def verifyDerivatives(dimensions, verbose=True):
if verbose: print 'verifyDerivatives:'
passedList = []
for d in dimensions:
s = SimplexNoise(0, d)
stepSize = .01
stepCount = 256
v = [
s.simplexNoise([x * stepSize] * d, True) for x in xrange(stepCount)
]
estimate = v[0][0]
changeSum = 0
for i in xrange(len(v) - 1):
val = v[i]
der = val[1]
estimate += sum(der)
changeSum += abs(val[0] - v[1 + 1][0])
estimate *= stepSize
true = v[-1][0]
error = abs(estimate - true)
error /= changeSum
error *= 100
passed = error < 0.1
if verbose:
print str(d) + ' dimensional:'
print ' error percent: %5.8f' % error
print ' ' + ('passed' if passed else 'FAILED')
passedList.append(passed)
return all(passedList)
def verifyDerivatives(dimensions,verbose=True):
if verbose: print 'verifyDerivatives:'
passedList=[]
for d in dimensions:
s=SimplexNoise(0,d)
stepSize=.01
stepCount=256
v=[s.simplexNoise([x*stepSize]*d,True) for x in xrange(stepCount)]
estimate=v[0][0]
changeSum=0
for i in xrange(len(v)-1):
val=v[i]
der=val[1]
estimate+=sum(der)
changeSum+=abs(val[0]-v[1+1][0])
estimate*=stepSize
true=v[-1][0]
error=abs(estimate-true)
error/=changeSum
error*=100
passed=error<0.1
if verbose:
print str(d)+' dimensional:'
print ' error percent: %5.8f' % error
print ' '+('passed' if passed else 'FAILED')
passedList.append(passed)
return all(passedList)
def analyze(dimensions,verbose=True):
if verbose: print 'analyze:'
for d in dimensions:
if verbose:
print str(d)+' dimensional:'
count=50000
s=SimplexNoise(0,d)
data=[s.simplexNoise([random.random()*1000.0 for a in xrange(d)],True) for x in xrange(count)]
distributionCheck([v[0] for v in data],[v[1] for v in data],verbose)
def analyze(dimensions, verbose=True):
if verbose: print 'analyze:'
for d in dimensions:
if verbose:
print str(d) + ' dimensional:'
count = 50000
s = SimplexNoise(0, d)
data = [
s.simplexNoise([random.random() * 1000.0 for a in xrange(d)], True)
for x in xrange(count)
]
distributionCheck([v[0] for v in data], [v[1] for v in data], verbose)
def loopTest():
loopCount=10000
print 'dimensions','ms','max value','min value'
#histo=[0 for i in xrange(100)]
print 'der'
for i in xrange(2,5):
s=SimplexNoise(0,i)
maxV=0.0
minV=0.0
t=time()
for a in xrange(loopCount):
v=s.simplexNoise([random.random()*100 for x in xrange(i)],True)
d=v[1]
v=d[0]
maxV=max(maxV,v)
minV=min(minV,v)
#print i,(time()-t)/loopCount*1000,maxV,minV
print 'derivative check'
stepSize=.01
stepCount=200
v=[s.simplexNoise([x*stepSize]*i,True) for x in xrange(stepCount)]
estimate=v[0][0]
for val in v[:-1]:
der=val[1]
estimate+=sum(der)
estimate*=stepSize
true=v[-1][0]
print estimate-true,estimate,true
print 'reg'
if False:
for i in xrange(2,5):
s=SimplexNoise(0,i)
maxV=0.0
minV=0.0
t=time()
for a in xrange(loopCount):
v=s.simplexNoise(([random.random()*100 for x in xrange(i)]))
maxV=max(maxV,v)
minV=min(minV,v)
print i,(time()-t)/loopCount*1000,maxV,minV
def noise2D(sizeX,sizeY,scale):
s=SimplexNoise(0,2)
noiseTex=Texture("NoiseTex")
noiseTex.setup2dTexture(sizeX,sizeY, Texture.TUnsignedByte, Texture.FRgb)
p=noiseTex.modifyRamImage()
print 'making tex '+str(sizeX)+' by '+str(sizeY)
for y in range(sizeY):
for x in range(sizeX):
index = (sizeX * y + x)*noiseTex.getNumComponents()*noiseTex.getComponentWidth()
v,der=s.simplexNoise([x/scale,y/scale],True)
p.setElement(index, min(255,max(0,der[1]*8*128+128)))#Blue
p.setElement(index+1, min(255,max(0,der[0]*8*128+128)))#Green
p.setElement(index+2, min(255,max(0,v*128+128)))#Red
