pearson correlation coefficient

correlation.js

/** * calculates pearson correlation 
* @param{number[]}d1 
* @param{number[]}d2
*/
export function corr(d1, d2) {
  let { min, pow, sqrt } =Math
  let add = (a, b) => a + b
  let n = min(d1.length, d2.length)
  if (n ===0) {
    return0
  }
  [d1, d2] = [d1.slice(0, n), d2.slice(0, n)]
  let [sum1, sum2] = [d1, d2].map(l=>l.reduce(add))
  let [pow1, pow2] = [d1, d2].map(l=>l.reduce((a, b) => a +pow(b, 2), 0))
  let mulSum =d1.map((n, i) => n * d2[i]).reduce(add)
  let dense =sqrt((pow1 -pow(sum1, 2) / n) * (pow2 -pow(sum2, 2) / n))
  if (dense ===0) {
    return0
  }
  return (mulSum - (sum1 * sum2 / n)) / dense
}