1.方式
1.1方式一：先把App操作過程錄製成視訊，然後根據視訊轉換成Gif
參考：http://www.jb51.net/article/78236.htm
1.2方式二：採用截圖的方式得到bitmaps陣列，然後根據bitmaps陣列生成gif
2.方式二舉例

//截圖類
package com.example.androidgifmaker;

import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.IOException;
import java.util.ArrayList
 
;

import android.app.Activity;
import android.graphics.Bitmap;
import android.graphics.Rect;
import android.util.Log;

public class ScreenShot {
    public static String TAG = "ScreenShot";
    public static ArrayList<Bitmap> bitmaps; //Add your bitmaps from internal or external storage.

    // 獲取指定Activity的截圖，儲存到png檔案
    private static Bitmap takeScreenShot(Activity activity) {
        // View是你需要截圖的View
        View view = activity.getWindow
 
().getDecorView();
        view.setDrawingCacheEnabled(true);
        view.buildDrawingCache();
        Bitmap b1 = view.getDrawingCache();

        // 獲取狀態列高度
        Rect frame = new Rect();
        activity.getWindow().getDecorView().getWindowVisibleDisplayFrame(frame);
        int statusBarHeight = frame.top
 
;
        Log.i(TAG, "狀態列的高度" + statusBarHeight);

        int wintop = activity.getWindow().findViewById(android.R.id.content).getTop();
        int titleBarHeight = wintop-statusBarHeight;
        Log.i(TAG, "標題欄的高度:"+ titleBarHeight);

        // 獲取螢幕長和高
        int width = activity.getWindowManager().getDefaultDisplay().getWidth();
        int height = activity.getWindowManager().getDefaultDisplay().getHeight();
        Log.i(TAG, "螢幕的寬度：" + width);
        Log.i(TAG, "螢幕的高度：" + height);
        // 去掉標題欄
        // Bitmap b = Bitmap.createBitmap(b1, 0, 25, 320, 455);
        Bitmap b = Bitmap.createBitmap(b1, 0, statusBarHeight, width, height - statusBarHeight);
        view.destroyDrawingCache();
        return b;
    }

    // 程式入口
    public static void shoot(Activity a) {
        if(bitmaps!=null){
            bitmaps.add(ScreenShot.takeScreenShot(a));
        }
    }
}

//Gif生成類AnimatedGifMaker.class 
//開源專案：https://github.com/dilligan/AndroidGifMaker
package com.example.androidgifmaker;

import java.io.BufferedOutputStream;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStream;
import java.nio.ByteBuffer;
import android.graphics.Bitmap;
import android.graphics.Color;

public class AnimatedGifMaker{
    // still logs noWRITE and noEXISTER
    // use Paint for instance field transparent in the future
    protected int width; // image size

    protected int height;

    protected Color transparent = null; // transparent color if given

    protected int transIndex; // transparent index in color table

    protected int repeat = -1; // no repeat

    protected int delay = 0; // frame delay (hundredths)

    protected boolean started = false; // ready to output frames

    protected OutputStream out;

    protected Bitmap image; // current frame

    protected byte[] pixels; // BGR byte array from frame

    protected byte[] indexedPixels; // converted frame indexed to palette

    protected int colorDepth; // number of bit planes

    protected byte[] colorTab; // RGB palette

    protected boolean[] usedEntry = new boolean[256]; // active palette entries

    protected int palSize = 7; // color table size (bits-1)

    protected int dispose = -1; // disposal code (-1 = use default)

    protected boolean closeStream = false; // close stream when finished

    protected boolean firstFrame = true;

    protected boolean sizeSet = false; // if false, get size from first frame

    protected int sample = 10; // default sample interval for quantizer

    /**
     * Sets the delay time between each frame, or changes it for subsequent
     * frames (applies to last frame added).
     * 
     * @param ms
     *            int delay time in milliseconds
     */
    public void setDelay(int ms) {
        delay = Math.round(ms / 10.0f);
    }

    /**
     * Sets the GIF frame disposal code for the last added frame and any
     * subsequent frames. Default is 0 if no transparent color has been set,
     * otherwise 2.
     * 
     * @param code
     *            int disposal code.
     */
    public void setDispose(int code) {
        if (code >= 0) {
            dispose = code;
        }
    }

