text: import React, { Component } from 'react';
  import { Image } from 'image-js';
  import kmeans from 'ml-kmeans';
  import { connect } from 'react-redux';
  import ScrollableTabsButtonAuto from './ScrollableTabsButtonAuto';
  // import  * as forEach from 'p-iteration';
  
  
  // import * as Vibrant from 'node-vibrant';
  /*
   * Color Thief v2.0
   * by Lokesh Dhakar - http://www.lokeshdhakar.com
   *
   * Thanks
   * ------
   * Nick Rabinowitz - For creating quantize.js.
   * John Schulz - For clean up and optimization. @JFSIII
   * Nathan Spady - For adding drag and drop support to the demo page.
   *
   * License
   * -------
   * Copyright 2011, 2015 Lokesh Dhakar
   * Released under the MIT license
   * https://raw.githubusercontent.com/lokesh/color-thief/master/LICENSE
   *
   * @license
   */
  
  
  /*
    CanvasImage Class
    Class that wraps the html image element and canvas.
    It also simplifies some of the canvas context manipulation
    with a set of helper functions.
  */
  var CanvasImage = function (image) {
      this.canvas  = document.createElement('canvas');
      this.context = this.canvas.getContext('2d');
  
      document.body.appendChild(this.canvas);
  
      this.width  = this.canvas.width  = image.width;
      this.height = this.canvas.height = image.height;
  
      this.context.drawImage(image, 0, 0, this.width, this.height);
  };
  
  CanvasImage.prototype.clear = function () {
      this.context.clearRect(0, 0, this.width, this.height);
  };
  
  CanvasImage.prototype.update = function (imageData) {
      this.context.putImageData(imageData, 0, 0);
  };
  
  CanvasImage.prototype.getPixelCount = function () {
      return this.width * this.height;
  };
  
  CanvasImage.prototype.getImageData = function () {
      return this.context.getImageData(0, 0, this.width, this.height);
  };
  
  CanvasImage.prototype.removeCanvas = function () {
      this.canvas.parentNode.removeChild(this.canvas);
  };
  
  
  var ColorThief = function () {};
  
  /*
   * getColor(sourceImage[, quality])
   * returns {r: num, g: num, b: num}
   *
   * Use the median cut algorithm provided by quantize.js to cluster similar
   * colors and return the base color from the largest cluster.
   *
   * Quality is an optional argument. It needs to be an integer. 1 is the highest quality settings.
   * 10 is the default. There is a trade-off between quality and speed. The bigger the number, the
   * faster a color will be returned but the greater the likelihood that it will not be the visually
   * most dominant color.
   *
   * */
  ColorThief.prototype.getColor = function(sourceImage, quality) {
      var palette       = this.getPalette(sourceImage, 5, quality);
      var dominantColor = palette[0];
      return dominantColor;
  };
  
  
  /*
   * getPalette(sourceImage[, colorCount, quality])
   * returns array[ {r: num, g: num, b: num}, {r: num, g: num, b: num}, ...]
   *
   * Use the median cut algorithm provided by quantize.js to cluster similar colors.
   *
   * colorCount determines the size of the palette; the number of colors returned. If not set, it
   * defaults to 10.
   *
   * BUGGY: Function does not always return the requested amount of colors. It can be +/- 2.
   *
   * quality is an optional argument. It needs to be an integer. 1 is the highest quality settings.
   * 10 is the default. There is a trade-off between quality and speed. The bigger the number, the
   * faster the palette generation but the greater the likelihood that colors will be missed.
   *
   *
   */
  ColorThief.prototype.getPalette = function(sourceImage, colorCount, quality) {
  
      if (typeof colorCount === 'undefined' || colorCount < 2 || colorCount > 256) {
          colorCount = 10;
      }
      if (typeof quality === 'undefined' || quality < 1) {
          quality = 10;
      }
  
      // Create custom CanvasImage object
      var image      = new CanvasImage(sourceImage);
      var imageData  = image.getImageData();
      var pixels     = imageData.data;
      var pixelCount = image.getPixelCount();
  
