const linearSearch = (arr, item) => {
  for (const i in arr) {
    if (arr[i] === item) return +i;
  }
  return -1;
};

linearSearch([2, 9, 9], 9); // 1
linearSearch([2, 9, 9], 7); // -1

const getSubsets = arr => arr.reduce((prev, curr) => prev.concat(prev.map(k => k.concat(curr))), [[]]);

// Examples
getSubsets([1, 2]);     // [[], [1], [2], [1, 2]]
getSubsets([1, 2, 3]);  // [[], [1], [2], [1, 2], [3], [1, 3], [2, 3], [1, 2, 3]]

const primes = num => {
  let arr = Array.from({ length: num - 1 }).map((x, i) => i + 2),
    sqroot = Math.floor(Math.sqrt(num)),
    numsTillSqroot = Array.from({ length: sqroot - 1 }).map((x, i) => i + 2);
  numsTillSqroot.forEach(x => (arr = arr.filter(y => y % x !== 0 || y === x)));
  return arr;
};

primes(10); // [2, 3, 5, 7]

const getURLParameters = url =>
(url.match(/([^?=&]+)(=([^&]*))/g) || []).reduce(
    (a, v) => (
      (a[v.slice(0, v.indexOf('='))] = v.slice(v.indexOf('=') + 1)), a
    ),
    {}
);

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]

const heapsort = arr => {
  const a = [...arr];
  let l = a.length;

  const heapify = (a, i) => {
    const left = 2 * i + 1;
    const right = 2 * i + 2;
    let max = i;
    if (left < l && a[left] > a[max]) max = left;
    if (right < l && a[right] > a[max]) max = right;
    if (max !== i) {
      [a[max], a[i]] = [a[i], a[max]];
      heapify(a, max);
    }
  };

  for (let i = Math.floor(l / 2); i >= 0; i -= 1) heapify(a, i);
  for (i = a.length - 1; i > 0; i--) {
    [a[0], a[i]] = [a[i], a[0]];
    l--;
    heapify(a, 0);
  }
  return a;
};

heapsort([6, 3, 4, 1]); // [1, 3, 4, 6]