N (Number)

Aggregation

sum(nums: number[]): number
mean(nums: number[]): number
median(nums: number[]): number
variance(nums: number[]): number
standardDeviation(nums: number[]): number
min(nums: number[]): number
max(nums: number[]): number
minMax(nums: number[]): [number, number]

Dual

percentile(nums: number[], p: number): number
clamp(value: number, min: number, max: number): number
dotProduct(a: number[], b: number[]): number

Predicates

isEven(n: number): boolean
isOdd(n: number): boolean

Examples

import { pipe, A, N } from '@stopcock/fp'

// stats on response times
const times = [120, 95, 200, 88, 150, 300, 110]
N.mean(times)               // ~151.9
N.median(times)             // 120
N.standardDeviation(times)  // ~68.6
N.percentile(times, 95)     // 300

// clamp user input
pipe(userAge, N.clamp(0, 150))

// average score, ignoring zeros
pipe(scores, A.filter(s => s > 0), N.mean)

// feature vector similarity
N.dotProduct([1, 0, 1], [0, 1, 1])  // 1