Commit | Line | Data |
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9bf0ef23 | 1 | import { isEmptyArray, isNullOrUndefined } from './Utils'; |
4884b8d3 JB |
2 | |
3 | export const median = (dataSet: number[]): number => { | |
9bf0ef23 | 4 | if (isEmptyArray(dataSet)) { |
4884b8d3 JB |
5 | return 0; |
6 | } | |
7 | if (Array.isArray(dataSet) === true && dataSet.length === 1) { | |
8 | return dataSet[0]; | |
9 | } | |
10 | const sortedDataSet = dataSet.slice().sort((a, b) => a - b); | |
11 | return ( | |
12 | (sortedDataSet[(sortedDataSet.length - 1) >> 1] + sortedDataSet[sortedDataSet.length >> 1]) / 2 | |
13 | ); | |
14 | }; | |
15 | ||
16 | // TODO: use order statistics tree https://en.wikipedia.org/wiki/Order_statistic_tree | |
17 | export const nthPercentile = (dataSet: number[], percentile: number): number => { | |
18 | if (percentile < 0 && percentile > 100) { | |
19 | throw new RangeError('Percentile is not between 0 and 100'); | |
20 | } | |
9bf0ef23 | 21 | if (isEmptyArray(dataSet)) { |
4884b8d3 JB |
22 | return 0; |
23 | } | |
24 | const sortedDataSet = dataSet.slice().sort((a, b) => a - b); | |
25 | if (percentile === 0 || sortedDataSet.length === 1) { | |
26 | return sortedDataSet[0]; | |
27 | } | |
28 | if (percentile === 100) { | |
29 | return sortedDataSet[sortedDataSet.length - 1]; | |
30 | } | |
31 | const percentileIndexBase = (percentile / 100) * (sortedDataSet.length - 1); | |
32 | const percentileIndexInteger = Math.floor(percentileIndexBase); | |
9bf0ef23 | 33 | if (!isNullOrUndefined(sortedDataSet[percentileIndexInteger + 1])) { |
4884b8d3 JB |
34 | return ( |
35 | sortedDataSet[percentileIndexInteger] + | |
36 | (percentileIndexBase - percentileIndexInteger) * | |
37 | (sortedDataSet[percentileIndexInteger + 1] - sortedDataSet[percentileIndexInteger]) | |
38 | ); | |
39 | } | |
40 | return sortedDataSet[percentileIndexInteger]; | |
41 | }; | |
42 | ||
43 | export const stdDeviation = (dataSet: number[]): number => { | |
44 | let totalDataSet = 0; | |
45 | for (const data of dataSet) { | |
46 | totalDataSet += data; | |
47 | } | |
48 | const dataSetMean = totalDataSet / dataSet.length; | |
49 | let totalGeometricDeviation = 0; | |
50 | for (const data of dataSet) { | |
51 | const deviation = data - dataSetMean; | |
52 | totalGeometricDeviation += deviation * deviation; | |
53 | } | |
54 | return Math.sqrt(totalGeometricDeviation / dataSet.length); | |
55 | }; |