      // Store the RGB values in an array format suitable for quantize function
      var pixelArray = [];
      for (var i = 0, offset, r, g, b, a; i < pixelCount; i = i + quality) {
          offset = i * 4;
          r = pixels[offset + 0];
          g = pixels[offset + 1];
          b = pixels[offset + 2];
          a = pixels[offset + 3];
          // If pixel is mostly opaque and not white
          if (a >= 125) {
              if (!(r > 250 && g > 250 && b > 250)) {
                  pixelArray.push([r, g, b]);
              }
          }
      }
  
      // Send array to quantize function which clusters values
      // using median cut algorithm
      var cmap    = MMCQ.quantize(pixelArray, colorCount);
      var palette = cmap? cmap.palette() : null;
  
      // Clean up
      image.removeCanvas();
  
      return palette;
  };
  
  ColorThief.prototype.getColorFromUrl = function(imageUrl, callback, quality) {
      let sourceImage = document.createElement("img");
      var thief = this;
      sourceImage.addEventListener('load' , function(){
          var palette = thief.getPalette(sourceImage, 5, quality);
          var dominantColor = palette[0];
          callback(dominantColor, imageUrl);
      });
      sourceImage.src = imageUrl
  };
  
  ColorThief.prototype.getPaletteFromUrl = function(imageUrl, callback, quality=1) {
      let sourceImage = document.createElement("img");
      var thief = this;
      sourceImage.addEventListener('load' , function(){
          var palette = thief.getPalette(sourceImage, 5, quality);
          // var dominantColor = palette[0];
          callback(palette, imageUrl);
      });
      // console.log('set url')
      sourceImage.src = imageUrl + '?' + new Date().getTime();
      sourceImage.setAttribute('crossOrigin', '');
  };
  
  
  ColorThief.prototype.getImageData = function(imageUrl, callback) {
      let xhr = new XMLHttpRequest();
      xhr.open('GET', imageUrl, true);
      xhr.responseType = 'arraybuffer'
      xhr.onload = function(e) {
          if (this.status == 200) {
              let uInt8Array = new Uint8Array(this.response)
              i = uInt8Array.length
              let binaryString = new Array(i);
              for (var i = 0; i < uInt8Array.length; i++){
                  binaryString[i] = String.fromCharCode(uInt8Array[i])
              }
              let data = binaryString.join('')
              let base64 = window.btoa(data)
              callback ("data:image/png;base64,"+base64)
          }
      }
      xhr.send();
  };
  
  ColorThief.prototype.getColorAsync = function(imageUrl, callback, quality) {
      var thief = this;
      this.getImageData(imageUrl, function(imageData){
          let sourceImage = document.createElement("img");
          sourceImage.addEventListener('load' , function(){
              var palette = thief.getPalette(sourceImage, 5, quality);
              var dominantColor = palette[0];
              callback(dominantColor, this);
          });
          sourceImage.src = imageData;      
      });
  };
  
  
  
  /*!
   * quantize.js Copyright 2008 Nick Rabinowitz.
   * Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php
   * @license
   */
  
  // fill out a couple protovis dependencies
  /*!
   * Block below copied from Protovis: http://mbostock.github.com/protovis/
   * Copyright 2010 Stanford Visualization Group
   * Licensed under the BSD License: http://www.opensource.org/licenses/bsd-license.php
   * @license
   */
  if (!pv) {
      var pv = {
          map: function(array, f) {
            var o = {};
            return f ? array.map(function(d, i) { o.index = i; return f.call(o, d); }) : array.slice();
          },
          naturalOrder: function(a, b) {
              return (a < b) ? -1 : ((a > b) ? 1 : 0);
          },
          sum: function(array, f) {
            var o = {};
            return array.reduce(f ? function(p, d, i) { o.index = i; return p + f.call(o, d); } : function(p, d) { return p + d; }, 0);
          },
          max: function(array, f) {
            return Math.max.apply(null, f ? pv.map(array, f) : array);
          }
      };
  }
  
  
  
  /**
   * Basic Javascript port of the MMCQ (modified median cut quantization)
   * algorithm from the Leptonica library (http://www.leptonica.com/).
   * Returns a color map you can use to map original pixels to the reduced
   * palette. Still a work in progress.
   *
   * @author Nick Rabinowitz
   * @example
  
