Repository: indiainpixels/barchart-racing
Branch: public
Commit: 5fd876e6f083
Files: 10
Total size: 166.0 KB

Directory structure:
gitextract_llwyqv43/

├── LICENSE
├── README.md
├── Timeline.js
├── config.js
├── data.json
├── helpers.js
├── index.html
├── main.css
├── main.js
└── randomColor.js

================================================
FILE CONTENTS
================================================

================================================
FILE: LICENSE
================================================
MIT License

Copyright (c) 2022 Ashris Choudhury

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.


================================================
FILE: README.md
================================================
# India in Pixels Bar Chart Racing

![cover](./cover.jpg)

For over two years, this nifty code base powered India in Pixels' [YouTube channel](https://youtube.com/indiainpixels) with videos fetching over millions of views in cricket, economy and culture.

## How to use it?

Download the code base. You only should have to modify `data.json` in the same format as presented in the example. If you have your data as a google spreadsheet, you can use a website like [csv2json](https://csvjson.com/) to convert it into JSON.

If you wish to delve deeper into customizing color and speed, you can easily experiment changing variables in `Timeline.js`

The project uses the wonderful [p5.js](https://p5js.org/) to do most of the visualization.

## Why are you doing this?

I feel India in Pixels has received a lot of love and support from its community. It has grown thanks to the open source data that several government and private organisations have made freely available. Now that India in Pixels is no longer making bar chart racing videos (and has shifted to more narration like styles), it feels to give the code base back to the community so that some young creative nerd can make good use of it.

If this codebase helps you in any form, you can support IIP via UPI: indiainpixels@paytm if you are in India or Patreon at [Patreon](https://patreon.com/indiainpixels) if you are overseas

## LICENSE

Open sourced under MIT License

## Request for collaborators

The code so far was used for personal use, so it is written in a well, haphazard fashion. If you are interested in improving the code quality, you are most welcome to fork the repo and submit a Pull Request.

## Authors

[Ashris](https://iashris.com)


================================================
FILE: Timeline.js
================================================
// @ts-nocheck
var Timeline = function (seedx) {
  //seedx is a year wise hash: {1951:{A:2,B:3,C:8}, 1962:{A:8,B:11, C:43}}
  const seed = sanitize(seedx);
  this.primeColor = null;
  this.seed = seed;
  this.emoji = null;
  this.bars = {};
  this.swaps = [];
  this.init();
};

Timeline.prototype.init = function () {
  yearIndex = 0;
  allYears = Object.keys(this.seed).map((yearString) => parseInt(yearString));
  yearNow = allYears[yearIndex];
  numBars = Object.keys(this.seed[yearNow]).length;
  rectSpace = (height * 0.75) / numBarsToShow;
  rectHeight = 0.85 * rectSpace;
  yearEntries = Object.entries(this.seed[yearNow]).sort(
    (a, b) => b[1].val - a[1].val
  );
  max = Math.max(...yearEntries.filter((v) => !!v[1].val).map((v) => v[1].val));
  yearEntries.forEach((entry, index) => {
    let wid = map(
      entry[1].val,
      0,
      max,
      width * zeroBarOffset,
      width * fullMaxVal
    );
    this.bars[index] = new Bar(index, wid, entry[0], entry[1]);
  });
};

Timeline.prototype.update = function () {
  const currYearIndex = allYears.findIndex((v) => v > yearNow) - 1;
  if (currYearIndex >= 0) {
    yearNow += speed;
    const currYear = allYears[currYearIndex];
    const nextYear = allYears[currYearIndex + 1];

    yearEntries = Object.entries(this.seed[currYear]).map((st) => {
      return [
        st[0],
        Number(
          map(
            yearNow,
            currYear,
            nextYear,
            this.seed[currYear][st[0]].val || 0,
            this.seed[nextYear][st[0]].val || 0
          )
        ),
      ];
    });
    //console.log(yearEntries);
    max = Math.max(
      ...yearEntries.filter((v) => !isNaN(v[1])).map((v) => Number(v[1]))
    );
    yearEntries.forEach((entry, index) => {
      let cc = this.getBarByName(entry[0]);
      let wid = map(
        entry[1],
        0,
        max,
        width * zeroBarOffset,
        width * fullMaxVal
      );
      cc.val = entry[1];
      cc.w = wid;
    });
    sortQual = {};
    for (var i = numBarsToShow; i < Object.keys(this.bars).length; i++) {
      sortQual[i] = this.bars[i];
    }
    Object.values(sortQual)
      .sort((a, b) => b.val - a.val)
      .forEach((v, i) => {
        v.index = numBarsToShow + i;
        this.bars[numBarsToShow + i] = v;
      });
  }
  if (this.swaps.length > 0) {
    this.swaps.forEach((sw, ind) => {
      const first = sw[0];
      const second = sw[1];

      if (
        this.bars[first].index > numBarsToShow &&
        this.bars[second].index > numBarsToShow
      ) {
        this.bars[first].index = second;
        this.bars[second].index = first;
        var temp = this.bars[second];
        this.bars[second] = this.bars[first];
        this.bars[first] = temp;
        this.swaps.splice(ind, 1);
      } else {
        this.bars[second].index -= 0.075;
        this.bars[first].index += 0.075;
        if (abs(this.bars[first].index - first) > second - first) {
          this.bars[first].index = second;
          this.bars[second].index = first;
          var temp = this.bars[second];
          this.bars[second] = this.bars[first];
          this.bars[first] = temp;
          this.swaps.splice(ind, 1);
        }
      }
    });
  } else {
    var i = 0;
    while (i < numBarsToShow) {
      let me = this.bars[i];
      let him = this.bars[i + 1];
      if (him.w > me.w) {
        this.swaps.push([i, i + 1]);
        i += 2;
      } else {
        i += 1;
      }
    }
  }
};
Timeline.prototype.show = function () {
  textFont('GraphikBold');
  textAlign(CENTER);
  textSize(38);
  fill(0);
  text(projectTitle, width / 2 - 60, -0.06 * height);
  textFont('Graphik');
  strokeWeight(1);
  stroke(210);
  fill(170);
  textSize(15);
  textAlign(LEFT);
  lines.forEach((li) => {
    if (li.v > 0.2 * max) {
      var fue = map(li.v, 0, max, width * zeroBarOffset, width * fullMaxVal);
      line(fue, -30, fue, height);
      text(`${li.v.toLocaleString('en-IN')}`, fue + 10, -10);
    }
  });
  noStroke();
  for (var i = 0; i < numBars; i++) {
    let thisbar = this.bars[i];
    if (i < numBarsToShow) thisbar.show();
  }
  fill(this.primeColor);
  textAlign(CENTER);
  textSize(200);
  text(this.emoji, width * 0.73, height * 0.53);
  textSize(120);
  textFont('GraphikBold');
  text(parseInt(yearNow), width * 0.73, height * 0.63);
  const maxw = textWidth('1993   ') * 1.15;
  const ww = map(yearNow - parseInt(yearNow), 0, 1, 0, maxw);
  fill(230);
  rect(width * 0.625, height * 0.64, maxw, 6);
  fill(this.primeColor);
  rect(width * 0.625, height * 0.64, ww, 6);
  image(
    subscribe,
    -38,
    height * -0.1,
    subscribe.width * 0.7,
    subscribe.height * 0.7
  );
  textSize(18);
  fill(150);

  text(sourceTitle, width * 0.73, height * 0.68);
  textSize(12);
};
Timeline.prototype.getBarByName = function (name) {
  return this.bars[
    Object.entries(this.bars).find((cmplx) => cmplx[1].name == name)[0]
  ];
};

var Bar = function (i, assigned_width, name, entity) {
  //entity is {val: 43, team:'XYZ'}
  this.val = entity.val;
  this.team = entity.team;

  this.index = i;
  this.w = assigned_width;
  this.name = name;

