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SimplexNoise Modual for C#
By: a guest on
Mar 10th, 2012
| syntax:
C#
| size: 24.81 KB | hits: 227 | expires: Never
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Text below is selected. Please press Ctrl+C to copy to your clipboard. (⌘+C on Mac)
public
class
SimplexNoise
{
// Simplex noise in 2D, 3D and 4D
/* 2D, 3D and 4D Simplex Noise functions return 'random' values in (-1, 1).
This algorithm was originally designed by Ken Perlin, but my code has been
adapted from the implementation written by Stefan Gustavson (stegu@itn.liu.se)
Raw Simplex noise functions return the value generated by Ken's algorithm.
Scaled Raw Simplex noise functions adjust the range of values returned from the
traditional (-1, 1) to whichever bounds are passed to the function.
Multi-Octave Simplex noise functions compine multiple noise values to create a
more complex result. Each successive layer of noise is adjusted and scaled.
Scaled Multi-Octave Simplex noise functions scale the values returned from the
traditional (-1,1) range to whichever range is passed to the function.
In many cases, you may think you only need a 1D noise function, but in practice
2D is almost always better. For instance, if you're using the current frame
number as the parameter for the noise, all objects will end up with the same
noise value at each frame. By adding a second parameter on the second
dimension, you can ensure that each gets a unique noise value and they don't
all look identical.
*/
// 2D Multi-octave Simplex noise.
//
// For each octave, a higher frequency/lower amplitude function will be added to the original.
// The higher the persistence [0-1], the more of each succeeding octave will be added.
// The gradients are the midpoints of the vertices of a cube.
private
static
int
[
]
[
]
grad3
=
new
int
[
]
[
]
{
new
int
[
]
{
1
,
1
,
0
}
,
new
int
[
]
{
-
1
,
1
,
0
}
,
new
int
[
]
{
1
,
-
1
,
0
}
,
new
int
[
]
{
-
1
,
-
1
,
0
}
,
new
int
[
]
{
1
,
0
,
1
}
,
new
int
[
]
{
-
1
,
0
,
1
}
,
new
int
[
]
{
1
,
0
,
-
1
}
,
new
int
[
]
{
-
1
,
0
,
-
1
}
,
new
int
[
]
{
0
,
1
,
1
}
,
new
int
[
]
{
0
,
-
1
,
1
}
,
new
int
[
]
{
0
,
1
,
-
1
}
,
new
int
[
]
{
0
,
-
1
,
-
1
}
}
;
private
static
int
[
]
[
]
grad4
=
new
int
[
]
[
]
{
new
int
[
]
{
0
,
1
,
1
,
1
}
,
new
int
[
]
{
0
,
1
,
1
,
-
1
}
,
new
int
[
]
{
0
,
1
,
-
1
,
1
}
,
new
int
[
]
{
0
,
1
,
-
1
,
-
1
}
,
new
int
[
]
{
0
,
-
1
,
1
,
1
}
,
new
int
[
]
{
0
,
-
1
,
1
,
-
1
}
,
new
int
[
]
{
0
,
-
1
,
-
1
,
1
}
,
new
int
[
]
{
0
,
-
1
,
-
1
,
-
1
}
,
new
int
[
]
{
1
,
0
,
1
,
1
}
,
new
int
[
]
{
1
,
0
,
1
,
-
1
}
,
new
int
[
]
{
1
,
0
,
-
1
,
1
}
,
new
int
[
]
{
1
,
0
,
-
1
,
-
1
}
,
new
int
[
]
{
-
1
,
0
,
1
,
1
}
,
new
int
[
]
{
-
1
,
0
,
1
,
-
1
}
,
new
int
[
]
{
-
1
,
0
,
-
1
,
1
}
,
new
int
[
]
{
-
1
,
0
,
-
1
,
-
1
}
,
new
int
[
]
{
1
,
1
,
0
,
1
}
,
new
int
[
]
{
1
,
1
,
0
,
-
1
}
,
new
int
[
]
{
1
,
-
1
,
0
,
1
}
,
new
int
[
]
{
1
,
-
1
,
0
,
-
1
}
,
new
int
[
]
{
-
1
,
1
,
0
,
1
}
,
new
int
[
]
{
-
1
,
1
,
0
,
-
1
}
,
new
int
[
]
{
-
1
,
-
1
,
0
,
1
}
,
new
int
[
]
{
-
1
,
-
1
,
0
,
-
1
}
,
new
int
[
]
{
1
,
1
,
1
,
0
}
,
new
int
[
]
{
1
,
1
,
-
1
,
0
}
,
new
int
[
]
{
1
,
-
1
,
1
,
0
}
,
new
int
[
]
{
1
,
-
1
,
-
1
,
0
}
,
new
int
[
]
{
-
1
,
1
,
1
,
0
}
,
new
int
[
]
{
-
1
,
1
,
-
1
,
0
}
,
new
int
[
]
{
-
1
,
-
1
,
1
,
0
}
,
new
int
[
]
{
-
1
,
-
1
,
-
1
,
0
}
}
;
private
static
int
[
]
p
=
new
int
[
]
{
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
,
26
,
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
,
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
,
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
,
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
int
[
]
perm
=
new
int
[
512
]
;
// A lookup table to traverse the simplex around a given point in 4D.
