def run(self): # perlin = Perlin(12345) # frac = FractalNoise(h=1.0, lacunarity=50.0, octaves=4.2, noise=perlin ) self._perlin_data = [] z = 0.5 octaves = 6 scale = 2 * octaves ls3 = 10 * octaves ls2 = 15 * octaves ls = 20 * octaves for x in range(self._x_start, self._x_end): for y in xrange(self._size): value = _perlin.noise3(float(x) / ls, float(y) / ls, z, octaves, 0.5)#, base=0) if value > 0.8 or value < 0: value = -1 else: value += _perlin.noise3(float(x) / scale, float(y) / scale, z, octaves, 0.5)#, base=0) value += _perlin.noise3(float(x) / ls2, float(y) / ls2, z, octaves, 0.5)#, base=0) value += _perlin.noise3(float(x) / ls3, float(y) / ls3, z, octaves, 0.5)#, base=0) value = value * 127.0 + 128.0 self._perlin_data += [value, value, value, 1.0]
def _get_noise(self, pos):
# noise
x = pos.x
y = pos.y
z = pos.z
#first_scale = 8 * self._octaves
# h = self._planet_root.max_height * self._planet_root.noise.ridged_multi_fractal3(p.x, p.y, p.z, 0.0, 1.0)
#frac = self._noise.ridged_multi_fractal3(x / first_scale, y / first_scale, z / first_scale, -0.1, 1.0)
#frac += self._noise.turbulance3(x / first_scale, y / first_scale, z / first_scale)
# data.append( perlin.noise3( v.x, v.y, v.z) * 255.0 )
# data.append( self._noise.brownian_motion3( v.x, v.y, v.z) * 255.0 )
# data.append( ( (self._noise.ridged_multi_fractal3(v.x, v.y, v.z, -0.1, 1.0) + 1.0) / 2.0) * 255.0 )
# frac = self._noise.ridged_multi_fractal3(v.x / first_scale, v.y / first_scale, v.z / first_scale, -0.1, 1.0)
# frac += self._noise.turbulance3(v.x / first_scale, v.y / first_scale, v.z / first_scale)
#frac = pnoise3(v.x / first_scale, v.y / first_scale, v.z / first_scale)#, octaves=4)
#frac += pnoise3(v.x / second_scale, v.y / second_scale, v.z / second_scale)#, octaves=4 )
#frac += pnoise3(v.x / second_scale, v.y / second_scale, v.z / second_scale, octaves=4 )
#height = ( frac * 127.0 ) + 128.0
octaves = 6.0
ioct = int(octaves)
scale = 2 * octaves
ls3 = 10 * octaves
ls2 = 15 * octaves
ls = 20 * octaves
value = _perlin.noise3(x / ls, y / ls, z / ls, ioct, 0.5)#, base=0)
if value > 0.8 or value < 0:
value = -1
# else:
# if value < -0.8:
# value = -1
else:
value += _perlin.noise3(x / scale, y / scale, z / scale, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls2, y / ls2, z / ls2, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls3, y / ls3, z / ls3, ioct, 0.5)#, base=0)
frac = value
#print frac
return frac
def single_threaded_image(self):
# perlin = Perlin(12345)
# frac = FractalNoise(h=1.0, lacunarity=50.0, octaves=4.2, noise=perlin )
perlin_data = []
x = 0#self._image_size
octaves = 6.0
ioct = int(octaves)
scale = 2 * octaves
ls3 = 10 * octaves
ls2 = 15 * octaves
ls = 20 * octaves
for y in xrange(self._image_size):
for z in xrange(self._image_size):
#value = ( (perlin.noise3(float(x) / scale, float(y) / scale, z) * 127.0) + 128.0)
# value = pnoise3(float(x) / scale, float(y) / scale, z) * 127.0 + 128.0
# value = snoise3(float(x) / scale, float(y) / scale, z) * 127.0 + 128.0
# value = perlin.noise3(x,y,z)
#value = frac.ridged_multi_fractal3(float(x) / scale, float(y) / scale, z, 0, 1.0)
#value = snoise3(float(x) / scale, float(y) / scale, z)
#value = _simplex.noise3(float(x) / scale, float(y) / scale, z, 32, 1.0)#, base=0)
######
# value = _perlin.noise3(float(x) / ls, float(y) / ls, z / ls, octaves, 0.5)#, base=0)
# if value > 0.8 or value < 0:
# value = -1
# else:
# value += _perlin.noise3(float(x) / scale, float(y) / scale, z / ls, octaves, 0.5)#, base=0)
# value += _perlin.noise3(float(x) / ls2, float(y) / ls2, z / ls, octaves, 0.5)#, base=0)
# value += _perlin.noise3(float(x) / ls3, float(y) / ls3, z / ls, octaves, 0.5)#, base=0)
####
value = _perlin.noise3(x / ls, y / ls, z / ls, ioct, 0.5)#, base=0)
if value > 0.8 or value < 0:
value = -1
else:
value += _perlin.noise3(x / scale, y / scale, z / scale, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls2, y / ls2, z / ls2, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls3, y / ls3, z / ls2, ioct, 0.5)#, base=0)
# value *= 1000
#print value
#value = max(min(value, 0.6), 0.4)
# value += math.cos(x + value)
# value *= 20
# value = value - int(value)
#value += frac.ridged_multi_fractal3(float(x) / scale, float(y) / scale, z, 0, 1.0)
