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65 lines
1.3 KiB
65 lines
1.3 KiB
2 years ago
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import math, random
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W = 255
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H = 255
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background=(100,100,100)
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gradtable = [ (0,0) for i in range(0,W*H) ]
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def precalc_gradtable():
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rnd = random.Random()
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for i in range(0,H):
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for j in range(0, W):
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x = float((rnd.randint(1,2*W))-W)/W
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y = float((rnd.randint(1,2*H))-H)/H
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s = math.sqrt(x * x + y * y)
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if s!=0:
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x = x / s
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y = y / s
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else:
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x = 0
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y = 0
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gradtable[i*H+j] = (x,y)
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#calculate dot product for v1 and v2
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def dot(v1,v2):
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return ( (v1[0]*v2[0]) + (v1[1]*v2[1]) )
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# get a pseudorandom gradient vector
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def gradient(x,y):
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# normalize!
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return gradtable[y*H+x]
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def s_curve(x):
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return ( 3*x*x - 2*x*x*x )
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def noise2d(x,y):
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x0 = math.floor(x)
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y0 = math.floor(y)
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x1 = x0 + 1.0
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y1 = y0 + 1.0
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i_x0 = int(x0)
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i_x1 = int(x1)
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i_y0 = int(y0)
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i_y1 = int(y1)
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s = dot(gradient(i_x0, i_y0),(x-x0, y-y0))
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t = dot(gradient(i_x1, i_y0),(x-x1, y-y0))
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u = dot(gradient(i_x0, i_y1),(x-x0, y-y1))
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v = dot(gradient(i_x1, i_y1),(x-x1, y-y1))
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s_x = s_curve( x - x0 )
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a = s + s_x*t - s_x*s
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b = u + s_x*v - s_x*u
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s_y = s_curve( y - y0 )
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z = a + s_y*b - s_y*a
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return z
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def col( a ):
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return int(round((128-(128*a))))
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precalc_gradtable()
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