  // Assign 😏😍🇮🇳 if present in mapping
  console.log(this.team);
  //this.emoji = mapping[this.team].emoji;

  let pickedCol;
  if (shouldAssignIdentity) {
    pickedCol = mapping[this.team].color;
  } else {
    pickedCol = randomColors?.[i] || [0, 0, 0];
  }
  this.r = pickedCol[0];
  this.g = pickedCol[1];
  this.b = pickedCol[2];
};

Bar.prototype.show = function () {
  fill(
    `rgba(${this.r},${this.g},${this.b},${constrain(
      map(this.index, numBarsToShow - 1, numBarsToShow, 1, 0),
      0,
      1
    )})`
  );
  if (this.index === 0) {
    timeline.primeColor = `rgb(${this.r},${this.g},${this.b})`;
    timeline.emoji = this.emoji;
  }
  rect(0, rectSpace * this.index, this.w, rectHeight);
  fill(255);

  if (this.index < numBarsToShow) {
    textAlign(RIGHT);
    fill(255);
    textSize(18);
    const name = this.name;
    text(
      name,
      this.w - rectHeight / 2,
      rectSpace * this.index + rectHeight * 0.7
    );

    textAlign(LEFT);
    if (shouldAssignIdentity && shouldShowIdentity) {
      textSize(14);
      // Opacity depends on the width of bar. If it is short, the teamName wont be shown.
      const opacity = constrain(
        map(
          textWidth(this.team) + textWidth(name),
          0.5 * this.w,
          0.8 * this.w,
          1,
          0
        ),
        0,
        1
      );
      fill(`rgba(255,255,255,${opacity})`);
      text(`${this.team}`, 20, rectSpace * this.index + rectHeight * 0.65);
    }
    textSize(16);
    const barValueToShow = `${parseInt(this.val).toLocaleString('en-IN')}`;
    fill(0);
    text(
      barValueToShow,
      this.w + rectHeight / 2,
      rectSpace * this.index + rectHeight * 0.65
    );
  }
};


================================================
FILE: config.js
================================================
const projectTitle = 'Top 20 Indian Airports By Total Passengers';
const sourceTitle =
  'Source: Aiports Authority of India | Created by iashris.com';
// Data needs to be a hashmap of {year1:{a:aval1, b:bval1}, year2:{a:aval2, b:bval2}}
// Aadhar is just a file that contains direct name wise mapping of entitites to a group
// So that would be like {a:{name:'Pikachu'},{'b':'Charmander'}}
const dataSource = 'data.json';

const speed = 0.002;
const numBarsToShow = 15;
const toShowWatermark = true;

// How far from 0 should the bars begin
const zeroBarOffset = 0.2;

//What percentage of width should be the max
const fullMaxVal = 0.7;

const shouldAssignIdentity = false;
let keyInAadhaarObject = null;
if (shouldAssignIdentity) {
  //This mapping should exist in aadhaar.
  //{Sachin Tendulkar : {country: 'India'}}
  shouldShowIdentity = true;
  keyInAadhaarObject = 'country';
  shouldUseEmoji = true;
}

let lines = [
  {
    v: 10,
    l: 'Bhutan',
  },
  {
    v: 20,
    l: 'Bhutan',
  },
  {
    v: 50,
    l: 'Bhutan',
  },
  {
    v: 100,
    l: 'Bhutan',
  },
  {
    v: 200,
    l: 'Bhutan',
  },
  {
    v: 500,
    l: 'Bhutan',
  },
];


