|
|
@@ -3,341 +3,341 @@ package eu.mjdev.desktop.helpers.gif;
|
|
|
|
|
|
@SuppressWarnings("ALL")
|
|
|
public class NeuQuant {
|
|
|
- protected static final int netsize = 256;
|
|
|
- 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);
|
|
|
- protected static final int maxnetpos = (netsize - 1);
|
|
|
- protected static final int netbiasshift = 4;
|
|
|
- protected static final int ncycles = 100;
|
|
|
- protected static final int intbiasshift = 16;
|
|
|
- protected static final int intbias = (1 << intbiasshift);
|
|
|
- protected static final int gammashift = 10;
|
|
|
- protected static final int gamma = (1 << gammashift);
|
|
|
- protected static final int betashift = 10;
|
|
|
- protected static final int beta = (intbias >> betashift);
|
|
|
- protected static final int betagamma = (intbias << (gammashift - betashift));
|
|
|
- protected static final int initrad = (netsize >> 3);
|
|
|
- protected static final int radiusbiasshift = 6;
|
|
|
- protected static final int radiusbias = (1 << radiusbiasshift);
|
|
|
- protected static final int initradius = (initrad * radiusbias);
|
|
|
- protected static final int radiusdec = 30;
|
|
|
- protected static final int alphabiasshift = 10;
|
|
|
- protected static final int initalpha = (((int) 1) << alphabiasshift);
|
|
|
- protected int alphadec;
|
|
|
- protected static final int radbiasshift = 8;
|
|
|
- protected static final int radbias = (1 << radbiasshift);
|
|
|
- protected static final int alpharadbshift = (alphabiasshift + radbiasshift);
|
|
|
- protected static final int alpharadbias = (((int) 1) << alpharadbshift);
|
|
|
- protected byte[] thepicture;
|
|
|
- protected int lengthcount;
|
|
|
- protected int samplefac;
|
|
|
- protected int[][] network;
|
|
|
- protected int[] netindex = new int[256];
|
|
|
- protected int[] bias = new int[netsize];
|
|
|
- protected int[] freq = new int[netsize];
|
|
|
- protected int[] radpower = new int[initrad];
|
|
|
+ protected static final int netsize = 256;
|
|
|
+ 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);
|
|
|
+ protected static final int maxnetpos = (netsize - 1);
|
|
|
+ protected static final int netbiasshift = 4;
|
|
|
+ protected static final int ncycles = 100;
|
|
|
+ protected static final int intbiasshift = 16;
|
|
|
+ protected static final int intbias = (1 << intbiasshift);
|
|
|
+ protected static final int gammashift = 10;
|
|
|
+ protected static final int gamma = (1 << gammashift);
|
|
|
+ protected static final int betashift = 10;
|
|
|
+ protected static final int beta = (intbias >> betashift);
|
|
|
+ protected static final int betagamma = (intbias << (gammashift - betashift));
|
|
|
+ protected static final int initrad = (netsize >> 3);
|
|
|
+ protected static final int radiusbiasshift = 6;
|
|
|
+ protected static final int radiusbias = (1 << radiusbiasshift);
|
|
|
+ protected static final int initradius = (initrad * radiusbias);
|
|
|
+ protected static final int radiusdec = 30;
|
|
|
+ protected static final int alphabiasshift = 10;
|
|
|
+ protected static final int initalpha = (((int) 1) << alphabiasshift);
|
|
|
+ protected int alphadec;
|
|
|
+ protected static final int radbiasshift = 8;
|
|
|
+ protected static final int radbias = (1 << radbiasshift);
|
|
|
+ protected static final int alpharadbshift = (alphabiasshift + radbiasshift);
|
|
|
+ protected static final int alpharadbias = (((int) 1) << alpharadbshift);
|
|
|
+ protected byte[] thepicture;
|
|
|
+ protected int lengthcount;
|
|
|
+ protected int samplefac;
|
|
|
+ protected int[][] network;
|
|
|
+ protected int[] netindex = new int[256];
|
|
|
+ protected int[] bias = new int[netsize];
|
|
|
+ protected int[] freq = new int[netsize];
|
|
|
+ protected int[] radpower = new int[initrad];
|
|
|
|
|
|
- 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;
|
|
|
- }
|
|
|
-
|
|
|
- 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 */
|
|
|
- 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];
|
|
|
- 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;
|
|
|
- }
|
|
|
- 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 */
|
|
|
- }
|
|
|
-
|
|
|
- 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));
|
|
|
- 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));
|
|
|
- }
|
|
|
- }
|
|
|
- }
|
|
|
-
|
|
|
- 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 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[] process() {
|
|
|
- learn();
|
|
|
- unbiasnet();
|
|
|
- inxbuild();
|
|
|
- return colorMap();
|
|
|
- }
|
|
|
-
|
|
|
- public void unbiasnet() {
|
|
|
- int i, j;
|
|
|