// Details can be found where this table is used, in the 4D noise method.
private
static
int
[
,
]
simplex
=
new
int
[
,
]
{
{
0
,
1
,
2
,
3
}
,
{
0
,
1
,
3
,
2
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
2
,
3
,
1
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
1
,
2
,
3
,
0
}
,
{
0
,
2
,
1
,
3
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
3
,
1
,
2
}
,
{
0
,
3
,
2
,
1
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
1
,
3
,
2
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
1
,
2
,
0
,
3
}
,
{
0
,
0
,
0
,
0
}
,
{
1
,
3
,
0
,
2
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
2
,
3
,
0
,
1
}
,
{
2
,
3
,
1
,
0
}
,
{
1
,
0
,
2
,
3
}
,
{
1
,
0
,
3
,
2
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
2
,
0
,
3
,
1
}
,
{
0
,
0
,
0
,
0
}
,
{
2
,
1
,
3
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
2
,
0
,
1
,
3
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
3
,
0
,
1
,
2
}
,
{
3
,
0
,
2
,
1
}
,
{
0
,
0
,
0
,
0
}
,
{
3
,
1
,
2
,
0
}
,
{
2
,
1
,
0
,
3
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
0
,
0
,
0
,
0
}
,
{
3
,
1
,
0
,
2
}
,
{
0
,
0
,
0
,
0
}
,
{
3
,
2
,
0
,
1
}
,
{
3
,
2
,
1
,
0
}
}
;
public
float
octave_noise_2d
(
float
octaves,
float
persistence,
float
scale,
float
x,
float
y
)
{
float
total
=
0
;
float
frequency
=
scale
;
float
amplitude
=
1
;
// We have to keep track of the largest possible amplitude,
// because each octave adds more, and we need a value in [-1, 1].
float
maxAmplitude
=
0
;
for
(
int
i
=
0
;
i
<
octaves
;
i
++
)
{
total
+=
raw_noise_2d
(
x
*
frequency, y
*
frequency
)
*
amplitude
;
frequency
*=
2
;
maxAmplitude
+=
amplitude
;
amplitude
*=
persistence
;
}
return
total
/
maxAmplitude
;
}
// 3D Multi-octave Simplex noise.
//
// For each octave, a higher frequency/lower amplitude function will be added to the original.
// The higher the persistence [0-1], the more of each succeeding octave will be added.
public
float
octave_noise_3d
(
float
octaves,
float
persistence,
float
scale,
float
x,
float
y,
float
z
)
{
float
total
=
0
;
float
frequency
=
scale
;
float
amplitude
=
1
;
// We have to keep track of the largest possible amplitude,
// because each octave adds more, and we need a value in [-1, 1].
float
maxAmplitude
=
0
;
for
(
int
i
=
0
;
i
<
octaves
;
i
++
)
{
total
+=
raw_noise_3d
(
x
*
frequency, y
*
frequency, z
*
frequency
)
*
amplitude
;
frequency
*=
2
;
maxAmplitude
+=
amplitude
;
amplitude
*=
persistence
;
}
return
total
/
maxAmplitude
;
}
// 4D Multi-octave Simplex noise.
//
// For each octave, a higher frequency/lower amplitude function will be added to the original.
// The higher the persistence [0-1], the more of each succeeding octave will be added.
public
float
octave_noise_4d
(
float
octaves,
float
persistence,
float
scale,
float
x,
float
y,
float
z,
float
w
)
{
float
total
=
0
;
float
frequency
=
scale
;
float
amplitude
=
1
;
// We have to keep track of the largest possible amplitude,
// because each octave adds more, and we need a value in [-1, 1].
float
maxAmplitude
=
0
;
for
(
int
i
=
0
;
i
<
octaves
;
i
++
)
{
total
+=
raw_noise_4d
(
x
*
frequency, y
*
frequency, z
*
frequency, w
*
frequency
)
*
amplitude
;
frequency
*=
2
;
maxAmplitude
+=
amplitude
;
amplitude
*=
persistence
;
}
return
total
/
maxAmplitude
;
}
// 2D Scaled Multi-octave Simplex noise.
//
// Returned value will be between loBound and hiBound.
public
float
scaled_octave_noise_2d
(
float
octaves,
float
persistence,
float
scale,
float
loBound,
float
hiBound,
float
x,
float
y
)
{
return
octave_noise_2d
(
octaves, persistence, scale, x, y
)
*
(
hiBound
-
loBound
)
/
2
+
(
hiBound
+
loBound
)
/
2
;
}
// 3D Scaled Multi-octave Simplex noise.
//
// Returned value will be between loBound and hiBound.
public
float
scaled_octave_noise_3d
(
float
octaves,
float
persistence,
float
scale,
float
loBound,
float
hiBound,
float
x,
float
y,
float
z
)
{
return
octave_noise_3d
(
octaves, persistence, scale, x, y, z
)
*
(
hiBound
-
loBound
)
/
2
+
(
hiBound
+
loBound
)
/
2
;
}
// 4D Scaled Multi-octave Simplex noise.
//
// Returned value will be between loBound and hiBound.
public
float
scaled_octave_noise_4d
(
float
octaves,
float
persistence,
float
scale,
float
loBound,
float
hiBound,
float
x,
float
y,
float
z,
float
w
)
{
return
octave_noise_4d
(
octaves, persistence, scale, x, y, z, w
)
*
(
hiBound
-
loBound
)
/
2
+
(
hiBound
+
loBound
)
/
2
;
}
// 2D Scaled Simplex raw noise.
//
// Returned value will be between loBound and hiBound.
public
float
scaled_raw_noise_2d
(
float
loBound,
float
hiBound,
float
x,
float
y
)
{
return
raw_noise_2d
(
x, y
)
*
(
hiBound
-
loBound
)
/
2
+
(
hiBound
+
loBound
)
/
2
;
}
// 3D Scaled Simplex raw noise.
