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