482 lines
16 KiB
Plaintext
482 lines
16 KiB
Plaintext
/**
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* 健康数据图表处理工具
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* 提供将原始健康数据转换为ak-charts显示格式的功能
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*/
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import type { HealthData } from '../../uni_modules/ak-sbsrv/utssdk/interface.uts'
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import type { ChartOption, ChartType } from '../../uni_modules/ak-charts/interface.uts'
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type MultiMetricBucket = {
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heart?: number[]
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spo2?: number[]
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speed?: number[]
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steps?: number[]
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}
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// Re-export ChartOption for use in other modules
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export type { ChartOption, ChartType }
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/**
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* 心率数据处理配置
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*/
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export type HeartRateChartConfig = {
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maxPoints?: number; // 最大显示点数，默认50
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frequency?: number; // 数据频率控制，每N个点取一个，默认1（全部）
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color?: string; // 图表颜色，默认'#FF6384'
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}
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/**
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* 血氧数据处理配置
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*/
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export type Spo2ChartConfig = {
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maxPoints?: number; // 最大显示点数，默认50
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frequency?: number; // 数据频率控制，默认1
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color?: string; // 图表颜色，默认'#36A2EB'
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}
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/**
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* 步数数据处理配置
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*/
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export type StepsChartConfig = {
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maxPoints?: number; // 最大显示点数，默认50
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frequency?: number; // 数据频率控制，默认1
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color?: string; // 图表颜色，默认'#FFCE56'
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}
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/**
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* 处理心率数据为图表格式
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* @param healthDataArray 健康数据数组
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* @param config 配置选项
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* @returns ChartOption对象
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*/
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export function processHeartRateData(
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healthDataArray: HealthData[],
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config: HeartRateChartConfig = {}
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): ChartOption {
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const {
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maxPoints = 100, // 增加到100个点
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frequency = 1,
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color = '#FF6384'
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} = config
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// 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
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// frequency字段 legacy 用法仍然支持按索引采样
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const freq = frequency
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const useBucket = freq >= 1 && freq <= 10
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if (!useBucket) {
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// legacy 行为：按索引采样
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const heartRateData = healthDataArray
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.filter(data => data.type === 'heart' && data.heartRate != null)
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.filter((_, index) => index % frequency === 0)
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.slice(-maxPoints)
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const data = heartRateData.map(item => item.heartRate!)
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const labels = heartRateData.map((_, index) => ((index + 1) % 10 === 0 ? `${index + 1}` : ''))
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return { type: 'line' as ChartType, data, labels, color }
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}
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// 使用时间分桶（默认1s或5s）: 将心率按时间区间取最大值
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const intervalSeconds = Math.max(1, Math.floor(freq))
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const intervalMs = intervalSeconds * 1000
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const buckets = new Map<number, number[]>()
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for (let i = 0; i < healthDataArray.length; i++) {
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const d = healthDataArray[i]
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if (d.type !== 'heart' || d.heartRate == null) continue
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const timestamp = d.timestamp
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const ts = (timestamp == null) ? Date.now() : (typeof timestamp === 'number' ? timestamp : new Date(timestamp as string).getTime())
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const key = Math.floor(ts / intervalMs) * intervalMs
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if (!buckets.has(key)) buckets.set(key, [])
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const heartRateValue = d.heartRate != null ? Number.parseFloat(d.heartRate.toString()) : 0
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buckets.get(key)!.push(heartRateValue)
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}
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// 按时间排序并只取最新maxPoints
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const keys: number[] = []
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buckets.forEach((_, key) => { keys.push(key) })
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keys.sort((a, b) => a - b)
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const slicedKeys = keys.slice(-maxPoints)
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const data: number[] = []
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const labels: string[] = []
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for (let i = 0; i < slicedKeys.length; i++) {
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const key = slicedKeys[i]
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const arr = (buckets.get(key) != null) ? buckets.get(key)! : []
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let maxValue = NaN
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for (let j = 0; j < arr.length; j++) {
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const num = arr[j] as number
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if (isNaN(num)) continue
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if (isNaN(maxValue) || num > maxValue) {
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maxValue = num
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}
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}
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data.push(maxValue)
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const labelDate = new Date(key)
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const ss = labelDate.getSeconds().toString().padStart(2, '0')
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const mm = labelDate.getMinutes().toString().padStart(2, '0')
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labels.push(`${mm}:${ss}`)
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}
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return { type: 'line' as ChartType, data, labels, color }
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}
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/**
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* 处理血氧数据为图表格式
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* @param healthDataArray 健康数据数组
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* @param config 配置选项
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* @returns ChartOption对象
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*/
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export function processSpo2Data(
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healthDataArray: HealthData[],
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config: Spo2ChartConfig = {}
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): ChartOption {
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const {
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maxPoints = 100, // 增加到100个点
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frequency = 1,
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color = '#36A2EB'
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} = config
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// 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）
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const freq = frequency
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const useBucket = freq >= 1 && freq <= 10
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if (!useBucket) {
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const spo2Data = healthDataArray
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.filter(data => data.type === 'spo2' && data.spo2 != null)
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.filter((_, index) => index % frequency === 0)
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.slice(-maxPoints)
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const data = spo2Data.map(item => item.spo2!)
