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Translating simplex noise code from java to perl

by grondilu (Pilgrim)
on Mar 03, 2014 at 19:57 UTC ( #1076808=CUFP: print w/ replies, xml ) Need Help??

Hi monks,

I've been growing an interest for computer graphics lately, and most especially for proceduraly generated landscapes (the kind of stuff we can see in open-world or sandbox games). So while educating myself on this subject I learnt a few things about noise, and I learnt about the so-called Perlin noise, which was invented in the eighties or something. In 2002, Perlin improved his algorithm by using a better tesselation of space. It's called the Simplex noise and it's discussed and explained by Stefan Gustavson in this document, while providing a java implementation in public domain.

Well, I don't like java so I wanted to translate it into Perl. I've done it for the 2D dimension, and I thought it was worth sharing with you monks. I'll certainly translate the rest (3D and 4D) later. I will almost certainly write a Perl 6 version as well.

I also added a few lines to create a noise image in PGM format. Here is the result:

http://imgur.com/ArVvBvN

And here is the code (the original java code is in the __END__)

package SimplexNoise; # see __END__ for credits use strict; use warnings; my @grad3 = ( [1, 1, 0], [-1, 1, 0], [1, -1, 0], [-1, -1, 0], [1, 0, 1], [-1, 0, 1], [1, 0, -1], [-1, 0, -1], [0, 1, 1], [0, -1, 1], [0, 1, -1], [0, -1, -1], ); my @grad4 = ( [0, 1, 1, 1], [0, 1, 1, -1], [0, 1, -1, 1], [0, 1, -1, -1], [0, -1, 1, 1], [0, -1, 1, -1], [0, -1, -1, 1], [0, -1, -1, -1], [1, 0, 1, 1], [1, 0, 1, -1], [1, 0, -1, 1], [1, 0, -1, -1], [-1, 0, 1, 1], [-1, 0, 1, -1], [-1, 0, -1, 1], [-1, 0, -1, -1], [1, 1, 0, 1], [1, 1, 0, -1], [1, -1, 0, 1], [1, -1, 0, -1], [-1, 1, 0, 1], [-1, 1, 0, -1], [-1, -1, 0, 1], [-1, -1, 0, -1], [1, 1, 1, 0], [1, 1, -1, 0], [1, -1, 1, 0], [1, -1, -1, 0], [-1, 1, 1, 0], [-1, 1, -1, 0], [-1, -1, 1, 0], [-1, -1, -1, 0], ); use constant p => qw(151 160 137 91 90 15 131 13 201 95 96 53 194 233 +7 225 140 36 103 30 69 142 8 99 37 240 21 10 23 190 6 148 247 120 234 75 0 2 +6 197 62 94 252 219 203 117 35 11 32 57 177 33 88 237 149 56 87 174 20 125 136 +171 168 68 175 74 165 71 134 139 48 27 166 77 146 158 231 83 111 229 122 60 21 +1 133 230 220 105 92 41 55 46 245 40 244 102 143 54 65 25 63 161 1 216 80 73 209 + 76 132 187 208 89 18 169 200 196 135 130 116 188 159 86 164 100 109 198 173 1 +86 3 64 52 217 226 250 124 123 5 202 38 147 118 126 255 82 85 212 207 206 59 2 +27 47 16 58 17 182 189 28 42 223 183 170 213 119 248 152 2 44 154 163 70 221 15 +3 101 155 167 43 172 9 129 22 39 253 19 98 108 110 79 113 224 232 178 185 112 10 +4 218 246 97 228 251 34 242 193 238 210 144 12 191 179 162 241 81 51 145 235 249 + 14 239 107 49 192 214 31 181 199 106 157 184 84 204 176 115 121 50 45 127 4 1 +50 254 138 236 205 93 222 114 67 29 24 72 243 141 128 195 78 66 215 61 156 18 +0); use constant perm => (p, p); use constant permMod12 => map { $_ % 12 } perm; # Skewing and unskewing factors for 2, 3, and 4 dimensions use constant { F2 => 0.5 * (sqrt(3.0) - 1.0), G2 => (3.0 - sqrt(3.0)) / 6.0, F3 => 1.0 / 3.0, G3 => 1.0 / 6.0, F4 => (sqrt(5.0) - 1.0) / 4.0, G4 => (5.0 - sqrt(5.0)) / 20.0, }; sub floor { my $x = shift; my $xi = int($x); return $x < $xi ? $xi - 1 : $xi; } sub dot { my @grad = @{shift()}; my $sum = 0; $sum += $_ * shift @grad for @_; $sum; } sub noise { if (@_ == 2) { # 2D noise my ($n0, $n1, $n2); my ($xin, $yin) = @_; my $s = ($xin + $yin) * F2; my ($i, $j) = map { floor($_) } $xin + $s, $yin + $s; my $t = ($i + $j) * G2; my ($X0, $Y0) = ($i - $t, $j - $t); my ($x0, $y0) = ($xin - $X0, $yin - $Y0); my ($i1, $j1) = $x0 > $y0 ? (1, 0) : (0, 1); my ($x1, $y1) = ($x0 - $i1 + G2, $y0 - $j1 + G2); my ($x2, $y2) = ($x0 - 1 + 2 * G2, $y0 - 1 + 2 * G2); my ($ii, $jj) = ($i & 255, $j & 255); my ($gi0, $gi1, $gi2) = (permMod12)[ $ii + (perm)[$jj], $ii + $i1 + (perm)[$jj + $j1], $ii + 1 + (perm)[$jj + 1] ]; my $t0 = 0.5 - $x0 * $x0 - $y0 * $y0; if ($t0 < 0) { $n0 = 0 } else { $t0 *= $t0; $n0 = $t0 * $t0 * dot($grad3[$gi0], $x0, $y0); } my $t1 = 0.5 - $x1 * $x1 - $y1 * $y1; if ($t1 < 0) { $n1 = 0 } else { $t1 *= $t1; $n1 = $t1 * $t1 * dot($grad3[$gi1], $x1, $y1); } my $t2 = 0.5 - $x2 * $x2 - $y2 * $y2; if ($t2 < 0) { $n2 = 0 } else { $t2 *= $t2; $n2 = $t2 * $t2 * dot($grad3[$gi2], $x2, $y2); } return 70 * ($n0 + $n1 + $n2); } elsif (@_ == 3) { # 3D noise ... } elsif (@_ == 4) { # 4D noise ... } else {...} } my $N = 256; print "P2\n"; print "$N $N\n"; print "255\n"; for my $i (1 .. $N) { my $x = $i / 10; for my $j (1 .. $N) { my $y = $j / 10; my $noise = noise $x, $y; print int(($noise + 1) / 2 * 256); print $j == $N ? "\n" : ' '; } } __END__ =pod =begin java /* * A speed-improved simplex noise algorithm for 2D, 3D and 4D in J +ava. * * Based on example code by Stefan Gustavson (stegu@itn.liu.se). * Optimisations by Peter Eastman (peastman@drizzle.stanford.edu). * Better rank ordering method by Stefan Gustavson in 2012. * * This could be speeded up even further, but it's useful as it is +. * * Version 2012-03-09 * * This code was placed in the public domain by its original autho +r, * Stefan Gustavson. You may use it as you see fit, but * attribution is appreciated. * */ public class SimplexNoise { // Simplex noise in 2D, 3D and 4D private static Grad grad3[] = {new Grad(1,1,0),new Grad(-1,1,0), +new Grad(1,-1,0),new Grad(-1,-1,0), new Grad(1,0,1),new Grad(-1,0,1),new Grad(1,0,-1) +,new Grad(-1,0,-1), new Grad(0,1,1),new Grad(0,-1,1),new Grad(0,1,-1) +,new Grad(0,-1,-1)}; private static Grad grad4[]= {new Grad(0,1,1,1),new Grad(0,1,1,- +1),new Grad(0,1,-1,1),new Grad(0,1,-1,-1), new Grad(0,-1,1,1),new Grad(0,-1,1,-1),new Grad(0,-1,-1 +,1),new Grad(0,-1,-1,-1), new Grad(1,0,1,1),new Grad(1,0,1,-1),new Grad(1,0,-1,1) +,new Grad(1,0,-1,-1), new Grad(-1,0,1,1),new Grad(-1,0,1,-1),new Grad(-1,0,-1 +,1),new Grad(-1,0,-1,-1), new Grad(1,1,0,1),new Grad(1,1,0,-1),new Grad(1,-1,0,1) +,new Grad(1,-1,0,-1), new