  // array of pixels as [R,G,B] arrays
  var myPixels = [[190,197,190], [202,204,200], [207,214,210], [211,214,211], [205,207,207]
                  // etc
                  ];
  var maxColors = 4;
  
  var cmap = MMCQ.quantize(myPixels, maxColors);
  var newPalette = cmap.palette();
  var newPixels = myPixels.map(function(p) {
      return cmap.map(p);
  });
  
   */
  var MMCQ = (function() {
      // private constants
      var sigbits = 5,
          rshift = 8 - sigbits,
          maxIterations = 1000,
          fractByPopulations = 0.75;
  
      // get reduced-space color index for a pixel
      function getColorIndex(r, g, b) {
          return (r << (2 * sigbits)) + (g << sigbits) + b;
      }
  
      // Simple priority queue
      function PQueue(comparator) {
          var contents = [],
              sorted = false;
  
          function sort() {
              contents.sort(comparator);
              sorted = true;
          }
  
          return {
              push: function(o) {
                  contents.push(o);
                  sorted = false;
              },
              peek: function(index) {
                  if (!sorted) sort();
                  if (index===undefined) index = contents.length - 1;
                  return contents[index];
              },
              pop: function() {
                  if (!sorted) sort();
                  return contents.pop();
              },
              size: function() {
                  return contents.length;
              },
              map: function(f) {
                  return contents.map(f);
              },
              debug: function() {
                  if (!sorted) sort();
                  return contents;
              }
          };
      }
  
      // 3d color space box
      function VBox(r1, r2, g1, g2, b1, b2, histo) {
          var vbox = this;
          vbox.r1 = r1;
          vbox.r2 = r2;
          vbox.g1 = g1;
          vbox.g2 = g2;
          vbox.b1 = b1;
          vbox.b2 = b2;
          vbox.histo = histo;
      }
      VBox.prototype = {
          volume: function(force) {
              var vbox = this;
              if (!vbox._volume || force) {
                  vbox._volume = ((vbox.r2 - vbox.r1 + 1) * (vbox.g2 - vbox.g1 + 1) * (vbox.b2 - vbox.b1 + 1));
              }
              return vbox._volume;
          },
          count: function(force) {
              var vbox = this,
                  histo = vbox.histo;
              if (!vbox._count_set || force) {
                  var npix = 0,
                      index, i, j, k;
                  for (i = vbox.r1; i <= vbox.r2; i++) {
                      for (j = vbox.g1; j <= vbox.g2; j++) {
                          for (k = vbox.b1; k <= vbox.b2; k++) {
                               index = getColorIndex(i,j,k);
                               npix += (histo[index] || 0);
                          }
                      }
                  }
                  vbox._count = npix;
                  vbox._count_set = true;
              }
              return vbox._count;
          },
          copy: function() {
              var vbox = this;
              return new VBox(vbox.r1, vbox.r2, vbox.g1, vbox.g2, vbox.b1, vbox.b2, vbox.histo);
          },
          avg: function(force) {
              var vbox = this,
                  histo = vbox.histo;
              if (!vbox._avg || force) {
                  var ntot = 0,
                      mult = 1 << (8 - sigbits),
                      rsum = 0,
                      gsum = 0,
                      bsum = 0,
                      hval,
                      i, j, k, histoindex;
                  for (i = vbox.r1; i <= vbox.r2; i++) {
                      for (j = vbox.g1; j <= vbox.g2; j++) {
                          for (k = vbox.b1; k <= vbox.b2; k++) {
                               histoindex = getColorIndex(i,j,k);
                               hval = histo[histoindex] || 0;
                               ntot += hval;
                               rsum += (hval * (i + 0.5) * mult);
                               gsum += (hval * (j + 0.5) * mult);
                               bsum += (hval * (k + 0.5) * mult);
                          }
                      }
                  }
                  if (ntot) {
                      vbox._avg = [~~(rsum/ntot), ~~(gsum/ntot), ~~(bsum/ntot)];
                  } else {
  //                    console.log('empty box');
                      vbox._avg = [
                          ~~(mult * (vbox.r1 + vbox.r2 + 1) / 2),
                          ~~(mult * (vbox.g1 + vbox.g2 + 1) / 2),
                          ~~(mult * (vbox.b1 + vbox.b2 + 1) / 2)
                      ];
                  }
              }
              return vbox._avg;
          },
          contains: function(pixel) {
              var vbox = this,
                  rval = pixel[0] >> rshift,
                  gval = pixel[1] >> rshift,
                  bval = pixel[2] >> rshift;
              return (rval >= vbox.r1 && rval <= vbox.r2 &&
                      gval >= vbox.g1 && gval <= vbox.g2 &&
                      bval >= vbox.b1 && bval <= vbox.b2);
          }
      };
  