value = value * 127.0 + 128.0
perlin_data += [value, value, value, 1.0]
return perlin_data
def process_image_section(out_queue, pr):
perlin_data = []
octaves = 6.0
scale = 2 * octaves
ls3 = 10 * octaves
ls2 = 15 * octaves
ls = 20 * octaves
# If the FRONT or BACK
if pr.face == 4 or pr.face == 1:
z = pr.zstart
x_start = pr.x_start
x_end = pr.x_end
y_end = pr.y_end
for x in range(x_start, x_end):
for y in xrange(y_end):
value = _perlin.noise3(x / ls, y / ls, z / ls, octaves, 0.5)#, base=0)
if value > 0.8 or value < 0:
value = -1
else:
value += _perlin.noise3(x / scale, y / scale, z / scale, octaves, 0.5)#, base=0)
value += _perlin.noise3(x / ls2, y / ls2, z / ls2, octaves, 0.5)#, base=0)
value += _perlin.noise3(x / ls3, y / ls3, z / ls2, octaves, 0.5)#, base=0)
value = value * 127.0 + 128.0
perlin_data += [value, value, value, 1.0]
# if the TOP or BOTTOM
elif pr.face == 0 or pr.face == 3:
y = pr.ystart
x_start = pr.x_start
x_end = pr.x_end
z_end = pr.z_end
for x in range(x_start, x_end):
for z in xrange(z_end):
value = _perlin.noise3(x / ls, y / ls, z, octaves, 0.5)#, base=0)
if value > 0.8 or value < 0:
value = -1
else:
value += _perlin.noise3(x / scale, y / scale, z / scale, octaves, 0.5)#, base=0)
value += _perlin.noise3(x / ls2, y / ls2, z / ls2, octaves, 0.5)#, base=0)
value += _perlin.noise3(x / ls3, y / ls3, z / ls3, octaves, 0.5)#, base=0)
value = value * 127.0 + 128.0
perlin_data += [value, value, value, 1.0]
# if the RIGHT or LEFT
elif pr.face == 2 or pr.face == 5:
x = pr.xstart
y_end = pr.y_end
z_start = pr.z_start
z_end = pr.z_end
for z in range(z_start, z_end):
for y in xrange(y_end):
value = _perlin.noise3(x / ls, y / ls, z, octaves, 0.5)#, base=0)
if value > 0.8 or value < 0:
value = -1
else:
value += _perlin.noise3(x / scale, y / scale, z / scale, octaves, 0.5)#, base=0)
value += _perlin.noise3(x / ls2, y / ls2, z / ls2, octaves, 0.5)#, base=0)
value += _perlin.noise3(x / ls3, y / ls3, z / ls3, octaves, 0.5)#, base=0)
value = value * 127.0 + 128.0
perlin_data += [value, value, value, 1.0]
out_queue.put([face, pos, perlin_data] )
def __call__(self):
octaves = 6.0
ioct = int(octaves)
scale = 2 * octaves
ls3 = 10 * octaves
ls2 = 15 * octaves
ls = 20 * octaves
# If the FRONT or BACK
if self._pr.face == 4 or self._pr.face == 1:
z = self._pr.z_start
x_start = self._pr.x_start
x_end = self._pr.x_end
y_end = self._pr.y_end
for x in range(x_start, x_end):
for y in xrange(y_end):
value = _perlin.noise3(x / ls, y / ls, z / ls, ioct, 0.5)#, base=0)
if value > 0.8 or value < 0:
value = -1
else:
value += _perlin.noise3(x / scale, y / scale, z / scale, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls2, y / ls2, z / ls2, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls3, y / ls3, z / ls2, ioct, 0.5)#, base=0)
value = value * 127.0 + 128.0
self._perlin_data += [value, value, value, 1.0]
# if the TOP or BOTTOM
elif self._pr.face == 0 or self._pr.face == 3:
y = self._pr.y_start
x_start = self._pr.x_start
x_end = self._pr.x_end
z_end = self._pr.z_end
for x in range(x_start, x_end):
for z in xrange(z_end):
value = _perlin.noise3(x / ls, y / ls, z / ls, ioct, 0.5)#, base=0)
if value > 0.8 or value < 0:
value = -1
else:
value += _perlin.noise3(x / scale, y / scale, z / scale, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls2, y / ls2, z / ls2, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls3, y / ls3, z / ls3, ioct, 0.5)#, base=0)
value = value * 127.0 + 128.0
self._perlin_data += [value, value, value, 1.0]
# if the RIGHT or LEFT
elif self._pr.face == 2 or self._pr.face == 5:
x = self._pr.x_start
y_end = self._pr.y_end
z_start = self._pr.z_start
z_end = self._pr.z_end
for z in range(z_start, z_end):
for y in xrange(y_end):
value = _perlin.noise3(x / ls, y / ls, z / ls, ioct, 0.5)#, base=0)
if value > 0.8 or value < 0:
value = -1
else:
value += _perlin.noise3(x / scale, y / scale, z / scale, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls2, y / ls2, z / ls2, ioct, 0.5)#, base=0)
value += _perlin.noise3(x / ls3, y / ls3, z / ls3, ioct, 0.5)#, base=0)
value = value * 127.0 + 128.0
self._perlin_data += [value, value, value, 1.0]
return [self._pr.face, self._pr.pos, self._perlin_data]