Grad(-1,1,0,1),new Grad(-1,1,0,-1),new Grad(-1,-1,0 +,1),new Grad(-1,-1,0,-1), new Grad(1,1,1,0),new Grad(1,1,-1,0),new Grad(1,-1,1,0) +,new Grad(1,-1,-1,0), new Grad(-1,1,1,0),new Grad(-1,1,-1,0),new Grad(-1,-1,1 +,0),new Grad(-1,-1,-1,0)}; private static short p[] = {151,160,137,91,90,15, 131,13,201,95,96,53,194,233,7,225,140,36,103,30,69,142,8,99,37,2 +40,21,10,23, 190, 6,148,247,120,234,75,0,26,197,62,94,252,219,203,117,35,11,3 +2,57,177,33, 88,237,149,56,87,174,20,125,136,171,168, 68,175,74,165,71,134,13 +9,48,27,166, 77,146,158,231,83,111,229,122,60,211,133,230,220,105,92,41,55,46 +,245,40,244, 102,143,54, 65,25,63,161, 1,216,80,73,209,76,132,187,208, 89,18, +169,200,196, 135,130,116,188,159,86,164,100,109,198,173,186, 3,64,52,217,226, +250,124,123, 5,202,38,147,118,126,255,82,85,212,207,206,59,227,47,16,58,17,18 +2,189,28,42, 223,183,170,213,119,248,152, 2,44,154,163, 70,221,153,101,155,16 +7, 43,172,9, 129,22,39,253, 19,98,108,110,79,113,224,232,178,185, 112,104,218 +,246,97,228, 251,34,242,193,238,210,144,12,191,179,162,241, 81,51,145,235,249 +,14,239,107, 49,192,214, 31,181,199,106,157,184, 84,204,176,115,121,50,45,127 +, 4,150,254, 138,236,205,93,222,114,67,29,24,72,243,141,128,195,78,66,215,61, +156,180}; // To remove the need for index wrapping, double the permutation + table length private static short perm[] = new short[512]; private static short permMod12[] = new short[512]; static { for(int i=0; i<512; i++) { perm[i]=p[i & 255]; permMod12[i] = (short)(perm[i] % 12); } } // Skewing and unskewing factors for 2, 3, and 4 dimensions private static final double F2 = 0.5*(Math.sqrt(3.0)-1.0); private static final double G2 = (3.0-Math.sqrt(3.0))/6.0; private static final double F3 = 1.0/3.0; private static final double G3 = 1.0/6.0; private static final double F4 = (Math.sqrt(5.0)-1.0)/4.0; private static final double G4 = (5.0-Math.sqrt(5.0))/20.0; // This method is a *lot* faster than using (int)Math.floor(x) private static int fastfloor(double x) { int xi = (int)x; return x<xi ? xi-1 : xi; } private static double dot(Grad g, double x, double y) { return g.x*x + g.y*y; } private static double dot(Grad g, double x, double y, double z) +{ return g.x*x + g.y*y + g.z*z; } private static double dot(Grad g, double x, double y, double z, +double w) { return g.x*x + g.y*y + g.z*z + g.w*w; } // 2D simplex noise public static double noise(double xin, double yin) { double n0, n1, n2; // Noise contributions from the three corners // Skew the input space to determine which simplex cell we're in double s = (xin+yin)*F2; // Hairy factor for 2D int i = fastfloor(xin+s); int j = fastfloor(yin+s); double t = (i+j)*G2; double X0 = i-t; // Unskew the cell origin back to (x,y) space double Y0 = j-t; double x0 = xin-X0; // The x,y distances from the cell origin double y0 = yin-Y0; // For the 2D case, the simplex shape is an equilateral triangle. // Determine which simplex we are in. int i1, j1; // Offsets for second (middle) corner of simplex in (i +,j) coords