def _brain(X):
lookup = numpy.ndarray(shape=0x10000, dtype=numpy.uint8)
mdecay = 2 * (X.decay + 1)
if mdecay > 256:
mdecay = 256
for i in range(0x10000):
if i & 0x10: #alive
if bit_count[i & 0x1EF] in X.survival:
lookup[i] = 1
else:
lookup[i] = 2 % mdecay
elif i < 0x200: #dead
lookup[i] = bit_count[i & 0x1FF] in X.birth and 1 or 0
else: #dying
lookup[i] = ((i >> 9) * 2 + 2) % mdecay
return algorithm('bytescan',
evolve=evolve,
table=lookup,
states=range(2) + range(2, (X.decay + 1) * 2, 2),
)
def _complex(X):
lookup = list(X.moore)
lookup.append(X.history)
lookup.append(X.potential)
lookup.append(X.denom)
return algorithm('complexscan',
evolve=cc1_evolve,
table=numpy.asarray(lookup, dtype = numpy.complex128),
planes=2)
def _water(X):
lookup = list(X.moore)
lookup.append(X.history)
lookup.append((1.0 - X.damping) / sum(lookup))
lookup.append((X.max + X.min) * X.damping / 2.0 + X.heat)
lookup.extend((X.min, X.max, X.under, X.over))
return algorithm('floatscan',
evolve=dd1_evolve,
table=numpy.asarray(lookup, dtype = numpy.float))
def _redox(X):
lookup = X.copy()
lookup.reduction = numpy.array(lookup.reduction, numpy.uint8)
states = range(max(lookup.activation.keys()) + 1)
return algorithm('sparse',
evolve=evolve,
table=lookup,
states=states)
def _life(X):
lookup0 = []
for i in range(0x200):
if bit_count[i & 0x1EF] in (X.birth, X.survival)[(i & 0x10) and 1]:
lookup0.append(1)
else:
lookup0.append(0)
return algorithm('bytescan',
evolve=evolve,
table=numpy.tile(numpy.asarray(lookup0, dtype = numpy.uint8), 0x80),
states=(0,1))
def _banks(X,
out_to_in = None):
birth, survival, decay = X.birth, X.survival, X.decay
if out_to_in is None:
#in order NESW, like mcell
if len(birth) <= 16:
out_to_in = {1 << 1:1 << 0,
1 << 3:1 << 3,
1 << 5:1 << 1,
1 << 7:1 << 2}
else:
out_to_in = {1 << 0:1 << 7,
1 << 1:1 << 0,
1 << 2:1 << 1,
1 << 3:1 << 6,
1 << 5:1 << 2,
1 << 6:1 << 5,
1 << 7:1 << 4,
1 << 8:1 << 3}
lookup = numpy.ndarray(shape=0x20000, dtype=numpy.uint8)
mdecay = decay + 2
if mdecay > 256:
mdecay = 256
for i in range(0x20000):
target = 0
for obit, ibit in out_to_in.items():
if i & obit:
target |= ibit
if i & 0x10: #alive
if survival[target]:
lookup[i] = survival[target]
else:
lookup[i] = 2 % mdecay
elif i < 0x200: #dead
lookup[i] = birth[target]
else: #dying
lookup[i] = ((i >> 9) + 1) % mdecay
return algorithm('bytescan',
evolve=evolve,
table=lookup,
states=range(decay + 2),
)
def _rivers(X):
lookup = list()
return algorithm('floatscan',
planes=3,
evolve=rivers_evolve,
table=numpy.asarray(lookup, dtype = numpy.float))
