def runExperiment(table, gamma): print("(Expected payoff, variance) over 1000 trials is %r" % (payoffStats(table, gamma),)) reward, Gmax, weights, bestStock, tickers = exp3Stocks(table, gamma) print("For a single run: ") print("Payoff was %.2f" % reward) print("Regret was %.2f" % (Gmax - reward)) print("Best stock was %s at %.2f" % (bestStock, Gmax)) print("weights: %r" % (prettyList(distr(weights)),))
def weightsStats(table, gamma): weightDs = [] # dictionaries of final weights across all rounds for i in range(1000): reward, Gmax, weights, bestStock, tickers = exp3Stocks(table, gamma) weightDs.append(dict(zip(tickers, distr(weights)))) weightMatrix = [] for key in tickers: print("weight stats for %s: %r" % (key, prettyList(stats(d[key] for d in weightDs))))