locutus/r/_helpers/_stats.js

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

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.toRNumericArray = toRNumericArray;
exports.toRNumber = toRNumber;
exports.sortedRNumbers = sortedRNumbers;
exports.medianOfSorted = medianOfSorted;
exports.sampleVariance = sampleVariance;
exports.sampleCovariance = sampleCovariance;
function toRNumericArray(data, functionName) {
    if (!Array.isArray(data)) {
        throw new TypeError(`${functionName}() data must be an array`);
    }
    return data.map((value) => toRNumber(value, functionName));
}
function toRNumber(value, functionName) {
    if (typeof value === 'number') {
        return value;
    }
    if (typeof value === 'boolean') {
        return value ? 1 : 0;
    }
    if (typeof value === 'bigint') {
        const numericValue = Number(value);
        if (!Number.isSafeInteger(numericValue)) {
            throw new RangeError(`${functionName}() bigint values must fit within JS safe integer precision`);
        }
        return numericValue;
    }
    throw new TypeError(`${functionName}() data must contain only numeric values`);
}
function sortedRNumbers(data, functionName) {
    return [...toRNumericArray(data, functionName)].sort((left, right) => left - right);
}
function medianOfSorted(values, low = false, high = false) {
    if (values.length === 0) {
        return Number.NaN;
    }
    const middle = Math.floor(values.length / 2);
    if (values.length % 2 === 1) {
        return values[middle] ?? Number.NaN;
    }
    if (low) {
        return values[middle - 1] ?? Number.NaN;
    }
    if (high) {
        return values[middle] ?? Number.NaN;
    }
    return ((values[middle - 1] ?? Number.NaN) + (values[middle] ?? Number.NaN)) / 2;
}
function sampleVariance(values) {
    if (values.length < 2) {
        return Number.NaN;
    }
    const mean = values.reduce((sum, value) => sum + value, 0) / values.length;
    const squaredDeltaSum = values.reduce((sum, value) => {
        const delta = value - mean;
        return sum + delta * delta;
    }, 0);
    return squaredDeltaSum / (values.length - 1);
}
function sampleCovariance(left, right, functionName) {
    if (left.length !== right.length) {
        throw new Error(`${functionName}() requires arrays with the same length`);
    }
    if (left.length < 2) {
        return Number.NaN;
    }
    const leftMean = left.reduce((sum, value) => sum + value, 0) / left.length;
    const rightMean = right.reduce((sum, value) => sum + value, 0) / right.length;
    let total = 0;
    for (let index = 0; index < left.length; index += 1) {
        total += ((left[index] ?? 0) - leftMean) * ((right[index] ?? 0) - rightMean);
    }
    return total / (left.length - 1);
}