      // Color map
      function CMap() {
          this.vboxes = new PQueue(function(a,b) {
              return pv.naturalOrder(
                  a.vbox.count()*a.vbox.volume(),
                  b.vbox.count()*b.vbox.volume()
              );
          });
      }
      CMap.prototype = {
          push: function(vbox) {
              this.vboxes.push({
                  vbox: vbox,
                  color: vbox.avg()
              });
          },
          palette: function() {
              return this.vboxes.map(function(vb) { return vb.color; });
          },
          size: function() {
              return this.vboxes.size();
          },
          map: function(color) {
              var vboxes = this.vboxes;
              for (var i=0; i<vboxes.size(); i++) {
                  if (vboxes.peek(i).vbox.contains(color)) {
                      return vboxes.peek(i).color;
                  }
              }
              return this.nearest(color);
          },
          nearest: function(color) {
              var vboxes = this.vboxes,
                  d1, d2, pColor;
              for (var i=0; i<vboxes.size(); i++) {
                  d2 = Math.sqrt(
                      Math.pow(color[0] - vboxes.peek(i).color[0], 2) +
                      Math.pow(color[1] - vboxes.peek(i).color[1], 2) +
                      Math.pow(color[2] - vboxes.peek(i).color[2], 2)
                  );
                  if (d2 < d1 || d1 === undefined) {
                      d1 = d2;
                      pColor = vboxes.peek(i).color;
                  }
              }
              return pColor;
          },
          forcebw: function() {
              // XXX: won't  work yet
              var vboxes = this.vboxes;
              vboxes.sort(function(a,b) { return pv.naturalOrder(pv.sum(a.color), pv.sum(b.color));});
  
              // force darkest color to black if everything < 5
              var lowest = vboxes[0].color;
              if (lowest[0] < 5 && lowest[1] < 5 && lowest[2] < 5)
                  vboxes[0].color = [0,0,0];
  
              // force lightest color to white if everything > 251
              var idx = vboxes.length-1,
                  highest = vboxes[idx].color;
              if (highest[0] > 251 && highest[1] > 251 && highest[2] > 251)
                  vboxes[idx].color = [255,255,255];
          }
      };
  
      // histo (1-d array, giving the number of pixels in
      // each quantized region of color space), or null on error
      function getHisto(pixels) {
          var histosize = 1 << (3 * sigbits),
              histo = new Array(histosize),
              index, rval, gval, bval;
          pixels.forEach(function(pixel) {
              rval = pixel[0] >> rshift;
              gval = pixel[1] >> rshift;
              bval = pixel[2] >> rshift;
              index = getColorIndex(rval, gval, bval);
              histo[index] = (histo[index] || 0) + 1;
          });
          return histo;
      }
  
      function vboxFromPixels(pixels, histo) {
          var rmin=1000000, rmax=0,
              gmin=1000000, gmax=0,
              bmin=1000000, bmax=0,
              rval, gval, bval;
          // find min/max
          pixels.forEach(function(pixel) {
              rval = pixel[0] >> rshift;
              gval = pixel[1] >> rshift;
              bval = pixel[2] >> rshift;
              if (rval < rmin) rmin = rval;
              else if (rval > rmax) rmax = rval;
              if (gval < gmin) gmin = gval;
              else if (gval > gmax) gmax = gval;
              if (bval < bmin) bmin = bval;
              else if (bval > bmax)  bmax = bval;
          });
          return new VBox(rmin, rmax, gmin, gmax, bmin, bmax, histo);
      }
  
      function medianCutApply(histo, vbox) {
          if (!vbox.count()) return;
  