//
// Returned value will be between loBound and hiBound.
public
float
scaled_raw_noise_3d
(
float
loBound,
float
hiBound,
float
x,
float
y,
float
z
)
{
return
raw_noise_3d
(
x, y, z
)
*
(
hiBound
-
loBound
)
/
2
+
(
hiBound
+
loBound
)
/
2
;
}
// 4D Scaled Simplex raw noise.
//
// Returned value will be between loBound and hiBound.
public
float
scaled_raw_noise_4d
(
float
loBound,
float
hiBound,
float
x,
float
y,
float
z,
float
w
)
{
return
raw_noise_4d
(
x, y, z, w
)
*
(
hiBound
-
loBound
)
/
2
+
(
hiBound
+
loBound
)
/
2
;
}
// 2D raw Simplex noise
public
float
raw_noise_2d
(
float
x,
float
y
)
{
// Noise contributions from the three corners
float
n0, n1, n2
;
// Skew the input space to determine which simplex cell we're in
float
F2
=
0
.
5f
*
(
(
float
)
Math
.
Sqrt
(
3
.
0f
)
-
1
.
0f
)
;
// Hairy factor for 2D
float
s
=
(
x
+
y
)
*
F2
;
int
i
=
fastfloor
(
x
+
s
)
;
int
j
=
fastfloor
(
y
+
s
)
;
float
G2
=
(
3
.
0f
-
(
float
)
Math
.
Sqrt
(
3
.
0f
)
)
/
6
.
0f
;
float
t
=
(
i
+
j
)
*
G2
;
// Unskew the cell origin back to (x,y) space
float
X0
=
i
-
t
;
float
Y0
=
j
-
t
;
// The x,y distances from the cell origin
float
x0
=
x
-
X0
;
float
y0
=
y
-
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), where
// c = (3-sqrt(3))/6
float
x1
=
x0
-
i1
+
G2
;
// Offsets for middle corner in (x,y) unskewed coords
float
y1
=
y0
-
j1
+
G2
;
float
x2
=
x0
-
1
.
0f
+
2
.
0f
*
G2
;
// Offsets for last corner in (x,y) unskewed coords
float
y2
=
y0
-
1
.
0f
+
2
.
0f
*
G2
;
// Work out the hashed gradient indices of the three simplex corners
int
ii
=
i
&
255
;
int
jj
=
j
&
255
;
int
gi0
=
perm
[
ii
+
perm
[
jj
]
]
%
12
;
int
gi1
=
perm
[
ii
+
i1
+
perm
[
jj
+
j1
]
]
%
12
;
int
gi2
=
perm
[
ii
+
1
+
perm
[
jj
+
1
]
]
%
12
;
// Calculate the contribution from the three corners
float
t0
=
0
.
5f
-
x0
*
x0
-
y0
*
y0
;
if
(
t0
<
0
)
n0
=
0
.
0f
;
else
{
t0
*=
t0
;
n0
=
t0
*
t0
*
dot
(
grad3
[
gi0
]
, x0, y0
)
;
// (x,y) of grad3 used for 2D gradient
}
float
t1
=
0
.
5f
-
x1
*
x1
-
y1
*
y1
;
if
(
t1
<
0
)
n1
=
0
.
0f
;
else
{
t1
*=
t1
;
n1
=
t1
*
t1
*
dot
(
grad3
[
gi1
]
, x1, y1
)
;
}
float
t2
=
0
.
5f
-
x2
*
x2
-
y2
*
y2
;
if
(
t2
<
0
)
n2
=
0
.
0f
;
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
.
0f
*
(
n0
+
n1
+
n2
)
;
}
// 3D raw Simplex noise
public
float
raw_noise_3d
(
float
x,
float
y,
float
z
)
{
float
n0, n1, n2, n3
;
// Noise contributions from the four corners
// Skew the input space to determine which simplex cell we're in
float
F3
=
1
.
0f
/
3
.
0f
;
float
s
=
(
x
+
y
+
z
)
*
F3
;
// Very nice and simple skew factor for 3D
int
i
=
fastfloor
(
x
+
s
)
;
int
j
=
fastfloor
(
y
+
s
)
;
int
k
=
fastfloor
(
z
+
s
)
;
float
G3
=
1
.
0f
/
6
.
0f
;
// Very nice and simple unskew factor, too
float
t
=
(
i
+
j
+
k
)
*
G3
;
float
X0
=
i
-
t
;
// Unskew the cell origin back to (x,y,z) space
float
Y0
=
j
-
t
;
float
Z0
=
k
-
t
;
float
x0
=
x
-
X0
;
// The x,y,z distances from the cell origin
float
y0
=
y
-
Y0
;
float
z0
=
z
-
Z0
;
// For the 3D case, the simplex shape is a slightly irregular tetrahedron.
// 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.
float
x1
=
x0
-
i1
+
G3
;
// Offsets for second corner in (x,y,z) coords
float
y1
=
y0
-
j1
+
G3
;
float
z1
=
z0
-
k1
+
G3
;
float
x2
=
x0
-
i2
+
2
.
0f
*
G3
;
// Offsets for third corner in (x,y,z) coords
float
y2
=
y0
-
j2
+
2
.
0f
*
G3
;
float
z2
=
z0
-
k2
+
2
.
0f
*
G3
;
float
x3
=
x0
-
1
.
0f
+
3
.
0f
*
G3
;
// Offsets for last corner in (x,y,z) coords
float
y3
=
y0
-
1
.
0f
+
3
.
0f
*
G3
;
float
z3
=
z0
-
1
.
0f
+
3
.
