Line |
Branch |
Exec |
Source |
1 |
|
|
#include "percolation.hpp" |
2 |
|
|
#include "interaction.hpp" |
3 |
|
|
#include "particle.hpp" |
4 |
|
|
#include "potentials.hpp" |
5 |
|
|
#include "types.hpp" |
6 |
|
|
#include <algorithm> |
7 |
|
|
#include <iterator> |
8 |
|
|
#include <map> |
9 |
|
|
#include <set> |
10 |
|
|
|
11 |
|
✗ |
Clusterer::Clusterer(std::vector<Particle> &particles, const Vec &L, double cutoff, |
12 |
|
|
std::vector<int> &particle2Coordination, std::vector<int> &particle2Cluster, |
13 |
|
✗ |
std::map<int, std::list<int>> &cluster2Particles) |
14 |
|
✗ |
: particles(particles), L(L), cutoff(cutoff), cutoffsq(cutoff * cutoff), |
15 |
|
✗ |
particle2Coordination(particle2Coordination), particle2Cluster(particle2Cluster), |
16 |
|
✗ |
cluster2Particles(cluster2Particles) {} |
17 |
|
|
|
18 |
|
✗ |
double Clusterer::operator()(Particle &p1, Particle &p2) { |
19 |
|
✗ |
int i = std::distance(&particles.front(), &p1); |
20 |
|
✗ |
int j = std::distance(&particles.front(), &p2); |
21 |
|
✗ |
double distsq = r_ij(L, particles[i].r, particles[j].r).squaredNorm(); |
22 |
|
✗ |
if (distsq < cutoffsq && particle2Cluster[i] != particle2Cluster[j]) { |
23 |
|
✗ |
particle2Coordination[i]++; |
24 |
|
✗ |
particle2Coordination[j]++; |
25 |
|
✗ |
int oldCluster = std::max(particle2Cluster[i], particle2Cluster[j]); |
26 |
|
✗ |
int newCluster = std::min(particle2Cluster[i], particle2Cluster[j]); |
27 |
|
✗ |
for (int i : cluster2Particles[oldCluster]) { |
28 |
|
✗ |
particle2Cluster[i] = newCluster; |
29 |
|
|
} |
30 |
|
✗ |
cluster2Particles[newCluster].splice(cluster2Particles[newCluster].end(), |
31 |
|
✗ |
cluster2Particles[oldCluster]); |
32 |
|
|
} |
33 |
|
✗ |
return 0.; |
34 |
|
|
} |
35 |
|
|
|
36 |
|
75 |
Percolation::Percolation(System *system) |
37 |
|
75 |
: system(system), tLast(std::numeric_limits<double>::quiet_NaN()) {} |
38 |
|
|
|
39 |
|
✗ |
void Percolation::update() { |
40 |
|
✗ |
if (system->t == tLast) { |
41 |
|
✗ |
return; |
42 |
|
|
} |
43 |
|
|
// Initialize data structures |
44 |
|
✗ |
this->tLast = system->t; |
45 |
|
✗ |
int n = system->particles.size(); |
46 |
|
✗ |
numClusters = 0; |
47 |
|
✗ |
coordinationCount.clear(); |
48 |
|
✗ |
coordinationCount.resize(n + 1); |
49 |
|
✗ |
clusterSizeCount.clear(); |
50 |
|
✗ |
clusterSizeCount.resize(n + 1); |
51 |
|
✗ |
particle2Coordination.resize(n); |
52 |
|
✗ |
std::fill(particle2Coordination.begin(), particle2Coordination.end(), 0); |
53 |
|
✗ |
particle2Cluster.resize(n); |
54 |
|
✗ |
for (int i = 0; i < n; ++i) { |
55 |
|
✗ |
particle2Cluster[i] = i; |
56 |
|
✗ |
cluster2Particles[i] = {i}; |
57 |
|
|
} |
58 |
|
|
// Do the clustering algorithm |
59 |
|
✗ |
Clusterer clusterer(system->particles, system->L, system->interaction->internal->range, |
60 |
|
✗ |
particle2Coordination, particle2Cluster, cluster2Particles); |
61 |
|
✗ |
system->interaction->iteratePairs(clusterer, true, false); |
62 |
|
|
// Do the coordination statistics |
63 |
|
|
// Just go through all particles and make a histogram of the coordinations |
64 |
|
✗ |
for (int coord : particle2Coordination) { |
65 |
|
✗ |
coordinationCount[coord]++; |
66 |
|
|
} |
67 |
|
|
// Do the cluster sizes |
68 |
|
|
// Go through all cluster lists and get their sizes |
69 |
|
✗ |
for (auto &[_, particlesInCluster] : cluster2Particles) { |
70 |
|
✗ |
int clusterSize = particlesInCluster.size(); |
71 |
|
✗ |
if (clusterSize > 0) { |
72 |
|
✗ |
numClusters++; |
73 |
|
✗ |
clusterSizeCount[clusterSize] += clusterSize; |
74 |
|
|
} |
75 |
|
|
} |
76 |
|
|
// coordinationCount and clusterSizeCount are normed to the number of particles |
77 |
|
|
} |
78 |
|
|
|