示例#1
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    def straight_and_highcards(self, straights, highcards):
        """
        Unique five card sets. Straights and highcards. 

        Reuses bit sequences from flush calculations.
        """
        rank = LookupTable.MAX_FLUSH + 1

        for s in straights:
            prime_product = Card.prime_product_from_rankbits(s)
            self.unsuited_lookup[prime_product] = rank
            rank += 1

        rank = LookupTable.MAX_PAIR + 1
        for h in highcards:
            prime_product = Card.prime_product_from_rankbits(h)
            self.unsuited_lookup[prime_product] = rank
            rank += 1
示例#2
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    def straight_and_highcards(self, straights, highcards):
        """
        Unique five card sets. Straights and highcards. 

        Reuses bit sequences from flush calculations.
        """
        rank = LookupTable.MAX_FLUSH + 1

        for s in straights:
            prime_product = Card.prime_product_from_rankbits(s)
            self.unsuited_lookup[prime_product] = rank
            rank += 1

        rank = LookupTable.MAX_PAIR + 1
        for h in highcards:
            prime_product = Card.prime_product_from_rankbits(h)
            self.unsuited_lookup[prime_product] = rank
            rank += 1
示例#3
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    def _five(self, cards):
        """
        Performs an evalution given cards in integer form, mapping them to
        a rank in the range [1, 7462], with lower ranks being more powerful.

        Variant of Cactus Kev's 5 card evaluator, though I saved a lot of memory
        space using a hash table and condensing some of the calculations. 
        """
        # if flush
        if cards[0] & cards[1] & cards[2] & cards[3] & cards[4] & 0xF000:
            handOR = (cards[0] | cards[1] | cards[2] | cards[3] | cards[4]) >> 16
            prime = Card.prime_product_from_rankbits(handOR)
            return self.table.flush_lookup[prime]

        # otherwise
        else:
            prime = Card.prime_product_from_hand(cards)
            return self.table.unsuited_lookup[prime]
示例#4
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    def _five(self, cards):
        """
        Performs an evalution given cards in integer form, mapping them to
        a rank in the range [1, 7462], with lower ranks being more powerful.

        Variant of Cactus Kev's 5 card evaluator, though I saved a lot of memory
        space using a hash table and condensing some of the calculations. 
        """
        # if flush
        if cards[0] & cards[1] & cards[2] & cards[3] & cards[4] & 0xF000:
            handOR = (cards[0] | cards[1] | cards[2] | cards[3] | cards[4]) >> 16
            prime = Card.prime_product_from_rankbits(handOR)
            return self.table.flush_lookup[prime]

        # otherwise
        else:
            prime = Card.prime_product_from_hand(cards)
            return self.table.unsuited_lookup[prime]
示例#5
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    def flushes(self):
        """
        Straight flushes and flushes. 

        Lookup is done on 13 bit integer (2^13 > 7462):
        xxxbbbbb bbbbbbbb => integer hand index
        """

        # straight flushes in rank order
        straight_flushes = [
            7936,  # int('0b1111100000000', 2), # royal flush
            3968,  # int('0b111110000000', 2),
            1984,  # int('0b11111000000', 2),
            992,  # int('0b1111100000', 2),
            496,  # int('0b111110000', 2),
            248,  # int('0b11111000', 2),
            124,  # int('0b1111100', 2),
            62,  # int('0b111110', 2),
            31,  # int('0b11111', 2),
            4111  # int('0b1000000001111', 2) # 5 high
        ]

        # now we'll dynamically generate all the other
        # flushes (including straight flushes)
        flushes = []
        gen = self.get_lexographically_next_bit_sequence(int('0b11111', 2))

        # 1277 = number of high cards
        # 1277 + len(str_flushes) is number of hands with all cards unique rank
        for i in range(1277 + len(straight_flushes) -
                       1):  # we also iterate over SFs
            # pull the next flush pattern from our generator
            f = next(gen)

            # if this flush matches perfectly any
            # straight flush, do not add it
            notSF = True
            for sf in straight_flushes:
                # if f XOR sf == 0, then bit pattern
                # is same, and we should not add
                if not f ^ sf:
                    notSF = False

            if notSF:
                flushes.append(f)

        # we started from the lowest straight pattern, now we want to start ranking from
        # the most powerful hands, so we reverse
        flushes.reverse()

        # now add to the lookup map:
        # start with straight flushes and the rank of 1
        # since theyit is the best hand in poker
        # rank 1 = Royal Flush!
        rank = 1
        for sf in straight_flushes:
            prime_product = Card.prime_product_from_rankbits(sf)
            self.flush_lookup[prime_product] = rank
            rank += 1

        # we start the counting for flushes on max full house, which
        # is the worst rank that a full house can have (2,2,2,3,3)
        rank = LookupTable.MAX_FULL_HOUSE + 1
        for f in flushes:
            prime_product = Card.prime_product_from_rankbits(f)
            self.flush_lookup[prime_product] = rank
            rank += 1

        # we can reuse these bit sequences for straights
        # and high cards since they are inherently related
        # and differ only by context
        self.straight_and_highcards(straight_flushes, flushes)
示例#6
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    def flushes(self):
        """
        Straight flushes and flushes. 

        Lookup is done on 13 bit integer (2^13 > 7462):
        xxxbbbbb bbbbbbbb => integer hand index
        """

        # straight flushes in rank order
        straight_flushes = [
            7936, # int('0b1111100000000', 2), # royal flush
            3968, # int('0b111110000000', 2),
            1984, # int('0b11111000000', 2),
            992, # int('0b1111100000', 2),
            496, # int('0b111110000', 2),
            248, # int('0b11111000', 2),
            124, # int('0b1111100', 2),
            62, # int('0b111110', 2),
            31, # int('0b11111', 2),
            4111 # int('0b1000000001111', 2) # 5 high
        ]

        # now we'll dynamically generate all the other
        # flushes (including straight flushes)
        flushes = []
        gen = self.get_lexographically_next_bit_sequence(int('0b11111', 2))

        # 1277 = number of high cards
        # 1277 + len(str_flushes) is number of hands with all cards unique rank
        for i in range(1277 + len(straight_flushes) - 1): # we also iterate over SFs
            # pull the next flush pattern from our generator
            f = next(gen)

            # if this flush matches perfectly any
            # straight flush, do not add it
            notSF = True
            for sf in straight_flushes:
                # if f XOR sf == 0, then bit pattern 
                # is same, and we should not add
                if not f ^ sf:
                    notSF = False

            if notSF:
                flushes.append(f)

        # we started from the lowest straight pattern, now we want to start ranking from
        # the most powerful hands, so we reverse
        flushes.reverse()

        # now add to the lookup map:
        # start with straight flushes and the rank of 1
        # since theyit is the best hand in poker
        # rank 1 = Royal Flush!
        rank = 1
        for sf in straight_flushes:
            prime_product = Card.prime_product_from_rankbits(sf)
            self.flush_lookup[prime_product] = rank
            rank += 1

        # we start the counting for flushes on max full house, which
        # is the worst rank that a full house can have (2,2,2,3,3)
        rank = LookupTable.MAX_FULL_HOUSE + 1
        for f in flushes:
            prime_product = Card.prime_product_from_rankbits(f)
            self.flush_lookup[prime_product] = rank
            rank += 1

        # we can reuse these bit sequences for straights
        # and high cards since they are inherently related
        # and differ only by context 
        self.straight_and_highcards(straight_flushes, flushes)