0f
*
G3
;
// Work out the hashed gradient indices of the four simplex corners
int
ii
=
i
&
255
;
int
jj
=
j
&
255
;
int
kk
=
k
&
255
;
int
gi0
=
perm
[
ii
+
perm
[
jj
+
perm
[
kk
]
]
]
%
12
;
int
gi1
=
perm
[
ii
+
i1
+
perm
[
jj
+
j1
+
perm
[
kk
+
k1
]
]
]
%
12
;
int
gi2
=
perm
[
ii
+
i2
+
perm
[
jj
+
j2
+
perm
[
kk
+
k2
]
]
]
%
12
;
int
gi3
=
perm
[
ii
+
1
+
perm
[
jj
+
1
+
perm
[
kk
+
1
]
]
]
%
12
;
// Calculate the contribution from the four corners
float
t0
=
0
.
6f
-
x0
*
x0
-
y0
*
y0
-
z0
*
z0
;
if
(
t0
<
0
)
n0
=
0
.
0f
;
else
{
t0
*=
t0
;
n0
=
t0
*
t0
*
dot
(
grad3
[
gi0
]
, x0, y0, z0
)
;
}
float
t1
=
0
.
6f
-
x1
*
x1
-
y1
*
y1
-
z1
*
z1
;
if
(
t1
<
0
)
n1
=
0
.
0f
;
else
{
t1
*=
t1
;
n1
=
t1
*
t1
*
dot
(
grad3
[
gi1
]
, x1, y1, z1
)
;
}
float
t2
=
0
.
6f
-
x2
*
x2
-
y2
*
y2
-
z2
*
z2
;
if
(
t2
<
0
)
n2
=
0
.
0f
;
else
{
t2
*=
t2
;
n2
=
t2
*
t2
*
dot
(
grad3
[
gi2
]
, x2, y2, z2
)
;
}
float
t3
=
0
.
6f
-
x3
*
x3
-
y3
*
y3
-
z3
*
z3
;
if
(
t3
<
0
)
n3
=
0
.
0f
;
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
.
0f
*
(
n0
+
n1
+
n2
+
n3
)
;
}
// 4D raw Simplex noise
public
float
raw_noise_4d
(
float
x,
float
y,
float
z,
float
w
)
{
// The skewing and unskewing factors are hairy again for the 4D case
float
F4
=
(
(
float
)
Math
.
Sqrt
(
5
.
0f
)
-
1
.
0f
)
/
4
.
0f
;
float
G4
=
(
5
.
0f
-
(
float
)
Math
.
Sqrt
(
5
.
0f
)
)
/
20
.
0f
;
float
n0, n1, n2, n3, n4
;
// Noise contributions from the five corners
// Skew the (x,y,z,w) space to determine which cell of 24 simplices we're in
float
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
)
;
float
t
=
(
i
+
j
+
k
+
l
)
*
G4
;
// Factor for 4D unskewing
float
X0
=
i
-
t
;
// Unskew the cell origin back to (x,y,z,w) space
float
Y0
=
j
-
t
;
float
Z0
=
k
-
t
;
float
W0
=
l
-
t
;
float
x0
=
x
-
X0
;
// The x,y,z,w distances from the cell origin
float
y0
=
y
-
Y0
;
float
z0
=
z
-
Z0
;
float
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 need to
// determine the magnitude ordering of x0, y0, z0 and w0.
// The method below is a good way of finding the ordering of x,y,z,w and
// then find the correct traversal order for the simplex we're in.
// First, six pair-wise comparisons are performed between each possible pair
// of the four coordinates, and the results are used to add up binary bits
// for an integer index.
int
c1
=
(
x0
>
y0
)
?
32
:
0
;
int
c2
=
(
x0
>
z0
)
?
16
:
0
;
int
c3
=
(
y0
>
z0
)
?
8
:
0
;
int
c4
=
(
x0
>
w0
)
?
4
:
0
;
int
c5
=
(
y0
>
w0
)
?
2
:
0
;
int
c6
=
(
z0
>
w0
)
?
1
:
0
;
int
c
=
c1
+
c2
+
c3
+
c4
+
c5
+
c6
;
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 corner
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 make any sense.
// We use a thresholding to set the coordinates in turn from the largest magnitude.
// The number 3 in the "simplex" array is at the position of the largest coordinate.
i1
=
simplex
[
c,
0
]
>=
3
?
1
:
0
;
j1
=
simplex
[
c,
1
]
>=
3
?
1
:
0
;
k1
=
simplex
[
c,
2
]
>=
3
?
1
:
0
;
l1
=
simplex
[
c,
3
]
>=
3
?
1
:
0
;
// The number 2 in the "simplex" array is at the second largest coordinate.
i2
=
simplex
[
c,
0
]
>=
2
?
1
:
0
;
j2
=
simplex
[
c,
1
]
>=
2
?
1
:
0
;
k2
=
simplex
[
c,
2
]
>=
2
?
1
:
0
;
l2
=
simplex
[
c,
3
]
>=
2
?
1
:
0
;
// The number 1 in the "simplex" array is at the second smallest coordinate.
i3
=
simplex
[
c,
0
]
>=
1
?
1
:
0
;
j3
=
simplex
[
c,
1
]
>=
1
?
1
:
0
;
k3
=
simplex
[
c,
2
]
>=
1
?
1
:
0
;
l3
=
simplex
[
c,
3
]
>=
1
?
1
:
0
;
// The fifth corner has all coordinate offsets = 1, so no need to look that up.
float
x1
=
x0
-
i1
+
G4
;
// Offsets for second corner in (x,y,z,w) coords
float
y1
=
y0
-
j1
+
G4
;
float
z1
=
z0
-
k1
+
G4
;
float
w1
=
w0
-
l1
+
G4
;
float
x2
=
x0
-
i2
+
2
.
