/*
 * jQuery Nivo Slider v2.6
 * http://nivo.dev7studios.com
 *
 * Copyright 2011, Gilbert Pellegrom
 * Free to use and abuse under the MIT license.
 * http://www.opensource.org/licenses/mit-license.php
 * 
 * March 2010
 */

(function($){var NivoSlider=function(element,options){var settings=$.extend({},$.fn.nivoSlider.defaults,options);var vars={currentSlide:0,currentImage:'',totalSlides:0,randAnim:'',running:false,paused:false,stop:false};var slider=$(element);slider.data('nivo:vars',vars);slider.css('position','relative');slider.addClass('nivoSlider');var kids=slider.children();kids.each(function(){var child=$(this);var link='';if(!child.is('img')){if(child.is('a')){child.addClass('nivo-imageLink');link=child;}
child=child.find('img:first');}
var childWidth=child.width();if(childWidth==0)childWidth=child.attr('width');var childHeight=child.height();if(childHeight==0)childHeight=child.attr('height');if(childWidth>slider.width()){slider.width(childWidth);}
if(childHeight>slider.height()){slider.height(childHeight);}
if(link!=''){link.css('display','none');}
child.css('display','none');vars.totalSlides++;});if(settings.startSlide>0){if(settings.startSlide>=vars.totalSlides)settings.startSlide=vars.totalSlides-1;vars.currentSlide=settings.startSlide;}
if($(kids[vars.currentSlide]).is('img')){vars.currentImage=$(kids[vars.currentSlide]);}else{vars.currentImage=$(kids[vars.currentSlide]).find('img:first');}
if($(kids[vars.currentSlide]).is('a')){$(kids[vars.currentSlide]).css('display','block');}
slider.css('background','url("'+vars.currentImage.attr('src')+'") no-repeat');slider.append($('<div class="nivo-caption"><p></p></div>').css({display:'none',opacity:settings.captionOpacity}));var processCaption=function(settings){var nivoCaption=$('.nivo-caption',slider);if(vars.currentImage.attr('title')!=''&&vars.currentImage.attr('title')!=undefined){var title=vars.currentImage.attr('title');if(title.substr(0,1)=='#')title=$(title).html();if(nivoCaption.css('display')=='block'){nivoCaption.find('p').fadeOut(settings.animSpeed,function(){$(this).html(title);$(this).fadeIn(settings.animSpeed);});}else{nivoCaption.find('p').html(title);}
nivoCaption.fadeIn(settings.animSpeed);}else{nivoCaption.fadeOut(settings.animSpeed);}}
processCaption(settings);var timer=0;if(!settings.manualAdvance&&kids.length>1){timer=setInterval(function(){nivoRun(slider,kids,settings,false);},settings.pauseTime);}
if(settings.directionNav){slider.append('<div class="nivo-directionNav"><a class="nivo-prevNav">'+settings.prevText+'</a><a class="nivo-nextNav">'+settings.nextText+'</a></div>');if(settings.directionNavHide){$('.nivo-directionNav',slider).hide();slider.hover(function(){$('.nivo-directionNav',slider).show();},function(){$('.nivo-directionNav',slider).hide();});}
$('a.nivo-prevNav',slider).live('click',function(){if(vars.running)return false;clearInterval(timer);timer='';vars.currentSlide-=2;nivoRun(slider,kids,settings,'prev');});$('a.nivo-nextNav',slider).live('click',function(){if(vars.running)return false;clearInterval(timer);timer='';nivoRun(slider,kids,settings,'next');});}
if(settings.controlNav){var nivoControl=$('<div class="nivo-controlNav"></div>');slider.append(nivoControl);for(var i=0;i<kids.length;i++){if(settings.controlNavThumbs){var child=kids.eq(i);if(!child.is('img')){child=child.find('img:first');}
if(settings.controlNavThumbsFromRel){nivoControl.append('<a class="nivo-control" rel="'+i+'"><img src="'+child.attr('rel')+'" alt="" /></a>');}else{nivoControl.append('<a class="nivo-control" rel="'+i+'"><img src="'+child.attr('src').replace(settings.controlNavThumbsSearch,settings.controlNavThumbsReplace)+'" alt="" /></a>');}}else{nivoControl.append('<a class="nivo-control" rel="'+i+'">'+(i+1)+'</a>');}}
$('.nivo-controlNav a:eq('+vars.currentSlide+')',slider).addClass('active');$('.nivo-controlNav a',slider).live('click',function(){if(vars.running)return false;if($(this).hasClass('active'))return false;clearInterval(timer);timer='';slider.css('background','url("'+vars.currentImage.attr('src')+'") no-repeat');vars.currentSlide=$(this).attr('rel')-1;nivoRun(slider,kids,settings,'control');});}