    /**
     * Sets the number of times the set of GIF frames should be played. Default
     * is 1; 0 means play indefinitely. Must be invoked before the first image
     * is added.
     * 
     * @param iter
     *            int number of iterations.
     * @return
     */
    public void setRepeat(int iter) {
        if (iter >= 0) {
            repeat = iter;
        }
    }

    /**
     * MAKES ABSOLUTE WHITE (0,0,0) THE TRANSPARENT COLOR. 
     * 
     * @param c
     *            Color to be treated as transparent on display.
     */
    public void setTransparent(Color c) {
        transparent = c;
    }

    /**
     * Adds next GIF frame. The frame is not written immediately, but is
     * actually deferred until the next frame is received so that timing data
     * can be inserted. Invoking <code>finish()</code> flushes all frames. If
     * <code>setSize</code> was not invoked, the size of the first image is used
     * for all subsequent frames.
     * 
     * @param im
     *            BufferedImage containing frame to write.
     * @return true if successful.
     */
    public boolean addFrame(Bitmap im) {
        if ((im == null) || !started) {
            return false;
        }
        boolean ok = true;
        try {
            if (!sizeSet) {
                // use first frame's size
                setSize(im.getWidth(), im.getHeight());
            }
            image = im;
            getImagePixels(); // convert to correct format if necessary
            analyzePixels(); // build color table & map pixels
            if (firstFrame) {
                writeLSD(); // logical screen descriptior
                writePalette(); // global color table
                if (repeat >= 0) {
                    // use NS app extension to indicate reps
                    writeNetscapeExt();
                }
            }
            writeGraphicCtrlExt(); // write graphic control extension THIS IS IT
            writeImageDesc(); // image descriptor
            if (!firstFrame) {
                writePalette(); // local color table
            }
            writePixels(); // encode and write pixel data
            firstFrame = false;
        } catch (IOException e) {
            ok = false;
        }

        return ok;
    }

    /**
     * Flushes any pending data and closes output file. If writing to an
     * OutputStream, the stream is not closed.
     */
    public boolean finish() {
        if (!started)
            return false;
        boolean ok = true;
        started = false;
        try {
            out.write(0x3b); // gif trailer
            out.flush();
            if (closeStream) {
                out.close();
            }
        } catch (IOException e) {
            ok = false;
        }

        // reset for subsequent use
        transIndex = 0;
        out = null;
        image = null;
        pixels = null;
        indexedPixels = null;
        colorTab = null;
        closeStream = false;
        firstFrame = true;

        return ok;
    }

    /**
     * Sets frame rate in frames per second. Equivalent to
     * <code>setDelay(1000/fps)</code>.
     * 
     * @param fps
     *            float frame rate (frames per second)
     */
    public void setFrameRate(float fps) {
        if (fps != 0f) {
            delay = Math.round(100f / fps);
        }
    }

    /**
     * Sets quality of color quantization (conversion of images to the maximum
     * 256 colors allowed by the GIF specification). Lower values (minimum = 1)
     * produce better colors, but slow processing significantly. 10 is the
     * default, and produces good color mapping at reasonable speeds. Values
     * greater than 20 do not yield significant improvements in speed.
     * 
     * @param quality
     *            int greater than 0.
     * @return
     */
    public void setQuality(int quality) {
        if (quality < 1)
            quality = 1;
        sample = quality;
    }

    /**
     * Sets the GIF frame size. The default size is the size of the first frame
     * added if this method is not invoked.
     * 
     * @param w
     *            int frame width.
     * @param h
     *            int frame width.
     */
    public void setSize(int w, int h) {
        if (started && !firstFrame)
            return;
        width = w;
        height = h;
        if (width < 1)
            width = 320;
        if (height < 1)
            height = 240;
        sizeSet = true;
    }

    /**
     * Initiates GIF file creation on the given stream. The stream is not closed
     * automatically.
     * 
     * @param os
     *            OutputStream on which GIF images are written.
     * @return false if initial write failed.
     */
    public boolean start(OutputStream os) {
        if (os == null)
            return false;
        boolean ok = true;
        closeStream = false;
        out = os;
        try {
            writeString("GIF87a"); // header
        } catch (IOException e) {
            ok = false;
        }
        return started = ok;
    }

    /**
     * Initiates writing of a GIF file with the specified name.
     * 
     * @param file
     *            String containing output file name.
     * @return false if open or initial write failed.
     */
    public boolean start(String file) {
        boolean ok = true;
        try {
            out = new BufferedOutputStream(new FileOutputStream(file));
            ok = start(out);
            closeStream = true;
        } catch (IOException e) {
            ok = false;
        }
        return started = ok;
    }