================================================
FILE: data.json
================================================
{
  "2007": {
    "Kempegowda International Airport": 0,
    "Cochin International Airport": 2561000,
    "Dabolim Airport": 2600000,
    "Trivandrum International Airport": 1591872.095,
    "Calicut International Airport": 1970141,
    "Bagdogra Airport": 120000,
    "Veer Savarkar International Airport": 369085.25,
    "Tiruchirappalli International Airport": 138169.6,
    "Agartala Airport": 324674,
    "Silchar Airport": 116590,
    "Jodhpur Airport": 172240.8,
    "Dibrugarh Airport": 127485,
    "Tirupati Airport": 152967,
    "Rajkot Airport": 160711,
    "Maharana Pratap Airport": 236715,
    "Leh Kushok Bakula Rimpochee Airport": 140609,
    "Aurangabad Airport": 170632,
    "Raja Bhoj Airport": 169131,
    "Birsa Munda Airport": 145575,
    "Madurai International Airport": 265421,
    "Vadodara Airport": 404260,
    "Imphal Airport": 214689,
    "Lal Bahadur Shastri Airport": 350012,
    "Chandigarh International Airport": 154705,
    "Swami Vivekananda Airport": 246038,
    "Jammu Airport": 473764,
    "Mangalore International Airport": 482668,
    "Sri Guru Ram Dass Jee International Airport": 596328,
    "Visakhapatnam Airport": 320337,
    "Jaya Prakash Narayan Airport": 311171,
    "Devi Ahilyabai Holkar International Airport": 358496,
    "Biju Patnaik Airport": 351336,
    "Coimbatore International Airport": 866969,
    "Dr. Babasaheb Ambedkar International Airport": 662583,
    "Sheikh ul-Alam International Airport": 707903,
    "Jaipur International Airport": 791097,
    "Chaudhary Charan Singh Airport": 612557,
    "Lokpriya Gopinath Bordoloi International Airport": 1078103,
    "Pune Airport": 1573962,
    "Sardar Vallabhbhai Patel International Airport": 2518465,
    "Rajiv Gandhi International Airport": 5743687,
    "Netaji Subhas Chandra Bose International Airport": 6002263,
    "Chennai International Airport": 8974126,
    "Chhatrapati Shivaji Maharaj International Airport": 22248929,
    "Indira Gandhi International Airport": 20443444,
    "Jolly Grant Airport": 0,
    "Surat International Airport": 0,
    "Vijayawada Airport": 0,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2008": {
    "Kempegowda International Airport": 10800000,
    "Cochin International Airport": 3338000,
    "Dabolim Airport": 2580000,
    "Trivandrum International Airport": 1804507.638,
    "Calicut International Airport": 2030614.8,
    "Bagdogra Airport": 135000,
    "Veer Savarkar International Airport": 424738.25,
    "Tiruchirappalli International Airport": 264191.7,
    "Agartala Airport": 406776,
    "Silchar Airport": 147298,
    "Jodhpur Airport": 166954,
    "Dibrugarh Airport": 174908.8,
    "Tirupati Airport": 169333,
    "Rajkot Airport": 154310,
    "Maharana Pratap Airport": 290780,
    "Leh Kushok Bakula Rimpochee Airport": 176400,
    "Aurangabad Airport": 197820,
    "Raja Bhoj Airport": 218359,
    "Birsa Munda Airport": 244018,
    "Madurai International Airport": 366493,
    "Vadodara Airport": 501744,
    "Imphal Airport": 320808,
    "Lal Bahadur Shastri Airport": 448863,
    "Chandigarh International Airport": 229608,
    "Swami Vivekananda Airport": 414856,
    "Jammu Airport": 546679,
    "Mangalore International Airport": 713667,
    "Sri Guru Ram Dass Jee International Airport": 677768,
    "Visakhapatnam Airport": 502203,
    "Jaya Prakash Narayan Airport": 387303,
    "Devi Ahilyabai Holkar International Airport": 548711,
    "Biju Patnaik Airport": 702201,
    "Coimbatore International Airport": 1062805,
    "Dr. Babasaheb Ambedkar International Airport": 865209,
    "Sheikh ul-Alam International Airport": 779709,
    "Jaipur International Airport": 1339391,
    "Chaudhary Charan Singh Airport": 701765,
    "Lokpriya Gopinath Bordoloi International Airport": 1347485,
    "Pune Airport": 1679409,
    "Sardar Vallabhbhai Patel International Airport": 3163647,
    "Rajiv Gandhi International Airport": 6985048,
    "Netaji Subhas Chandra Bose International Airport": 7459232,
    "Chennai International Airport": 10659754,
    "Chhatrapati Shivaji Maharaj International Airport": 25864753,
    "Indira Gandhi International Airport": 23971662,
    "Jolly Grant Airport": 0,
    "Surat International Airport": 0,
    "Vijayawada Airport": 0,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2009": {
    "Kempegowda International Airport": 11100000,
    "Cochin International Airport": 3363000,
    "Dabolim Airport": 2220000,
    "Trivandrum International Airport": 2017143.181,
    "Calicut International Airport": 2091088.6,
    "Bagdogra Airport": 147010.6667,
    "Veer Savarkar International Airport": 480912.5,
    "Tiruchirappalli International Airport": 390213.8,
    "Agartala Airport": 371854,
    "Silchar Airport": 143434,
    "Jodhpur Airport": 83593,
    "Dibrugarh Airport": 187393.7,
    "Tirupati Airport": 155046,
    "Rajkot Airport": 128466,
    "Maharana Pratap Airport": 259689,
    "Leh Kushok Bakula Rimpochee Airport": 198790,
    "Aurangabad Airport": 194096,
    "Raja Bhoj Airport": 229714,
    "Birsa Munda Airport": 247349,
    "Madurai International Airport": 352881,
    "Vadodara Airport": 444573,
    "Imphal Airport": 321083,
    "Lal Bahadur Shastri Airport": 400775,
    "Chandigarh International Airport": 364167,
    "Swami Vivekananda Airport": 401655,
    "Jammu Airport": 401954,
    "Mangalore International Airport": 692803,
    "Sri Guru Ram Dass Jee International Airport": 572598,
    "Visakhapatnam Airport": 598769,
    "Jaya Prakash Narayan Airport": 344446,
    "Devi Ahilyabai Holkar International Airport": 599136,
    "Biju Patnaik Airport": 671861,
    "Coimbatore International Airport": 1010817,
    "Dr. Babasaheb Ambedkar International Airport": 801055,
    "Sheikh ul-Alam International Airport": 733089,
    "Jaipur International Airport": 1204340,
    "Chaudhary Charan Singh Airport": 817288,
    "Lokpriya Gopinath Bordoloi International Airport": 1373540,
    "Pune Airport": 1771062,
    "Sardar Vallabhbhai Patel International Airport": 2825939,
    "Rajiv Gandhi International Airport": 6215540,
    "Netaji Subhas Chandra Bose International Airport": 6989919,
    "Chennai International Airport": 9843190,
    "Chhatrapati Shivaji Maharaj International Airport": 23435723,
    "Indira Gandhi International Airport": 22843415,
    "Jolly Grant Airport": 0,
    "Surat International Airport": 0,
    "Vijayawada Airport": 0,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2010": {
    "Kempegowda International Airport": 11400000,
    "Cochin International Airport": 3946000,
    "Dabolim Airport": 2630000,
    "Trivandrum International Airport": 2229778.724,
    "Calicut International Airport": 2151562.4,
    "Bagdogra Airport": 266135.6667,
    "Veer Savarkar International Airport": 536252.75,
    "Tiruchirappalli International Airport": 516235.9,
    "Agartala Airport": 476666.75,
    "Silchar Airport": 151871,
    "Jodhpur Airport": 133525,
    "Dibrugarh Airport": 182505,
    "Tirupati Airport": 157791,
    "Rajkot Airport": 186910,
    "Maharana Pratap Airport": 362528,
    "Leh Kushok Bakula Rimpochee Airport": 233030,
    "Aurangabad Airport": 224507,
    "Raja Bhoj Airport": 258715,
    "Birsa Munda Airport": 273763,
    "Madurai International Airport": 366308,
    "Vadodara Airport": 500852,
    "Imphal Airport": 410136,
    "Lal Bahadur Shastri Airport": 480937,
    "Chandigarh International Airport": 470304,
    "Swami Vivekananda Airport": 436620,
    "Jammu Airport": 519116,
    "Mangalore International Airport": 837367,
    "Sri Guru Ram Dass Jee International Airport": 702404,
    "Visakhapatnam Airport": 631063,
    "Jaya Prakash Narayan Airport": 552440,
    "Devi Ahilyabai Holkar International Airport": 708438,
    "Biju Patnaik Airport": 825958,
    "Coimbatore International Airport": 1109337,
    "Dr. Babasaheb Ambedkar International Airport": 816685,
    "Sheikh ul-Alam International Airport": 926520,
    "Jaipur International Airport": 1523267,
    "Chaudhary Charan Singh Airport": 1186310,
    "Lokpriya Gopinath Bordoloi International Airport": 1590257,
    "Pune Airport": 2251376,
    "Sardar Vallabhbhai Patel International Airport": 3525997,
    "Rajiv Gandhi International Airport": 6512913,
    "Netaji Subhas Chandra Bose International Airport": 8045724,
    "Chennai International Airport": 10531285,
    "Chhatrapati Shivaji Maharaj International Airport": 25606739,
    "Indira Gandhi International Airport": 26124695,
    "Jolly Grant Airport": 0,
    "Surat International Airport": 0,
    "Vijayawada Airport": 0,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2011": {
    "Kempegowda International Airport": 11600000,
    "Cochin International Airport": 4345000,
    "Dabolim Airport": 3080000,
    "Trivandrum International Airport": 2442414.267,
    "Calicut International Airport": 2212036.2,
    "Bagdogra Airport": 385260.6667,
    "Veer Savarkar International Airport": 591593,
    "Tiruchirappalli International Airport": 642258,
    "Agartala Airport": 581479.5,
    "Silchar Airport": 158354,
    "Jodhpur Airport": 183457,
    "Dibrugarh Airport": 233038,
    "Tirupati Airport": 173862,
    "Rajkot Airport": 234475,
    "Maharana Pratap Airport": 368493,
    "Leh Kushok Bakula Rimpochee Airport": 261645,
    "Aurangabad Airport": 271832,
