/*!
 * Color Thief v2.0
 * by Lokesh Dhakar - http://www.lokeshdhakar.com
 * Adapted for Jimp by Jean-Matthieu Dechristé
 *
 * 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/jeanmatthieud/color-thief-jimp/master/LICENSE
 *
 */

var Jimp = require('jimp');

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 = 10;
    }
    if (typeof quality === 'undefined' || quality < 1) {
        quality = 10;
    }

    var image      = sourceImage;
    var imageData  = image.bitmap;
    var pixels     = imageData.data;
    var pixelCount = imageData.width * imageData.height;

    // 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 = null;

    return palette;
};

/*
 * getColorHex(sourceImage[, quality])
 * returns the color as string, in hexadecimal format (RRGGBB)
 *
 * 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.getColorHex = function(sourceImage, quality) {
    var paletteHex    = this.getPaletteHex(sourceImage, 5, quality);
    var dominantColor = paletteHex[0];
    return dominantColor;
};

/*
 * getPaletteHex(sourceImage[, colorCount, quality])
 * returns array[ "RRGGBB", "RRGGBB", ...]
 *
 * 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.getPaletteHex = function(sourceImage, colorCount, quality) {
    var palette = this.getPalette(sourceImage, colorCount, quality);
    return palette.map(function (colorRgb) {
        var colorInt = Jimp.rgbaToInt(colorRgb[0], colorRgb[1], colorRgb[2], 255);
        return colorInt.toString(16).substring(0, 6);
    });
};

module.exports = new ColorThief();


/*!
 * 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 && 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
    };
})();
