| 1 | import { mean } from 'rambda' |
| 2 | |
| 3 | export const min = (...args: number[]): number => |
| 4 | args.reduce((minimum, num) => (minimum < num ? minimum : num), Infinity) |
| 5 | |
| 6 | export const max = (...args: number[]): number => |
| 7 | args.reduce((maximum, num) => (maximum > num ? maximum : num), -Infinity) |
| 8 | |
| 9 | // TODO: use order statistics tree https://en.wikipedia.org/wiki/Order_statistic_tree |
| 10 | export const nthPercentile = (dataSet: number[], percentile: number): number => { |
| 11 | if (percentile < 0 && percentile > 100) { |
| 12 | throw new RangeError('Percentile is not between 0 and 100') |
| 13 | } |
| 14 | if (Array.isArray(dataSet) && dataSet.length === 0) { |
| 15 | return 0 |
| 16 | } |
| 17 | const sortedDataSet = dataSet.slice().sort((a, b) => a - b) |
| 18 | if (percentile === 0 || sortedDataSet.length === 1) { |
| 19 | return sortedDataSet[0] |
| 20 | } |
| 21 | if (percentile === 100) { |
| 22 | return sortedDataSet[sortedDataSet.length - 1] |
| 23 | } |
| 24 | const base = (percentile / 100) * (sortedDataSet.length - 1) |
| 25 | const baseIndex = Math.floor(base) |
| 26 | // eslint-disable-next-line @typescript-eslint/no-unnecessary-condition |
| 27 | if (sortedDataSet[baseIndex + 1] != null) { |
| 28 | return ( |
| 29 | sortedDataSet[baseIndex] + |
| 30 | (base - baseIndex) * (sortedDataSet[baseIndex + 1] - sortedDataSet[baseIndex]) |
| 31 | ) |
| 32 | } |
| 33 | return sortedDataSet[baseIndex] |
| 34 | } |
| 35 | |
| 36 | /** |
| 37 | * Computes the sample standard deviation of the given data set. |
| 38 | * |
| 39 | * @param dataSet - Data set. |
| 40 | * @param dataSetAverage - Average of the data set. |
| 41 | * @returns The sample standard deviation of the given data set. |
| 42 | * @see https://en.wikipedia.org/wiki/Unbiased_estimation_of_standard_deviation |
| 43 | * @internal |
| 44 | */ |
| 45 | export const stdDeviation = (dataSet: number[], dataSetAverage: number = mean(dataSet)): number => { |
| 46 | if (Array.isArray(dataSet) && (dataSet.length === 0 || dataSet.length === 1)) { |
| 47 | return 0 |
| 48 | } |
| 49 | return Math.sqrt( |
| 50 | dataSet.reduce((accumulator, num) => accumulator + Math.pow(num - dataSetAverage, 2), 0) / |
| 51 | (dataSet.length - 1) |
| 52 | ) |
| 53 | } |