if(x0>y0) {i1=1; j1=0;} // lower triangle, XY order: (0,0)->(1,0)- +>(1,1) else {i1=0; j1=1;} // upper triangle, YX order: (0,0)->(0,1)- +>(1,1) // A step of (1,0) in (i,j) means a step of (1-c,-c) in (x,y), and // a step of (0,1) in (i,j) means a step of (-c,1-c) in (x,y), whe +re // c = (3-sqrt(3))/6 double x1 = x0 - i1 + G2; // Offsets for middle corner in (x,y) un +skewed coords double y1 = y0 - j1 + G2; double x2 = x0 - 1.0 + 2.0 * G2; // Offsets for last corner in (x, +y) unskewed coords double y2 = y0 - 1.0 + 2.0 * G2; // Work out the hashed gradient indices of the three simplex corne +rs int ii = i & 255; int jj = j & 255; int gi0 = permMod12[ii+perm[jj]]; int gi1 = permMod12[ii+i1+perm[jj+j1]]; int gi2 = permMod12[ii+1+perm[jj+1]]; // Calculate the contribution from the three corners double t0 = 0.5 - x0*x0-y0*y0; if(t0<0) n0 = 0.0; else { t0 *= t0; n0 = t0 * t0 * dot(grad3[gi0], x0, y0); // (x,y) of grad3 used +for 2D gradient } double t1 = 0.5 - x1*x1-y1*y1; if(t1<0) n1 = 0.0; else { t1 *= t1; n1 = t1 * t1 * dot(grad3[gi1], x1, y1); } double t2 = 0.5 - x2*x2-y2*y2; if(t2<0) n2 = 0.0; else { t2 *= t2; n2 = t2 * t2 * dot(grad3[gi2], x2, y2); } // Add contributions from each corner to get the final noise value +. // The result is scaled to return values in the interval [-1,1]. return 70.0 * (n0 + n1 + n2); } // 3D simplex noise public static double noise(double xin, double yin, double zin) { double n0, n1, n2, n3; // Noise contributions from the four corner +s // Skew the input space to determine which simplex cell we're in double s = (xin+yin+zin)*F3; // Very nice and simple skew factor f +or 3D int i = fastfloor(xin+s); int j = fastfloor(yin+s); int k = fastfloor(zin+s); double t = (i+j+k)*G3; double X0 = i-t; // Unskew the cell origin back to (x,y,z) space double Y0 = j-t; double Z0 = k-t; double x0 = xin-X0; // The x,y,z distances from the cell origin double y0 = yin-Y0; double z0 = zin-Z0; // For the 3D case, the simplex shape is a slightly irregular tetr +ahedron. // Determine which simplex we are in. int i1, j1, k1; // Offsets for second corner of simplex in (i,j,k) + coords int i2, j2, k2; // Offsets for third corner of simplex in (i,j,k) +coords if(x0>=y0) { if(y0>=z0) { i1=1; j1=0; k1=0; i2=1; j2=1; k2=0; } // X Y Z order else if(x0>=z0) { i1=1; j1=0; k1=0; i2=1; j2=0; k2=1; } // X Z + Y order else { i1=0; j1=0; k1=1; i2=1; j2=0; k2=1; } // Z X Y order } else { // x0<y0 if(y0<z0) { i1=0; j1=0; k1=1; i2=0; j2=1; k2=1; } // Z Y X order else if(x0<z0) { i1=0; j1=1; k1=0; i2=0; j2=1; k2=1; } // Y Z X +order else { i1=0; j1=1; k1=0; i2=1; j2=1; k2=0; } // Y X Z order } // A step of (1,0,0) in (i,j,k) means a step of (1-c,-c,-c) in (x, +y,z), // a step of (0,1,0) in (i,j,k) means a step of (-c,1-c,-c) in (x, +y,z), and // a step of (0,0,1) in (i,j,k) means a step of (-c,-c,1-c) in (x, +y,z), where // c = 1/6. double x1 = x0 - i1 + G3; // Offsets for second corner in (x,y,z) +coords double y1 = y0 - j1 + G3; double z1 = z0 - k1 + G3; double x2 = x0 - i2 + 2.0*G3; // Offsets for third corner in (x,y, +z) coords double y2 = y0 - j2 + 2.0*G3; double z2 = z0 - k2 + 2.0*G3; double x3 = x0 - 1.0 + 3.0*G3; // Offsets for last corner in (x,y, +z) coords double y3 = y0 - 1.0 + 3.0*G3; double z3 = z0 - 1.0 + 3.0*G3; // Work out the hashed gradient indices of the four simplex corner +s int ii = i & 255; int jj = j & 255; int kk = k & 255; int gi0 = permMod12[ii+perm[jj+perm[kk]]]; int gi1 = permMod12[ii+i1+perm[jj+j1+perm[kk+k1]]]; int gi2 = permMod12[ii+i2+perm[jj+j2+perm[kk+k2]]]; int gi3 = permMod12[ii+1+perm[jj+1+perm[kk+1]]]; // Calculate the contribution from the four corners double t0 = 0.6 - x0*x0 - y0*y0 - z0*z0; if(t0<0) n0 = 0.0; else { t0 *= t0; n0 = t0 * t0 * dot(grad3[gi0], x0, y0, z0); } double t1 = 0.6 - x1*x1 - y1*y1 - z1*z1; if(t1<0) n1 = 0.0; else { t1 *= t1; n1 = t1 * t1 * dot(grad3[gi1], x1, y1, z1); } double t2 = 0.6 - x2*x2 - y2*y2 - z2*z2; if(t2<0) n2 = 0.0; else { t2 *= t2; n2 = t2 * t2 * dot(grad3[gi2], x2, y2, z2); } double t3 = 0.6 - x3*x3 - y3*y3 - z3*z3; if(t3<0) n3 = 0.0; else { t3 *= t3; n3 = t3 * t3 * dot(grad3[gi3], x3, y3, z3); } // Add contributions from each corner to get the final noise value +. // The result is scaled to stay just inside [-1,1] return 32.0*(n0 + n1 + n2 + n3); } // 4D simplex noise, better simplex rank ordering method 2012-03 +-09 public static double noise(double x, double y, double z, double +w) { double n0, n1, n2, n3, n4; // Noise contributions from the five co +rners // Skew the (x,y,z,w) space to determine which cell of 24 simplice +s we're in double s = (x + y + z + w) * F4; // Factor for 4D skewing int i = fastfloor(x + s); int j = fastfloor(y + s); int k = fastfloor(z + s); int l = fastfloor(w + s); double t = (i + j + k + l) * G4; // Factor for 4D unskewing double X0 = i - t; // Unskew the cell origin back to (x,y,z,w) spa +ce double Y0 = j - t; double Z0 = k - t; double W0 = l - t; double x0 = x - X0; // The x,y,z,w distances from the cell origin double y0 = y - Y0; double z0 = z - Z0; double w0 = w - W0; // For the 4D case, the simplex is a 4D shape I won't even try to +describe. // To find out which of the 24 possible simplices we're in, we nee +d to // determine the magnitude ordering of x0, y0, z0 and w0. // Six pair-wise comparisons are performed between each possible p +air // of the four coordinates, and the results are used to rank the n +umbers. int rankx = 0; int ranky = 0; int rankz = 0; int rankw = 0; if(x0 > y0) rankx++; else ranky++; if(x0 > z0) rankx++; else rankz++; if(x0 > w0) rankx++; else rankw++; if(y0 > z0) ranky++; else rankz++; if(y0 > w0) ranky++; else rankw++; if(z0 > w0) rankz++; else rankw++; int i1, j1, k1, l1; // The integer offsets for the second simplex +corner int i2, j2, k2, l2; // The integer offsets for the third simplex c +orner int i3, j3, k3, l3; // The integer offsets for the fourth simplex +corner // simplex[c] is a 4-vector with the numbers 0, 1, 2 and 3 in some + order. // Many values of c will never occur, since e.g. x>y>z>w makes x<z +, y<w and x<w // impossible. Only the 24 indices which have non-zero entries mak +e any sense. // We use a thresholding to set the coordinates in turn from the l +argest magnitude. // Rank 3 denotes the largest coordinate. i1 = rankx >= 3 ? 