if(settings.keyboardNav){$(window).keypress(function(event){if(event.keyCode=='37'){if(vars.running)return false;clearInterval(timer);timer='';vars.currentSlide-=2;nivoRun(slider,kids,settings,'prev');}
if(event.keyCode=='39'){if(vars.running)return false;clearInterval(timer);timer='';nivoRun(slider,kids,settings,'next');}});}
if(settings.pauseOnHover){slider.hover(function(){vars.paused=true;clearInterval(timer);timer='';},function(){vars.paused=false;if(timer==''&&!settings.manualAdvance){timer=setInterval(function(){nivoRun(slider,kids,settings,false);},settings.pauseTime);}});}
slider.bind('nivo:animFinished',function(){vars.running=false;$(kids).each(function(){if($(this).is('a')){$(this).css('display','none');}});if($(kids[vars.currentSlide]).is('a')){$(kids[vars.currentSlide]).css('display','block');}
if(timer==''&&!vars.paused&&!settings.manualAdvance){timer=setInterval(function(){nivoRun(slider,kids,settings,false);},settings.pauseTime);}
settings.afterChange.call(this);});var createSlices=function(slider,settings,vars){for(var i=0;i<settings.slices;i++){var sliceWidth=Math.round(slider.width()/settings.slices);if(i==settings.slices-1){slider.append($('<div class="nivo-slice"></div>').css({left:(sliceWidth*i)+'px',width:(slider.width()-(sliceWidth*i))+'px',height:'0px',opacity:'0',background:'url("'+vars.currentImage.attr('src')+'") no-repeat -'+((sliceWidth+(i*sliceWidth))-sliceWidth)+'px 0%'}));}else{slider.append($('<div class="nivo-slice"></div>').css({left:(sliceWidth*i)+'px',width:sliceWidth+'px',height:'0px',opacity:'0',background:'url("'+vars.currentImage.attr('src')+'") no-repeat -'+((sliceWidth+(i*sliceWidth))-sliceWidth)+'px 0%'}));}}}
var createBoxes=function(slider,settings,vars){var boxWidth=Math.round(slider.width()/settings.boxCols);var boxHeight=Math.round(slider.height()/settings.boxRows);for(var rows=0;rows<settings.boxRows;rows++){for(var cols=0;cols<settings.boxCols;cols++){if(cols==settings.boxCols-1){slider.append($('<div class="nivo-box"></div>').css({opacity:0,left:(boxWidth*cols)+'px',top:(boxHeight*rows)+'px',width:(slider.width()-(boxWidth*cols))+'px',height:boxHeight+'px',background:'url("'+vars.currentImage.attr('src')+'") no-repeat -'+((boxWidth+(cols*boxWidth))-boxWidth)+'px -'+((boxHeight+(rows*boxHeight))-boxHeight)+'px'}));}else{slider.append($('<div class="nivo-box"></div>').css({opacity:0,left:(boxWidth*cols)+'px',top:(boxHeight*rows)+'px',width:boxWidth+'px',height:boxHeight+'px',background:'url("'+vars.currentImage.attr('src')+'") no-repeat -'+((boxWidth+(cols*boxWidth))-boxWidth)+'px -'+((boxHeight+(rows*boxHeight))-boxHeight)+'px'}));}}}}
var nivoRun=function(slider,kids,settings,nudge){var vars=slider.data('nivo:vars');if(vars&&(vars.currentSlide==vars.totalSlides-1)){settings.lastSlide.call(this);}
if((!vars||vars.stop)&&!nudge)return false;settings.beforeChange.call(this);if(!nudge){slider.css('background','url("'+vars.currentImage.attr('src')+'") no-repeat');}else{if(nudge=='prev'){slider.css('background','url("'+vars.currentImage.attr('src')+'") no-repeat');}
if(nudge=='next'){slider.css('background','url("'+vars.currentImage.attr('src')+'") no-repeat');}}
vars.currentSlide++;if(vars.currentSlide==vars.totalSlides){vars.currentSlide=0;settings.slideshowEnd.call(this);}
if(vars.currentSlide<0)vars.currentSlide=(vars.totalSlides-1);if($(kids[vars.currentSlide]).is('img')){vars.currentImage=$(kids[vars.currentSlide]);}else{vars.currentImage=$(kids[vars.currentSlide]).find('img:first');}
if(settings.controlNav){$('.nivo-controlNav a',slider).removeClass('active');$('.nivo-controlNav a:eq('+vars.currentSlide+')',slider).addClass('active');}
