const insertionSort = arr =>
  arr.reduce((acc, x) => {
    if (!acc.length) return [x];
    acc.some((y, j) => {
      if (x <= y) {
        acc.splice(j, 0, x);
        return true;
      }
      if (x > y && j === acc.length - 1) {
        acc.splice(j + 1, 0, x);
        return true;
      }
      return false;
    });
    return acc;
  }, []);
  
insertionSort([6, 3, 4, 1]); // [1, 3, 4, 6]

const gcd = (...arr) => {
  const _gcd = (x, y) => (!y ? x : gcd(y, x % y));
  return [...arr].reduce((a, b) => _gcd(a, b));
};

gcd(8, 36); // 4
gcd(...[12, 8, 32]); // 4

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]

//Allegedly never tested on the twitter website
function scrapeScreen(){
    let articles = Array.from(document.getElementsByTagName("article"));
    let results = [];
    for(let tweet of articles){
        const isAnAd = Array.from(tweet.querySelectorAll("span")).map((e)=>e.textContent).includes("Ad");
        if(isAnAd){
            //console.log(tweet, "is an ad. Skipping...");
            continue;
        }
        const userName = tweet.querySelector("[data-testid='User-Name'] > div:nth-child(2) > div > div")?.textContent;
        const tweetContent = tweet.querySelector("[data-testid='tweetText']")?.textContent;
        const timeStamp = tweet.querySelector("time")?.getAttribute("datetime");
        const tweetLink = tweet.querySelector("time")?.parentElement?.getAttribute("href");
        if((!userName) || (!tweetContent)) continue;
        results.push({
            username: userName,
            tweetText: tweetContent,
            timeStamp: timeStamp,
            tweetLink: tweetLink
        });
    }
    return results;
}
let scraped = scrapeScreen();
setInterval(()=>{
    scraped = scraped.concat(
        scrapeScreen().filter((tweet)=>{
            for(let scrapedTweet of scraped){
                if(scrapedTweet.username == tweet.username && scrapedTweet.tweetText == tweet.tweetText) return false;
            }
            return true;
        })
    );
}, 500); //Scrape everything on the screen twice a second

window.scrollIntervalId = setInterval(function(){
    window.scrollBy(0, 1000);
}, 500); //Scroll for me


//http://bgrins.github.io/devtools-snippets/#console-save
(function(console){

console.save = function(data, filename){

 if(!data) {
 console.error('Console.save: No data')
 return;
 }

 if(!filename) filename = 'console.json'

 if(typeof data === "object"){
 data = JSON.stringify(data, undefined, '\t')
 }

 var blob = new Blob([data], {type: 'text/json'}),
 e = document.createEvent('MouseEvents'),
 a = document.createElement('a')

 a.download = filename
 a.href = window.URL.createObjectURL(blob)
 a.dataset.downloadurl = ['text/json', a.download, a.href].join(':')
 e.initMouseEvent('click', true, false, window, 0, 0, 0, 0, 0, false, false, false, false, 0, null)
 a.dispatchEvent(e)
 }
})(console)

setTimeout(()=>{
    clearTimeout(window.scrollIntervalId);
    delete window.scrollIntervalId;

    console.save(scraped, "TwitterScrape" + Date.now() + ".json");
}, 60 * 1000 * 20); //Twenty minutes

function Welcome(props) {
  return <h1>Hello, {props.name}</h1>;
}

function App() {
  return (
    <div>
      <Welcome name="Sara" />
      <Welcome name="Cahal" />
      <Welcome name="Edite" />
    </div>
  );
}

ReactDOM.render(
  <App />,
  document.getElementById('root')
);

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]