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データ列に対してmapすると移動平均が得られるフィルタ関数。chartjs が移動平均線の描画に対応してないっぽいが、これを噛ましてやれば自力で移動平均用のデータ列が作れる。
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| const movingAverageFilter = (ws=3) => { | |
| if(!Number.isInteger(ws) || ws < 1) { | |
| throw new Error(`Invalid window size. ws must be >=1. You entered: ws=${ws}.`) | |
| } | |
| let win = [] | |
| let sum = 0 | |
| let pos = 0 | |
| let tail = 0 | |
| return (head) => { | |
| sum = sum + head - tail | |
| win[pos] = head | |
| pos = pos < ws - 1 ? pos + 1 : 0 | |
| if(win.length < ws) { | |
| return | |
| } | |
| tail = win[pos] | |
| return sum/ws | |
| } | |
| } | |
| // test | |
| const data = [1,2,3,4,5,6,7,8,9,10]; | |
| [1,2,3,5,10].forEach(ws => { | |
| console.log(`ws=${ws}`, data.map(movingAverageFilter(ws))) | |
| }) |
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| const removeOutliersIqr = (windowSize = 12, thresholdFactor = 1.5) => { | |
| // 移動平均とIQRを基に外れ値をフィルタ判定する関数を返す | |
| const q1index = Math.floor(windowSize / 4) | |
| const q3index = Math.floor(windowSize * 3 / 4) | |
| return function(v, i, a) { | |
| if (a.length < windowSize) { | |
| return v; | |
| } else { | |
| const windowData = i < windowSize ? a.slice(0, windowSize) : a.slice(i - windowSize, i) | |
| const movingAvg = windowData.reduce((a, b) => a + b, 0) / windowSize; | |
| const sortedWindowData = windowData.slice().sort((a,b)=>a-b) | |
| const q1 = sortedWindowData[q1index] | |
| const q3 = sortedWindowData[q3index] | |
| const iqr = q3 - q1 | |
| const lowerBound = movingAvg - thresholdFactor * iqr | |
| const upperBound = movingAvg + thresholdFactor * iqr | |
| console.log({q1index,q3index,q1,q3,iqr,lowerBound,movingAvg,upperBound,windowData,sortedWindowData}) | |
| if (v < lowerBound || v > upperBound) { | |
| // 外れ値の場合、移動平均値を返す | |
| return [v,movingAvg] | |
| } else { | |
| return v | |
| } | |
| } | |
| } | |
| } | |
| data=[650,1002.64,1002.63,1002.58,1002.6,1002.6,1002.61,1002.61,1002.66,1002.64,1002.63,1002.63,1002.7,1002.64,1002.53,1002.53,1002.66,1002.71,1002.65,1002.61,1002.68,1002.61,1002.63]; | |
| windowSizes = [5,10] | |
| thresholdFactors = [1.5, 3, 5, 10] | |
| for(const tf of thresholdFactors) { | |
| for(const ws of windowSizes) { | |
| console.log(`ws=${ws} tf=${tf}`, data.map(removeOutliersIqr(ws, tf))) | |
| } | |
| } |
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