          var rw = vbox.r2 - vbox.r1 + 1,
              gw = vbox.g2 - vbox.g1 + 1,
              bw = vbox.b2 - vbox.b1 + 1,
              maxw = pv.max([rw, gw, bw]);
          // only one pixel, no split
          if (vbox.count() == 1) {
              return [vbox.copy()];
          }
          /* Find the partial sum arrays along the selected axis. */
          var total = 0,
              partialsum = [],
              lookaheadsum = [],
              i, j, k, sum, index;
          if (maxw == rw) {
              for (i = vbox.r1; i <= vbox.r2; i++) {
                  sum = 0;
                  for (j = vbox.g1; j <= vbox.g2; j++) {
                      for (k = vbox.b1; k <= vbox.b2; k++) {
                          index = getColorIndex(i,j,k);
                          sum += (histo[index] || 0);
                      }
                  }
                  total += sum;
                  partialsum[i] = total;
              }
          }
          else if (maxw == gw) {
              for (i = vbox.g1; i <= vbox.g2; i++) {
                  sum = 0;
                  for (j = vbox.r1; j <= vbox.r2; j++) {
                      for (k = vbox.b1; k <= vbox.b2; k++) {
                          index = getColorIndex(j,i,k);
                          sum += (histo[index] || 0);
                      }
                  }
                  total += sum;
                  partialsum[i] = total;
              }
          }
          else {  /* maxw == bw */
              for (i = vbox.b1; i <= vbox.b2; i++) {
                  sum = 0;
                  for (j = vbox.r1; j <= vbox.r2; j++) {
                      for (k = vbox.g1; k <= vbox.g2; k++) {
                          index = getColorIndex(j,k,i);
                          sum += (histo[index] || 0);
                      }
                  }
                  total += sum;
                  partialsum[i] = total;
              }
          }
          partialsum.forEach(function(d,i) {
              lookaheadsum[i] = total-d;
          });
          function doCut(color) {
              var dim1 = color + '1',
                  dim2 = color + '2',
                  left, right, vbox1, vbox2, d2, count2=0;
              for (i = vbox[dim1]; i <= vbox[dim2]; i++) {
                  if (partialsum[i] > total / 2) {
                      vbox1 = vbox.copy();
                      vbox2 = vbox.copy();
                      left = i - vbox[dim1];
                      right = vbox[dim2] - i;
                      if (left <= right)
                          d2 = Math.min(vbox[dim2] - 1, ~~(i + right / 2));
                      else d2 = Math.max(vbox[dim1], ~~(i - 1 - left / 2));
                      // avoid 0-count boxes
                      while (!partialsum[d2]) d2++;
                      count2 = lookaheadsum[d2];
                      while (!count2 && partialsum[d2-1]) count2 = lookaheadsum[--d2];
                      // set dimensions
                      vbox1[dim2] = d2;
                      vbox2[dim1] = vbox1[dim2] + 1;
  //                    console.log('vbox counts:', vbox.count(), vbox1.count(), vbox2.count());
                      return [vbox1, vbox2];
                  }
              }
  
          }
          // determine the cut planes
          return maxw == rw ? doCut('r') :
              maxw == gw ? doCut('g') :
              doCut('b');
      }
  
      function quantize(pixels, maxcolors) {
          // short-circuit
          if (!pixels.length || maxcolors < 2 || maxcolors > 256) {
  //            console.log('wrong number of maxcolors');
              return false;
          }
  
          // XXX: check color content and convert to grayscale if insufficient
  
          var histo = getHisto(pixels),
              histosize = 1 << (3 * sigbits);
  
          // check that we aren't below maxcolors already
          var nColors = 0;
          histo.forEach(function() { nColors++; });
          if (nColors <= maxcolors) {
              // XXX: generate the new colors from the histo and return
          }
  
          // get the beginning vbox from the colors
          var vbox = vboxFromPixels(pixels, histo),
              pq = new PQueue(function(a,b) { return pv.naturalOrder(a.count(), b.count()); });
          pq.push(vbox);
  