- 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 */
|
|
|
- }
|
|
|
- }
|
|
|
-
|
|
|
- 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[1] -= (a * (p[1] - g)) / alpharadbias;
|
|
|
- p[2] -= (a * (p[2] - r)) / alpharadbias;
|
|
|
- } catch (Exception e) {
|
|
|
- } // prevents 1.3 miscompilation
|
|
|
- }
|
|
|
- if (k > lo) {
|
|
|
- p = network[k--];
|
|
|
- try {
|
|
|
- p[0] -= (a * (p[0] - b)) / alpharadbias;
|
|
|
- p[1] -= (a * (p[1] - g)) / alpharadbias;
|
|
|
- p[2] -= (a * (p[2] - r)) / alpharadbias;
|
|
|
- } catch (Exception e) {
|
|
|
- }
|
|
|
- }
|
|
|
- }
|
|
|
- }
|
|
|
-
|
|
|
- protected void altersingle(int alpha, int i, int b, int g, int r) {
|
|
|
- int[] n = network[i];
|
|
|
- n[0] -= (alpha * (n[0] - b)) / initalpha;
|
|
|
- n[1] -= (alpha * (n[1] - g)) / initalpha;
|
|
|
- n[2] -= (alpha * (n[2] - r)) / initalpha;
|
|
|
- }
|
|
|
-
|
|
|
- protected int contest(int b, int g, int r) {
|
|
|
- int i, dist, a, biasdist, betafreq;
|
|
|
- int bestpos, bestbiaspos, bestd, bestbiasd;
|
|
|
- int[] n;
|
|
|
- bestd = ~(((int) 1) << 31);
|
|
|
- bestbiasd = bestd;
|
|
|
- bestpos = -1;
|
|
|
- bestbiaspos = bestpos;
|
|
|
- for (i = 0; i < netsize; i++) {
|
|
|
- n = network[i];
|
|
|
- dist = n[0] - b;
|
|
|
- if (dist < 0)
|
|
|
- dist = -dist;
|
|
|
- a = n[1] - g;
|
|
|
- if (a < 0)
|
|
|
- a = -a;
|
|
|
- dist += a;
|
|
|
- a = n[2] - r;
|
|
|
- if (a < 0)
|
|
|
- a = -a;
|
|
|
- dist += a;
|
|
|
- if (dist < bestd) {
|
|
|
- bestd = dist;
|
|
|
- bestpos = i;
|
|
|
- }
|
|
|
- biasdist = dist - ((bias[i]) >> (intbiasshift - netbiasshift));
|
|
|
- if (biasdist < bestbiasd) {
|
|
|
- bestbiasd = biasdist;
|
|
|
- bestbiaspos = i;
|
|
|
- }
|
|
|
- betafreq = (freq[i] >> betashift);
|
|
|
- freq[i] -= betafreq;
|
|
|
- bias[i] += (betafreq << gammashift);
|
|
|
- }
|
|
|
- freq[bestpos] += beta;
|
|
|
- bias[bestpos] -= betagamma;
|
|
|
- return (bestbiaspos);
|
|
|
- }
|
|
|
+ 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;
|
|
|
+ }
|
|
|
+
|
|
|
+ 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 */
|
|
|
+ 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];
|
|
|
+ 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;
|
|
|
+ }
|
|
|
+ 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 */
|
|
|
+ }
|
|
|
+
|
|
|
+ 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));
|
|
|
+ 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));
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ 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();
|
|
|
+ }
|
|
|
+
|
|
|
+ public void unbiasnet() {
|
|
|
+ int i, j;
|
|
|
+ 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 */
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ 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[1] -= (a * (p[1] - g)) / alpharadbias;
|
|
|
+ p[2] -= (a * (p[2] - r)) / alpharadbias;
|
|
|
+ } catch (Exception e) {
|
|
|
+ } // prevents 1.3 miscompilation
|
|
|
+ }
|
|
|
+ if (k > lo) {
|
|
|
+ p = network[k--];
|
|
|
+ try {
|
|
|
+ p[0] -= (a * (p[0] - b)) / alpharadbias;
|
|
|
+ p[1] -= (a * (p[1] - g)) / alpharadbias;
|
|
|
+ p[2] -= (a * (p[2] - r)) / alpharadbias;
|
|
|
+ } catch (Exception e) {
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+ }
|
|
|
+
|
|
|
+ protected void altersingle(int alpha, int i, int b, int g, int r) {
|
|
|
+ int[] n = network[i];
|
|
|
+ n[0] -= (alpha * (n[0] - b)) / initalpha;
|
|
|
+ n[1] -= (alpha * (n[1] - g)) / initalpha;
|
|
|
+ n[2] -= (alpha * (n[2] - r)) / initalpha;
|
|
|
+ }
|
|
|
+
|
|
|
+ protected int contest(int b, int g, int r) {
|
|
|
+ int i, dist, a, biasdist, betafreq;
|
|
|
+ int bestpos, bestbiaspos, bestd, bestbiasd;
|
|
|
+ int[] n;
|
|
|
+ bestd = ~(((int) 1) << 31);
|
|
|
+ bestbiasd = bestd;
|
|
|
+ bestpos = -1;
|
|
|
+ bestbiaspos = bestpos;
|
|
|
+ for (i = 0; i < netsize; i++) {
|
|
|
+ n = network[i];
|
|
|
+ dist = n[0] - b;
|
|
|
+ if (dist < 0)
|
|
|
+ dist = -dist;
|
|
|
+ a = n[1] - g;
|
|
|
+ if (a < 0)
|
|
|
+ a = -a;
|
|
|
+ dist += a;
|
|
|
+ a = n[2] - r;
|
|
|
+ if (a < 0)
|
|
|
+ a = -a;
|
|
|
+ dist += a;
|
|
|
+ if (dist < bestd) {
|
|
|
+ bestd = dist;
|
|
|
+ bestpos = i;
|
|
|
+ }
|
|
|
+ biasdist = dist - ((bias[i]) >> (intbiasshift - netbiasshift));
|
|
|
+ if (biasdist < bestbiasd) {
|
|
|
+ bestbiasd = biasdist;
|
|
|
+ bestbiaspos = i;
|
|
|
+ }
|
|
|
+ betafreq = (freq[i] >> betashift);
|
|
|
+ freq[i] -= betafreq;
|
|
|
+ bias[i] += (betafreq << gammashift);
|
|
|
+ }
|
|
|
+ freq[bestpos] += beta;
|
|
|
+ bias[bestpos] -= betagamma;
|
|
|
+ return (bestbiaspos);
|
|
|
+ }
|
|
|
}
|