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/*
* Copyright (C) 2003, 2004 Jason Bevins (original libnoise code)
* Copyright 2010 Thomas J. Hodge (java port of libnoise)
*
* This file is part of libnoiseforjava.
*
* libnoiseforjava is a Java port of the C++ library libnoise, which may be found at
* http://libnoise.sourceforge.net/. libnoise was developed by Jason Bevins, who may be
* contacted at jlbezigvins@gmzigail.com (for great email, take off every 'zig').
* Porting to Java was done by Thomas Hodge, who may be contacted at
* libnoisezagforjava@gzagmail.com (remove every 'zag').
*
* libnoiseforjava is free software: you can redistribute it and/or modify it
* under the terms of the GNU General Public License as published by the Free Software
* Foundation, either version 3 of the License, or (at your option) any later version.
*
* libnoiseforjava is distributed in the hope that it will be useful, but
* WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License along with
* libnoiseforjava. If not, see <http://www.gnu.org/licenses/>.
*
*/
package libnoiseforjava;
public class NoiseGen
{
/// Enumerates the noise quality.
public enum NoiseQuality
{
/// Generates coherent noise quickly. When a coherent-noise function with
/// this quality setting is used to generate a bump-map image, there are
/// noticeable "creasing" artifacts in the resulting image. This is
/// because the derivative of that function is discontinuous at integer
/// boundaries.
QUALITY_FAST,
/// Generates standard-quality coherent noise. When a coherent-noise
/// function with this quality setting is used to generate a bump-map
/// image, there are some minor "creasing" artifacts in the resulting
/// image. This is because the second derivative of that function is
/// discontinuous at integer boundaries.
QUALITY_STD,
/// Generates the best-quality coherent noise. When a coherent-noise
/// function with this quality setting is used to generate a bump-map
/// image, there are no "creasing" artifacts in the resulting image. This
/// is because the first and second derivatives of that function are
/// continuous at integer boundaries.
QUALITY_BEST
}
static final int X_NOISE_GEN = 1619;
static final int Y_NOISE_GEN = 31337;
static final int Z_NOISE_GEN = 6971;
static final int SEED_NOISE_GEN = 1013;
static final int SHIFT_NOISE_GEN = 8;
public static double GradientCoherentNoise3D (double x, double y, double z, int seed,
NoiseQuality noiseQuality)
{
// Create a unit-length cube aligned along an integer boundary. This cube
// surrounds the input point.
int x0 = (x > 0.0? (int)x: (int)x - 1);
int x1 = x0 + 1;
int y0 = (y > 0.0? (int)y: (int)y - 1);
int y1 = y0 + 1;
int z0 = (z > 0.0? (int)z: (int)z - 1);
int z1 = z0 + 1;
// Map the difference between the coordinates of the input value and the
// coordinates of the cube's outer-lower-left vertex onto an S-curve.
double xs = 0, ys = 0, zs = 0;
switch (noiseQuality)
{
case QUALITY_FAST:
xs = (x - (double)x0);
ys = (y - (double)y0);
zs = (z - (double)z0);
break;
case QUALITY_STD:
xs = Interp.SCurve3 (x - (double)x0);
ys = Interp.SCurve3 (y - (double)y0);
zs = Interp.SCurve3 (z - (double)z0);
break;
case QUALITY_BEST:
xs = Interp.SCurve5 (x - (double)x0);
ys = Interp.SCurve5 (y - (double)y0);
zs = Interp.SCurve5 (z - (double)z0);
break;
}
// Now calculate the noise values at each vertex of the cube. To generate
// the coherent-noise value at the input point, interpolate these eight
// noise values using the S-curve value as the interpolant (trilinear
// interpolation.)
double n0, n1, ix0, ix1, iy0, iy1;
n0 = GradientNoise3D (x, y, z, x0, y0, z0, seed);
n1 = GradientNoise3D (x, y, z, x1, y0, z0, seed);
ix0 = Interp.linearInterp (n0, n1, xs);
n0 = GradientNoise3D (x, y, z, x0, y1, z0, seed);
n1 = GradientNoise3D (x, y, z, x1, y1, z0, seed);
ix1 = Interp.linearInterp (n0, n1, xs);
iy0 = Interp.linearInterp (ix0, ix1, ys);
n0 = GradientNoise3D (x, y, z, x0, y0, z1, seed);
n1 = GradientNoise3D (x, y, z, x1, y0, z1, seed);
ix0 = Interp.linearInterp (n0, n1, xs);
n0 = GradientNoise3D (x, y, z, x0, y1, z1, seed);
n1 = GradientNoise3D (x, y, z, x1, y1, z1, seed);
ix1 = Interp.linearInterp (n0, n1, xs);
iy1 = Interp.linearInterp (ix0, ix1, ys);
return Interp.linearInterp (iy0, iy1, zs);
}
public static double GradientNoise3D (double fx, double fy, double fz, int ix,
int iy, int iz, int seed)
{
//VectorTable vectorTable = new VectorTable();
// Randomly generate a gradient vector given the integer coordinates of the
// input value. This implementation generates a random number and uses it
// as an index into a normalized-vector lookup table.
