问题
I have N points that lie only on the vertices of a cube, of dimension D, where D is something like 3.
A vertex may not contain any point. So every point has coordinates in {0, 1}D. I am only interested in query time, as long as the memory cost is reasonable ( not exponential in N for example :) ).
Given a query that lies on one of the cube's vertices and an input parameter r
, find all the vertices (thus points) that have hamming distance <= r
with the query.
What's the way to go in a c++ environment?
I am thinking of a kd-tree, but I am not sure and want help, any input, even approximative, would be appreciated! Since hamming distance comes into play, bitwise manipulations should help (e.g. XOR).
回答1:
There is a nice bithack to go from one bitmask with k
bits set to the lexicographically next permutation, which means it's fairly simple to loop through all masks with k
bits set. XORing these masks with an initial value gives all the values at hamming distance exactly k
away from it.
So for D
dimensions, where D
is less than 32 (otherwise change the types),
uint32_t limit = (1u << D) - 1;
for (int k = 1; k <= r; k++) {
uint32_t diff = (1u << k) - 1;
while (diff <= limit) {
// v is the input vertex
uint32_t vertex = v ^ diff;
// use it
diff = nextBitPermutation(diff);
}
}
Where nextBitPermutation
may be implemented in C++ as something like (if you have __builtin_ctz
)
uint32_t nextBitPermutation(uint32_t v) {
// see https://graphics.stanford.edu/~seander/bithacks.html#NextBitPermutation
uint32_t t = v | (v - 1);
return (t + 1) | (((~t & -~t) - 1) >> (__builtin_ctz(v) + 1));
}
Or for MSVC (not tested)
uint32_t nextBitPermutation(uint32_t v) {
// see https://graphics.stanford.edu/~seander/bithacks.html#NextBitPermutation
uint32_t t = v | (v - 1);
unsigned long tzc;
_BitScanForward(&tzc, v); // v != 0 so the return value doesn't matter
return (t + 1) | (((~t & -~t) - 1) >> (tzc + 1));
}
If D is really low, 4 or lower, the old popcnt
-with-pshufb
works really well and generally everything just lines up well, like this:
uint16_t query(int vertex, int r, int8_t* validmask)
{
// validmask should be array of 16 int8_t's,
// 0 for a vertex that doesn't exist, -1 if it does
__m128i valid = _mm_loadu_si128((__m128i*)validmask);
__m128i t0 = _mm_set1_epi8(vertex);
__m128i r0 = _mm_set1_epi8(r + 1);
__m128i all = _mm_setr_epi8(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15);
__m128i popcnt_lut = _mm_setr_epi8(0, 1, 1, 2, 1, 2, 2, 3, 1, 2, 2, 3, 2, 3, 3, 4);
__m128i dist = _mm_shuffle_epi8(popcnt_lut, _mm_xor_si128(t0, all));
__m128i close_enough = _mm_cmpgt_epi8(r0, dist);
__m128i result = _mm_and_si128(close_enough, valid);
return _mm_movemask_epi8(result);
}
This should be fairly fast; fast compared to the bithack above (nextBitPermutation
, which is fairly heavy, is used a lot there) and also compared to looping over all vertices and testing whether they are in range (even with builtin popcnt
, that automatically takes at least 16 cycles and the above shouldn't, assuming everything is cached or even permanently in a register). The downside is the result is annoying to work with, since it's a mask of which vertices both exist and are in range of the queried point, not a list of them. It would combine well with doing some processing on data associated with the points though.
This also scales down to D=3 of course, just make none of the points >= 8 valid. D>4 can be done similarly but it takes more code then, and since this is really a brute force solution that is only fast due to parallelism it fundamentally gets slower exponentially in D.
来源:https://stackoverflow.com/questions/40768507/query-points-on-the-vertices-of-a-hamming-cube