          // inner function to do the iteration
          function iter(lh, target) {
              var ncolors = 1,
                  niters = 0,
                  vbox;
              while (niters < maxIterations) {
                  vbox = lh.pop();
                  if (!vbox.count())  { /* just put it back */
                      lh.push(vbox);
                      niters++;
                      continue;
                  }
                  // do the cut
                  var vboxes = medianCutApply(histo, vbox),
                      vbox1 = vboxes[0],
                      vbox2 = vboxes[1];
  
                  if (!vbox1) {
  //                    console.log("vbox1 not defined; shouldn't happen!");
                      return;
                  }
                  lh.push(vbox1);
                  if (vbox2) {  /* vbox2 can be null */
                      lh.push(vbox2);
                      ncolors++;
                  }
                  if (ncolors >= target) return;
                  if (niters++ > maxIterations) {
  //                    console.log("infinite loop; perhaps too few pixels!");
                      return;
                  }
              }
          }
  
          // first set of colors, sorted by population
          iter(pq, fractByPopulations * maxcolors);
  
          // Re-sort by the product of pixel occupancy times the size in color space.
          var pq2 = new PQueue(function(a,b) {
              return pv.naturalOrder(a.count()*a.volume(), b.count()*b.volume());
          });
          while (pq.size()) {
              pq2.push(pq.pop());
          }
  
          // next set - generate the median cuts using the (npix * vol) sorting.
          iter(pq2, maxcolors - pq2.size());
  
          // calculate the actual colors
          var cmap = new CMap();
          while (pq2.size()) {
              cmap.push(pq2.pop());
          }
  
          return cmap;
      }
  
      return {
          quantize: quantize
      };
  })();
  
  let once = false;
  
  class ClusterComponent extends Component {
  
  // accepts an array of objects [{},{},...]
  // returns an array of array of objects (clustered) [ [{},{},...] , [{},{},...] , ...]
  // object format : 
  // {
  // URL,
  // palette,
  // ...
  // }
  constructor(props) 
      { 
          super(props); 
          this.state = { cluster : [], palette : [] }; 
      } 
  histograms = [];
  numberOfClusters = 5;  
  palettes = [];
  cl = [[],[],[],[],[]];
  
  
   getHistogram = async () => {
      // let colorThief = new ColorThief();
      // colorThief.getPaletteFromUrl(i.url, (palette) => {
      //     i.palette = palette;
      //     this.palettes.push(palette);
      // });
      // return await forEach(this.props.images, async (i) => {
      //     console.log(i);
      //     debugger;
      //     let image = await Image.load(i.url);
      //     debugger;
      //     let histogram = image.getColorHistogram({nbSlots: 512});
      //     this.histograms.push(histogram);
      //     colorThief.getPaletteFromUrl(i.url, (palette) => {
      //         i.palette = palette;
      //     });
      // });
  
  
  
  
  
      var j=0;
      for (let i of this.props.images) {
          
          console.log('test', j);
          // debugger;
          let image = await Image.load(i);
          // debugger;
          let histogram = image.getColorHistogram({useAlpha: true, nbSlots: 64});
          this.histograms.push(histogram);
          // colorThief.getPaletteFromUrl(i.url, (palette) => {
          //     i.palette = palette;
          //     this.palettes.push(palette);
          // });
          j++;
      }
      console.log('length------------------------------------------',this.props.images.length)
  
  
  
  
      // for (var i=0;i<this.props.images.length;i++) {
      //     // let palette = Vibrant.from(this.props.images[i].url)
      //     // .getPalette()
      //     // .then((palette) => {
      //     //     console.log(palette)
      //     //     this.props.images[i].palette = palette;
      //     //     // console.log(this.props)
      //     // })
          
      //     console.log('test', i);
      //     // debugger;
      //     let image = await Image.load(this.props.images[i].url);
      //     // debugger;
      //     let histogram = image.getColorHistogram({nbSlots: 512});
      //     this.histograms.push(histogram);
      //     // colorThief.getPaletteFromUrl(this.props.images[i].url, (palette) => {
      //     //     this.props.images[i].palette = palette;
      //     // });
      // }
  
      // debugger;
      // let _ = this.props.images.map(async image => {
      //     let i = await Image.load(image.url);
      //     let histogram = i.getColorHistogram({nbSlots: 512});
      //     this.histograms.push(histogram);
      //     colorThief.getPaletteFromUrl(image.url, (palette) => {
      //         image.palette = palette;
      //         this.palettes.push(palette);
      //     });
      //     return 1;
      // });
      // debugger;
  