return noiseTex
def noise1D(sizeX, scale):
s = SimplexNoise(0, 1)
noiseTex = Texture("NoiseTex")
noiseTex.setup2dTexture(sizeX, sizeX, Texture.TUnsignedByte, Texture.FRgb)
p = noiseTex.modifyRamImage()
print 'making tex ' + str(sizeX) + ' by ' + str(sizeX)
for y in range(sizeX):
v, der = s.simplexNoise([y / scale], True)
for x in range(sizeX):
index = (sizeX * y + x) * noiseTex.getNumComponents(
) * noiseTex.getComponentWidth()
p.setElement(index, min(255, max(0, 0))) #Blue
p.setElement(index + 1, min(255, max(0, 0))) #Green
p.setElement(index + 2, min(255, max(0, v * 128 + 128))) #Red
return noiseTex
def noise3D(sizeX,sizeY,sizeZ,scale):
s=SimplexNoise(0,3)
noiseTex=Texture("NoiseTex")
noiseTex.setup3dTexture(sizeX,sizeY,sizeZ, Texture.TUnsignedByte, Texture.FRgba)
p=noiseTex.modifyRamImage()
for z in range(sizeZ):
offset = sizeX * sizeY * z
print 'making slice '+str(z)+' of '+str(sizeZ)
for y in range(sizeY):
for x in range(sizeX):
index = (offset + sizeX * y + x)*noiseTex.getNumComponents()*noiseTex.getComponentWidth()
v=s.simplexNoise([x/scale,y/scale,z/scale],True)
der=v[1]
v=v[0]
p.setElement(index, min(255,max(0,der[1]*8*128+128)))#Blue
p.setElement(index+1, min(255,max(0,der[0]*8*128+128)))#Green
p.setElement(index+2, min(255,max(0,v*128+128)))#Red
p.setElement(index+3, 255)#Alpha
return noiseTex
def loopTest():
loopCount = 10000
print 'dimensions', 'ms', 'max value', 'min value'
#histo=[0 for i in xrange(100)]
print 'der'
for i in xrange(2, 5):
s = SimplexNoise(0, i)
maxV = 0.0
minV = 0.0
t = time()
for a in xrange(loopCount):
v = s.simplexNoise([random.random() * 100 for x in xrange(i)],
True)
d = v[1]
v = d[0]
maxV = max(maxV, v)
minV = min(minV, v)
#print i,(time()-t)/loopCount*1000,maxV,minV
print 'derivative check'
stepSize = .01
stepCount = 200
v = [
s.simplexNoise([x * stepSize] * i, True) for x in xrange(stepCount)
]
estimate = v[0][0]
for val in v[:-1]:
der = val[1]
estimate += sum(der)
estimate *= stepSize
true = v[-1][0]
print estimate - true, estimate, true
print 'reg'
if False:
for i in xrange(2, 5):
s = SimplexNoise(0, i)
maxV = 0.0
minV = 0.0
t = time()
for a in xrange(loopCount):
v = s.simplexNoise(
([random.random() * 100 for x in xrange(i)]))
maxV = max(maxV, v)
minV = min(minV, v)
print i, (time() - t) / loopCount * 1000, maxV, minV
def noise3D(sizeX, sizeY, sizeZ, scale):
s = SimplexNoise(0, 3)
noiseTex = Texture("NoiseTex")
noiseTex.setup3dTexture(sizeX, sizeY, sizeZ, Texture.TUnsignedByte,
Texture.FRgba)
p = noiseTex.modifyRamImage()
for z in range(sizeZ):
offset = sizeX * sizeY * z
print 'making slice ' + str(z) + ' of ' + str(sizeZ)
for y in range(sizeY):
for x in range(sizeX):
index = (offset + sizeX * y + x) * noiseTex.getNumComponents(
) * noiseTex.getComponentWidth()
v = s.simplexNoise([x / scale, y / scale, z / scale], True)
der = v[1]
v = v[0]
p.setElement(index, min(255,
max(0, der[1] * 8 * 128 + 128))) #Blue
p.setElement(index + 1,
min(255, max(0, der[0] * 8 * 128 + 128))) #Green
p.setElement(index + 2, min(255, max(0, v * 128 + 128))) #Red
p.setElement(index + 3, 255) #Alpha
return noiseTex
def __init__(
self,
widthToHeightRatio,
sealevel,
mountainlevel,
numPlayerCountries,
totalCountries,
regionsPerPlayerCountry,
regionsPerNeutralCountry,
neutralSupplyProportion,
startingSupplyCentersPerPlayer,
):
"""Generate a diplomacy map. This algorithm generates terrain first, and allocates the player countries out of land only. It should look more organic."""