    /**
     * Analyzes image colors and creates color map.
     */
    protected void analyzePixels() {
        int len = pixels.length;
        int nPix = len / 3;
        indexedPixels = new byte[nPix];
        NeuQuant nq = new NeuQuant(pixels, len, sample);
        // initialize quantizer
        colorTab = nq.process(); // create reduced palette
        // convert map from BGR to RGB
        for (int i = 0; i < colorTab.length; i += 3) {
            byte temp = colorTab[i];
            colorTab[i] = colorTab[i + 2];
            colorTab[i + 2] = temp;
            usedEntry[i / 3] = false;
        }
        // map image pixels to new palette
        // HACK
        int k = 0;
        for (int i = 0; i < nPix; i++) {
            int index = nq.map(pixels[k++] & 0xff, pixels[k++] & 0xff,
                    pixels[k++] & 0xff);
            usedEntry[index] = true;
            indexedPixels[i] = (byte) index;
        }
        pixels = null;
        colorDepth = 8;
        palSize = 7;
        // get closest match to transparent color if specified
        if (transparent != null) {
            transIndex = findClosest(transparent);
        }
    }

    /**
     * Returns index of palette color closest to c
     * 
     */
    protected int findClosest(Color c) {
        if (colorTab == null)
            return -1;
        // HACK
        int r = 0;
        int g = 0;
        int b = 0;
        int minpos = 0;
        int dmin = 256 * 256 * 256;
        int len = colorTab.length;
        for (int i = 0; i < len;) {
            int dr = r - (colorTab[i++] & 0xff);
            int dg = g - (colorTab[i++] & 0xff);
            int db = b - (colorTab[i] & 0xff);
            int d = dr * dr + dg * dg + db * db;
            int index = i / 3;
            if (usedEntry[index] && (d < dmin)) {
                dmin = d;
                minpos = index;
            }
            i++;
        }
        return minpos;
    }

    /**
     * Extracts image pixels into byte array "pixels"
     */
    protected void getImagePixels() {
        // calculate how many bytes our image consists of.
        int bytes = image.getByteCount();

        ByteBuffer buffer = ByteBuffer.allocate(bytes); // Create a new buffer
        image.copyPixelsToBuffer(buffer); // Move the byte data to the buffer

        byte[] inputBytes = buffer.array(); // Get the underlying array
                                            // containing the data.

        pixels = new byte[(3 * inputBytes.length) / 4];
        for (int i = 0; i < inputBytes.length / 4; i++) {
            byte r = inputBytes[4 * i];
            byte g = inputBytes[4 * i + 1];
            byte b = inputBytes[4 * i + 2];
            // ignore alpha
            pixels[3 * i] = r;
            pixels[3 * i + 1] = g;
            pixels[3 * i + 2] = b;
        }
        for (int i = 0; i < pixels.length; i += 3) {
            //switch R and B
            byte temp = pixels[i];
            pixels[i] = pixels[i + 2];
            pixels[i + 2] = temp;
        }

    }

    /**
     * Writes Graphic Control Extension
     */
    protected void writeGraphicCtrlExt() throws IOException {
        out.write(0x21); // extension introducer
        out.write(0xf9); // GCE label
        out.write(4); // data block size
        int transp, disp;
        if (transparent == null) {
            transp = 0;
            disp = 0; // dispose = no action
        } else {
            transp = 1;
            disp = 2; // force clear if using transparent color
        }
        if (dispose >= 0) {
            disp = dispose & 7; // user override
        }
        disp <<= 2;

        // packed fields
        out.write(0 | // 1:3 reserved
                disp | // 4:6 disposal
                0 | // 7 user input - 0 = none
                transp); // 8 transparency flag
        writeShort(delay); // delay x 1/100 sec
        out.write(transIndex); // transparent color index
        out.write(0); // block terminator
    }

    /**
     * Writes Image Descriptor
     */
    protected void writeImageDesc() throws IOException {
        out.write(0x2c); // image separator
        writeShort(0); // image position x,y = 0,0
        writeShort(0);
        writeShort(width); // image size
        writeShort(height);
        // packed fields
        if (firstFrame) {
            // no LCT - GCT is used for first (or only) frame
            out.write(0);
        } else {
            // specify normal LCT
            out.write(0x80 | // 1 local color table 1=yes
                    0 | // 2 interlace - 0=no
                    0 | // 3 sorted - 0=no
                    0 | // 4-5 reserved
                    palSize); // 6-8 size of color table
        }
    }