processCaption(settings);$('.nivo-slice',slider).remove();$('.nivo-box',slider).remove();if(settings.effect=='random'){var anims=new Array('sliceDownRight','sliceDownLeft','sliceUpRight','sliceUpLeft','sliceUpDown','sliceUpDownLeft','fold','fade','boxRandom','boxRain','boxRainReverse','boxRainGrow','boxRainGrowReverse');vars.randAnim=anims[Math.floor(Math.random()*(anims.length+1))];if(vars.randAnim==undefined)vars.randAnim='fade';}
if(settings.effect.indexOf(',')!=-1){var anims=settings.effect.split(',');vars.randAnim=anims[Math.floor(Math.random()*(anims.length))];if(vars.randAnim==undefined)vars.randAnim='fade';}
vars.running=true;if(settings.effect=='sliceDown'||settings.effect=='sliceDownRight'||vars.randAnim=='sliceDownRight'||settings.effect=='sliceDownLeft'||vars.randAnim=='sliceDownLeft'){createSlices(slider,settings,vars);var timeBuff=0;var i=0;var slices=$('.nivo-slice',slider);if(settings.effect=='sliceDownLeft'||vars.randAnim=='sliceDownLeft')slices=$('.nivo-slice',slider)._reverse();slices.each(function(){var slice=$(this);slice.css({'top':'0px'});if(i==settings.slices-1){setTimeout(function(){slice.animate({height:'100%',opacity:'1.0'},settings.animSpeed,'',function(){slider.trigger('nivo:animFinished');});},(100+timeBuff));}else{setTimeout(function(){slice.animate({height:'100%',opacity:'1.0'},settings.animSpeed);},(100+timeBuff));}
timeBuff+=50;i++;});}
else if(settings.effect=='sliceUp'||settings.effect=='sliceUpRight'||vars.randAnim=='sliceUpRight'||settings.effect=='sliceUpLeft'||vars.randAnim=='sliceUpLeft'){createSlices(slider,settings,vars);var timeBuff=0;var i=0;var slices=$('.nivo-slice',slider);if(settings.effect=='sliceUpLeft'||vars.randAnim=='sliceUpLeft')slices=$('.nivo-slice',slider)._reverse();slices.each(function(){var slice=$(this);slice.css({'bottom':'0px'});if(i==settings.slices-1){setTimeout(function(){slice.animate({height:'100%',opacity:'1.0'},settings.animSpeed,'',function(){slider.trigger('nivo:animFinished');});},(100+timeBuff));}else{setTimeout(function(){slice.animate({height:'100%',opacity:'1.0'},settings.animSpeed);},(100+timeBuff));}
timeBuff+=50;i++;});}
else if(settings.effect=='sliceUpDown'||settings.effect=='sliceUpDownRight'||vars.randAnim=='sliceUpDown'||settings.effect=='sliceUpDownLeft'||vars.randAnim=='sliceUpDownLeft'){createSlices(slider,settings,vars);var timeBuff=0;var i=0;var v=0;var slices=$('.nivo-slice',slider);if(settings.effect=='sliceUpDownLeft'||vars.randAnim=='sliceUpDownLeft')slices=$('.nivo-slice',slider)._reverse();slices.each(function(){var slice=$(this);if(i==0){slice.css('top','0px');i++;}else{slice.css('bottom','0px');i=0;}
if(v==settings.slices-1){setTimeout(function(){slice.animate({height:'100%',opacity:'1.0'},settings.animSpeed,'',function(){slider.trigger('nivo:animFinished');});},(100+timeBuff));}else{setTimeout(function(){slice.animate({height:'100%',opacity:'1.0'},settings.animSpeed);},(100+timeBuff));}
timeBuff+=50;v++;});}
else if(settings.effect=='fold'||vars.randAnim=='fold'){createSlices(slider,settings,vars);var timeBuff=0;var i=0;$('.nivo-slice',slider).each(function(){var slice=$(this);var origWidth=slice.width();slice.css({top:'0px',height:'100%',width:'0px'});if(i==settings.slices-1){setTimeout(function(){slice.animate({width:origWidth,opacity:'1.0'},settings.animSpeed,'',function(){slider.trigger('nivo:animFinished');});},(100+timeBuff));}else{setTimeout(function(){slice.animate({width:origWidth,opacity:'1.0'},settings.animSpeed);},(100+timeBuff));}
timeBuff+=50;i++;});}
else if(settings.effect=='fade'||vars.randAnim=='fade'){createSlices(slider,settings,vars);var firstSlice=$('.nivo-slice:first',slider);firstSlice.css({'height':'100%','width':slider.width()+'px'});firstSlice.animate({opacity:'1.0'},(settings.animSpeed*2),'',function(){slider.trigger('nivo:animFinished');});}
else if(settings.effect=='slideInRight'||vars.randAnim=='slideInRight'){createSlices(slider,settings,vars);var firstSlice=$('.nivo-slice:first',slider);firstSlice.css({'height':'100%','width':'0px','opacity':'1'});firstSlice.animate({width:slider.width()+'px'},(settings.animSpeed*2),'',function(){slider.trigger('nivo:animFinished');});}