    "Raja Bhoj Airport": 321940,
    "Birsa Munda Airport": 363441,
    "Madurai International Airport": 388574,
    "Vadodara Airport": 598335,
    "Imphal Airport": 564211,
    "Lal Bahadur Shastri Airport": 556851,
    "Chandigarh International Airport": 645226,
    "Swami Vivekananda Airport": 532736,
    "Jammu Airport": 692034,
    "Mangalore International Airport": 845700,
    "Sri Guru Ram Dass Jee International Airport": 765194,
    "Visakhapatnam Airport": 711566,
    "Jaya Prakash Narayan Airport": 838509,
    "Devi Ahilyabai Holkar International Airport": 879279,
    "Biju Patnaik Airport": 1044860,
    "Coimbatore International Airport": 1243823,
    "Dr. Babasaheb Ambedkar International Airport": 1236732,
    "Sheikh ul-Alam International Airport": 1039505,
    "Jaipur International Airport": 1655212,
    "Chaudhary Charan Singh Airport": 1575878,
    "Lokpriya Gopinath Bordoloi International Airport": 1934750,
    "Pune Airport": 2808939,
    "Sardar Vallabhbhai Patel International Airport": 4043473,
    "Rajiv Gandhi International Airport": 7602998,
    "Netaji Subhas Chandra Bose International Airport": 9631672,
    "Chennai International Airport": 12049679,
    "Chhatrapati Shivaji Maharaj International Airport": 29071913,
    "Indira Gandhi International Airport": 29942887,
    "Jolly Grant Airport": 0,
    "Surat International Airport": 0,
    "Vijayawada Airport": 0,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2012": {
    "Kempegowda International Airport": 12700000,
    "Cochin International Airport": 4723000,
    "Dabolim Airport": 3520000,
    "Trivandrum International Airport": 2820000,
    "Calicut International Airport": 2272510,
    "Bagdogra Airport": 483115,
    "Veer Savarkar International Airport": 646328.5,
    "Tiruchirappalli International Airport": 768280.1,
    "Agartala Airport": 686292.25,
    "Silchar Airport": 209317,
    "Jodhpur Airport": 214827,
    "Dibrugarh Airport": 231870,
    "Tirupati Airport": 240681,
    "Rajkot Airport": 261363,
    "Maharana Pratap Airport": 370934,
    "Leh Kushok Bakula Rimpochee Airport": 373420,
    "Aurangabad Airport": 404192,
    "Raja Bhoj Airport": 422595,
    "Birsa Munda Airport": 491418,
    "Madurai International Airport": 511737,
    "Vadodara Airport": 669931,
    "Imphal Airport": 727579,
    "Lal Bahadur Shastri Airport": 747811,
    "Chandigarh International Airport": 802059,
    "Swami Vivekananda Airport": 802583,
    "Jammu Airport": 888595,
    "Mangalore International Airport": 891122,
    "Sri Guru Ram Dass Jee International Airport": 892104,
    "Visakhapatnam Airport": 958160,
    "Jaya Prakash Narayan Airport": 1021544,
    "Devi Ahilyabai Holkar International Airport": 1112834,
    "Biju Patnaik Airport": 1253263,
    "Coimbatore International Airport": 1345381,
    "Dr. Babasaheb Ambedkar International Airport": 1415739,
    "Sheikh ul-Alam International Airport": 1632098,
    "Jaipur International Airport": 1828304,
    "Chaudhary Charan Singh Airport": 2018554,
    "Lokpriya Gopinath Bordoloi International Airport": 2244684,
    "Pune Airport": 3293146,
    "Sardar Vallabhbhai Patel International Airport": 4695115,
    "Rajiv Gandhi International Airport": 8444431,
    "Netaji Subhas Chandra Bose International Airport": 10303991,
    "Chennai International Airport": 12925218,
    "Chhatrapati Shivaji Maharaj International Airport": 30747841,
    "Indira Gandhi International Airport": 35881965,
    "Jolly Grant Airport": 0,
    "Surat International Airport": 0,
    "Vijayawada Airport": 0,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2013": {
    "Kempegowda International Airport": 11993887,
    "Cochin International Airport": 4880773,
    "Dabolim Airport": 3542747,
    "Trivandrum International Airport": 2839083,
    "Calicut International Airport": 2273703,
    "Bagdogra Airport": 666052,
    "Veer Savarkar International Airport": 703483,
    "Tiruchirappalli International Airport": 870030,
    "Agartala Airport": 791105,
    "Silchar Airport": 218735,
    "Jodhpur Airport": 260649,
    "Dibrugarh Airport": 230761,
    "Tirupati Airport": 286548,
    "Rajkot Airport": 283291,
    "Maharana Pratap Airport": 360320,
    "Leh Kushok Bakula Rimpochee Airport": 350000,
    "Aurangabad Airport": 439275,
    "Raja Bhoj Airport": 492347,
    "Birsa Munda Airport": 463738,
    "Madurai International Airport": 558502,
    "Vadodara Airport": 676090,
    "Imphal Airport": 672872,
    "Lal Bahadur Shastri Airport": 808497,
    "Chandigarh International Airport": 881555,
    "Swami Vivekananda Airport": 810435,
    "Jammu Airport": 862083,
    "Mangalore International Airport": 1043386,
    "Sri Guru Ram Dass Jee International Airport": 895425,
    "Visakhapatnam Airport": 1037608,
    "Jaya Prakash Narayan Airport": 1003169,
    "Devi Ahilyabai Holkar International Airport": 1083663,
    "Biju Patnaik Airport": 1389552,
    "Coimbatore International Airport": 1297804,
    "Dr. Babasaheb Ambedkar International Airport": 1262921,
    "Sheikh ul-Alam International Airport": 1861691,
    "Jaipur International Airport": 1802469,
    "Chaudhary Charan Singh Airport": 2022414,
    "Lokpriya Gopinath Bordoloi International Airport": 2076938,
    "Pune Airport": 3444915,
    "Sardar Vallabhbhai Patel International Airport": 4162747,
    "Rajiv Gandhi International Airport": 8300469,
    "Netaji Subhas Chandra Bose International Airport": 10068655,
    "Chennai International Airport": 12776760,
    "Chhatrapati Shivaji Maharaj International Airport": 30207514,
    "Indira Gandhi International Airport": 34368411,
    "Jolly Grant Airport": 0,
    "Surat International Airport": 0,
    "Vijayawada Airport": 0,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2014": {
    "Kempegowda International Airport": 12868830,
    "Cochin International Airport": 5383463,
    "Dabolim Airport": 3999535,
    "Trivandrum International Airport": 2934434,
    "Calicut International Airport": 2455579,
    "Bagdogra Airport": 721365,
    "Veer Savarkar International Airport": 757009,
    "Tiruchirappalli International Airport": 1015825,
    "Agartala Airport": 824496,
    "Silchar Airport": 214000,
    "Jodhpur Airport": 303678,
    "Dibrugarh Airport": 246068,
    "Tirupati Airport": 272095,
    "Rajkot Airport": 306441,
    "Maharana Pratap Airport": 435197,
    "Leh Kushok Bakula Rimpochee Airport": 330001,
    "Aurangabad Airport": 447917,
    "Raja Bhoj Airport": 429680,
    "Birsa Munda Airport": 517006,
    "Madurai International Airport": 670516,
    "Vadodara Airport": 686235,
    "Imphal Airport": 628766,
    "Lal Bahadur Shastri Airport": 826282,
    "Chandigarh International Airport": 1050397,
    "Swami Vivekananda Airport": 839534,
    "Jammu Airport": 845555,
    "Mangalore International Airport": 1283667,
    "Sri Guru Ram Dass Jee International Airport": 1031821,
    "Visakhapatnam Airport": 1012522,
    "Jaya Prakash Narayan Airport": 1044127,
    "Devi Ahilyabai Holkar International Airport": 1114980,
    "Biju Patnaik Airport": 1335832,
    "Coimbatore International Airport": 1244300,
    "Dr. Babasaheb Ambedkar International Airport": 1263837,
    "Sheikh ul-Alam International Airport": 2003186,
    "Jaipur International Airport": 1981936,
    "Chaudhary Charan Singh Airport": 2312291,
    "Lokpriya Gopinath Bordoloi International Airport": 2196545,
    "Pune Airport": 3596684,
    "Sardar Vallabhbhai Patel International Airport": 4564225,
    "Rajiv Gandhi International Airport": 8653784,
    "Netaji Subhas Chandra Bose International Airport": 10100232,
    "Chennai International Airport": 12896055,
    "Chhatrapati Shivaji Maharaj International Airport": 32221395,
    "Indira Gandhi International Airport": 36876986,
    "Jolly Grant Airport": 306832,
    "Surat International Airport": 0,
    "Vijayawada Airport": 0,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2015": {
    "Kempegowda International Airport": 15401392,
    "Cochin International Airport": 6414135,
    "Dabolim Airport": 4513201,
    "Trivandrum International Airport": 3174018,
    "Calicut International Airport": 2583740,
    "Bagdogra Airport": 1035887,
    "Veer Savarkar International Airport": 815873,
    "Tiruchirappalli International Airport": 1189218,
    "Agartala Airport": 879182,
    "Silchar Airport": 205000,
    "Jodhpur Airport": 295863,
    "Dibrugarh Airport": 319260,
    "Tirupati Airport": 245049,
    "Rajkot Airport": 351343,
    "Maharana Pratap Airport": 457942,
    "Leh Kushok Bakula Rimpochee Airport": 403243,
    "Aurangabad Airport": 426855,
    "Raja Bhoj Airport": 416284,
    "Birsa Munda Airport": 653832,
    "Madurai International Airport": 687221,
    "Vadodara Airport": 712447,
    "Imphal Airport": 612188,
    "Lal Bahadur Shastri Airport": 1019973,
    "Chandigarh International Airport": 1206292,
    "Swami Vivekananda Airport": 925504,
    "Jammu Airport": 952641,
    "Mangalore International Airport": 1307083,
    "Sri Guru Ram Dass Jee International Airport": 1083684,
    "Visakhapatnam Airport": 1099480,
    "Jaya Prakash Narayan Airport": 1196540,
    "Devi Ahilyabai Holkar International Airport": 1353300,
    "Biju Patnaik Airport": 1493356,
    "Coimbatore International Airport": 1429198,
    "Dr. Babasaheb Ambedkar International Airport": 1401147,
    "Sheikh ul-Alam International Airport": 2040808,
    "Jaipur International Airport": 2197959,