    /**
     * Writes Logical Screen Descriptor
     */
    protected void writeLSD() throws IOException {
        // logical screen size
        writeShort(width);
        writeShort(height);
        // packed fields
        out.write((0x80 | // 1 : global color table flag = 1 (gct used)
        0x70 | // 2-4 : color resolution = 7
        0x00 | // 5 : gct sort flag = 0
        palSize)); // 6-8 : gct size

        out.write(0); // background color index
        out.write(0); // pixel aspect ratio - assume 1:1
    }

    /**
     * Writes Netscape application extension to define repeat count.
     */
    protected void writeNetscapeExt() throws IOException {
        out.write(0x21); // extension introducer
        out.write(0xff); // app extension label
        out.write(11); // block size
        writeString("NETSCAPE" + "2.0"); // app id + auth code
        out.write(3); // sub-block size
        out.write(1); // loop sub-block id
        writeShort(repeat); // loop count (extra iterations, 0=repeat forever)
        out.write(0); // block terminator
    }

    /**
     * Writes color table
     */
    protected void writePalette() throws IOException {
        out.write(colorTab, 0, colorTab.length);
        int n = (3 * 256) - colorTab.length;
        for (int i = 0; i < n; i++) {
            out.write(0);
        }
    }

    /**
     * Encodes and writes pixel data
     */
    protected void writePixels() throws IOException {
        LZWEncoder encoder = new LZWEncoder(width, height, indexedPixels,
                colorDepth);
        encoder.encode(out);
    }

    /**
     * Write 16-bit value to output stream, LSB first
     */
    protected void writeShort(int value) throws IOException {
        out.write(value & 0xff);
        out.write((value >> 8) & 0xff);
    }

    /**
     * Writes string to output stream
     */
    protected void writeString(String s) throws IOException {
        for (int i = 0; i < s.length(); i++) {
            out.write((byte) s.charAt(i));
        }
    }
}

class NeuQuant {

    protected static final int netsize = 256; /* number of colours used */

    /* four primes near 500 - assume no image has a length so large */
    /* that it is divisible by all four primes */
    protected static final int prime1 = 499;

    protected static final int prime2 = 491;

    protected static final int prime3 = 487;

    protected static final int prime4 = 503;

    protected static final int minpicturebytes = (3 * prime4);

    /* minimum size for input image */

    /*
     * Program Skeleton ---------------- [select samplefac in range 1..30] [read
     * image from input file] pic = (unsigned char*) malloc(3*width*height);
     * initnet(pic,3*width*height,samplefac); learn(); unbiasnet(); [write
     * output image header, using writecolourmap(f)] inxbuild(); write output
     * image using inxsearch(b,g,r)
     */

    /*
     * Network Definitions -------------------
     */

    protected static final int maxnetpos = (netsize - 1);

    protected static final int netbiasshift = 4; /* bias for colour values */

    protected static final int ncycles = 100; /* no. of learning cycles */

    /* defs for freq and bias */
    protected static final int intbiasshift = 16; /* bias for fractions */

    protected static final int intbias = (((int) 1) << intbiasshift);

    protected static final int gammashift = 10; /* gamma = 1024 */

    protected static final int gamma = (((int) 1) << gammashift);

    protected static final int betashift = 10;

    protected static final int beta = (intbias >> betashift); /* beta = 1/1024 */

    protected static final int betagamma = (intbias << (gammashift - betashift));

    /* defs for decreasing radius factor */
    protected static final int initrad = (netsize >> 3); /*
                                                         * for 256 cols, radius
                                                         * starts
                                                         */

    protected static final int radiusbiasshift = 6; /* at 32.0 biased by 6 bits */

    protected static final int radiusbias = (((int) 1) << radiusbiasshift);

    protected static final int initradius = (initrad * radiusbias); /*
                                                                     * and
                                                                     * decreases
                                                                     * by a
                                                                     */

    protected static final int radiusdec = 30; /* factor of 1/30 each cycle */

    /* defs for decreasing alpha factor */
    protected static final int alphabiasshift = 10; /* alpha starts at 1.0 */

    protected static final int initalpha = (((int) 1) << alphabiasshift);

    protected int alphadec; /* biased by 10 bits */

    /* radbias and alpharadbias used for radpower calculation */
    protected static final int radbiasshift = 8;

    protected static final int radbias = (((int) 1) << radbiasshift);

    protected static final int alpharadbshift = (alphabiasshift + radbiasshift);

    protected static final int alpharadbias = (((int) 1) << alpharadbshift);

