e3994bddae3cf254a2401e09e051c6b05bdd12c9,decisionmaker/montecarlo_numpy.py,Evaluation,distribute_cards,#Evaluation#Any#Any#Any#,24

Before Change

        cards_combined = np.append(np.tile(mycards, reps=(iterations, 1)), shuffled, axis=1)[:,
                         player_id * card_amount_at_river - card_amount_at_river:card_amount_at_river * player_id]
        cards = np.ceil(cards_combined / 4)
        suits = cards_combined % 4 + 1
        self.decks = np.dstack((cards, suits))

        self.cards = self.decks[:, :, 0]
        self.suits = self.decks[:, :, 1]

    def run_evaluation(self, card1, card2, iterations):
        self.start = time.time()
        self.distribute_cards(card1, card2, iterations)

After Change

        self.player_amount=2

        cards_combined1 = np.append(np.tile(plr1_crds, resp=(iterations,1)), shuffled, axis=1)[:,0:card_amount_at_river]
        cards_combined1 = np.append(np.tile(plr1_crds, resp=(iterations, 1)), shuffled, axis=1)[:,
                          0:card_amount_at_river]

    def run_evaluation(self, card1, card2, iterations):
        self.start = time.time()
        self.distribute_cards(card1, card2, iterations)

Instances