    "Chaudhary Charan Singh Airport": 2541241,
    "Lokpriya Gopinath Bordoloi International Airport": 2233601,
    "Pune Airport": 4190509,
    "Sardar Vallabhbhai Patel International Airport": 5050433,
    "Rajiv Gandhi International Airport": 10404353,
    "Netaji Subhas Chandra Bose International Airport": 10916699,
    "Chennai International Airport": 14299200,
    "Chhatrapati Shivaji Maharaj International Airport": 37694824,
    "Indira Gandhi International Airport": 40895555,
    "Jolly Grant Airport": 378646,
    "Surat International Airport": 0,
    "Vijayawada Airport": 233617,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 0
  },
  "2016": {
    "Kempegowda International Airport": 18971149,
    "Cochin International Airport": 7749901,
    "Dabolim Airport": 5375555,
    "Trivandrum International Airport": 3470788,
    "Calicut International Airport": 2305547,
    "Bagdogra Airport": 1087239,
    "Veer Savarkar International Airport": 871318,
    "Tiruchirappalli International Airport": 1297212,
    "Agartala Airport": 921591,
    "Silchar Airport": 200855,
    "Jodhpur Airport": 301859,
    "Dibrugarh Airport": 319646,
    "Tirupati Airport": 371060,
    "Rajkot Airport": 413207,
    "Maharana Pratap Airport": 711187,
    "Leh Kushok Bakula Rimpochee Airport": 408541,
    "Aurangabad Airport": 301046,
    "Raja Bhoj Airport": 662615,
    "Birsa Munda Airport": 739961,
    "Madurai International Airport": 842300,
    "Vadodara Airport": 931092,
    "Imphal Airport": 766877,
    "Lal Bahadur Shastri Airport": 1383962,
    "Chandigarh International Airport": 1534058,
    "Swami Vivekananda Airport": 1206844,
    "Jammu Airport": 1117252,
    "Mangalore International Airport": 1674251,
    "Sri Guru Ram Dass Jee International Airport": 1250370,
    "Visakhapatnam Airport": 1804634,
    "Jaya Prakash Narayan Airport": 1584013,
    "Devi Ahilyabai Holkar International Airport": 1692892,
    "Biju Patnaik Airport": 1894732,
    "Coimbatore International Airport": 1691553,
    "Dr. Babasaheb Ambedkar International Airport": 1595241,
    "Sheikh ul-Alam International Airport": 2310829,
    "Jaipur International Airport": 2887189,
    "Chaudhary Charan Singh Airport": 3241892,
    "Lokpriya Gopinath Bordoloi International Airport": 2784315,
    "Pune Airport": 5417167,
    "Sardar Vallabhbhai Patel International Airport": 6480111,
    "Rajiv Gandhi International Airport": 12388159,
    "Netaji Subhas Chandra Bose International Airport": 12761007,
    "Chennai International Airport": 15218017,
    "Chhatrapati Shivaji Maharaj International Airport": 41670351,
    "Indira Gandhi International Airport": 48424165,
    "Jolly Grant Airport": 471542,
    "Surat International Airport": 94824,
    "Vijayawada Airport": 398643,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 223903
  },
  "2017": {
    "Kempegowda International Airport": 22881392,
    "Cochin International Airport": 8955441,
    "Dabolim Airport": 6856362,
    "Trivandrum International Airport": 3881509,
    "Calicut International Airport": 2651088,
    "Bagdogra Airport": 1524516,
    "Veer Savarkar International Airport": 1238331,
    "Tiruchirappalli International Airport": 1359447,
    "Agartala Airport": 1183867,
    "Silchar Airport": 212228,
    "Jodhpur Airport": 350583,
    "Dibrugarh Airport": 305796,
    "Tirupati Airport": 486029,
    "Rajkot Airport": 405518,
    "Maharana Pratap Airport": 1089899,
    "Leh Kushok Bakula Rimpochee Airport": 563800,
    "Aurangabad Airport": 326971,
    "Raja Bhoj Airport": 676015,
    "Birsa Munda Airport": 1035740,
    "Madurai International Airport": 978919,
    "Vadodara Airport": 1103981,
    "Imphal Airport": 886338,
    "Lal Bahadur Shastri Airport": 1916454,
    "Chandigarh International Airport": 1825881,
    "Swami Vivekananda Airport": 1396179,
    "Jammu Airport": 1159937,
    "Mangalore International Airport": 1734810,
    "Sri Guru Ram Dass Jee International Airport": 1566407,
    "Visakhapatnam Airport": 2358029,
    "Jaya Prakash Narayan Airport": 2112150,
    "Devi Ahilyabai Holkar International Airport": 1784073,
    "Biju Patnaik Airport": 2332433,
    "Coimbatore International Airport": 2104904,
    "Dr. Babasaheb Ambedkar International Airport": 1891475,
    "Sheikh ul-Alam International Airport": 2101762,
    "Jaipur International Airport": 3783458,
    "Chaudhary Charan Singh Airport": 3968950,
    "Lokpriya Gopinath Bordoloi International Airport": 3789656,
    "Pune Airport": 6787391,
    "Sardar Vallabhbhai Patel International Airport": 7405282,
    "Rajiv Gandhi International Airport": 15102672,
    "Netaji Subhas Chandra Bose International Airport": 15819539,
    "Chennai International Airport": 17718017,
    "Chhatrapati Shivaji Maharaj International Airport": 45154345,
    "Indira Gandhi International Airport": 57703096,
    "Jolly Grant Airport": 882564,
    "Surat International Airport": 194564,
    "Vijayawada Airport": 622354,
    "Hubli Airport": 0,
    "Rajahmundry Airport": 261348
  },
  "2018": {
    "Kempegowda International Airport": 26910431,
    "Cochin International Airport": 10172839,
    "Dabolim Airport": 7607249,
    "Trivandrum International Airport": 4393469,
    "Calicut International Airport": 3139432,
    "Bagdogra Airport": 2255768,
    "Veer Savarkar International Airport": 1549951,
    "Tiruchirappalli International Airport": 1513273,
    "Agartala Airport": 1379090,
    "Silchar Airport": 366955,
    "Jodhpur Airport": 469239,
    "Dibrugarh Airport": 336851,
    "Tirupati Airport": 584732,
    "Rajkot Airport": 365427,
    "Maharana Pratap Airport": 1147067,
    "Leh Kushok Bakula Rimpochee Airport": 692010,
    "Aurangabad Airport": 344180,
    "Raja Bhoj Airport": 722243,
    "Birsa Munda Airport": 1778349,
    "Madurai International Airport": 1442807,
    "Vadodara Airport": 1008506,
    "Imphal Airport": 987506,
    "Lal Bahadur Shastri Airport": 2087581,
    "Chandigarh International Airport": 2137739,
    "Swami Vivekananda Airport": 1628134,
    "Jammu Airport": 1443965,
    "Mangalore International Airport": 2269949,
    "Sri Guru Ram Dass Jee International Airport": 2319955,
    "Visakhapatnam Airport": 2480379,
    "Jaya Prakash Narayan Airport": 3111273,
    "Devi Ahilyabai Holkar International Airport": 2269971,
    "Biju Patnaik Airport": 3250635,
    "Coimbatore International Airport": 2403935,
    "Dr. Babasaheb Ambedkar International Airport": 2186137,
    "Sheikh ul-Alam International Airport": 2440467,
    "Jaipur International Airport": 4757178,
    "Chaudhary Charan Singh Airport": 4752921,
    "Lokpriya Gopinath Bordoloi International Airport": 4668053,
    "Pune Airport": 8164840,
    "Sardar Vallabhbhai Patel International Airport": 9174425,
    "Rajiv Gandhi International Airport": 18156789,
    "Netaji Subhas Chandra Bose International Airport": 19892524,
    "Chennai International Airport": 20361482,
    "Chhatrapati Shivaji Maharaj International Airport": 48496430,
    "Indira Gandhi International Airport": 65691662,
    "Jolly Grant Airport": 1124937,
    "Surat International Airport": 681465,
    "Vijayawada Airport": 746392,
    "Hubli Airport": 49227,
    "Rajahmundry Airport": 268001
  },
  "2019": {
    "Kempegowda International Airport": 33307702,
    "Cochin International Airport": 10119825,
    "Dabolim Airport": 8467326,
    "Trivandrum International Airport": 4434459,
    "Calicut International Airport": 3360847,
    "Bagdogra Airport": 2898784,
    "Veer Savarkar International Airport": 1711881,
    "Tiruchirappalli International Airport": 1578831,
    "Agartala Airport": 1441089,
    "Silchar Airport": 386665,
    "Jodhpur Airport": 506826,
    "Dibrugarh Airport": 367929,
    "Tirupati Airport": 834652,
    "Rajkot Airport": 334068,
    "Maharana Pratap Airport": 1392210,
    "Leh Kushok Bakula Rimpochee Airport": 821689,
    "Aurangabad Airport": 347781,
    "Raja Bhoj Airport": 810307,
    "Birsa Munda Airport": 2254108,
    "Madurai International Airport": 1520016,
    "Vadodara Airport": 1155716,
    "Imphal Airport": 1277163,
    "Lal Bahadur Shastri Airport": 2785015,
    "Chandigarh International Airport": 2097698,
    "Swami Vivekananda Airport": 2028548,
    "Jammu Airport": 1334313,
    "Mangalore International Airport": 2240664,
    "Sri Guru Ram Dass Jee International Airport": 2523794,
    "Visakhapatnam Airport": 2853390,
    "Jaya Prakash Narayan Airport": 4061990,
    "Devi Ahilyabai Holkar International Airport": 3158938,
    "Biju Patnaik Airport": 4158731,
    "Coimbatore International Airport": 3000882,
    "Dr. Babasaheb Ambedkar International Airport": 2801910,
    "Sheikh ul-Alam International Airport": 2737560,
    "Jaipur International Airport": 5471223,
    "Chaudhary Charan Singh Airport": 5532819,
    "Lokpriya Gopinath Bordoloi International Airport": 5745628,
    "Pune Airport": 9070917,
    "Sardar Vallabhbhai Patel International Airport": 11172468,
    "Rajiv Gandhi International Airport": 21403972,
    "Netaji Subhas Chandra Bose International Airport": 21877350,
    "Chennai International Airport": 22543822,
    "Chhatrapati Shivaji Maharaj International Airport": 48815063,
    "Indira Gandhi International Airport": 69233864,
    "Jolly Grant Airport": 1240173,
    "Surat International Airport": 1238724,
    "Vijayawada Airport": 1192000,
    "Hubli Airport": 460462,
    "Rajahmundry Airport": 440429
  }
}


