/**
 * @param {number[]} nums
 * @param {number} target
 * @return {number[]}
 */
var twoSum = function(nums, target) {
    for(let i = 0; i < nums.length; i++) {
        for(let j = 0; j < nums.length; j++) {
            if(nums[i] + nums[j] === target && i !== j) {
                return [i, j]
            }
        }
    }
};

const shuffle = ([...arr]) => {
  let m = arr.length;
  while (m) {
    const i = Math.floor(Math.random() * m--);
    [arr[m], arr[i]] = [arr[i], arr[m]];
  }
  return arr;
};

const foo = [1, 2, 3];
shuffle(foo); // [2, 3, 1], foo = [1, 2, 3]

console.log("xa")

const getSearchTerm = delimiter => {
	let searchTerm = "";

	for (let i = 1; i < commands.length - 1; i++)
	searchTerm = searchTerm + commands[i] + delimiter;

	searchTerm += commands[commands.length - 1];

	return searchTerm;
	};

function printHeap(heap, index, level) {
    if (index >= heap.length) {
        return;
    }
    console.log("  ".repeat(level) + heap[index]);
    printHeap(heap, 2 * index + 1, level + 1);
    printHeap(heap, 2 * index + 2, level + 1);
}

//You can call this function by passing in the heap array and the index of the root node, which is typically 0, and level = 0.

let heap = [3, 8, 7, 15, 17, 30, 35, 2, 4, 5, 9];
printHeap(heap,0,0)

const kMeans = (data, k = 1) => {
  const centroids = data.slice(0, k);
  const distances = Array.from({ length: data.length }, () =>
    Array.from({ length: k }, () => 0)
  );
  const classes = Array.from({ length: data.length }, () => -1);
  let itr = true;

  while (itr) {
    itr = false;

    for (let d in data) {
      for (let c = 0; c < k; c++) {
        distances[d][c] = Math.hypot(
          ...Object.keys(data[0]).map(key => data[d][key] - centroids[c][key])
        );
      }
      const m = distances[d].indexOf(Math.min(...distances[d]));
      if (classes[d] !== m) itr = true;
      classes[d] = m;
    }

    for (let c = 0; c < k; c++) {
      centroids[c] = Array.from({ length: data[0].length }, () => 0);
      const size = data.reduce((acc, _, d) => {
        if (classes[d] === c) {
          acc++;
          for (let i in data[0]) centroids[c][i] += data[d][i];
        }
        return acc;
      }, 0);
      for (let i in data[0]) {
        centroids[c][i] = parseFloat(Number(centroids[c][i] / size).toFixed(2));
      }
    }
  }

  return classes;
};
kMeans([[0, 0], [0, 1], [1, 3], [2, 0]], 2); // [0, 1, 1, 0]