| 1 | import { isEmptyArray } from './Utils.js' |
| 2 | |
| 3 | /** |
| 4 | * Computes the average of the given data set. |
| 5 | * |
| 6 | * @param dataSet - Data set. |
| 7 | * @returns The average of the given data set. |
| 8 | * @internal |
| 9 | */ |
| 10 | export const average = (dataSet: number[]): number => { |
| 11 | if (Array.isArray(dataSet) && dataSet.length === 0) { |
| 12 | return 0 |
| 13 | } |
| 14 | if (Array.isArray(dataSet) && dataSet.length === 1) { |
| 15 | return dataSet[0] |
| 16 | } |
| 17 | return dataSet.reduce((accumulator, nb) => accumulator + nb, 0) / dataSet.length |
| 18 | } |
| 19 | |
| 20 | /** |
| 21 | * Computes the median of the given data set. |
| 22 | * |
| 23 | * @param dataSet - Data set. |
| 24 | * @returns The median of the given data set. |
| 25 | * @internal |
| 26 | */ |
| 27 | export const median = (dataSet: number[]): number => { |
| 28 | if (isEmptyArray(dataSet)) { |
| 29 | return 0 |
| 30 | } |
| 31 | if (Array.isArray(dataSet) && dataSet.length === 1) { |
| 32 | return dataSet[0] |
| 33 | } |
| 34 | const sortedDataSet = dataSet.slice().sort((a, b) => a - b) |
| 35 | return ( |
| 36 | (sortedDataSet[(sortedDataSet.length - 1) >> 1] + sortedDataSet[sortedDataSet.length >> 1]) / 2 |
| 37 | ) |
| 38 | } |
| 39 | |
| 40 | // TODO: use order statistics tree https://en.wikipedia.org/wiki/Order_statistic_tree |
| 41 | export const nthPercentile = (dataSet: number[], percentile: number): number => { |
| 42 | if (percentile < 0 && percentile > 100) { |
| 43 | throw new RangeError('Percentile is not between 0 and 100') |
| 44 | } |
| 45 | if (isEmptyArray(dataSet)) { |
| 46 | return 0 |
| 47 | } |
| 48 | const sortedDataSet = dataSet.slice().sort((a, b) => a - b) |
| 49 | if (percentile === 0 || sortedDataSet.length === 1) { |
| 50 | return sortedDataSet[0] |
| 51 | } |
| 52 | if (percentile === 100) { |
| 53 | return sortedDataSet[sortedDataSet.length - 1] |
| 54 | } |
| 55 | const percentileIndexBase = (percentile / 100) * (sortedDataSet.length - 1) |
| 56 | const percentileIndexInteger = Math.floor(percentileIndexBase) |
| 57 | if (sortedDataSet[percentileIndexInteger + 1] != null) { |
| 58 | return ( |
| 59 | sortedDataSet[percentileIndexInteger] + |
| 60 | (percentileIndexBase - percentileIndexInteger) * |
| 61 | (sortedDataSet[percentileIndexInteger + 1] - sortedDataSet[percentileIndexInteger]) |
| 62 | ) |
| 63 | } |
| 64 | return sortedDataSet[percentileIndexInteger] |
| 65 | } |
| 66 | |
| 67 | /** |
| 68 | * Computes the sample standard deviation of the given data set. |
| 69 | * |
| 70 | * @param dataSet - Data set. |
| 71 | * @param dataSetAverage - Average of the data set. |
| 72 | * @returns The sample standard deviation of the given data set. |
| 73 | * @see https://en.wikipedia.org/wiki/Unbiased_estimation_of_standard_deviation |
| 74 | * @internal |
| 75 | */ |
| 76 | export const stdDeviation = ( |
| 77 | dataSet: number[], |
| 78 | dataSetAverage: number = average(dataSet) |
| 79 | ): number => { |
| 80 | if (isEmptyArray(dataSet)) { |
| 81 | return 0 |
| 82 | } |
| 83 | if (Array.isArray(dataSet) && dataSet.length === 1) { |
| 84 | return 0 |
| 85 | } |
| 86 | return Math.sqrt( |
| 87 | dataSet.reduce((accumulator, num) => accumulator + Math.pow(num - dataSetAverage, 2), 0) / |
| 88 | (dataSet.length - 1) |
| 89 | ) |
| 90 | } |