问题
Referring to the original problem: Optimizing hand-evaluation algorithm for Poker-Monte-Carlo-Simulation
I have a list of 5 to 7 cards and want to store their value in a hashtable, which should be an array of 32-bit-integers and directly accessed by the hashfunctions value as index. Regarding the large amount of possible combinations in a 52-card-deck, I don't want to waste too much memory.
Numbers:
- 7-card-combinations: 133784560
- 6-card-combinations: 20358520
- 5-card-combinations: 2598960
- Total: 156.742.040 possible combinations
Storing 157 million 32-bit-integer values costs about 580MB. So I would like to avoid increasing this number by reserving memory in an array for values that aren't needed.
So the question is: How could a hashfunction look like, that maps each possible, non duplicated combination of cards to a consecutive value between 0 and 156.742.040 or at least comes close to it?
回答1:
Paul Senzee has a great post on this here for 7 cards.
His code is basically a bunch of pre-computed tables and then one function to look up the array index for a given 7-card hand (represented as a 64-bit number with the lowest 52 bits signifying cards):
inline unsigned index52c7(unsigned __int64 x)
{
const unsigned short *a = (const unsigned short *)&x;
unsigned A = a[3], B = a[2], C = a[1], D = a[0],
bcA = _bitcount[A], bcB = _bitcount[B], bcC = _bitcount[C], bcD = _bitcount[D],
mulA = _choose48x[7 - bcA], mulB = _choose32x[7 - (bcA + bcB)], mulC = _choose16x[bcD];
return _offsets52c[bcA] + _table4[A] * mulA +
_offsets48c[ (bcA << 4) + bcB] + _table [B] * mulB +
_offsets32c[((bcA + bcB) << 4) + bcC] + _table [C] * mulC +
_table [D];
}
In short, it's a bunch of lookups and bitwise operations powered by pre-computed lookup tables based on perfect hashing.
If you go back and look at this website, you can get the perfect hash code that Senzee used to create the 7-card hash and repeat the process for 5- and 6-card tables (essentially creating a new index52c7.h
for each). You might be able to smash all 3 into one table, but I haven't tried that.
All told that should be ~628 MB (4 bytes * 157 M entries). Or, if you want to split it up, you can map it to 16-bit numbers (since I believe most poker hand evaluators only need 7,462 unique hand scores) and then have a separate map from those 7,462 hand scores to whatever hand categories you want. That would be 314 MB.
回答2:
Here's a different answer based on the colex function concept. It works with bitsets that are sorted in descending order. Here's a Python implementation (both recursive so you can see the logic and iterative). The main concept is that, given a bitset, you can always calculate how many bitsets there are with the same number of set bits but less than (in either the lexicographical or mathematical sense) your given bitset. I got the idea from this paper on hand isomorphisms.
from math import factorial
def n_choose_k(n, k):
return 0 if n < k else factorial(n) // (factorial(k) * factorial(n - k))
def indexset_recursive(bitset, lowest_bit=0):
"""Return number of bitsets with same number of set bits but less than
given bitset.
Args:
bitset (sequence) - Sequence of set bits in descending order.
lowest_bit (int) - Name of the lowest bit. Default = 0.
>>> indexset_recursive([51, 50, 49, 48, 47, 46, 45])
133784559
>>> indexset_recursive([52, 51, 50, 49, 48, 47, 46], lowest_bit=1)
133784559
>>> indexset_recursive([6, 5, 4, 3, 2, 1, 0])
0
>>> indexset_recursive([7, 6, 5, 4, 3, 2, 1], lowest_bit=1)
0
"""
m = len(bitset)
first = bitset[0] - lowest_bit
if m == 1:
return first
else:
t = n_choose_k(first, m)
return t + indexset_recursive(bitset[1:], lowest_bit)
def indexset(bitset, lowest_bit=0):
"""Return number of bitsets with same number of set bits but less than
given bitset.
Args:
bitset (sequence) - Sequence of set bits in descending order.
lowest_bit (int) - Name of the lowest bit. Default = 0.
>>> indexset([51, 50, 49, 48, 47, 46, 45])
133784559
>>> indexset([52, 51, 50, 49, 48, 47, 46], lowest_bit=1)
133784559
>>> indexset([6, 5, 4, 3, 2, 1, 0])
0
>>> indexset([7, 6, 5, 4, 3, 2, 1], lowest_bit=1)
0
"""
m = len(bitset)
g = enumerate(bitset)
return sum(n_choose_k(bit - lowest_bit, m - i) for i, bit in g)
来源:https://stackoverflow.com/questions/22477192/hashfunction-to-map-combinations-of-5-to-7-cards