# switching19_fix

This program has been disqualified.

 Author pyfex Submission date 2011-06-23 19:31:15.186639 Rating 5004 Matches played 2 Win rate 50.0

## Source code:

``````# See http://overview.cc/RockPaperScissors for more information about rock, paper, scissors
# Switching with multiple different switching strategies. 450 different predictors. Maybe
# it gets disqualified for that, but let's see.

import random
import operator
from collections import defaultdict

if input == "":
both_hist = ""
my_hist = ""
opp_hist = ""
my_stats = {'R':0, 'P':0, 'S': 0}
beat = {'P': 'S', 'S': 'R', 'R': 'P'}
cede = {'P': 'R', 'S': 'P', 'R': 'S'}

both_patterns = defaultdict(str)
opp_patterns = defaultdict(str)
my_patterns = defaultdict(str)

def shift(n, move):
return {0: move, 1:beat[move], 2:cede[move]}[n%2]

def unshift(n, move):
return {0: move, 1:cede[move], 2:beat[move]}[n%2]

score = {'RR': 0, 'PP': 0, 'SS': 0, 'PR': 1, 'RS': 1, 'SP': 1,'RP': -1, 'SR': -1, 'PS': -1,}
output = random.choice(["R", "P", "S"])

candidates = [output] * 450

performance = [[(2,0)]*6, [(2,0)]*6, [0]*6, [(2,0)]*450, 0, 0]
main_performance = [0, 0, 0, 0, 0, 0]
main_candidates = [output] * 6
indices = [0, 0, 0, 0] # only the first 4 main strats are switching strats
main_index = 0
wins = losses = ties = 0
else:
my_stats[output] += 1

sc = score[output+input]
if sc == 1:
wins += 1
elif sc == 0:
ties += 1
elif sc == -1:
losses += 1

both_hist += output+input
my_hist += output
opp_hist += input

for length in range(min(5, len(my_hist)), 0, -1):
opp_patterns[opp_hist[-length:]] += output + input
my_patterns[my_hist[-length:]] += output + input
both_patterns[both_hist[-2*length:]] += output + input

for i, c in enumerate(candidates[:6]):
performance[0][i] = ({1:performance[0][i][0]+1, 0: 2, -1: 2}[score[c+input]],
performance[0][i][1]+score[c+input])
performance[1][i] = ({1:performance[1][i][0]+1, 0: performance[1][i][0], -1: 2}[score[c+input]],
performance[1][i][1]+score[c+input])
performance[2][i] += score[c+input]

for i, c in enumerate(candidates):
performance[3][i] = ({1:performance[3][i][0]+1, 0: 2, -1: 2}[score[c+input]],
performance[3][i][1]+score[c+input])

indices[0] = performance[0].index(max(performance[0], key=lambda x: x[0]**3+x[1]))
indices[1] = performance[1].index(max(performance[1], key=lambda x: x[0]**3+x[1]))
indices[2] = performance[2].index(max(performance[2]))
indices[3] = performance[3].index(max(performance[3], key=lambda x: x[0]**3+x[1]))

for i, c in enumerate(main_candidates):
main_performance[i] += score[c+input]

main_index = main_performance.index(max(main_performance))

output = random.choice(['R', 'P', 'S'])
candidates = [output] * 450

for length in range(min(5, len(my_hist)), 0, -1):
p = both_patterns[both_hist[-2*length:]]
if p != "":
opp = p[-1]
my = p[-2]
candidates[0] = beat[opp]
candidates[1] = cede[my]
candidates[2] = opp
candidates[3] = my
candidates[4] = cede[opp]
candidates[5] = beat[my]
for i, a in enumerate(candidates[:6]):
for offset in range(3):
candidates[6+24*i+offset*8] = shift(offset+wins, a)
candidates[6+24*i+offset*8+1] = shift(offset+wins+ties, a)
candidates[6+24*i+offset*8+2] = shift(offset+losses+ties, a)
candidates[6+24*i+offset*8+3] = shift(offset+losses, a)
candidates[6+24*i+offset*8+4] = unshift(offset+wins, a)
candidates[6+24*i+offset*8+5] = unshift(offset+wins+ties, a)
candidates[6+24*i+offset*8+6] = unshift(offset+losses+ties, a)
candidates[6+24*i+offset*8+7] = unshift(offset+losses, a)
main_candidates[4] = beat[opp]
break

for length in range(min(5, len(my_hist)), 0, -1):
p = my_patterns[my_hist[-length:]]
if p != "":
opp = p[-1]
my = p[-2]
candidates[150] = beat[opp]
candidates[151] = cede[my]
candidates[152] = opp
candidates[153] = my
candidates[154] = cede[opp]
candidates[155] = beat[my]
for i, a in enumerate(candidates[150:156]):
for offset in range(3):
candidates[150+6+24*i+offset*8] = shift(offset+wins, a)
candidates[150+6+24*i+offset*8+1] = shift(offset+wins+ties, a)
candidates[150+6+24*i+offset*8+2] = shift(offset+losses+ties, a)
candidates[150+6+24*i+offset*8+3] = shift(offset+losses, a)
candidates[150+6+24*i+offset*8+4] = unshift(offset+wins, a)
candidates[150+6+24*i+offset*8+5] = unshift(offset+wins+ties, a)
candidates[150+6+24*i+offset*8+6] = unshift(offset+losses+ties, a)
candidates[150+6+24*i+offset*8+7] = unshift(offset+losses, a)
break

for length in range(min(5, len(opp_hist)), 0, -1):
p = opp_patterns[opp_hist[-length:]]
if p != "":
opp = p[-1]
my = p[-2]
candidates[300] = beat[opp]
candidates[301] = cede[my]
candidates[302] = opp
candidates[303] = my
candidates[304] = cede[opp]
candidates[305] = beat[my]
for i, a in enumerate(candidates[300:306]):
for offset in range(3):
candidates[300+6+24*i+offset*8] = shift(offset+wins, a)
candidates[300+6+24*i+offset*8+1] = shift(offset+wins+ties, a)
candidates[300+6+24*i+offset*8+2] = shift(offset+losses+ties, a)
candidates[300+6+24*i+offset*8+3] = shift(offset+losses, a)
candidates[300+6+24*i+offset*8+4] = unshift(offset+wins, a)
candidates[300+6+24*i+offset*8+5] = unshift(offset+wins+ties, a)
candidates[300+6+24*i+offset*8+6] = unshift(offset+losses+ties, a)
candidates[300+6+24*i+offset*8+7] = unshift(offset+losses, a)
break

for i in range(4):
main_candidates[i] = candidates[indices[i]]

main_candidates[5] = cede[max([e for e in my_stats.items()], key=operator.itemgetter(1))[0]]
output = main_candidates[main_index]``````