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#include <stack>
#include <list>
#include <cstdlib>
#include <getopt.h>
#include "eigen/Eigen/Dense"
#include "randutils/randutils.hpp"
#include "pcg-cpp/include/pcg_random.hpp"
using Rng = randutils::random_generator<pcg32>;
using Real = double;
using Vector = Eigen::Matrix<Real, Eigen::Dynamic, 1>;
using Matrix = Eigen::Matrix<Real, Eigen::Dynamic, Eigen::Dynamic>;
class Vertex;
class HalfEdge {
public:
unsigned index;
Vertex& neighbor;
HalfEdge(unsigned index, Vertex& v) : index(index), neighbor(v) {};
};
class Vertex {
public:
std::vector<HalfEdge> bonds;
unsigned index;
};
class Cluster : public std::list<std::reference_wrapper<const Vertex>> {};
unsigned uPow(unsigned x, unsigned a) {
unsigned result = 1;
while (a) {
if (a & 1) {
result *= x;
}
a >>= 1;
x *= x;
}
return result;
}
class Graph {
public:
unsigned D;
unsigned L;
std::vector<Vertex> vertices;
std::vector<unsigned> multiplicities;
unsigned Nv() const {
return vertices.size();
}
unsigned Ne() const {
return D * Nv();
}
unsigned squaredDistance(unsigned vi, unsigned vj) const {
unsigned sd = 0;
for (unsigned i = 0; i < D; i++) {
int x1 = (vi / uPow(L, i)) % uPow(L, i + 1);
int x2 = (vj / uPow(L, i)) % uPow(L, i + 1);
unsigned Δx = abs(x1 - x2);
if (Δx > L / 2) {
Δx = L - Δx;
}
sd += Δx * Δx;
}
return sd;
}
/* Initialize a square lattice */
Graph(unsigned D, unsigned L) : D(D), L(L), vertices(uPow(L, D)), multiplicities(D * L * L / 4) {
for (unsigned i = 0; i < Nv(); i++) {
vertices[i].index = i;
vertices[i].bonds.reserve(2 * D);
for (unsigned j = 0; j < D; j++) {
unsigned n1 = uPow(L, j + 1) * (i / uPow(L, j + 1)) + (i + uPow(L, j)) % uPow(L, j + 1);
unsigned n2 = uPow(L, j + 1) * (i / uPow(L, j + 1)) + (uPow(L, j + 1) + i - uPow(L, j)) % uPow(L, j + 1);
unsigned e1 = j * Nv() + i;
unsigned e2 = j * Nv() + n2;
HalfEdge he1(e1, vertices[n1]);
HalfEdge he2(e2, vertices[n2]);
vertices[i].bonds.push_back(he1);
vertices[i].bonds.push_back(he2);
}
}
for (const Vertex& v1 : vertices) {
for (const Vertex& v2 : vertices) {
unsigned dist = squaredDistance(v1.index, v2.index);
if (dist > 0) {
multiplicities[dist - 1]++;
}
}
}
}
std::vector<Cluster> markClusters(const std::vector<short unsigned>& activeEdges) const {
std::vector<Cluster> clusters;
std::vector<unsigned> indicies(Nv());
unsigned nClusters = 0;
for (const Vertex& v : vertices) {
if (indicies[v.index] == 0) {
nClusters++;
clusters.push_back({});
std::stack<std::reference_wrapper<const Vertex>> inCluster;
inCluster.push(v);
while (!inCluster.empty()) {
const Vertex& vn = inCluster.top();
inCluster.pop();
if (indicies[vn.index] == 0) {
indicies[vn.index] = nClusters;
clusters[nClusters - 1].push_back(vn);
}
for (const HalfEdge& e : vn.bonds) {
if (activeEdges[e.index] && indicies[e.neighbor.index] == 0) {
inCluster.push(e.neighbor);
}
}
}
}
}
return clusters;
}
Matrix laplacian(const std::vector<short unsigned>& activeEdges) const {
Matrix L = Matrix::Zero(Nv(), Nv());
for (const Vertex& v : vertices) {
for (const HalfEdge& e : v.bonds) {
if (activeEdges[e.index]) {
L(v.index, v.index) += 1;
L(v.index, e.neighbor.index) -= 1;
}
}
}
return L;
}
};
int main(int argc, char* argv[]) {
Rng r;
unsigned D = 2;
unsigned L = 8;
double p = 0.5;
unsigned n = 10;
int opt;
while ((opt = getopt(argc, argv, "D:L:p:n:")) != -1) {
switch (opt) {
case 'D':
D = atoi(optarg);
break;
case 'L':
L = atoi(optarg);
break;
case 'p':
p = atof(optarg);
break;
case 'n':
n = (unsigned)atof(optarg);
break;
default:
exit(1);
}
}
Graph G(D, L);
for (unsigned trials = 0; trials < n; trials++) {
std::vector<short unsigned> activeEdges(G.Ne());
for (short unsigned& edge : activeEdges) {
edge = r.uniform(0.0, 1.0) < p;
}
std::vector<Cluster> clusters = G.markClusters(activeEdges);
Matrix laplacian = G.laplacian(activeEdges);
std::vector<Real> conductivities(L * L * D / 4);
for (const Cluster& c : clusters) {
std::vector<unsigned> inds;
inds.reserve(c.size());
for (const Vertex& v : c){
inds.push_back(v.index);
}
Matrix subLaplacian = laplacian(inds, inds);
subLaplacian(0,0)++; /* Set voltage of first node to zero */
Matrix subLaplacianInv = subLaplacian.inverse();
for (unsigned i = 0; i < c.size(); i++) {
for (unsigned j = 0; j < i; j++) {
Vector input = Vector::Zero(inds.size());
input(i) = 1;
input(j) = -1;
Vector output = subLaplacianInv * input;
double ΔV = std::abs(output(i) - output(j));
conductivities[G.squaredDistance(inds[i], inds[j]) - 1] += 1 / ΔV;
}
}
}
for (unsigned i = 0; i < conductivities.size(); i++) {
if (G.multiplicities[i] != 0) {
std::cout << conductivities[i] / G.multiplicities[i] << " ";
} else {
std::cout << 0 << " ";
}
}
std::cout << std::endl;
}
return 0;
}
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