BUTT DESTROYER V2.11

This program has been disqualified.

Source code:

# Author: JFreegman
# Contact: JFreegman@gmail.com
# Date: July 27, 2012
# v2.11

# All code is written from scratch. The general idea is based off Iocaine Powder 
# by Dan Egnor (http://ofb.net/~egnor/iocaine.html).

import random

def get_history_match(hist, n=100):
    start = len(hist) - min(len(hist) / 2, n)
    end = len(hist)
    for i in xrange(start, end):
        partition = hist[i:end]
        match = hist[:-1].find(partition)
        if match != -1:
            return hist[match+len(partition)]
    return random_weapon()

def get_probs(total_moves, n):
    last = get_move_freq(total_moves[-n:])
    probs = {}
    probs['R'] = float(last['R']) / last['total']
    probs['S'] = float(last['S']) / last['total']
    probs['P'] = float(last['P']) / last['total']
    return probs

def get_move_freq(moves):
    mov_freq = {'R': 0, 'P': 0, 'S': 0}
    count = 0
    for move in moves:
        if move == 'R':
            mov_freq['R'] += 1
        elif move == 'P':
            mov_freq['P'] += 1
        elif move == 'S':
            mov_freq['S'] += 1
        else:
            raise ValueError, 'Invalid move'
        count += 1
    mov_freq['total'] = count
    return mov_freq

def random_weapon():
    return random.choice(['R', 'P', 'S'])

if not input:
    last_strats = {}
    res_history = []
    winning_move = {'R': 'P', 'P': 'S', 'S': 'R'}
    losing_move = {'R': 'S', 'P': 'R', 'S': 'P'}
    opp_moves = ""
    strat_success = {'freq20': 0,'hist': 0, 'random': 0, 'freq100': 0, 
                     'freqtot': 0, 'freq5': 0, 'hist5': 0,'hist20': 0, 
                     'my_hist': 0, 'c_my_move_my_hist': 0, 'c1_my_move_my_hist': 0,}
    output = random_weapon()
    my_moves = output
else:
    # update strategy success rates based on last round results
    opp_moves += input
    last_opp_move = input
    beat_opp = winning_move[last_opp_move]
    lose_opp = losing_move[last_opp_move]
    for s in last_strats:
        if last_strats[s] == beat_opp:
            strat_success[s] += 1
        elif last_strats[s] == lose_opp:
            strat_success[s] -= 1

    # get opponent's most probable move based on frequency and history 
    # pattern matches
    opp_freq5 = get_probs(opp_moves, 5)
    opp_prob_f_5 = max(opp_freq5, key=opp_freq5.get)
    opp_freq20 = get_probs(opp_moves, 20)
    opp_prob_f_20 = max(opp_freq20, key=opp_freq20.get)
    opp_freq100 = get_probs(opp_moves, 100)
    opp_prob_f_100 = max(opp_freq100, key=opp_freq100.get)
    opp_freqtot = get_probs(opp_moves, len(opp_moves))
    opp_prob_f_tot = max(opp_freqtot, key=opp_freqtot.get)
    opp_prob_h = get_history_match(opp_moves)
    opp_prob_h20 = get_history_match(opp_moves, 20)
    opp_prob_h5 = get_history_match(opp_moves, 5)

    # get my most probable move based on history
    my_prob_h = get_history_match(my_moves)

    # naive moves for each strategy
    my_move_freq5 = winning_move[opp_prob_f_5]
    my_move_freq20 = winning_move[opp_prob_f_20]
    my_move_freq100 = winning_move[opp_prob_f_100]
    my_move_freqtot = winning_move[opp_prob_f_tot]
    my_move_hist = winning_move[opp_prob_h]
    my_move_hist20 = winning_move[opp_prob_h20]    
    my_move_hist5 = winning_move[opp_prob_h5]
    my_move_my_hist = losing_move[my_prob_h]
    c_my_move_my_hist = losing_move[my_move_my_hist]
    c1_my_move_my_hist = losing_move[c_my_move_my_hist]

    random_move = random_weapon()
    # dict of all available strategies and their move
    strats = {'freq20': my_move_freq20, 'freq100': my_move_freq100, 
              'hist': my_move_hist, 'random': random_move,
              'freqtot': my_move_freqtot,'freq5': my_move_freq5,
              'hist5': my_move_hist5, 'hist20': my_move_hist20,
              'my_hist': my_move_my_hist, 'c_my_move_my_hist': c_my_move_my_hist,
              'c1_my_move_my_hist': c1_my_move_my_hist }

    # Pick the strategy with the highest current success rate
    strat = max(strats, key=lambda x: strat_success[x])
    output = strats[strat]
    my_moves += output
    last_strats = strats