Hashing 2D, 3D and nD vectors

Question

What are good hashing functions (fast, good distribution, few collisions) for hashing 2d and 3d vectors composed of IEEE 32bit floats. I assume general 3d vectors, but algor

Answer 1

I wrote this in Python based on the comments seen here,

l = 5
n = 5
p1,p2,p3 = 73856093, 19349663, 83492791

x1 = [33,4,11]
x2 = [31,1,14]
x3 = [10,44,19]

def spatial_hash(x):
    ix,iy,iz = np.floor(x[0]/l), np.floor(x[1]/l), np.floor(x[2]/l)
    return (int(ix*p1) ^ int(iy*p2) ^ int(iz*p3)) % n

print (spatial_hash(x1))
print (spatial_hash(x2))
print (spatial_hash(x3))

It gives

1
1
3

It seemed to work.

In C++

#include 
#include 
#include 
#include 
#include 

#include 
using namespace Eigen;

using namespace std;
const int HASH_SIZE = 200;    
//const float MAX = 500.0;
const float L = 0.2f;
const float mmin = -1.f;
const float mmax = 1.f;

unordered_map> map ;

inline size_t hasha(Vector3d &p) {
    int ix = (unsigned int)((p[0]+2.f) / L);
    int iy = (unsigned int)((p[1]+2.f) / L);
    int iz = (unsigned int)((p[2]+2.f) / L);
    return (unsigned int)((ix * 73856093) ^ (iy * 19349663) ^ (iz * 83492791)) % HASH_SIZE;
}


int main(int argc, char** argv) {

    std::default_random_engine generator;
    std::uniform_real_distribution distribution(-1.0,1.0);

    
    for(size_t i=0;i<300;i++){
    float x = distribution(generator);
    float y = distribution(generator);
    float z = distribution(generator);
        Vector3d v(x,y,z);
        std::cout << hasha(v)  << " " << v[0] << " " << v[1] << " " << v[2] << std::endl;
    map[hasha(v)].push_back(v);
    vector entry = map[hasha(v)];
    std::cout << "size " << entry.size() << std::endl;
    }

    for (const auto & [ key, value ] : map) {
    cout << key << std::endl;
    vector v = map[key];
    float average = 0.0f;
    for (int i=0; i