1 : 0; j1 = ranky >= 3 ? 1 : 0; k1 = rankz >= 3 ? 1 : 0; l1 = rankw >= 3 ? 1 : 0; // Rank 2 denotes the second largest coordinate. i2 = rankx >= 2 ? 1 : 0; j2 = ranky >= 2 ? 1 : 0; k2 = rankz >= 2 ? 1 : 0; l2 = rankw >= 2 ? 1 : 0; // Rank 1 denotes the second smallest coordinate. i3 = rankx >= 1 ? 1 : 0; j3 = ranky >= 1 ? 1 : 0; k3 = rankz >= 1 ? 1 : 0; l3 = rankw >= 1 ? 1 : 0; // The fifth corner has all coordinate offsets = 1, so no need to +compute that. double x1 = x0 - i1 + G4; // Offsets for second corner in (x,y,z,w +) coords double y1 = y0 - j1 + G4; double z1 = z0 - k1 + G4; double w1 = w0 - l1 + G4; double x2 = x0 - i2 + 2.0*G4; // Offsets for third corner in (x,y, +z,w) coords double y2 = y0 - j2 + 2.0*G4; double z2 = z0 - k2 + 2.0*G4; double w2 = w0 - l2 + 2.0*G4; double x3 = x0 - i3 + 3.0*G4; // Offsets for fourth corner in (x,y +,z,w) coords double y3 = y0 - j3 + 3.0*G4; double z3 = z0 - k3 + 3.0*G4; double w3 = w0 - l3 + 3.0*G4; double x4 = x0 - 1.0 + 4.0*G4; // Offsets for last corner in (x,y, +z,w) coords double y4 = y0 - 1.0 + 4.0*G4; double z4 = z0 - 1.0 + 4.0*G4; double w4 = w0 - 1.0 + 4.0*G4; // Work out the hashed gradient indices of the five simplex corner +s int ii = i & 255; int jj = j & 255; int kk = k & 255; int ll = l & 255; int gi0 = perm[ii+perm[jj+perm[kk+perm[ll]]]] % 32; int gi1 = perm[ii+i1+perm[jj+j1+perm[kk+k1+perm[ll+l1]]]] % 32; int gi2 = perm[ii+i2+perm[jj+j2+perm[kk+k2+perm[ll+l2]]]] % 32; int gi3 = perm[ii+i3+perm[jj+j3+perm[kk+k3+perm[ll+l3]]]] % 32; int gi4 = perm[ii+1+perm[jj+1+perm[kk+1+perm[ll+1]]]] % 32; // Calculate the contribution from the five corners double t0 = 0.6 - x0*x0 - y0*y0 - z0*z0 - w0*w0; if(t0<0) n0 = 0.0; else { t0 *= t0; n0 = t0 * t0 * dot(grad4[gi0], x0, y0, z0, w0); } double t1 = 0.6 - x1*x1 - y1*y1 - z1*z1 - w1*w1; if(t1<0) n1 = 0.0; else { t1 *= t1; n1 = t1 * t1 * dot(grad4[gi1], x1, y1, z1, w1); } double t2 = 0.6 - x2*x2 - y2*y2 - z2*z2 - w2*w2; if(t2<0) n2 = 0.0; else { t2 *= t2; n2 = t2 * t2 * dot(grad4[gi2], x2, y2, z2, w2); } double t3 = 0.6 - x3*x3 - y3*y3 - z3*z3 - w3*w3; if(t3<0) n3 = 0.0; else { t3 *= t3; n3 = t3 * t3 * dot(grad4[gi3], x3, y3, z3, w3); } double t4 = 0.6 - x4*x4 - y4*y4 - z4*z4 - w4*w4; if(t4<0) n4 = 0.0; else { t4 *= t4; n4 = t4 * t4 * dot(grad4[gi4], x4, y4, z4, w4); } // Sum up and scale the result to cover the range [-1,1] return 27.0 * (n0 + n1 + n2 + n3 + n4); } // Inner class to speed upp gradient computations // (array access is a lot slower than member access) private static class Grad { double x, y, z, w; Grad(double x, double y, double z) { this.x = x; this.y = y; this.z = z; } Grad(double x, double y, double z, double w) { this.x = x; this.y = y; this.z = z; this.w = w; } } } =end java =cut