    /*
     * Types and Global Variables --------------------------
     */

    protected byte[] thepicture; /* the input image itself */

    protected int lengthcount; /* lengthcount = H*W*3 */

    protected int samplefac; /* sampling factor 1..30 */

    // typedef int pixel[4]; /* BGRc */
    protected int[][] network; /* the network itself - [netsize][4] */

    protected int[] netindex = new int[256];

    /* for network lookup - really 256 */

    protected int[] bias = new int[netsize];

    /* bias and freq arrays for learning */
    protected int[] freq = new int[netsize];

    protected int[] radpower = new int[initrad];

    /* radpower for precomputation */

    /*
     * Initialise network in range (0,0,0) to (255,255,255) and set parameters
     * -----------------------------------------------------------------------
     */
    public NeuQuant(byte[] thepic, int len, int sample) {

        int i;
        int[] p;

        thepicture = thepic;
        lengthcount = len;
        samplefac = sample;

        network = new int[netsize][];
        for (i = 0; i < netsize; i++) {
            network[i] = new int[4];
            p = network[i];
            p[0] = p[1] = p[2] = (i << (netbiasshift + 8)) / netsize;
            freq[i] = intbias / netsize; /* 1/netsize */
            bias[i] = 0;
        }
    }

    public byte[] colorMap() {
        byte[] map = new byte[3 * netsize];
        int[] index = new int[netsize];
        for (int i = 0; i < netsize; i++)
            index[network[i][3]] = i;
        int k = 0;
        for (int i = 0; i < netsize; i++) {
            int j = index[i];
            map[k++] = (byte) (network[j][0]);
            map[k++] = (byte) (network[j][1]);
            map[k++] = (byte) (network[j][2]);
        }
        return map;
    }

    /*
     * Insertion sort of network and building of netindex[0..255] (to do after
     * unbias)
     * ------------------------------------------------------------------
     * -------------
     */
    public void inxbuild() {

        int i, j, smallpos, smallval;
        int[] p;
        int[] q;
        int previouscol, startpos;

        previouscol = 0;
        startpos = 0;
        for (i = 0; i < netsize; i++) {
            p = network[i];
            smallpos = i;
            smallval = p[1]; /* index on g */
            /* find smallest in i..netsize-1 */
            for (j = i + 1; j < netsize; j++) {
                q = network[j];
                if (q[1] < smallval) { /* index on g */
                    smallpos = j;
                    smallval = q[1]; /* index on g */
                }
            }
            q = network[smallpos];
            /* swap p (i) and q (smallpos) entries */
            if (i != smallpos) {
                j = q[0];
                q[0] = p[0];
                p[0] = j;
                j = q[1];
                q[1] = p[1];
                p[1] = j;
                j = q[2];
                q[2] = p[2];
                p[2] = j;
                j = q[3];
                q[3] = p[3];
                p[3] = j;
            }
            /* smallval entry is now in position i */
            if (smallval != previouscol) {
                netindex[previouscol] = (startpos + i) >> 1;
                for (j = previouscol + 1; j < smallval; j++)
                    netindex[j] = i;
                previouscol = smallval;
                startpos = i;
            }
        }
        netindex[previouscol] = (startpos + maxnetpos) >> 1;
        for (j = previouscol + 1; j < 256; j++)
            netindex[j] = maxnetpos; /* really 256 */
    }

    /*
     * Main Learning Loop ------------------
     */
    public void learn() {

        int i, j, b, g, r;
        int radius, rad, alpha, step, delta, samplepixels;
        byte[] p;
        int pix, lim;

        if (lengthcount < minpicturebytes)
            samplefac = 1;
        alphadec = 30 + ((samplefac - 1) / 3);
        p = thepicture;
        pix = 0;
        lim = lengthcount;
        samplepixels = lengthcount / (3 * samplefac);
        delta = samplepixels / ncycles;
        alpha = initalpha;
        radius = initradius;

        rad = radius >> radiusbiasshift;
        if (rad <= 1)
            rad = 0;
        for (i = 0; i < rad; i++)
            radpower[i] = alpha
                    * (((rad * rad - i * i) * radbias) / (rad * rad));

