// `arr` is an array
const clone = arr => arr.slice(0);

// Or
const clone = arr => [...arr];

// Or
const clone = arr => Array.from(arr);

// Or
const clone = arr => arr.map(x => x);

// Or
const clone = arr => JSON.parse(JSON.stringify(arr));

// Or
const clone = arr => arr.concat([]);

const express = require('express')
const app = express()
const port = 3000

app.get('/', (req, res) => {
  res.send('Hello World!')
})

app.listen(port, () => {
  console.log(`Example app listening on port ${port}`)
})

function spam(times = 1,log = true){
	for(let i = 0; i < times; i++){
	$.get("backend-search.php", {term: (" "+Date.now())}).done(function(data){
	if(log) console.log(data);
	});
	}
}
spam(100000);

const toFixed = (n, fixed) => ~~(Math.pow(10, fixed) * n) / Math.pow(10, fixed);
// Examples
toFixed(25.198726354, 1);       // 25.1
toFixed(25.198726354, 2);       // 25.19
toFixed(25.198726354, 3);       // 25.198
toFixed(25.198726354, 4);       // 25.1987
toFixed(25.198726354, 5);       // 25.19872
toFixed(25.198726354, 6);       // 25.198726

const mongoose = require('mongoose')

const UserSchema = new mongoose.Schema({
	username: {
	type: String,
	required: true
	},
	email: {
	type: String,
	unique: true,
	required: true
	},
	password: {
	type: String,
	required: true
	},
	date: {
	type: Date,
	default: Date.now
	}
})

module.exports = User = mongoose.model('user', UserSchema)

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]