80 lines
2.5 KiB
JavaScript
80 lines
2.5 KiB
JavaScript
/**
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* Pick a certain amount of unique objects from sourceList.
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* If the amount requested is more than total number of objects in sourceList,
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* only everything available in sourceList and nothing more will be picked.
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* @param {list} sourceList
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* @param {number} amount
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* @return {object} - {sample: list, remainder: list}
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sample is the list of selected objects while
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remainder is the list of those unselected.
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*/
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export function takeSampleFrom(sourceList, amount) {
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let randElements = [],
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max = sourceList.length;
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if (amount >= max) {
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return {sample: sourceList, remainder: {}};
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}
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for (let i = 0; i < amount; ++i) {
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let rand = sourceList[Math.floor((Math.random() * max))];
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// Re-random until suitable value is found.
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while (randElements.includes(rand)) {
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rand = sourceList[Math.floor((Math.random() * max))];
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}
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randElements.push(rand);
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}
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var remainder = sourceList.filter(function (obj) {
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return !randElements.includes(obj);
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});
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return {
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sample: randElements,
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remainder: remainder
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};
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}
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/**
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* With a circle radius r, and center at (h,k),
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* Find the coordinate of a point at angle degrees
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* @param {number} h
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* @param {number} k
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* @param {number} angle
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* @param {number} r
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* @return {object} - coordinate {x: number, y: number} of the point
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*/
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export function pointOnCircle(h, k, angle, r) {
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let x = h + r*Math.cos(toRadians(angle));
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let y = k + r*Math.sin(toRadians(angle));
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return {
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x: x,
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y: y
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};
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}
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function toRadians(degrees) {
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return degrees * (Math.PI / 180);
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}
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/**
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* Find the sum of ( difference between high and low dimensional distance )
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* between a node and each of the samples. The high dimensional distances are
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* precalculated and stored in realDistances.
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* @param {object} node - a single node, must have x and y properties
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* @param {list} samples - list of other node objects to compare against
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* @param {list} realDistances - list of number distances between the node to
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each of the samples. Index must correspond to
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that of samples.
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* @return {number} - Sum of distances differences
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*/
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export function sumDistError(node, samples, realDistances) {
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let total = 0.0;
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for (let i = 0; i < samples.length; i++) {
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let sample = samples[i];
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let lowDDistance = Math.hypot(sample.x - node.x, sample.y - node.y);
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total += Math.abs(lowDDistance - realDistances[i]);
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}
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return total;
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}
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