================================================
FILE: helpers.js
================================================
const toppers_of_this_year = function(year_obj) {
  let toRet = {};
  Object.entries(year_obj)
    .sort((a, b) => b[1] - a[1])
    .slice(0, numBarsToShow + 1)
    .forEach(topperEntry => {
      toRet[topperEntry[0]] = topperEntry[1];
    });
  return toRet;
};

const sanitize = function(seed) {
  //Given the initial data, it sees who are the top numToShow + 1 people each year and fills the years where the top people dont feature
  var toppers_of_each_year = {};
  for (let year in seed) {
    const result = toppers_of_this_year(seed[year]);
    toppers_of_each_year[year] = result;
  }
  let topper_names = [];
  for (year in toppers_of_each_year) {
    topper_names = [...new Set([...topper_names, ...Object.keys(toppers_of_each_year[year])])];
  }
  for (year in toppers_of_each_year) {
    const absenteeNames = topper_names.filter(name => !(name in toppers_of_each_year[year]));
    absenteeNames.forEach(absenteeName => {
      toppers_of_each_year[year][absenteeName] = seed[year][absenteeName];
    });
  }
  const toRet = {};
  for (year in toppers_of_each_year) {
    toRet[year] = {};
    for (topper in toppers_of_each_year[year]) {
      const toBeAdded = { val: toppers_of_each_year[year][topper] };
      if (shouldAssignIdentity) {
        // toBeAdded.team = aadhar[topper][keyInAadhaarObject];
        toBeAdded.team = "ABC";
      }
      toRet[year][topper] = toBeAdded;
    }
  }
  return toRet;
};