else if(settings.effect=='slideInLeft'||vars.randAnim=='slideInLeft'){createSlices(slider,settings,vars);var firstSlice=$('.nivo-slice:first',slider);firstSlice.css({'height':'100%','width':'0px','opacity':'1','left':'','right':'0px'});firstSlice.animate({width:slider.width()+'px'},(settings.animSpeed*2),'',function(){firstSlice.css({'left':'0px','right':''});slider.trigger('nivo:animFinished');});}
else if(settings.effect=='boxRandom'||vars.randAnim=='boxRandom'){createBoxes(slider,settings,vars);var totalBoxes=settings.boxCols*settings.boxRows;var i=0;var timeBuff=0;var boxes=shuffle($('.nivo-box',slider));boxes.each(function(){var box=$(this);if(i==totalBoxes-1){setTimeout(function(){box.animate({opacity:'1'},settings.animSpeed,'',function(){slider.trigger('nivo:animFinished');});},(100+timeBuff));}else{setTimeout(function(){box.animate({opacity:'1'},settings.animSpeed);},(100+timeBuff));}
timeBuff+=20;i++;});}
else if(settings.effect=='boxRain'||vars.randAnim=='boxRain'||settings.effect=='boxRainReverse'||vars.randAnim=='boxRainReverse'||settings.effect=='boxRainGrow'||vars.randAnim=='boxRainGrow'||settings.effect=='boxRainGrowReverse'||vars.randAnim=='boxRainGrowReverse'){createBoxes(slider,settings,vars);var totalBoxes=settings.boxCols*settings.boxRows;var i=0;var timeBuff=0;var rowIndex=0;var colIndex=0;var box2Darr=new Array();box2Darr[rowIndex]=new Array();var boxes=$('.nivo-box',slider);if(settings.effect=='boxRainReverse'||vars.randAnim=='boxRainReverse'||settings.effect=='boxRainGrowReverse'||vars.randAnim=='boxRainGrowReverse'){boxes=$('.nivo-box',slider)._reverse();}
boxes.each(function(){box2Darr[rowIndex][colIndex]=$(this);colIndex++;if(colIndex==settings.boxCols){rowIndex++;colIndex=0;box2Darr[rowIndex]=new Array();}});for(var cols=0;cols<(settings.boxCols*2);cols++){var prevCol=cols;for(var rows=0;rows<settings.boxRows;rows++){if(prevCol>=0&&prevCol<settings.boxCols){(function(row,col,time,i,totalBoxes){var box=$(box2Darr[row][col]);var w=box.width();var h=box.height();if(settings.effect=='boxRainGrow'||vars.randAnim=='boxRainGrow'||settings.effect=='boxRainGrowReverse'||vars.randAnim=='boxRainGrowReverse'){box.width(0).height(0);}
if(i==totalBoxes-1){setTimeout(function(){box.animate({opacity:'1',width:w,height:h},settings.animSpeed/1.3,'',function(){slider.trigger('nivo:animFinished');});},(100+time));}else{setTimeout(function(){box.animate({opacity:'1',width:w,height:h},settings.animSpeed/1.3);},(100+time));}})(rows,prevCol,timeBuff,i,totalBoxes);i++;}
prevCol--;}
timeBuff+=100;}}}
var shuffle=function(arr){for(var j,x,i=arr.length;i;j=parseInt(Math.random()*i),x=arr[--i],arr[i]=arr[j],arr[j]=x);return arr;}
var trace=function(msg){if(this.console&&typeof console.log!="undefined")
console.log(msg);}
this.stop=function(){if(!$(element).data('nivo:vars').stop){$(element).data('nivo:vars').stop=true;trace('Stop Slider');}}
this.start=function(){if($(element).data('nivo:vars').stop){$(element).data('nivo:vars').stop=false;trace('Start Slider');}}
settings.afterLoad.call(this);return this;};$.fn.nivoSlider=function(options){return this.each(function(key,value){var element=$(this);if(element.data('nivoslider'))return element.data('nivoslider');var nivoslider=new NivoSlider(this,options);element.data('nivoslider',nivoslider);});};$.fn.nivoSlider.defaults={effect:'random',slices:15,boxCols:8,boxRows:4,animSpeed:500,pauseTime:3000,startSlide:0,directionNav:true,directionNavHide:true,controlNav:true,controlNavThumbs:false,controlNavThumbsFromRel:false,controlNavThumbsSearch:'.jpg',controlNavThumbsReplace:'_thumb.jpg',keyboardNav:true,pauseOnHover:true,manualAdvance:false,captionOpacity:0.8,prevText:'Prev',nextText:'Next',beforeChange:function(){},afterChange:function(){},slideshowEnd:function(){},lastSlide:function(){},afterLoad:function(){}};$.fn._reverse=[].reverse;})(jQuery);;
/*! 
 * quantize.js Copyright 2008 Nick Rabinowitz.
 * Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php
 */

