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#Perlin Noise
#Based on Javascript from p5.js (https://github.com/processing/p5.js/blob/master/src/math/noise.js)
import math
import random
PERLIN_YWRAPB = 4
PERLIN_YWRAP = 1<<PERLIN_YWRAPB
PERLIN_ZWRAPB = 8
PERLIN_ZWRAP = 1<<PERLIN_ZWRAPB
PERLIN_SIZE = 4095
perlin_octaves = 4
perlin_amp_falloff = 0.5
def scaled_cosine(i):
return 0.5*(1.0-math.cos(i*math.pi))
perlin = None
def noise(x,y=0,z=0):
global perlin
if perlin == None:
perlin = []
for i in range(0,PERLIN_SIZE+1):
perlin.append(random.random())
if x<0:x=-x
if y<0:y=-y
if z<0:z=-z
xi,yi,zi = int(x),int(y),int(z)
xf = x-xi
yf = y-yi
zf = z-zi
rxf = ryf = None
r = 0
ampl = 0.5
n1 = n2 = n3 = None
for o in range(0,perlin_octaves):
of=xi+(yi<<PERLIN_YWRAPB)+(zi<<PERLIN_ZWRAPB)
rxf = scaled_cosine(xf)
ryf = scaled_cosine(yf)
n1 = perlin[of&PERLIN_SIZE]
n1 += rxf*(perlin[(of+1)&PERLIN_SIZE]-n1)
n2 = perlin[(of+PERLIN_YWRAP)&PERLIN_SIZE]
n2 += rxf*(perlin[(of+PERLIN_YWRAP+1)&PERLIN_SIZE]-n2)
n1 += ryf*(n2-n1)
of += PERLIN_ZWRAP
n2 = perlin[of&PERLIN_SIZE]
n2 += rxf*(perlin[(of+1)&PERLIN_SIZE]-n2)
n3 = perlin[(of+PERLIN_YWRAP)&PERLIN_SIZE]
n3 += rxf*(perlin[(of+PERLIN_YWRAP+1)&PERLIN_SIZE]-n3)
n2 += ryf*(n3-n2)
n1 += scaled_cosine(zf)*(n2-n1)
r += n1*ampl
ampl *= perlin_amp_falloff
xi<<=1
xf*=2
yi<<=1
yf*=2
zi<<=1
zf*=2
if (xf>=1.0): xi+=1; xf-=1
if (yf>=1.0): yi+=1; yf-=1
if (zf>=1.0): zi+=1; zf-=1
return r
def noiseDetail(lod, falloff):
if lod>0:perlin_octaves=lod
if falloff>0:perlin_amp_falloff=falloff
class LCG():
def __init__(self):
self.m = 4294967296.0
self.a = 1664525.0
self.c = 1013904223.0
self.seed = self.z = None
def setSeed(self,val=None):
self.z = self.seed = (math.random()*self.m if val == None else val) >> 0
def getSeed(self):
return self.seed
def rand(self):
self.z = (self.a * self.z + self.c) % self.m
return self.z/self.m
def noiseSeed(seed):
lcg = LCG()
lcg.setSeed(seed)
perlin = []
for i in range(0,PERLIN_SIZE+1):
perlin.append(lcg.rand())
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