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Generators.py
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__author__ = 'Ian'
from noise import snoise2, pnoise2
import math
import MapUtility
# Returns a 2D array of perlin noise values
def generateNoise(resolution, offset, octaves, frequency):
arr = list()
min = 1.0
max = 0.0
for x in range(resolution):
arr.append(list())
for y in range(resolution):
sample = (snoise2((x+offset[0]) / frequency, (y+offset[1]) / frequency, octaves)/2) + 0.5
if sample < min:
min = sample
elif sample > max:
max = sample
sample = MapUtility.clamp(sample)
arr[x].append(sample)
print "min: " + str(min)
print "max: " + str(max)
return arr
def generateInflectedNoise(resolution, offset, octaves, frequency):
arr = list()
min = 1.0
max = 0.0
for x in range(resolution):
arr.append(list())
for y in range(resolution):
sample = sumInflectedNoise((x+offset[0], y+offset[1]), frequency, octaves)
if sample < min:
min = sample
elif sample > max:
max = sample
sample = MapUtility.clamp(sample)
arr[x].append(sample)
print "min: " + str(min)
print "max: " + str(max)
return arr
def generateRidgedNoise(resolution, offset, octaves, frequency):
arr = list()
min = 1.0
max = 0.0
for x in range(resolution):
arr.append(list())
for y in range(resolution):
sample = sumRidgedNoise((x+offset[0], y+offset[1]), frequency, octaves)
if sample < min:
min = sample
elif sample > max:
max = sample
sample = MapUtility.clamp(sample)
arr[x].append(sample)
print "min: " + str(min)
print "max: " + str(max)
return arr
# Returns a 2D array with a radial gradient
def generateRadial(resolution, threshold, scale=1.0):
arr = list()
center = resolution / 2
for x in range(resolution):
arr.append(list())
for y in range(resolution):
distance = math.pow(math.pow(x - center, 2) + math.pow(y - center, 2), 0.5)
val = ((center - (distance*(1/scale))) / resolution) * threshold
#val = MapUtility.clamp(val)
arr[x].append(val)
return arr
def sumNoise(point, frequency, octaves=2, lacunarity=2.0, persistence=0.5):
sum = (snoise2(point[0] / frequency, point[1] / frequency) / 2.0) + 0.5
amplitude = 1.0
ran = 1.0
for o in range(1, octaves):
frequency /= lacunarity
amplitude *= persistence
ran += amplitude
sum += (snoise2(point[0] / frequency, point[1] / frequency) * 0.5 + 0.5) * amplitude
return sum / ran
def sumInflectedNoise(point, frequency, octaves=2, lacunarity=2.0, persistence=0.5):
sum = abs(snoise2(point[0] / frequency, point[1] / frequency))
amplitude = 1.0
ran = 1.0
for o in range(1, octaves):
frequency /= lacunarity
amplitude *= persistence
ran += amplitude
sum += abs(snoise2(point[0] / frequency, point[1] / frequency)) * amplitude
return sum / ran
def sumRidgedNoise(point, frequency, octaves=2, lacunarity=2.0, persistence=0.5):
sum = 1.0 - abs(snoise2(point[0] / frequency, point[1] / frequency))
amplitude = 1.0
ran = 1.0
for o in range(1, octaves):
frequency /= lacunarity
amplitude *= persistence
ran += amplitude
sum += (1.0 - abs(snoise2(point[0] / frequency, point[1] / frequency))) * amplitude
return sum / ran
def generateFBMNoise(resolution, offset, octaves, frequency):
arr = list()
min = 1.0
max = 0.0
for x in range(resolution):
arr.append(list())
for y in range(resolution):
sample = sumNoise((x + offset[0], y + offset[1]), frequency, octaves)
if sample < min:
min = sample
elif sample > max:
max = sample
sample = MapUtility.clamp(sample)
arr[x].append(sample)
print "min: " + str(min)
print "max: " + str(max)
return arr