// 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
 */
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,
                    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 && rval <= vbox.g2 &&
                    bval >= vbox.b1 && rval <= 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[1] - vboxes.peek(i).color[1], 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);
        // console.log(pq.size(), pq.debug().length, pq.debug().slice());
        
        // 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
    }
})();;
/*
 * Image Palette v0.1
 * by Lokesh Dhakar - http://www.lokeshdhakar.com
 *
 * Licensed under the Creative Commons Attribution 2.5 License - http://creativecommons.org/licenses/by/2.5/
 *
 * The median cut palette function uses quantize.js which is written by Nick Rabinowitz
 * and licensed under the MIT license. Big props to Nick as this is where the magic happens.
 *
 * == Classes
 * CanvasImage
 * == Functions
 * getDominantColor()
 * createPalette()
 * getAverageRGB()
 * createAreaBasedPalette()
 *
 * Requires jquery and quantize.js.
*/


/*
	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){
	// If jquery object is passed in, get html element
	this.imgEl = (image.jquery)? image[0]: image;

	this.canvas = document.createElement('canvas'),
    this.context = this.canvas.getContext('2d');

	document.body.appendChild(this.canvas);

	this.width = this.canvas.width = jQuery(this.imgEl).width(),
	this.height = this.canvas.height = jQuery(this.imgEl).height();

	this.context.drawImage(this.imgEl, 0, 0);
}

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() {
  jQuery(this.canvas).remove();
}


/*
 * getDominantColor(sourceImage)
 * 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.
*/
function getDominantColor(sourceImage){

	var palette = [];

	// Create custom CanvasImage object
	var image = new CanvasImage(sourceImage),
		imageData = image.getImageData(),
		pixels = imageData.data,
		pixelCount = image.getPixelCount();

	// Store the RGB values in an array format suitable for quantize function
	var pixelArray = [];
	for (var i = 0; i < pixelCount; i++) {
		// If pixel is mostly opaque and not white
		if(pixels[i*4+3] >= 125){
			if(!(pixels[i*4] > 250 && pixels[i*4+1] > 250 && pixels[i*4+2] > 250)){
	   			pixelArray.push( [pixels[i*4], pixels[i*4+1], pixels[i*4+2]]);
			}
		}
	};

	// Send array to quantize function which clusters values
	// using median cut algorithm
	var cmap = MMCQ.quantize(pixelArray, 5);
	var newPalette = cmap.palette();

	// Clean up
	image.removeCanvas();

	return {r: newPalette[0][0], g: newPalette[0][1], b: newPalette[0][2]};
}



/*
 * createPalette(sourceImage, colorCount)
 * 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.
 *
 * BUGGY: Function does not always return the requested amount of colors. It can be +/- 2.
*/
function createPalette(sourceImage, colorCount){

	var palette = [];