      // for (var i=0;i<images.length;i++) {
      //     let histogram = images[i].getColorHistogram({nbSlots: 512});
      //     this.histograms.push(histogram);
      //     colorThief.getPaletteFromUrl(this.props.images[i].url, (palette) => {
      //         this.props.images[i].palette = palette;
      //     });
      // }
  
  
      console.log(this.histograms);
      return this.histograms;
  }
  
  getP = async (cluster) => {
      // debugger;
      // console.log('called');
      // debugger;
      // let p = []
      let colorThief = new ColorThief();
      var k=0;
      // let palettes = [[],[],[],[],[]];
      for (let i=0;i<cluster.length;i++) {
          // console.log('cluster: ', c);
  
          for (let j of cluster[i]) {
              // console.log(c)
  
              // console.log(c)
              let p = await colorThief.getPaletteFromUrl(j.props.src, (palette) => {
                  // return palette;
                  this.palettes.push(palette);
              });
              // console.log(p);
              
              
          }
          k++;
  }
  // console.log(this.palettes);
  return await this.palettes;
  }
  
  clusterKMeans = () => {
      // this.props.images is now an array of objects that has URL as well as palette
      // console.log(this.histograms.length);
      // console.log(this.histograms.length);
      let cluster = kmeans(this.histograms, this.numberOfClusters, {maxIterations: 100});
      
      return cluster;
  }
  
  getPaletteCluster = () => {
    // loop over array
    // get palette and add it to object
   
      // return <img src={this.props.images[0].url}></img>
      if(once===true) {
          return ;
      }
      once = true;    
      console.log(this.props.images);
      this.getHistogram().then(() => {
          let clusters = this.clusterKMeans();
          clusters = clusters.clusters;
  
          for (let i=0;i<clusters.length;i++) {
              this.cl[clusters[i]].push(<img src={this.props.images[i]}></img>)
          }
          // console.log(clusters.clusters);
          this.getP(this.cl).then(() => {
              setTimeout(()=>{
                  console.log(JSON.stringify(this.palettes)); // correct result
              var p = [[],[],[],[],[]];
              var c=0;
              for (var i=0;i<this.cl.length;i++) {
                  for(var j=0;j<this.cl[i].length;j++) {
                      // console.log(this.palettes);
                      p[i].push(this.palettes[c]);
                      c++;
                  }
              }
              console.log(p);
              this.setState({cluster: this.cl, palette: p}, () => {
                  console.log(this.state);
              });
              }, 5000)
              
          });
          // this.setState({cluster: this.cl}, () => {
          //     console.log(this.state);
          // });
      });
      
      // return "Hello";
      
      // console.log(this.props.images);
      // console.log(this.histograms);
       // call cluster function
      
      //  return "Hello"
  }
  
  showClusters =  () => {
      // debugger;
      if (this.state.cluster.length === 0) {
          return [];
      }
      // let clusters = [[],[],[],[],[]];
      // // clusters.fill([],0,this.numberOfClusters+1);
      // for (let i=0;i<this.state.cluster.length;i++) {
      //     clusters[this.state.cluster[i]].push(<img src={this.props.images[i]}></img>)
      // }
      // console.log(clusters);
      console.log('show: ', this.state)
      if(this.state.palette.length === 0) {
      //  this.getP(clusters).then(()=>{
      //      console.log('palettes: ',this.palettes);
      //      this.setState({palette: this.palettes});
      //  });
      }
  
      // console.log(this.palettes);
      // this.setState()
      return <ScrollableTabsButtonAuto cluster={this.state.cluster} palette={this.state.palette} />;
      
      
  }
  
       render () {
          // debugger;
          console.log('=========================', this.props.isGalleryLoading);
          
          
          return (
              <div>
                  {once === false && this.props.isGalleryLoading === false && this.props.images.length > 0 ? this.getPaletteCluster() : this.showClusters()}
                  
              </div>
          );
      }
  }
  
  const mapStateToProps = (state) => {
      return {
          images: state.list !== undefined ? [...new Set(state.list.map(item => item.url))] : [],
          isGalleryLoading: state.isGalleryLoading,
      };
    };
  
  export default connect(mapStateToProps)(ClusterComponent);