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const labels = spo2Data.map((_, index) => ((index + 1) % 10 === 0 ? `${index + 1}` : ''))
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return { type: 'line' as ChartType, data, labels, color }
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}
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const intervalSeconds = Math.max(1, Math.floor(freq))
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const intervalMs = intervalSeconds * 1000
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const buckets = new Map<number, number[]>()
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for (let i = 0; i < healthDataArray.length; i++) {
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const d = healthDataArray[i]
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if (d.type !== 'spo2' || d.spo2 == null) continue
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const timestamp = d.timestamp
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const ts = (timestamp == null) ? Date.now() : (typeof timestamp === 'number' ? timestamp : new Date(timestamp as string).getTime())
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const key = Math.floor(ts / intervalMs) * intervalMs
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if (!buckets.has(key)) buckets.set(key, [])
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const spo2Value = d.spo2 != null ? Number.parseFloat(d.spo2.toString()) : 0
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buckets.get(key)!.push(spo2Value)
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}
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const keys: number[] = []
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buckets.forEach((_, key) => { keys.push(key) })
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keys.sort((a, b) => a - b)
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const slicedKeys = keys.slice(-maxPoints)
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const data: number[] = []
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const labels: string[] = []
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for (let i = 0; i < slicedKeys.length; i++) {
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const key = slicedKeys[i]
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const bucketValue = buckets.get(key)
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const arr = (bucketValue != null) ? bucketValue : []
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let maxValue = NaN
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for (let j = 0; j < arr.length; j++) {
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const num = arr[j] as number
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if (isNaN(num)) continue
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if (isNaN(maxValue) || num > maxValue) {
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maxValue = num
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}
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}
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data.push(maxValue)
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const labelDate = new Date(key)
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const ss = labelDate.getSeconds().toString().padStart(2, '0')
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const mm = labelDate.getMinutes().toString().padStart(2, '0')
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labels.push(`${mm}:${ss}`)
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}
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return { type: 'line' as ChartType, data, labels, color }
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}
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/**
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* 处理步数数据为图表格式
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* @param healthDataArray 健康数据数组
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* @param config 配置选项
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* @returns ChartOption对象
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*/
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export function processStepsData(
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healthDataArray: HealthData[],
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config: StepsChartConfig = {}
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): ChartOption {
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const {
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maxPoints = 100, // 增加到100个点
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frequency = 1,
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color = '#FFCE56'
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} = config
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// 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）
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const freq = frequency
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const useBucket = freq >= 1 && freq <= 10
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if (!useBucket) {
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const stepsData = healthDataArray
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.filter(data => data.type === 'steps' && data.steps != null)
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.filter((_, index) => index % frequency === 0)
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.slice(-maxPoints)
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const data = stepsData.map(item => item.steps!)