        // fprintf(stderr,"beginning 1D learning: initial radius=%d\n", rad);

        if (lengthcount < minpicturebytes)
            step = 3;
        else if ((lengthcount % prime1) != 0)
            step = 3 * prime1;
        else {
            if ((lengthcount % prime2) != 0)
                step = 3 * prime2;
            else {
                if ((lengthcount % prime3) != 0)
                    step = 3 * prime3;
                else
                    step = 3 * prime4;
            }
        }

        i = 0;
        while (i < samplepixels) {
            b = (p[pix + 0] & 0xff) << netbiasshift;
            g = (p[pix + 1] & 0xff) << netbiasshift;
            r = (p[pix + 2] & 0xff) << netbiasshift;
            j = contest(b, g, r);

            altersingle(alpha, j, b, g, r);
            if (rad != 0)
                alterneigh(rad, j, b, g, r); /* alter neighbours */

            pix += step;
            if (pix >= lim)
                pix -= lengthcount;

            i++;
            if (delta == 0)
                delta = 1;
            if (i % delta == 0) {
                alpha -= alpha / alphadec;
                radius -= radius / radiusdec;
                rad = radius >> radiusbiasshift;
                if (rad <= 1)
                    rad = 0;
                for (j = 0; j < rad; j++)
                    radpower[j] = alpha
                            * (((rad * rad - j * j) * radbias) / (rad * rad));
            }
        }
        // fprintf(stderr,"finished 1D learning: final alpha=%f
        // !\n",((float)alpha)/initalpha);
    }

    /*
     * Search for BGR values 0..255 (after net is unbiased) and return colour
     * index
     * --------------------------------------------------------------------
     * --------
     */
    public int map(int b, int g, int r) {

        int i, j, dist, a, bestd;
        int[] p;
        int best;

        bestd = 1000; /* biggest possible dist is 256*3 */
        best = -1;
        i = netindex[g]; /* index on g */
        j = i - 1; /* start at netindex[g] and work outwards */

        while ((i < netsize) || (j >= 0)) {
            if (i < netsize) {
                p = network[i];
                dist = p[1] - g; /* inx key */
                if (dist >= bestd)
                    i = netsize; /* stop iter */
                else {
                    i++;
                    if (dist < 0)
                        dist = -dist;
                    a = p[0] - b;
                    if (a < 0)
                        a = -a;
                    dist += a;
                    if (dist < bestd) {
                        a = p[2] - r;
                        if (a < 0)
                            a = -a;
                        dist += a;
                        if (dist < bestd) {
                            bestd = dist;
                            best = p[3];
                        }
                    }
                }
            }
            if (j >= 0) {
                p = network[j];
                dist = g - p[1]; /* inx key - reverse dif */
                if (dist >= bestd)
                    j = -1; /* stop iter */
                else {
                    j--;
                    if (dist < 0)
                        dist = -dist;
                    a = p[0] - b;
                    if (a < 0)
                        a = -a;
                    dist += a;
                    if (dist < bestd) {
                        a = p[2] - r;
                        if (a < 0)
                            a = -a;
                        dist += a;
                        if (dist < bestd) {
                            bestd = dist;
                            best = p[3];
                        }
                    }
                }
            }
        }
        return (best);
    }

    public byte[] process() {
        learn();
        unbiasnet();
        inxbuild();
        return colorMap();
    }

    /*
     * Unbias network to give byte values 0..255 and record position i to
     * prepare for sort
     * ----------------------------------------------------------
     * -------------------------
     */
    public void unbiasnet() {

        int i;

        for (i = 0; i < netsize; i++) {
            network[i][0] >>= netbiasshift;
            network[i][1] >>= netbiasshift;
            network[i][2] >>= netbiasshift;
            network[i][3] = i; /* record colour no */
        }
    }

    /*
     * Move adjacent neurons by precomputed alpha*(1-((i-j)^2/[r]^2)) in
     * radpower[|i-j|]
     * ----------------------------------------------------------
     * -----------------------
     */
    protected void alterneigh(int rad, int i, int b, int g, int r) {

        int j, k, lo, hi, a, m;
        int[] p;

        lo = i - rad;
        if (lo < -1)
            lo = -1;
        hi = i + rad;
        if (hi > netsize)
            hi = netsize;

        j = i + 1;
        k = i - 1;
        m = 1;
        while ((j < hi) || (k > lo)) {
            a = radpower[m++];
            if (j < hi) {
                p = network[j++];
                try {
                    p[0] -= (a * (p[0] - b)) / alpharadbias;
                    p