0f
*
G4
;
// Offsets for third corner in (x,y,z,w) coords
float
y2
=
y0
-
j2
+
2
.
0f
*
G4
;
float
z2
=
z0
-
k2
+
2
.
0f
*
G4
;
float
w2
=
w0
-
l2
+
2
.
0f
*
G4
;
float
x3
=
x0
-
i3
+
3
.
0f
*
G4
;
// Offsets for fourth corner in (x,y,z,w) coords
float
y3
=
y0
-
j3
+
3
.
0f
*
G4
;
float
z3
=
z0
-
k3
+
3
.
0f
*
G4
;
float
w3
=
w0
-
l3
+
3
.
0f
*
G4
;
float
x4
=
x0
-
1
.
0f
+
4
.
0f
*
G4
;
// Offsets for last corner in (x,y,z,w) coords
float
y4
=
y0
-
1
.
0f
+
4
.
0f
*
G4
;
float
z4
=
z0
-
1
.
0f
+
4
.
0f
*
G4
;
float
w4
=
w0
-
1
.
0f
+
4
.
0f
*
G4
;
// Work out the hashed gradient indices of the five simplex corners
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
float
t0
=
0
.
6f
-
x0
*
x0
-
y0
*
y0
-
z0
*
z0
-
w0
*
w0
;
if
(
t0
<
0
)
n0
=
0
.
0f
;
else
{
t0
*=
t0
;
n0
=
t0
*
t0
*
dot
(
grad4
[
gi0
]
, x0, y0, z0, w0
)
;
}
float
t1
=
0
.
6f
-
x1
*
x1
-
y1
*
y1
-
z1
*
z1
-
w1
*
w1
;
if
(
t1
<
0
)
n1
=
0
.
0f
;
else
{
t1
*=
t1
;
n1
=
t1
*
t1
*
dot
(
grad4
[
gi1
]
, x1, y1, z1, w1
)
;
}
float
t2
=
0
.
6f
-
x2
*
x2
-
y2
*
y2
-
z2
*
z2
-
w2
*
w2
;
if
(
t2
<
0
)
n2
=
0
.
0f
;
else
{
t2
*=
t2
;
n2
=
t2
*
t2
*
dot
(
grad4
[
gi2
]
, x2, y2, z2, w2
)
;
}
float
t3
=
0
.
6f
-
x3
*
x3
-
y3
*
y3
-
z3
*
z3
-
w3
*
w3
;
if
(
t3
<
0
)
n3
=
0
.
0f
;
else
{
t3
*=
t3
;
n3
=
t3
*
t3
*
dot
(
grad4
[
gi3
]
, x3, y3, z3, w3
)
;
}
float
t4
=
0
.
6f
-
x4
*
x4
-
y4
*
y4
-
z4
*
z4
-
w4
*
w4
;
if
(
t4
<
0
)
n4
=
0
.
0f
;
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
.
0f
*
(
n0
+
n1
+
n2
+
n3
+
n4
)
;
}
int
fastfloor
(
float
x
)
{
return
x
>
0
?
(
int
)
x
:
(
int
)
x
-
1
;
}
unsafe
float
dot
(
int
[
]
g,
float
x,
float
y
)
{
return
g
[
0
]
*
x
+
g
[
1
]
*
y
;
}
unsafe
float
dot
(
int
[
]
g,
float
x,
float
y,
float
z
)
{
return
g
[
0
]
*
x
+
g
[
1
]
*
y
+
g
[
2
]
*
z
;
}
unsafe
float
dot
(
int
[
]
g,
float
x,
float
y,
float
z,
float
w
)
{
return
g
[
0
]
*
x
+
g
[
1
]
*
y
+
g
[
2
]
*
z
+
g
[
3
]
*
w
;
}
}
create a
new version
of this paste
RAW Paste Data
public class SimplexNoise { // Simplex noise in 2D, 3D and 4D /* 2D, 3D and 4D Simplex Noise functions return 'random' values in (-1, 1). This algorithm was originally designed by Ken Perlin, but my code has been adapted from the implementation written by Stefan Gustavson (stegu@itn.liu.se) Raw Simplex noise functions return the value generated by Ken's algorithm. Scaled Raw Simplex noise functions adjust the range of values returned from the traditional (-1, 1) to whichever bounds are passed to the function. Multi-Octave Simplex noise functions compine multiple noise values to create a more complex result. Each successive layer of noise is adjusted and scaled. Scaled Multi-Octave Simplex noise functions scale the values returned from the traditional (-1,1) range to whichever range is passed to the function. In many cases, you may think you only need a 1D noise function, but in practice 2D is almost always better. For instance, if you're using the current frame number as the parameter for the noise, all objects will end up with the same noise value at each frame. By adding a second parameter on the second dimension, you can ensure that each gets a unique noise value and they don't all look identical. */ // 2D Multi-octave Simplex noise. // // For each octave, a higher frequency/lower amplitude function will be added to the original. // The higher the persistence [0-1], the more of each succeeding octave will be added. // The gradients are the midpoints of the vertices of a cube. private static int[][] grad3 = new int[][] { new int[] {1,1,0}, new int[] {-1,1,0}, new int[] {1,-1,0}, new int[] {-1,-1,0}, new int[] {1,0,1}, new int[] {-1,0,1}, new int[] {1,0,-1}, new int[] {-1,0,-1}, new int[] {0,1,1}, new int[] {0,-1,1}, new int[] {0,1,-1}, new int[] {0,-1,-1}}; private static int[][] grad4 = new int[][] {new int[] {0,1,1,1}, new int[] {0,1,1,-1}, new int[] {0,1,-1,1}, new int[] {0,1,-1,-1}, new int[] {0,-1,1,1}, new int[] {0,-1,1,-1}, new int[] {0,-1,-1,1}, new int[] {0,-1,-1,-1}, new int[] {1,0,1,1}, new int[] {1,0,1,-1}, new int[] {1,0,-1,1}, new int[] {1,0,-1,-1}, new int[] {-1,0,1,1}, new int[] {-1,0,1,-1}, new int[] {-1,0,-1,1}, new int[] {-1,0,-1,-1}, new int[] {1,1,0,1}, new int[] {1,1,0,-1}, new int[] {1,-1,0,1}, new int[] {1,-1,0,-1}, new int[] {-1,1,0,1}, new int[] {-1,1,0,-1}, new int[] {-1,-1,0,1}, new int[] {-1,-1,0,-1}, new int[] {1,1,1,0}, new int[] {1,1,-1,0}, new int[] {1,-1,1,0}, new int[] {1,-1,-1,0}, new int[] {-1,1,1,0}, new