# BothCM_CH12RP

This program has been disqualified.

 Author david.werecat Submission date 2014-12-13 18:57:09.173359 Rating 5412 Matches played 1 Win rate 100.0

## Source code:

``````#Created by David Catt on December 13, 2014
import random
class CntModel:
def __init__(self, decay):
self.decay = decay
self.prob = [0.0, 0.0, 0.0]
def predict(self):
if self.prob[0] > self.prob[1]:
if self.prob[0] > self.prob[2]:
return 0
else:
return 2
else:
if self.prob[1] > self.prob[2]:
return 1
else:
return 2
def update(self, val):
self.prob[0] *= self.decay
self.prob[1] *= self.decay
self.prob[2] *= self.decay
self.prob[val] += 1.0
class CtxModel:
def __init__(self, order, decay):
self.order = order
self.decay = decay
self.mask = (3 ** order) << 2
self.prob = [0.0 if (i & 3) < 3 else random.randint(0, 2) for i in range(0, self.mask)]
self.ctx = 0
def predict(self):
tvl = 0
tpr = 0.0
prb = 0.0
p = [0,0,0]
for i in range(0, 3):
p[i] = prb = self.prob[self.ctx + i]
if prb > tpr:
tvl = i
tpr = prb
rv = random.random() * (p[0] + p[1] + p[2])
if rv <= p[0]:
return tvl, self.prob[self.ctx + 3], 0
elif rv <= p[1]:
return tvl, self.prob[self.ctx + 3], 1
else:
return tvl, self.prob[self.ctx + 3], 2
def update(self, cvl, val):
self.prob[self.ctx] *= self.decay
self.prob[self.ctx + 1] *= self.decay
self.prob[self.ctx + 2] *= self.decay
self.prob[self.ctx + 3] = val
self.prob[self.ctx + val] += 1.0
self.ctx = ((self.ctx * 3) + (cvl << 2)) % self.mask
def nxtctx(self, cvl):
self.ctx = ((self.ctx * 3) + (cvl << 2)) % self.mask
class ModelSwitch:
def __init__(self, count, decay):
self.value = [1,0,-1,-1,1,0,0,-1,1]
self.count = count
self.decay = decay
self.offset = [0.0] * count
self.weigh = [0.0] * count
self.pred = [0] * count
def setoffset(self, idx, val):
self.offset[idx] = val
def setvalue(self, idx, val):
self.pred[idx] = val
def predict(self):
tvl = 0
tpr = -1.0
prb = 0.0
for i in range(0, self.count):
prb = self.weigh[i] + self.offset[i]
if prb > tpr:
tvl = self.pred[i]
tpr = prb
return tvl
def update(self, val):
for i in range(0, self.count):
self.weigh[i] = (self.weigh[i] * self.decay) + self.value[(val * 3) + self.pred[i]]

if input == "":
winner = [1,2,0]
nval = {"R":0,"P":1,"S":2,"":0}
cval = ["R","P","S"]
mdls = [CtxModel((i % 6) + 1, 0.93) if i < 24 else CtxModel((((i - 24) % 4) + 1) * 2, 0.93) for i in range(0, 32)]
zmdl0 = CntModel(0.93)
zmdl1 = CntModel(0.93)
msse = ModelSwitch(301, 0.93)
for i in range(192, 288):
msse.setoffset(i, -0.05)
msse.setoffset(300, -0.1)
lval = 0
else:
val = nval[input]
for i in range(0, 6):
mdls[i].update(val, val)
mdls[i+6].update(lval, val)
mdls[i+12].update(val, lval)
mdls[i+18].update(lval, lval)
for i in range(24, 28):
mdls[i].nxtctx(val)
mdls[i].update(lval, val)
mdls[i+4].nxtctx(val)
mdls[i+4].update(lval, lval)
zmdl0.update(val)
zmdl1.update(lval)
msse.update(val)
pv = 0
for i in range(0, 32):
p1,p2,p3 = mdls[i].predict()
msse.setvalue(i, p1)
p1 = winner[p1]
msse.setvalue(i + 32, p1)
p1 = winner[p1]
msse.setvalue(i + 64, p1)
msse.setvalue(i + 96, p2)
p2 = winner[p2]
msse.setvalue(i + 128, p2)
p2 = winner[p2]
msse.setvalue(i + 160, p2)
msse.setvalue(i + 192, p3)
p3 = winner[p3]
msse.setvalue(i + 224, p3)
p3 = winner[p3]
msse.setvalue(i + 256, p3)
pv = zmdl0.predict()
msse.setvalue(288, pv)
pv = winner[pv]
msse.setvalue(289, pv)
pv = winner[pv]
msse.setvalue(290, pv)
pv = zmdl1.predict()
msse.setvalue(291, pv)
pv = winner[pv]
msse.setvalue(292, pv)
pv = winner[pv]
msse.setvalue(293, pv)
pv = nval[input]
msse.setvalue(294, pv)
pv = winner[pv]
msse.setvalue(295, pv)
pv = winner[pv]
msse.setvalue(296, pv)
pv = lval
msse.setvalue(297, pv)
pv = winner[pv]
msse.setvalue(298, pv)
pv = winner[pv]
msse.setvalue(299, pv)
msse.setvalue(300, random.randint(0, 2))
lval = winner[msse.predict()]
output = cval[lval]``````