Comment on Translating simplex noise code from java to perl
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Re: Translating simplex noise code from java to perl
by zentara (Archbishop) on Mar 04, 2014 at 11:54 UTC
    Wow, all I can say is that is as beautiful as the Mona Lisa. You said you had an few lines of code, which outputs the graphic? Can you post it, please?

    I am interested in background noise, as it supposedly clears the mind as you sleep. :-)

    My quarters sounds like a rocket flying thru deep space ... always in the background. :-) Full cruising speed ahead!!


    I'm not really a human, but I play one on earth.
    Old Perl Programmer Haiku ................... flash japh

      The code which outputs the graphics is in what I posted (the part which begins with print "P2\n"). Just run it and you'll get a noise image on stdout in ASCII.

      To display it, you can use Image magick for instance.

      $ perl SimplexNoise.pm |display -
Re: Translating simplex noise code from java to perl
by SuicideJunkie (Priest) on Mar 13, 2014 at 20:59 UTC

    I've looked at this a bit, with an eye to making it handle higher dimensions, and one of the easy changes is that the F and G constants can be simplified and extended:

    Playing around with 2D noise, stacking noise on multiple scales makes for really interesting pictures. I've tacked on a BMP output function to keep it all self-contained.

    Example picture: http://imgur.com/aD6cQZ9

    Image generation and BMP saving code below:

      Finally got it all working the same as the original!

      It works at multiple dimensions, although I don't know what the magic scaling factors should be for 1 dimension or 5+

        Here's the code I wrote (as a result of the discussion in my thread: Randomly biased, random numbers.), to implement the Improved Perlin Noise algorithm. It also runs it with various scales to produce finer and finer detail:

        #! perl -slw use strict; use Data::Dump qw[ pp ]; $Data::Dump::WIDTH = 1e3; use List::Util qw[ min max ]; use GD; use constant { X => 0, Y=> 1, R => 2 }; use constant P => [ 151,160,137,91,90,15,131,13,201,95,96,53,194,233,7,225,140,36,103,30,6 +9,142, 8,99,37,240,21,10,23,190,6,148,247,120,234,75,0,26,197,62,94,252,219,2 +03,117, 35,11,32,57,177,33,88,237,149,56,87,174,20,125,136,171,168,68,175,74,1 +65,71, 134,139,48,27,166,77,146,158,231,83,111,229,122,60,211,133,230,220,105 +,92,41, 55,46,245,40,244,102,143,54,65,25,63,161,1,216,80,73,209,76,132,187,20 +8,89, 18,169,200,196,135,130,116,188,159,86,164,100,109,198,173,186,3,64,52, +217, 226,250,124,123,5,202,38,147,118,126,255,82,85,212,207,206,59,227,47,1 +6,58,17, 182,189,28,42,223,183,170,213,119,248,152,2,44,154,163,70,221,153,101, +155,167, 43,172,9,129,22,39,253,19,98,108,110,79,113,224,232,178,185,112,104,21 +8,246, 97,228,251,34,242,193,238,210,144,12,191,179,162,241,81,51,145,235,249 +,14,239, 107,49,192,214,31,181,199,106,157,184,84,204,176,115,121,50,45,127,4,1 +50,254, 138,236,205,93,222,114,67,29,24,72,243,141,128,195,78,66,215,61,156,18 +0, 151,160,137,91,90,15,131,13,201,95,96,53,194,233,7,225,140,36,103,30,6 +9,142, 8,99,37,240,21,10,23,190,6,148,247,120,234,75,0,26,197,62,94,252,219,2 +03,117, 35,11,32,57,177,33,88,237,149,56,87,174,20,125,136,171,168,68,175,74,1 +65,71, 134,139,48,27,166,77,146,158,231,83,111,229,122,60,211,133,230,220,105 +,92,41, 55,46,245,40,244,102,143,54,65,25,63,161,1,216,80,73,209,76,132,187,20 +8,89, 18,169,200,196,135,130,116,188,159,86,164,100,109,198,173,186,3,64,52, +217, 226,250,124,123,5,202,38,147,118,126,255,82,85,212,207,206,59,227,47,1 +6,58,17, 182,189,28,42,223,183,170,213,119,248,152,2,44,154,163,70,221,153,101, +155,167, 43,172,9,129,22,39,253,19,98,108,110,79,113,224,232,178,185,112,104,21 +8,246, 97,228,251,34,242,193,238,210,144,12,191,179,162,241,81,51,145,235,249 +,14,239, 107,49,192,214,31,181,199,106,157,184,84,204,176,115,121,50,45,127,4,1 +50,254, 138,236,205,93,222,114,67,29,24,72,243,141,128,195,78,66,215,61,156,18 +0, ]; sub rgb2n{ local $^W; unpack 'N', pack 'CCCC', 0, @_ } my $RED = rgb2n( 255, 0, 0 ); my $GREEN = rgb2n( 0, 255, 0 ); my $BLUE = rgb2n( 0, 0, 255 ); my $YELLOW = rgb2n( 255, 255, 0 ); my $MAGENTA = rgb2n( 255, 0, 255 ); my $CYAN = rgb2n( 0, 255, 255 ); my $WHITE = rgb2n( 255,255,255 ); sub r2pd { my( $x, $y, $cx, $cy ) = @_; return sqrt( ( $x - $cx )**2 + ( $y - $cy )**2 ); } sub fade{ $_[0]**3 * ( $_[0] * ($_[0] * 6 - 15) + 10 ) } sub lerp{ $_[1] + $_[0] * ($_[2] - $_[1]) } sub grad{ my( $hash, $x, $y, $z ) = @_; my $h = $hash & 15; my $u = $h < 8 ? $x : $y; my $v = $h < 4 ? $y : $h == 12 || $h ==14 ? $x : $z; return (( $h & 1 ) == 0 ? $u : -$u ) + (( $h & 2 ) == 0 ? $v : -$v + ); } sub noise { my( $x, $y, $z ) = @_; my $X = int( $x ) & 255; $x -= int $x; my $u = fade( $x ); my $Y = int( $y ) & 255; $y -= int $y; my $v = fade( $y ); my $Z = int( $z ) & 255; $z -= int $z; my $w = fade( $z ); my $A = P->[$X ]+$Y; my $AA = P->[$A ]+$Z; my $AB = P->[$A+1]+$Z; my $B = P->[$X+1]+$Y; my $BA = P->[$B ]+$Z; my $BB = P->[$B+1]+$Z; return lerp( $w, lerp( $v, lerp( $u, grad( P->[$AA ], $x, $y , $z ), grad( P->[$B +A ], $x-1, $y , $z ) ), lerp( $u, grad( P->[$AB ], $x, $y-1, $z ), grad( P->[$B +B ], $x-1, $y-1, $z ) ) ), lerp( $v, lerp( $u, grad( P->[$AA+1], $x, $y , $z-1 ), grad( P->[$B +A+1], $x-1, $y , $z-1 ) ), lerp( $u, grad( P->[$AB+1], $x, $y-1, $z-1 ), grad( P->[$B +B+1], $x-1, $y-1, $z-1 ) ) ) ); } our $F //= 5; our $X //= 1024; our $Y //= 512; my @pix = map[ (0) x $X ], 1 .. $Y; for my $f ( 2,3,5,7,11,13,17,19 ) { my $yoff = 0; for my $y ( 0 .. $Y-1 ) { my $xoff = 0; for my $x ( 0 .. $X-1 ) { ( $pix[$y][$x] += ( (1+noise( $xoff, $yoff, 1 )) /2 ) ) /= + 2; $xoff += 0.01 * $f; } $yoff += 0.01 * $f; } my $im = GD::Image->new( $X, $Y, 1 ); for my $y ( 0 .. $Y-1 ) { for my $x ( 0 .. $X-1 ) { $im->setPixel( $x, $y, rgb2n( ( $pix[$y][$x] * ( 512 / $f +) ) x 3 ) ); } } open PNG, '>:raw', "$0.png" or die $!; print PNG $im->png; close PNG; system "$0.png"; } print min( map min( @$_ ), @pix ); print max( map max( @$_ ), @pix );

        The next step to producing good texture maps is to pick sets of scales and combine them to produce variable textures across the surface. I never got around to that as it wasn't my goal for the code.


        With the rise and rise of 'Social' network sites: 'Computers are making people easier to use everyday'
        Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
        "Science is about questioning the status quo. Questioning authority".
        In the absence of evidence, opinion is indistinguishable from prejudice.

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