locutus/python/statistics/correlation.js

Locutus other languages' standard libraries to JavaScript for fun and educational purposes

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.correlation = correlation;
const _statistics_ts_1 = require("../_helpers/_statistics.js");
function correlation(x, y, method = 'linear') {
    //      discuss at: https://locutus.io/python/statistics/correlation/
    // parity verified: Python 3.12
    //     original by: Kevin van Zonneveld (https://kvz.io)
    //          note 1: Returns Pearson correlation by default and supports Python's ranked mode for Spearman correlation.
    //       example 1: correlation([1, 2, 3], [1, 5, 7])
    //       returns 1: 0.9819805060619659
    //       example 2: correlation([1, 2, 3], [7, 5, 3])
    //       returns 2: -1
    //       example 3: correlation([1, 2, 3], [3, 2, 1], 'ranked')
    //       returns 3: -1
    const left = (0, _statistics_ts_1.assertStatisticsArray)(x, 'correlation').map((value) => (0, _statistics_ts_1.toStatisticNumber)(value, 'correlation'));
    const right = (0, _statistics_ts_1.assertStatisticsArray)(y, 'correlation').map((value) => (0, _statistics_ts_1.toStatisticNumber)(value, 'correlation'));
    const n = left.length;
    if (right.length !== n) {
        throw new Error('correlation requires that both inputs have same number of data points');
    }
    if (n < 2) {
        throw new Error('correlation requires at least two data points');
    }
    if (method !== 'linear' && method !== 'ranked') {
        throw new TypeError(`Unknown method: '${String(method)}'`);
    }
    const xValues = method === 'ranked' ? rankValues(left) : centerValues(left);
    const yValues = method === 'ranked' ? rankValues(right) : centerValues(right);
    const sxy = (0, _statistics_ts_1.sumProducts)(xValues, yValues);
    const sxx = (0, _statistics_ts_1.sumProducts)(xValues, xValues);
    const syy = (0, _statistics_ts_1.sumProducts)(yValues, yValues);
    const denominator = Math.sqrt(sxx * syy);
    if (denominator === 0) {
        throw new Error('at least one of the inputs is constant');
    }
    return sxy / denominator;
}
function centerValues(values) {
    const mean = values.reduce((sum, value) => sum + value, 0) / values.length;
    return values.map((value) => value - mean);
}
function rankValues(values) {
    const n = values.length;
    const start = (n - 1) / -2;
    const indexed = values.map((value, index) => ({ value, index })).sort((a, b) => a.value - b.value);
    const ranks = new Array(n);
    let position = 0;
    while (position < indexed.length) {
        let end = position + 1;
        while (end < indexed.length && indexed[end]?.value === indexed[position]?.value) {
            end += 1;
        }
        const averageRank = start + (position + end - 1) / 2;
        for (let cursor = position; cursor < end; cursor += 1) {
            const entry = indexed[cursor];
            if (entry) {
                ranks[entry.index] = averageRank;
            }
        }
        position = end;
    }
    return ranks;
}