How to use the @turf/center-mean function in @turf/center-mean

function standardDeviationalEllipse(points, options) {
    // Optional params
    options = options || {};
    if (!isObject(options)) throw new Error('options is invalid');
    var steps = options.steps || 64;
    var weight = options.weight;
    var properties = options.properties || {};

    // Validation:
    if (!isNumber(steps)) throw new Error('steps must be a number');
    if (!isObject(properties)) throw new Error('properties must be a number');

    // Calculate mean center:
    var meanCenter = centerMean(points, {weight: weight});

    // Calculate angle of rotation:
    // [X, Y] = mean center of all [x, y].
    // theta = arctan( (A + B) / C )
    // A = sum((x - X)^2) - sum((y - Y)^2)
    // B = sqrt(A^2 + 4(sum((x - X)(y - Y))^2))
    // C = 2(sum((x - X)(y - Y)))

    var xDeviationSquaredSum = 0;
    var yDeviationSquaredSum = 0;
    var xyDeviationSum = 0;

    featureEach(points, function(point){
      xDeviation = getCoords(point)[0] - getCoords(theMeanCenter)[0];
      yDeviation = getCoords(point)[1] - getCoords(theMeanCenter)[1];
      xDeviationSquaredSum += Math.pow(xDeviation, 2);

function centerMedian(
    features: FeatureCollection,
    options: { weight?: string, tolerance?: number, counter?: number} = {}
): Feature,
    [key: string]: any
}> {
    // Optional params
    options = options || {};
    if (!isObject(options)) throw new Error('options is invalid');
    var counter = options.counter || 10;
    if (!isNumber(counter)) throw new Error('counter must be a number');
    var weightTerm = options.weight;

    // Calculate mean center:
    var meanCenter = centerMean(features, {weight: options.weight});

    // Calculate center of every feature:
    var centroids: any = featureCollection([]);
    featureEach(features, function (feature) {
        centroids.features.push(centroid(feature, {properties: {weight: feature.properties[weightTerm]}}));
    });

    centroids.properties = {
        tolerance: options.tolerance,
        medianCandidates: []
    };
    return findMedian(meanCenter.geometry.coordinates, [0, 0], centroids, counter);
}