int vectorIndex = (X_NOISE_GEN * ix
+ Y_NOISE_GEN * iy
+ Z_NOISE_GEN * iz
+ SEED_NOISE_GEN * seed)
& 0xffffffff;
vectorIndex ^= (vectorIndex >> SHIFT_NOISE_GEN);
vectorIndex &= 0xff;
double xvGradient = VectorTable.getRandomVectors(vectorIndex, 0);
double yvGradient = VectorTable.getRandomVectors(vectorIndex, 1);
double zvGradient = VectorTable.getRandomVectors(vectorIndex, 2);
// array size too large when using this original, changed to above for all 3
// double zvGradient = vectorTable.getRandomVectors(vectorIndex << 2, 2);
// Set up us another vector equal to the distance between the two vectors
// passed to this function.
double xvPoint = (fx - (double)ix);
double yvPoint = (fy - (double)iy);
double zvPoint = (fz - (double)iz);
// Now compute the dot product of the gradient vector with the distance
// vector. The resulting value is gradient noise. Apply a scaling value
// so that this noise value ranges from -1.0 to 1.0.
return ((xvGradient * xvPoint)
+ (yvGradient * yvPoint)
+ (zvGradient * zvPoint)) * 2.12;
}
public static int IntValueNoise3D (int x, int y, int z, int seed)
{
// All constants are primes and must remain prime in order for this noise
// function to work correctly.
int n = (X_NOISE_GEN * x
+ Y_NOISE_GEN * y
+ Z_NOISE_GEN * z
+ SEED_NOISE_GEN * seed)
& 0x7fffffff;
n = (n >> 13) ^ n;
return (n * (n * n * 60493 + 19990303) + 1376312589) & 0x7fffffff;
}
public static double ValueCoherentNoise3D (double x, double y, double z, int seed,
NoiseQuality noiseQuality)
{
// Create a unit-length cube aligned along an integer boundary. This cube
// surrounds the input point.
int x0 = (x > 0.0? (int)x: (int)x - 1);
int x1 = x0 + 1;
int y0 = (y > 0.0? (int)y: (int)y - 1);
int y1 = y0 + 1;
int z0 = (z > 0.0? (int)z: (int)z - 1);
int z1 = z0 + 1;
// Map the difference between the coordinates of the input value and the
// coordinates of the cube's outer-lower-left vertex onto an S-curve.
double xs = 0, ys = 0, zs = 0;
switch (noiseQuality)
{
case QUALITY_FAST:
xs = (x - (double)x0);
ys = (y - (double)y0);
zs = (z - (double)z0);
break;
case QUALITY_STD:
xs = Interp.SCurve3 (x - (double)x0);
ys = Interp.SCurve3 (y - (double)y0);
zs = Interp.SCurve3 (z - (double)z0);
break;
case QUALITY_BEST:
xs = Interp.SCurve5 (x - (double)x0);
ys = Interp.SCurve5 (y - (double)y0);
zs = Interp.SCurve5 (z - (double)z0);
break;
}
// Now calculate the noise values at each vertex of the cube. To generate
// the coherent-noise value at the input point, interpolate these eight
// noise values using the S-curve value as the interpolant (trilinear
// interpolation.)
double n0, n1, ix0, ix1, iy0, iy1;
n0 = ValueNoise3D (x0, y0, z0, seed);
n1 = ValueNoise3D (x1, y0, z0, seed);
ix0 = Interp.linearInterp (n0, n1, xs);
n0 = ValueNoise3D (x0, y1, z0, seed);
n1 = ValueNoise3D (x1, y1, z0, seed);
ix1 = Interp.linearInterp (n0, n1, xs);
iy0 = Interp.linearInterp (ix0, ix1, ys);
n0 = ValueNoise3D (x0, y0, z1, seed);
n1 = ValueNoise3D (x1, y0, z1, seed);
ix0 = Interp.linearInterp (n0, n1, xs);
n0 = ValueNoise3D (x0, y1, z1, seed);
n1 = ValueNoise3D (x1, y1, z1, seed);
ix1 = Interp.linearInterp (n0, n1, xs);
iy1 = Interp.linearInterp (ix0, ix1, ys);
return Interp.linearInterp (iy0, iy1, zs);
}
public static double ValueNoise3D (int x, int y, int z, int seed)
{
return 1.0 - ((double)IntValueNoise3D (x, y, z, seed) / 1073741824.0);
}
/// Modifies a floating-point value so that it can be stored in a
/// int32 variable.
///
/// @param n A floating-point number.
///
/// @returns The modified floating-point number.
///
/// This function does not modify @a n.
///
/// In libnoise, the noise-generating algorithms are all integer-based;
/// they use variables of type int32. Before calling a noise
/// function, pass the @a x, @a y, and @a z coordinates to this function to
/// ensure that these coordinates can be cast to a int32 value.
///
/// Although you could do a straight cast from double to int32, the
/// resulting value may differ between platforms. By using this function,
/// you ensure that the resulting value is identical between platforms.
public static double MakeInt32Range (double n) {
if (n >= 1073741824.0)
return (2.0 * (n % 1073741824.0)) - 1073741824.0;
else if (n <= -1073741824.0)
return (2.0 * (n % 1073741824.0)) + 1073741824.0;
else
return n;
}
}
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