int[] {-1,1,-1,0}, new int[] {-1,-1,1,0}, new int[] {-1,-1,-1,0}}; private static int[] p = new int[] {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, 6,148,247,120,234,75,0,26,197,62,94,252,219,203,117,35,11,32,57,177,33, 88,237,149,56,87,174,20,125,136,171,168, 68,175,74,165,71,134,139,48,27,166, 77,146,158,231,83,111,229,122,60,211,133,230,220,105,92,41,55,46,245,40,244, 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, 5,202,38,147,118,126,255,82,85,212,207,206,59,227,47,16,58,17,182,189,28,42, 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, 112,104,218,246,97,228, 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 int[] perm = new int[512]; // A lookup table to traverse the simplex around a given point in 4D. // Details can be found where this table is used, in the 4D noise method. private static int[,] simplex = new int[,] {{0,1,2,3},{0,1,3,2},{0,0,0,0},{0,2,3,1},{0,0,0,0},{0,0,0,0},{0,0,0,0},{1,2,3,0}, {0,2,1,3},{0,0,0,0},{0,3,1,2},{0,3,2,1},{0,0,0,0},{0,0,0,0},{0,0,0,0},{1,3,2,0}, {0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0}, {1,2,0,3},{0,0,0,0},{1,3,0,2},{0,0,0,0},{0,0,0,0},{0,0,0,0},{2,3,0,1},{2,3,1,0}, {1,0,2,3},{1,0,3,2},{0,0,0,0},{0,0,0,0},{0,0,0,0},{2,0,3,1},{0,0,0,0},{2,1,3,0}, {0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0},{0,0,0,0}, {2,0,1,3},{0,0,0,0},{0,0,0,0},{0,0,0,0},{3,0,1,2},{3,0,2,1},{0,0,0,0},{3,1,2,0}, {2,1,0,3},{0,0,0,0},{0,0,0,0},{0,0,0,0},{3,1,0,2},{0,0,0,0},{3,2,0,1},{3,2,1,0}}; public float octave_noise_2d(float octaves, float persistence, float scale, float x, float y) { float total = 0; float frequency = scale; float amplitude = 1; // We have to keep track of the largest possible amplitude, // because each octave adds more, and we need a value in [-1, 1]. float maxAmplitude = 0; for (int i = 0; i < octaves; i++) { total += raw_noise_2d(x * frequency, y * frequency) * amplitude; frequency *= 2; maxAmplitude += amplitude; amplitude *= persistence; } return total / maxAmplitude; } // 3D Multi-octave Simplex noise. // // For each octave, a higher frequency/lower amplitude function will be added to the original. // The higher the persistence [0-1], the more of each succeeding octave will be added. public float octave_noise_3d(float octaves, float persistence, float scale, float x, float y, float z) { float total = 0; float frequency = scale; float amplitude = 1; // We have to keep track of the largest possible amplitude, // because each octave adds more, and we need a value in [-1, 1]. float maxAmplitude = 0; for (int i = 0; i < octaves; i++) { total += raw_noise_3d(x * frequency, y * frequency, z * frequency) * amplitude; frequency *= 2; maxAmplitude += amplitude; amplitude *= persistence; } return total / maxAmplitude; } // 4D Multi-octave Simplex noise. // // For each octave, a higher frequency/lower amplitude function will be added to the original. // The higher the persistence [0-1], the more of each succeeding octave will be added. public float octave_noise_4d(float octaves, float persistence, float scale, float x, float y, float z, float w) { float total = 0; float frequency = scale; float amplitude = 1; // We have to keep track of the largest possible amplitude, // because each octave adds more, and we need a value in [-1, 1]. float maxAmplitude = 0; for (int i = 0; i < octaves; i++) { total += raw_noise_4d(x * frequency, y * frequency, z * frequency, w * frequency) * amplitude; frequency *= 2; maxAmplitude += amplitude; amplitude *= persistence; } return total / maxAmplitude; } // 2D Scaled Multi-octave Simplex noise. // // Returned value will be between loBound and hiBound. public float scaled_octave_noise_2d(float octaves, float persistence, float scale, float loBound, float hiBound, float x, float y) { return octave_noise_2d(octaves, persistence, scale, x, y) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 3D Scaled Multi-octave Simplex noise. // // Returned value will be between loBound and hiBound. public float scaled_octave_noise_3d(float octaves, float persistence, float scale, float loBound, float hiBound, float x, float y, float z) { return octave_noise_3d(octaves, persistence, scale, x, y, z) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 4D Scaled Multi-octave Simplex noise. // // Returned value will be between loBound and hiBound. public float scaled_octave_noise_4d(float octaves, float persistence, float scale, float loBound, float hiBound, float x, float y, float z, float