================================================
FILE: index.html
================================================
<html lang="en">
  <head>
    <title>Timeline Maker</title>
  </head>
  <link rel="stylesheet" href="main.css" />
  <body>
    <div id="canvas"></div>
  </body>
  <script src="config.js"></script>
  <script src="helpers.js"></script>
  <script src="randomColor.js"></script>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.7.3/p5.min.js"></script>
  <script src="Timeline.js"></script>
  <script src="main.js"></script>
</html>


================================================
FILE: main.css
================================================
html,
body {
  margin: 0;
  padding: 0;
  font-family: Karma;
  overflow: hidden;
}

#canvas {
  width: 100vw;
  height: 100vh;
}

@font-face {
  font-family: "Graphik";
  src: 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)
    format("woff");
  font-weight: 400;
  font-style: normal;
  font-stretch: normal;
}

@font-face {
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)
    format("woff");
  font-weight: 500;
  font-style: normal;
  font-stretch: normal;
}


================================================
FILE: main.js
================================================
p5.disableFriendlyErrors = true;
let data, timeline, randomColors, subscribe;
function preload() {
  data = loadJSON(dataSource);
  subscribe = loadImage('subscribex.png');
}

function setup() {
  smooth();
  frameRate(300);
  randomColors = randomColor({
    luminosity: 'dark',
    count: 50,
    format: 'rgbArray',
    hue: 'random',
  });
  const parent = document.getElementById('canvas');
  const canvas = createCanvas(innerWidth, innerHeight);
  canvas.parent(parent);
  timeline = new Timeline(data);
}
let start = false;
function draw() {
  background('white');
  if (start) {
    if (toShowWatermark) {
      const txt = 'India in Pixels';
      fill(246);
      textSize(18);
      for (var i = 0; i < 15; i++) {
        for (var j = 0; j < 50; j++) {
          if (j % 2 == 0) {
            text(txt, i * textWidth(txt) * 1.2, j * 30);
          } else {
            text(txt, (i + 0.5) * textWidth(txt) * 1.2, j * 30);
          }
        }
      }
    }
    translate(130, 150);
    timeline.update();
    timeline.show();
  } else {
    textAlign(CENTER);
    textSize(30);
    fill(0);
    text('Press Enter to Start', width / 2, height / 2);
    textSize(14);
    fill(100);
    text(
      'To support, UPI: indiainpixels@paytm | patreon.com/indiainpixels',
      width / 2,
      height / 2 + 30
    );
  }
}
function keyPressed() {
  if (keyCode == ENTER) {
    start = true;
  }
}


================================================
FILE: randomColor.js
================================================
// randomColor by David Merfield under the CC0 license
// https://github.com/davidmerfield/randomColor/

;(function(root, factory) {

	// Support CommonJS
	if (typeof exports === 'object') {
	  var randomColor = factory();

	  // Support NodeJS & Component, which allow module.exports to be a function
	  if (typeof module === 'object' && module && module.exports) {
		exports = module.exports = randomColor;
	  }

	  // Support CommonJS 1.1.1 spec
	  exports.randomColor = randomColor;

	// Support AMD
	} else if (typeof define === 'function' && define.amd) {
	  define([], factory);

	// Support vanilla script loading
	} else {
	  root.randomColor = factory();
	}

  }(this, function() {

	// Seed to get repeatable colors
	var seed = null;

	// Shared color dictionary
	var colorDictionary = {};

	// Populate the color dictionary
	loadColorBounds();

	// check if a range is taken
	var colorRanges = [];

	var randomColor = function (options) {

	  options = options || {};

	  // Check if there is a seed and ensure it's an
	  // integer. Otherwise, reset the seed value.
	  if (options.seed !== undefined && options.seed !== null && options.seed === parseInt(options.seed, 10)) {
		seed = options.seed;

	  // A string was passed as a seed
	  } else if (typeof options.seed === 'string') {
		seed = stringToInteger(options.seed);

	  // Something was passed as a seed but it wasn't an integer or string
	  } else if (options.seed !== undefined && options.seed !== null) {
		throw new TypeError('The seed value must be an integer or string');

	  // No seed, reset the value outside.
	  } else {
		seed = null;
	  }

	  var H,S,B;

	  // Check if we need to generate multiple colors
	  if (options.count !== null && options.count !== undefined) {

		var totalColors = options.count,
			colors = [];
		// Value false at index i means the range i is not taken yet.
		for (var i = 0; i < options.count; i++) {
		  colorRanges.push(false)
		  }
		options.count = null;

		while (totalColors > colors.length) {

		  // Since we're generating multiple colors,
		  // incremement the seed. Otherwise we'd just
		  // generate the same color each time...
		  if (seed && options.seed) options.seed += 1;

		  colors.push(randomColor(options));
		}

		options.count = totalColors;

		return colors;
	  }

	  // First we pick a hue (H)
	  H = pickHue(options);

	  // Then use H to determine saturation (S)
	  S = pickSaturation(H, options);

	  // Then use S and H to determine brightness (B).
	  B = pickBrightness(H, S, options);

	  // Then we return the HSB color in the desired format
	  return setFormat([H,S,B], options);
	};

	function pickHue(options) {
	  if (colorRanges.length > 0) {
		var hueRange = getRealHueRange(options.hue)

		var hue = randomWithin(hueRange)

		//Each of colorRanges.length ranges has a length equal approximatelly one step
		var step = (hueRange[1] - hueRange[0]) / colorRanges.length

		var j = parseInt((hue - hueRange[0]) / step)

		//Check if the range j is taken
		if (colorRanges[j] === true) {
		  j = (j + 2) % colorRanges.length
		}
		else {
		  colorRanges[j] = true
			 }

		var min = (hueRange[0] + j * step) % 359,
			max = (hueRange[0] + (j + 1) * step) % 359;

		hueRange = [min, max]

		hue = randomWithin(hueRange)

		if (hue < 0) {hue = 360 + hue;}
		return hue
	  }
	  else {
		var hueRange = getHueRange(options.hue)

		hue = randomWithin(hueRange);
		// Instead of storing red as two seperate ranges,
		// we group them, using negative numbers
		if (hue < 0) {
		  hue = 360 + hue;
		}

		return hue;
	  }
	}

	function pickSaturation (hue, options) {

	  if (options.hue === 'monochrome') {
		return 0;
	  }

	  if (options.luminosity === 'random') {
		return randomWithin([0,100]);
	  }

	  var saturationRange = getSaturationRange(hue);

	  var sMin = saturationRange[0],
		  sMax = saturationRange[1];

	  switch (options.luminosity) {

		case 'bright':
		  sMin = 55;
		  break;

		case 'dark':
		  sMin = sMax - 10;
		  break;

		case 'light':
		  sMax = 55;
		  break;
	 }

	  return randomWithin([sMin, sMax]);

	}

	function pickBrightness (H, S, options) {

	  var bMin = getMinimumBrightness(H, S),
		  bMax = 100;

	  switch (options.luminosity) {

		case 'dark':
		  bMax = bMin + 20;
		  break;

		case 'light':
		  bMin = (bMax + bMin)/2;
		  break;

		case 'random':
		  bMin = 0;
		  bMax = 100;
		  break;
	  }

	  return randomWithin([bMin, bMax]);
	}

	function setFormat (hsv, options) {

	  switch (options.format) {

		case 'hsvArray':
		  return hsv;

		case 'hslArray':
		  return HSVtoHSL(hsv);

		case 'hsl':
		  var hsl = HSVtoHSL(hsv);
		  return 'hsl('+hsl[0]+', '+hsl[1]+'%, '+hsl[2]+'%)';

		case 'hsla':
		  var hslColor = HSVtoHSL(hsv);
		  var alpha = options.alpha || Math.random();
		  return 'hsla('+hslColor[0]+', '+hslColor[1]+'%, '+hslColor[2]+'%, ' + alpha + ')';

		case 'rgbArray':
		  return HSVtoRGB(hsv);

		case 'rgb':
		  var rgb = HSVtoRGB(hsv);
		  return 'rgb(' + rgb.join(', ') + ')';

		case 'rgba':
		  var rgbColor = HSVtoRGB(hsv);
		  var alpha = options.alpha || Math.random();
		  return 'rgba(' + rgbColor.join(', ') + ', ' + alpha + ')';

		default:
		  return HSVtoHex(hsv);
	  }

	}

	function getMinimumBrightness(H, S) {

	  var lowerBounds = getColorInfo(H).lowerBounds;

	  for (var i = 0; i < lowerBounds.length - 1; i++) {

		var s1 = lowerBounds[i][0],
			v1 = lowerBounds[i][1];

		var s2 = lowerBounds[i+1][0],
			v2 = lowerBounds[i+1][1];

		if (S >= s1 && S <= s2) {

		   var m = (v2 - v1)/(s2 - s1),
			   b = v1 - m*s1;

		   return m*S + b;
		}

	  }

	  return 0;
	}

	function getHueRange (colorInput) {

	  if (typeof parseInt(colorInput) === 'number') {

		var number = parseInt(colorInput);

		if (number < 360 && number > 0) {
		  return [number, number];
		}

	  }

	  if (typeof colorInput === 'string') {

		if (colorDictionary[colorInput]) {
		  var color = colorDictionary[colorInput];
		  if (color.hueRange) {return color.hueRange;}
		} else if (colorInput.match(/^#?([0-9A-F]{3}|[0-9A-F]{6})$/i)) {
		  var hue = HexToHSB(colorInput)[0];
		  return [ hue, hue ];
		}
	  }

	  return [0,360];