	// Create custom CanvasImage object
	var image = new CanvasImage(sourceImage),
		imageData = image.getImageData(),
		pixels = imageData.data,
		pixelCount = image.getPixelCount();

	// Store the RGB values in an array format suitable for quantize function
	var pixelArray = [];
	for (var i = 0; i < pixelCount; i++) {
		// If pixel is mostly opaque and not white
		if(pixels[i*4+3] >= 125){
			if(!(pixels[i*4] > 250 && pixels[i*4+1] > 250 && pixels[i*4+2] > 250)){
	    		pixelArray.push( [pixels[i*4], pixels[i*4+1], pixels[i*4+2]]);
			}
		}
	};

	// Send array to quantize function which clusters values
	// using median cut algorithm
	var cmap = MMCQ.quantize(pixelArray, colorCount);
	var newPalette = cmap.palette();

	// Clean up
	image.removeCanvas();

	return newPalette;
}


/*
 * getAverageRGB(sourceImage)
 * returns {r: num, g: num, b: num}
 *
 * Add up all pixels RGB values and return average.
 * Tends to return muddy gray/brown color. Most likely, you'll be better
 * off using getDominantColor() instead.
*/
function getAverageRGB(sourceImage) {
	// Config
	var sampleSize = 10;

	// Create custom CanvasImage object
	var image = new CanvasImage(sourceImage),
		imageData = image.getImageData(),
		pixels = imageData.data,
		pixelCount = image.getPixelCount();

	// Reset vars
	var i = 0,
		count = 0,
		rgb = {r:0,g:0,b:0};

	// Loop through every # pixels. (# is set in Config above via the blockSize var)
	// Add all the red values together, repeat for blue and green.
	// Last step, divide by the number of pixels checked to get average.
    while ( (i += sampleSize * 4) < pixelCount ) {
		// if pixel is mostly opaque
		if(pixels[i+3] > 125){
	        ++count;
			rgb.r += pixels[i];
	        rgb.g += pixels[i+1];
	        rgb.b += pixels[i+2];
		}
    }

  	rgb.r = Math.floor(rgb.r/count);
    rgb.g = Math.floor(rgb.g/count);
    rgb.b = Math.floor(rgb.b/count);

	return rgb;
}


/*
 * createAreaBasedPalette(sourceImage, colorCount)
 * returns array[ {r: num, g: num, b: num}, {r: num, g: num, b: num}, ...]
 *
 * Break the image into sections. Loops through pixel RGBS in the section and average color.
 * Tends to return muddy gray/brown color. You're most likely better off using createPalette().
 *
 * BUGGY: Function does not always return the requested amount of colors. It can be +/- 2.
 *
*/
function createAreaBasedPalette(sourceImage, colorCount){

	var palette = [];

	// Create custom CanvasImage object
	var image = new CanvasImage(sourceImage),
		imageData = image.getImageData(),
		pixels = imageData.data,
		pixelCount = image.getPixelCount();


	// How big a pixel area does each palette color get
	var rowCount = colCount = Math.round(Math.sqrt(colorCount)),
		colWidth = Math.round(image.width / colCount),
		rowHeight = Math.round(image.height / rowCount);

	var count = offset = rowOffset = vertOffset = horizOffset = 0,
		rgb = {r:0,g:0,b:0};

	// Loop through pixels section by section.
	// At the end of each section, push the average rgb color to palette array.
	for(var i=0; i<rowCount; i++){
		vertOffset = i * rowHeight * image.width * 4;

		for(var j=0; j<colCount; j++){
			horizOffset = j * colWidth * 4;

			for( var k = 0; k < rowHeight; k++){
				rowOffset = k * image.width * 4;

				for( var l = 0; l < colWidth; l++){
					offset = vertOffset + horizOffset + rowOffset + (l * 4);
				    rgb.r += pixels[offset];
			        rgb.g += pixels[offset+1];
			        rgb.b += pixels[offset+2];
					count++;
				}

			}
			rgb.r = Math.floor(rgb.r/count);
		    rgb.g = Math.floor(rgb.g/count);
		    rgb.b = Math.floor(rgb.b/count);
			palette.push(rgb);

			// reset before next section
			rgb = {r:0,g:0,b:0};
			count = 0;
		}
	}

	return palette;
}
;