w) { return octave_noise_4d(octaves, persistence, scale, x, y, z, w) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 2D Scaled Simplex raw noise. // // Returned value will be between loBound and hiBound. public float scaled_raw_noise_2d(float loBound, float hiBound, float x, float y) { return raw_noise_2d(x, y) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 3D Scaled Simplex raw noise. // // Returned value will be between loBound and hiBound. public float scaled_raw_noise_3d(float loBound, float hiBound, float x, float y, float z) { return raw_noise_3d(x, y, z) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 4D Scaled Simplex raw noise. // // Returned value will be between loBound and hiBound. public float scaled_raw_noise_4d(float loBound, float hiBound, float x, float y, float z, float w) { return raw_noise_4d(x, y, z, w) * (hiBound - loBound) / 2 + (hiBound + loBound) / 2; } // 2D raw Simplex noise public float raw_noise_2d(float x, float y) { // Noise contributions from the three corners float n0, n1, n2; // Skew the input space to determine which simplex cell we're in float F2 = 0.5f * ((float)Math.Sqrt(3.0f) - 1.0f); // Hairy factor for 2D float s = (x + y) * F2; int i = fastfloor(x + s); int j = fastfloor(y + s); float G2 = (3.0f - (float)Math.Sqrt(3.0f)) / 6.0f; float t = (i + j) * G2; // Unskew the cell origin back to (x,y) space float X0 = i - t; float Y0 = j - t; // The x,y distances from the cell origin float x0 = x - X0; float y0 = y - 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), where // c = (3-sqrt(3))/6 float x1 = x0 - i1 + G2; // Offsets for middle corner in (x,y) unskewed coords float y1 = y0 - j1 + G2; float x2 = x0 - 1.0f + 2.0f * G2; // Offsets for last corner in (x,y) unskewed coords float y2 = y0 - 1.0f + 2.0f * G2; // Work out the hashed gradient indices of the three simplex corners int ii = i & 255; int jj = j & 255; int gi0 = perm[ii + perm[jj]] % 12; int gi1 = perm[ii + i1 + perm[jj + j1]] % 12; int gi2 = perm[ii + 1 + perm[jj + 1]] % 12; // Calculate the contribution from the three corners float t0 = 0.5f - x0 * x0 - y0 * y0; if (t0 < 0) n0 = 0.0f; else { t0 *= t0; n0 = t0 * t0 * dot(grad3[gi0], x0, y0); // (x,y) of grad3 used for 2D gradient } float t1 = 0.5f - x1 * x1 - y1 * y1; if (t1 < 0) n1 = 0.0f; else { t1 *= t1; n1 = t1 * t1 * dot(grad3[gi1], x1, y1); } float t2 = 0.5f - x2 * x2 - y2 * y2; if (t2 < 0) n2 = 0.0f; 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 70.0f * (n0 + n1 + n2); } // 3D raw Simplex noise public float raw_noise_3d(float x, float y, float z) { float n0, n1, n2, n3; // Noise contributions from the four corners // Skew the input space to determine which simplex cell we're in float F3 = 1.0f / 3.0f; float s = (x + y + z) * F3; // Very nice and simple skew factor for 3D int i = fastfloor(x + s); int j = fastfloor(y + s); int k = fastfloor(z + s); float G3 = 1.0f / 6.0f; // Very nice and simple unskew factor, too float t = (i + j + k) * G3; float X0 = i - t; // Unskew the cell origin back to (x,y,z) space float Y0 = j - t; float Z0 = k - t; float x0 = x - X0; // The x,y,z distances from the cell origin float y0 = y - Y0; float z0 = z - Z0; // For the 3D case, the simplex shape is a slightly irregular tetrahedron. // 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. float x1 = x0 - i1 + G3; // Offsets for second corner in (x,y,z) coords float y1 = y0 - j1 + G3; float z1 = z0 - k1 + G3; float x2 = x0 - i2 + 2.0f * G3; // Offsets for third corner in (x,y,z) coords float y2 = y0 - j2 + 2.0f * G3; float z2 = z0 - k2 + 2.0f * G3; float x3 = x0 - 1.0f + 3.0f * G3; // Offsets for last corner in (x,y,z) coords float y3 = y0 - 1.0f + 3.0f * G3; float z3 = z0 - 1.0f + 3.0f * G3; // Work out the hashed gradient indices of the four simplex corners int ii = i & 255; int jj = j & 255; int kk = k & 255; int gi0 = perm[ii + perm[jj + perm[kk]]] % 12; int gi1 = perm[ii + i1 + perm[jj + j1 + perm[kk + k1]]] % 12; int gi2 = perm[ii + i2 + perm[jj + j2 + perm[kk + k2]]] % 12; int gi3 = perm[ii + 1 + perm[jj + 1 + perm[kk + 1]]] % 12; // Calculate the contribution from the four corners float t0 = 0.6f - x0 * x0 - y0 * y0 - z0 * z0; if (t0 < 0) n0 = 0.0f; else { t0 *= t0; n0 = t0 * t0 * dot(grad3[gi0], x0, y0, z0); } float t1 = 0.6f - x1 * x1 - y1 * y1 - z1 * z1; if (t1 < 0) n1 = 0.0f; else { t1 *= t1; n1 = t1 * t1 * dot(grad3[gi1], x1, y1, z1); } float t2 = 0.6f - x2 * x2 - y2 * y2 - z2 * z2; if (t2 < 0) n2 = 0.0f; else { t2 *= t2; n2 = t2 * t2 * dot(grad3[gi2], x2, y2, z2); } float t3 = 0.6f - x3 * x3 - y3 * y3 - z3 * z3; if (t3 < 0) n3 = 0.0f; 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 32.0f * (n0 + n1 + n2 + n3); } // 4D raw Simplex noise public float raw_noise_4d(float x, float y, float z, float w) { // The skewing and unskewing factors are hairy again for the 4D case float F4 = ((float)Math.Sqrt(5.0f) - 1.0f) / 4.0f; float G4 = (5.0f - (float)Math.Sqrt(5.0f)) / 20.0f; float n0, n1, n2, n3, n4; // Noise contributions from the five corners // Skew the (x,y,z,w) space to determine which cell of 24 simplices we're in float 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); float t = (i + j + k + l) * G4; // Factor for 4D unskewing float X0 = i - t; // Unskew the cell origin back to (x,y,z,w) space float Y0 = j - t; float Z0 = k - t; float W0 = l - t; float x0 = x - X0; // The x,y,z,w distances from the cell origin float y0 = y - Y0; float z0 = z - Z0; float 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 need to // determine the magnitude ordering of x0, y0, z0 and w0. // The method below is a good way of finding the ordering of x,y,z,w and // then find the correct traversal order for the simplex we're in. // First, six pair-wise comparisons are performed between each possible pair // of the four coordinates, and the results are used to add up binary bits // for an integer index. int c1 = (x0 > y0) ? 32 : 0; int c2 = (x0 > z0) ? 16 : 0; int c3 = (y0 > z0) ? 8 : 0; int c4 = (x0 > w0) ? 4 : 0; int c5 = (y0 > w0) ? 2 : 0; int c6 = (z0 > w0) ? 1 : 0; int c = c1 + c2 + c3 + c4 + c5 + c6; 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 corner 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 make any sense. // We use a thresholding to set the coordinates in turn from the largest magnitude. // The number 3 in the "simplex" array is at the position of the largest coordinate. i1 = simplex[c, 0] >= 3 ? 1 : 0; j1 = simplex[c, 1] >= 3 ? 1 : 0; k1 = simplex[c, 2] >= 3 ? 1 : 0; l1 = simplex[c, 3] >= 3 ? 1 : 0; // The number 2 in the "simplex" array is at the second largest coordinate. i2 = simplex[c, 0] >= 2 ? 1 : 0; j2 = simplex[c, 1] >= 2 ? 1 : 0; k2 = simplex[c, 2] >= 2 ? 1 : 0; l2 = simplex[c, 3] >= 2 ? 1 : 0; // The number 1 in the "simplex" array is at the second smallest coordinate. i3 = simplex[c, 0] >= 1 ? 1 : 0; j3 = simplex[c, 1] >= 1 ? 1 : 0; k3 = simplex[c, 2] >= 1 ? 1 : 0; l3 = simplex[c, 3] >= 1 ? 1 : 0; // The fifth corner has all coordinate offsets = 1, so no need to look that up. float x1 = x0 - i1 + G4; // Offsets for second corner in (x,y,z,w) coords float y1 = y0 - j1 + G4; float z1 = z0 - k1 + G4; float w1 = w0 - l1 + G4; float x2 = x0 - i2 + 2.0f * G4; // Offsets for third corner in (x,y,z,w) coords float y2 = y0 - j2 + 2.0f * G4; float z2 = z0 - k2 + 2.0f * G4; float w2 = w0 - l2 + 2.0f * G4; float x3 = x0 - i3 + 3.0f * G4; // Offsets for fourth corner in (x,y,z,w) coords float y3 = y0 - j3 + 3.0f * G4; float z3 = z0 - k3 + 3.0f * G4; float w3 = w0 - l3 + 3.0f * G4; float x4 = x0 - 1.0f + 4.0f * G4; // Offsets for last corner in (x,y,z,w) coords float y4 = y0 - 1.0f + 4.0f * G4; float z4 = z0 - 1.0f + 4.0f * G4; float w4 = w0 - 1.0f + 4.0f * G4; // Work out the hashed gradient indices of the five simplex corners 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 float t0 = 0.6f - x0 * x0 - y0 * y0 - z0 * z0 - w0 * w0; if (t0 < 0) n0 = 0.0f; else { t0 *= t0; n0 = t0 * t0 * dot(grad4[gi0], x0, y0, z0, w0); } float t1 = 0.6f - x1 * x1 - y1 * y1 - z1 * z1 - w1 * w1; if (t1 < 0) n1 = 0.0f; else { t1 *= t1; n1 = t1 * t1 * dot(grad4[gi1], x1, y1, z1, w1); } float t2 = 0.6f - x2 * x2 - y2 * y2 - z2 * z2 - w2 * w2; if (t2 < 0) n2 = 0.0f; else { t2 *= t2; n2 = t2 * t2 * dot(grad4[gi2], x2, y2, z2, w2); } float t3 = 0.6f - x3 * x3 - y3 * y3 - z3 * z3 - w3 * w3; if (t3 < 0) n3 = 0.0f; else { t3 *= t3; n3 = t3 * t3 * dot(grad4[gi3], x3, y3, z3, w3); } float t4 = 0.6f - x4 * x4 - y4 * y4 - z4 * z4 - w4 * w4; if (t4 < 0) n4 = 0.0f; 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 27.0f * (n0 + n1 + n2 + n3 + n4); } int fastfloor(float x) { return x > 0 ? (int)x : (int)x - 1; } unsafe float dot(int[] g, float x, float y) { return g[0] * x + g[1] * y; } unsafe float dot(int[] g, float x, float y, float z) { return g[0] * x + g[1] * y + g[2] * z; } unsafe float dot(int[] g, float x, float y, float z, float w) { return g[0] * x + g[1] * y + g[2] * z + g[3] * w; } }