	}

	function getSaturationRange (hue) {
	  return getColorInfo(hue).saturationRange;
	}

	function getColorInfo (hue) {

	  // Maps red colors to make picking hue easier
	  if (hue >= 334 && hue <= 360) {
		hue-= 360;
	  }

	  for (var colorName in colorDictionary) {
		 var color = colorDictionary[colorName];
		 if (color.hueRange &&
			 hue >= color.hueRange[0] &&
			 hue <= color.hueRange[1]) {
			return colorDictionary[colorName];
		 }
	  } return 'Color not found';
	}

	function randomWithin (range) {
	  if (seed === null) {
		//generate random evenly destinct number from : https://martin.ankerl.com/2009/12/09/how-to-create-random-colors-programmatically/
		var golden_ratio = 0.618033988749895
		var r=Math.random()
		r += golden_ratio
		r %= 1
		return Math.floor(range[0] + r*(range[1] + 1 - range[0]));
	  } else {
		//Seeded random algorithm from http://indiegamr.com/generate-repeatable-random-numbers-in-js/
		var max = range[1] || 1;
		var min = range[0] || 0;
		seed = (seed * 9301 + 49297) % 233280;
		var rnd = seed / 233280.0;
		return Math.floor(min + rnd * (max - min));
  }
	}

	function HSVtoHex (hsv){

	  var rgb = HSVtoRGB(hsv);

	  function componentToHex(c) {
		  var hex = c.toString(16);
		  return hex.length == 1 ? '0' + hex : hex;
	  }

	  var hex = '#' + componentToHex(rgb[0]) + componentToHex(rgb[1]) + componentToHex(rgb[2]);

	  return hex;

	}

	function defineColor (name, hueRange, lowerBounds) {

	  var sMin = lowerBounds[0][0],
		  sMax = lowerBounds[lowerBounds.length - 1][0],

		  bMin = lowerBounds[lowerBounds.length - 1][1],
		  bMax = lowerBounds[0][1];

	  colorDictionary[name] = {
		hueRange: hueRange,
		lowerBounds: lowerBounds,
		saturationRange: [sMin, sMax],
		brightnessRange: [bMin, bMax]
	  };

	}

	function loadColorBounds () {

	  defineColor(
		'monochrome',
		null,
		[[0,0],[100,0]]
	  );

	  defineColor(
		'red',
		[-26,18],
		[[20,100],[30,92],[40,89],[50,85],[60,78],[70,70],[80,60],[90,55],[100,50]]
	  );

	  defineColor(
		'orange',
		[19,46],
		[[20,100],[30,93],[40,88],[50,86],[60,85],[70,70],[100,70]]
	  );

	  defineColor(
		'yellow',
		[47,62],
		[[25,100],[40,94],[50,89],[60,86],[70,84],[80,82],[90,80],[100,75]]
	  );

	  defineColor(
		'green',
		[63,178],
		[[30,100],[40,90],[50,85],[60,81],[70,74],[80,64],[90,50],[100,40]]
	  );

	  defineColor(
		'blue',
		[179, 257],
		[[20,100],[30,86],[40,80],[50,74],[60,60],[70,52],[80,44],[90,39],[100,35]]
	  );

	  defineColor(
		'purple',
		[258, 282],
		[[20,100],[30,87],[40,79],[50,70],[60,65],[70,59],[80,52],[90,45],[100,42]]
	  );

	  defineColor(
		'pink',
		[283, 334],
		[[20,100],[30,90],[40,86],[60,84],[80,80],[90,75],[100,73]]
	  );

	}

	function HSVtoRGB (hsv) {

	  // this doesn't work for the values of 0 and 360
	  // here's the hacky fix
	  var h = hsv[0];
	  if (h === 0) {h = 1;}
	  if (h === 360) {h = 359;}

	  // Rebase the h,s,v values
	  h = h/360;
	  var s = hsv[1]/100,
		  v = hsv[2]/100;

	  var h_i = Math.floor(h*6),
		f = h * 6 - h_i,
		p = v * (1 - s),
		q = v * (1 - f*s),
		t = v * (1 - (1 - f)*s),
		r = 256,
		g = 256,
		b = 256;

	  switch(h_i) {
		case 0: r = v; g = t; b = p;  break;
		case 1: r = q; g = v; b = p;  break;
		case 2: r = p; g = v; b = t;  break;
		case 3: r = p; g = q; b = v;  break;
		case 4: r = t; g = p; b = v;  break;
		case 5: r = v; g = p; b = q;  break;
	  }

	  var result = [Math.floor(r*255), Math.floor(g*255), Math.floor(b*255)];
	  return result;
	}

	function HexToHSB (hex) {
	  hex = hex.replace(/^#/, '');
	  hex = hex.length === 3 ? hex.replace(/(.)/g, '$1$1') : hex;

	  var red = parseInt(hex.substr(0, 2), 16) / 255,
			green = parseInt(hex.substr(2, 2), 16) / 255,
			blue = parseInt(hex.substr(4, 2), 16) / 255;

	  var cMax = Math.max(red, green, blue),
			delta = cMax - Math.min(red, green, blue),
			saturation = cMax ? (delta / cMax) : 0;

	  switch (cMax) {
		case red: return [ 60 * (((green - blue) / delta) % 6) || 0, saturation, cMax ];
		case green: return [ 60 * (((blue - red) / delta) + 2) || 0, saturation, cMax ];
		case blue: return [ 60 * (((red - green) / delta) + 4) || 0, saturation, cMax ];
	  }
	}

	function HSVtoHSL (hsv) {
	  var h = hsv[0],
		s = hsv[1]/100,
		v = hsv[2]/100,
		k = (2-s)*v;

	  return [
		h,
		Math.round(s*v / (k<1 ? k : 2-k) * 10000) / 100,
		k/2 * 100
	  ];
	}

	function stringToInteger (string) {
	  var total = 0
	  for (var i = 0; i !== string.length; i++) {
		if (total >= Number.MAX_SAFE_INTEGER) break;
		total += string.charCodeAt(i)
	  }
	  return total
	}

	// get The range of given hue when options.count!=0
	function getRealHueRange(colorHue)
	{ if (!isNaN(colorHue)) {
	  var number = parseInt(colorHue);

	  if (number < 360 && number > 0) {
		return getColorInfo(colorHue).hueRange
	  }
	}
	  else if (typeof colorHue === 'string') {

		if (colorDictionary[colorHue]) {
		  var color = colorDictionary[colorHue];

		  if (color.hueRange) {
			return color.hueRange
		 }
	  } else if (colorHue.match(/^#?([0-9A-F]{3}|[0-9A-F]{6})$/i)) {
		  var hue = HexToHSB(colorHue)[0]
		  return getColorInfo(hue).hueRange
	  }
	}

	  return [0,360]
  }
	return randomColor;
  }));