.length; j++) {
+        const num = Number(arr[j])
+        if (isNaN(num)) continue
+        if (isNaN(maxValue) || num > maxValue) {
+          maxValue = num
+        }
+      }
+      data.push(maxValue)
+    }
+    results.push({ type: 'line' as ChartType, data, labels, color: '#2196F3' })
+  }
+  if (metrics.includes('speed')) {
+    const data: number[] = []
+    for (let i = 0; i < slicedKeys.length; i++) {
+      const key = slicedKeys[i]
+      const bucketValue = buckets.get(key)
+      const arr = (bucketValue?.speed != null) ? bucketValue.speed : []
+  let maxValue = NaN
+      for (let j = 0; j < arr.length; j++) {
+        const num = Number(arr[j])
+        if (isNaN(num)) continue
+        if (isNaN(maxValue) || num > maxValue) {
+          maxValue = num
+        }
+      }
+      data.push(maxValue)
+    }
+    results.push({ type: 'line' as ChartType, data, labels, color: '#FFA726' })
+  }
+  if (metrics.includes('steps')) {
+    const data: number[] = []
+    for (let i = 0; i < slicedKeys.length; i++) {
+      const key = slicedKeys[i]
+      const bucketValue = buckets.get(key)
+      const arr = (bucketValue?.steps != null) ? bucketValue.steps : []
+  let lastValue = NaN
+      if (arr.length > 0) {
+        const candidate = Number(arr[arr.length - 1])
+  lastValue = isNaN(candidate) ? NaN : candidate
+      }
+      data.push(lastValue)
+    }
+    results.push({ type: 'bar' as ChartType, data, labels, color: '#4CAF50' })
+  }
+
+  return results
+}
+
+/**
+ * 创建多指标组合图表数据
+ * @param healthDataArray 健康数据数组
+ * @param metrics 要包含的指标数组
+ * @param maxPoints 最大显示点数
+ * @returns ChartOption对象数组，每个指标一个图表
+ */
+export function createMultiMetricCharts(
+  healthDataArray: HealthData[],
+  metrics: ('heart' | 'spo2' | 'steps')[] = ['heart', 'spo2', 'steps'],
+  maxPoints: number = 100
+): ChartOption[] {
+  const charts: ChartOption[] = []
+
+  if (metrics.includes('heart')) {
+    charts.push(processHeartRateData(healthDataArray, { maxPoints }))
+  }
+
+  if (metrics.includes('spo2')) {
+    charts.push(processSpo2Data(healthDataArray, { maxPoints }))
+  }
+
+  if (metrics.includes('steps')) {
+    charts.push(processStepsData(healthDataArray, { maxPoints }))
+  }
+
+  return charts
+}
+
+/**
+ * 获取数据的最新值
+ * @param healthDataArray 健康数据数组
+ * @param dataType 数据类型
+ * @returns 最新值或null
+ */
+export function getLatestValue(
+  healthDataArray: HealthData[],
+  dataType: 'heart' | 'spo2' | 'steps'
+): number | null {
+  const filteredData = healthDataArray
+    .filter(data => data.type === dataType)
+    .filter(data => {
+      switch (dataType) {
+        case 'heart': return data.heartRate != null
+        case 'spo2': return data.spo2 != null
+        case 'steps': return data.steps != null
+        default: return false
+      }
+    })
+
+  if (filteredData.length === 0) return null
+
+  const latest = filteredData[filteredData.length - 1]
+  switch (dataType) {
+    case 'heart': return latest.heartRate!
+    case 'spo2': return latest.spo2!
+    case 'steps': return latest.steps!
+    default: return null
+  }
+}
+
+/**
+ * 检查是否有足够的数据用于图表显示
+ * @param healthDataArray 健康数据数组
+ * @param dataType 数据类型
+ * @param minPoints 最少点数，默认3
+ * @returns 是否有足够数据
+ */
+export function hasEnoughDataForChart(
+  healthDataArray: HealthData[],
+  dataType: 'heart' | 'spo2' | 'steps',
+  minPoints: number = 3
+): boolean {
+  const filteredData = healthDataArray.filter(data => data.type === dataType)
+  return filteredData.length >= minPoints
+}
+
+/**
+ * 测试数据处理功能（用于开发调试）
+ * @returns 测试结果
+ */
+export function testChartDataProcessing(): string {
+  // 创建测试数据
+  const testData: HealthData[] = [
+    { type: 'heart', heartRate: 72, timestamp: Date.now() },
+    { type: 'spo2', spo2: 98, timestamp: Date.now() },
+    { type: 'steps', steps: 150, timestamp: Date.now() },
+    { type: 'heart', heartRate: 75, timestamp: Date.now() },
+    { type: 'spo2', spo2: 97, timestamp: Date.now() },
+    { type: 'steps', steps: 200, timestamp: Date.now() }
+  ]
+
+  // 测试心率数据处理
+  const heartChart = processHeartRateData(testData, { maxPoints: 100 })
+  const spo2Chart = processSpo2Data(testData, { maxPoints: 100 })
+  const stepsChart = processStepsData(testData, { maxPoints: 100 })
+
+  return `测试完成 - 心率: ${heartChart.data.length}点, 血氧: ${spo2Chart.data.length}点, 步数: ${stepsChart.data.length}点`
+}