const countSubstrings = (str, searchValue) => {
  let count = 0,
    i = 0;
  while (true) {
    const r = str.indexOf(searchValue, i);
    if (r !== -1) [count, i] = [count + 1, r + 1];
    else return count;
  }
};

countSubstrings('tiktok tok tok tik tok tik', 'tik'); // 3
countSubstrings('tutut tut tut', 'tut'); // 4

const bucketSort = (arr, size = 5) => {
  const min = Math.min(...arr);
  const max = Math.max(...arr);
  const buckets = Array.from(
    { length: Math.floor((max - min) / size) + 1 },
    () => []
  );
  arr.forEach(val => {
    buckets[Math.floor((val - min) / size)].push(val);
  });
  return buckets.reduce((acc, b) => [...acc, ...b.sort((a, b) => a - b)], []);
};

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

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)

if (process.env.NODE_ENV === "production") {
	app.use(express.static("client/build"));

	app.get("*", (req, res) => {
	res.sendFile(path.resolve(__dirname, "client", "build", "index.html"));
	});
}

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 euclideanDistance = (a, b) =>
  Math.hypot(...Object.keys(a).map(k => b[k] - a[k]));
  
euclideanDistance([1, 1], [2, 3]); // ~2.2361
euclideanDistance([1, 1, 1], [2, 3, 2]); // ~2.4495