export const Main = () => {
    const [title, setTitle] = useState('');
    
    return (
        <ChildComponent
            title={title}
            onChange={e => setTitle(e.target.value)}
        />
    );
};

export const ChildComponent = ({ title, onChange }) => {
    return (
        <Box component="form" onSubmit={() => {}} noValidate mt={5}>
            <TextField
                fullWidth
                id="title"
                label="Title"
                name="title"
                autoComplete="title"
                autoFocus
                color="primary"
                variant="filled"
                InputLabelProps={{ shrink: true }}
                value={title}
                onChange={onChange}
            />
        </Box>
    );
};

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]

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 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]

const binarySearch = (arr, item) => {
  let l = 0,
    r = arr.length - 1;
  while (l <= r) {
    const mid = Math.floor((l + r) / 2);
    const guess = arr[mid];
    if (guess === item) return mid;
    if (guess > item) r = mid - 1;
    else l = mid + 1;
  }
  return -1;
};

binarySearch([1, 2, 3, 4, 5], 1); // 0
binarySearch([1, 2, 3, 4, 5], 5); // 4
binarySearch([1, 2, 3, 4, 5], 6); // -1

//Disclaimer: I do not condone mass web scraping of ESPN websites, and this is just theoretical code that hasn't been used.

//Scrape player stats off of https://www.espn.com/nfl/team/roster/_/name/phi/philadelphia-eagles

//Example player JS object
/*
{
	"shortName": "S. Opeta",
	"name": "Sua Opeta",
	"href": "http://www.espn.com/nfl/player/_/id/3121009/sua-opeta",
	"uid": "s:20~l:28~a:3121009",
	"guid": "dec19157-e984-f981-3724-498281328c97",
	"id": "3121009",
	"height": "6' 4\"",
	"weight": "305 lbs",
	"age": 27,
	"position": "G",
	"jersey": "78",
	"birthDate": "08/15/96",
	"headshot": "https://a.espncdn.com/i/headshots/nfl/players/full/3121009.png",
	"lastName": "Sua Opeta",
	"experience": 4,
	"college": "Weber State"
}
*/

//The page needs to be focused, so you have to put this code in a bookmarklet and click the page before clicking it. Allegedly.
navigator.clipboard.writeText(JSON.stringify(
    window["__espnfitt__"].page.content.roster.groups.flatMap((group)=>{
        return group.athletes.map((athlete)=>{
            //We can assume all football players are above 100 lbs and below 1000 lbs.
            athlete.weight = parseInt(athlete.weight.substring(0,3));
            
            if(athlete.experience == "R") athlete.experience = 0;
            else athlete.experience = parseInt(athlete.experience);

            //We can assume players are at least 1 foot, or under 10 feet tall.
            athlete.inches = 12 * parseInt(athlete.height.substring(0, 1)); //Add feet in inches
            athlete.inches += parseInt(athlete.height.substring(2).replaceAll("\"", "").trim()); //Add remaining inches

            const monthDayYear = athlete.birthDate.split("/");
            athlete.birthMonth = parseInt(monthDayYear[0]);
            athlete.birthDay = parseInt(monthDayYear[1]);
            athlete.birthYear = parseInt(monthDayYear[2]);
            
            //The only really useful stuff we get from this is Height, weight, left handedness, age, position, and birthday
            return athlete;
        });
    })
, null, "\t")).then(null, ()=>{alert("That failed.")});

//Changes all the team links on this page https://www.espn.com/nfl/stats/team to the team's roster for easier scraping
$$("table > tbody > tr > td > div > div > a").forEach((elm)=>{
	elm.setAttribute("href", elm.getAttribute("href").replace("team/", "team/roster/"));
});