self.widthToHeightRatio = widthToHeightRatio # remember this number for when we need to render.
diploMap = DiplomacyPolygon(
[(0, 0), (widthToHeightRatio, 0), (widthToHeightRatio, 1), (0, 1)]
) # this is the game board
assert numPlayerCountries <= totalCountries
# Let's make the geography first:
isEnoughLand = False
while not isEnoughLand:
bigSpaces = voronoiSegmentation(diploMap, totalCountries) # land regions, mountains, and seas.
seaSpaces = []
landSpaces = []
mountainSpaces = []
noiseGen = SimplexNoise(period=int(widthToHeightRatio))
for bigSpace in bigSpaces:
rndx, rndy = randomPointWithin(bigSpace)
elevation = noiseGen.noise2(2 * rndx / widthToHeightRatio, 2 * rndy) # float division
if elevation < sealevel:
seaSpaces.append(bigSpace)
elif elevation < mountainlevel:
landSpaces.append(bigSpace)
else:
mountainSpaces.append(bigSpace)
# let's first confirm that there is enough land for all players
isEnoughLand = len(landSpaces) >= numPlayerCountries
# if not isEnoughLand:
# print("There weren't enough land spaces to allocate all players. Regenerating geography...")
# now we need to decide which of these are players.
random.shuffle(landSpaces)
playerCountries = landSpaces[:numPlayerCountries]
neutralLandSpaces = landSpaces[numPlayerCountries:]
# now all the regions are made, and we have to segment the land.
self.neutralLandRegions = sum(
[voronoiSegmentation(space, regionsPerNeutralCountry) for space in neutralLandSpaces], []
)
self.playerRegions = [voronoiSegmentation(country, regionsPerPlayerCountry) for country in playerCountries]
# also save the seas and mountains to self memory
self.seaSpaces = seaSpaces
self.mountainSpaces = mountainSpaces
# ok, now the map itself is created and we need to handle some random odds and ends. Namely, we need to give things colors, and make some things be supply centers.
playerColors = [
(255, 0, 0), # red
(125, 0, 0), # burgundy
(255, 255, 0), # yellow
(125, 125, 0), # olive
(0, 255, 0), # lime
(0, 125, 0), # dark green
(0, 255, 255), # cyan
(0, 125, 125), # teal
(0, 0, 255), # blue
(0, 0, 125), # navy
(255, 0, 255), # magenta
(125, 0, 125), # purple
(181, 166, 66), # salmon
(255, 165, 0), # orange
(139, 69, 19), # brown
(200, 200, 200), # light grey
(120, 120, 120), # dark grey
(230, 230, 250), # lavender
]
while numPlayerCountries > len(playerColors): # awkward, we don't have enough colors.
playerColors.append(
(random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
) # Let's just make some up. This won't be as clear as using the defaults (could end up with a color that is too sea-like for example) but it will work.
for iii in range(numPlayerCountries):
supplyCentersSoFar = 0
random.shuffle(self.playerRegions[iii])
for region in self.playerRegions[iii]:
region.fill_color = playerColors[iii]
if supplyCentersSoFar < startingSupplyCentersPerPlayer:
supplyCentersSoFar += 1
region.isSupplyCenter = True
for seaSpace in self.seaSpaces:
seaSpace.fill_color = (255, 255, 255) # blank (to save ink)
for mountainSpace in self.mountainSpaces:
mountainSpace.fill_color = (0, 0, 0) # jet black
for neutralLandRegion in self.neutralLandRegions:
neutralLandRegion.fill_color = (255, 200, 150) # like they are on the diplomacy board.
if random.random() <= neutralSupplyProportion:
neutralLandRegion.isSupplyCenter = True
# having generated all the stuff, now we should give them names.
namesUsedSoFar = []
def makeRandomName():
""" helper function """
return chr(random.randint(65, 90)) + chr(random.randint(65, 90)) + chr(random.randint(65, 90))
for dp in (
self.seaSpaces
+ self.mountainSpaces
+ self.neutralLandRegions
+ list(itertools.chain.from_iterable(self.playerRegions))
): # iterate through ALL the polygons. Also check out that itertools thing, it takes a list of lists and flattens it.
isBad = True
while isBad:
rndName = makeRandomName()
isBad = rndName in namesUsedSoFar
namesUsedSoFar.append(rndName)
dp.name = rndName