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const labels = stepsData.map((_, index) => ((index + 1) % 10 === 0 ? `${index + 1}` : ''))
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return { type: 'bar' as ChartType, data, labels, color }
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}
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const intervalSeconds = Math.max(1, Math.floor(freq))
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const intervalMs = intervalSeconds * 1000
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const buckets = new Map<number, number[]>()
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for (let i = 0; i < healthDataArray.length; i++) {
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const d = healthDataArray[i]
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if (d.type !== 'steps' || d.steps == null) continue
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const ts = (d.timestamp == null) ? Date.now() : (typeof d.timestamp === 'number' ? d.timestamp : new Date(d.timestamp as string).getTime())
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const key = Math.floor(ts / intervalMs) * intervalMs
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if (!buckets.has(key)) buckets.set(key, [])
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const stepsValue = d.steps != null ? Number.parseFloat(d.steps.toString()) : 0
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buckets.get(key)!.push(stepsValue)
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}
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const keys: number[] = []
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buckets.forEach((_, key) => { keys.push(key) })
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keys.sort((a, b) => a - b)
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const slicedKeys = keys.slice(-maxPoints)
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const data: number[] = []
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const labels: string[] = []
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for (let i = 0; i < slicedKeys.length; i++) {
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const key = slicedKeys[i]
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const bucketValue = buckets.get(key)
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const arr = (bucketValue != null) ? bucketValue : []
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let lastValue = NaN
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if (arr.length > 0) {
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const candidate = Number.parseFloat(arr[arr.length - 1].toString())
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lastValue = isNaN(candidate) ? NaN : candidate
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}
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data.push(lastValue)
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const labelDate = new Date(key)
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const ss = labelDate.getSeconds().toString().padStart(2, '0')
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const mm = labelDate.getMinutes().toString().padStart(2, '0')
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labels.push(`${mm}:${ss}`)
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}
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return { type: 'bar' as ChartType, data, labels, color }
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}
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/**
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* 创建对齐的多指标图表数据（心率、血氧、速度、步数）
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* 返回一个数组，包含每个指标对应的 ChartOption，且 labels 保持一致
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*/
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export function processMultiMetricCharts(
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healthDataArray: HealthData[],
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intervalSeconds: number = 1,
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maxPoints: number = 100,
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metrics: ('heart' | 'spo2' | 'steps' | 'speed')[] = ['heart', 'spo2', 'steps']
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): ChartOption[] {
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const intervalMs = Math.max(1, intervalSeconds) * 1000
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const buckets = new Map<number, MultiMetricBucket>()
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for (let i = 0; i < healthDataArray.length; i++) {
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const d = healthDataArray[i]
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const ts = (d.timestamp == null) ? Date.now() : (typeof d.timestamp === 'number' ? d.timestamp : new Date(d.timestamp).getTime())
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const key = Math.floor(ts / intervalMs) * intervalMs
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if (!buckets.has(key)) buckets.set(key, {})
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const entry = buckets.get(key)!
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if (d.type === 'heart' && d.heartRate != null) {
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if (!entry.heart) entry.heart = []
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const heartRateValue = d.heartRate != null ? Number.parseFloat(d.heartRate.toString()) : 0
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entry.heart.push(heartRateValue)
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}
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if (d.type === 'spo2' && d.spo2 != null) {
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if (!entry.spo2) entry.spo2 = []
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const spo2Value = d.spo2 != null ? Number.parseFloat(d.spo2.toString()) : 0
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entry.spo2.push(spo2Value)
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}
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if ((d.type === 'speed' || d.type === 'heart') && (d as any).speed != null) {
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if (!entry.speed) entry.speed = []
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const speedValue = (d as any).speed != null ? Number.parseFloat((d as any).speed.toString()) : 0
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entry.speed.push(speedValue)
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}
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if (d.type === 'steps' && d.steps != null) {
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if (!entry.steps) entry.steps = []
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const stepsValue = d.steps != null ? Number.parseFloat(d.steps.toString()) : 0
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entry.steps.push(stepsValue)
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}
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}
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const keys: number[] = []
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buckets.forEach((_, key) => { keys.push(key) })
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keys.sort((a, b) => a - b)
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const slicedKeys = keys.slice(-maxPoints)
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const labels: string[] = []
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for (let i = 0; i < slicedKeys.length; i++) {
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const key = slicedKeys[i]
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const labelDate = new Date(key)
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const ss = labelDate.getSeconds().toString().padStart(2, '0')
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const mm = labelDate.getMinutes().toString().padStart(2, '0')
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labels.push(`${mm}:${ss}`)
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}
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const results: ChartOption[] = []
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if (metrics.includes('heart')) {
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const data: number[] = []
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for (let i = 0; i < slicedKeys.length; i++) {
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const key = slicedKeys[i]
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const bucketValue = buckets.get(key)
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const arr = (bucketValue?.heart != null) ? bucketValue.heart : []
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let maxValue = NaN
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for (let j = 0; j < arr.length; j++) {
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const num = Number.parseFloat(arr[j].toString())
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if (isNaN(num)) continue
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if (isNaN(maxValue) || num > maxValue) {
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maxValue = num
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}
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}
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data.push(maxValue)
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}
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results.push({ type: 'line' as ChartType, data, labels, color: '#FF6B6B' })
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}
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if (metrics.includes('spo2')) {
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const data: number[] = []
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for (let i = 0; i < slicedKeys.length; i++) {
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const key = slicedKeys[i]
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const bucketValue = buckets.get(key)
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const arr = (bucketValue?.spo2 != null) ? bucketValue.spo2 : []
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let maxValue = NaN
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for (let j = 0; j < arr.length; j++) {
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const num = Number(arr[j])
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if (isNaN(num)) continue
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if (isNaN(maxValue) || num > maxValue) {
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maxValue = num
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}
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}
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data.push(maxValue)
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}
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results.push({ type: 'line' as ChartType, data, labels, color: '#2196F3' })
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}
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if (metrics.includes('speed')) {
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const data: number[] = []
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for (let i = 0; i < slicedKeys.length; i++) {
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const key = slicedKeys[i]
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const bucketValue = buckets.get(key)
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const arr = (bucketValue?.speed != null) ? bucketValue.speed : []
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let maxValue = NaN
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for (let j = 0; j < arr.length; j++) {
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const num = Number(arr[j])
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if (isNaN(num)) continue
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if (isNaN(maxValue) || num > maxValue) {
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maxValue = num
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}
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}
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data.push(maxValue)
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}
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results.push({ type: 'line' as ChartType, data, labels, color: '#FFA726' })
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}
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if (metrics.includes('steps')) {
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const data: number[] = []
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for (let i = 0; i < slicedKeys.length; i++) {
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const key = slicedKeys[i]
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const bucketValue = buckets.get(key)
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const arr = (bucketValue?.steps != null) ? bucketValue.steps : []
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let lastValue = NaN
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if (arr.length > 0) {
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const candidate = Number(arr[arr.length - 1])
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lastValue = isNaN(candidate) ? NaN : candidate
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}
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data.push(lastValue)
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}
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results.push({ type: 'bar' as ChartType, data, labels, color: '#4CAF50' })
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}
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return results
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}
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/**
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* 创建多指标组合图表数据
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* @param healthDataArray 健康数据数组
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* @param metrics 要包含的指标数组
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* @param maxPoints 最大显示点数
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* @returns ChartOption对象数组，每个指标一个图表
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*/
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export function createMultiMetricCharts(
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healthDataArray: HealthData[],
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metrics: ('heart' | 'spo2' | 'steps')[] = ['heart', 'spo2', 'steps'],
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maxPoints: number = 100
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): ChartOption[] {
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const charts: ChartOption[] = []
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if (metrics.includes('heart')) {
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charts.push(processHeartRateData(healthDataArray, { maxPoints }))
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}
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if (metrics.includes('spo2')) {
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charts.push(processSpo2Data(healthDataArray, { maxPoints }))
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}
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if (metrics.includes('steps')) {
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charts.push(processStepsData(healthDataArray, { maxPoints }))
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}
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return charts
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}
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/**
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* 获取数据的最新值
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* @param healthDataArray 健康数据数组
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* @param dataType 数据类型
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* @returns 最新值或null
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*/
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export function getLatestValue(
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healthDataArray: HealthData[],
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dataType: 'heart' | 'spo2' | 'steps'
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): number | null {
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const filteredData = healthDataArray
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.filter(data => data.type === dataType)
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.filter(data => {
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switch (dataType) {
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case 'heart': return data.heartRate != null
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case 'spo2': return data.spo2 != null
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case 'steps': return data.steps != null
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default: return false
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}
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})
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if (filteredData.length === 0) return null
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const latest = filteredData[filteredData.length - 1]
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switch (dataType) {
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case 'heart': return latest.heartRate!
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case 'spo2': return latest.spo2!
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case 'steps': return latest.steps!
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default: return null
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}
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}
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/**
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* 检查是否有足够的数据用于图表显示
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* @param healthDataArray 健康数据数组
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* @param dataType 数据类型
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* @param minPoints 最少点数，默认3
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* @returns 是否有足够数据
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*/
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export function hasEnoughDataForChart(
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healthDataArray: HealthData[],
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dataType: 'heart' | 'spo2' | 'steps',
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minPoints: number = 3
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): boolean {
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||
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`
|
||
} |