void shuffle2(char *t) {
vertex *u, *v;
int i, j;
/* exact copy case */
if (k_ >= l_) {
strncpy(t, s_, l_);
return;
}
/* simple permutation case */
if (k_ <= 1) {
strncpy(t, s_, l_);
permutec(t, l_);
return;
}
/* the Wilson algorithm for random arborescence */
for (i = 0; i < n_vertices; i++)
vertices[i].intree = 0;
vertices[root].intree = 1;
for (i = 0; i < n_vertices; i++) {
u = &vertices[i];
while (!u->intree) {
u->next = (*randfunc)() % u->n_indices;
u = &vertices[u->indices[u->next]];
}
u = &vertices[i];
while (!u->intree) {
u->intree = 1;
u = &vertices[u->indices[u->next]];
}
}
/* shuffle indices to prepare for walk */
for (i = 0; i < n_vertices; i++) {
u = &vertices[i];
if (i != root) {
j = u->indices[u->n_indices - 1]; /* swap the last one */
u->indices[u->n_indices - 1] = u->indices[u->next];
u->indices[u->next] = j;
permutei(u->indices, u->n_indices - 1); /* permute the rest */
} else
permutei(u->indices, u->n_indices);
u->i_indices = 0; /* reset to zero before walk */
}
/* walk the graph */
strncpy(t, s_, k_ - 1); /* the first let remains the same */
u = &vertices[0];
i = k_ - 1;
while (u->i_indices < u->n_indices) {
v = &vertices[u->indices[u->i_indices]];
j = v->i_sequence + k_ - 2;
t[i++] = s_[j];
u->i_indices++;
u = v;
}
}
static void test_discrete_choice_structure() {
time_t seed;
time(&seed);
MTwist rng(seed);
// Range of discrete distribution
const int N = TEST_SIZE;
// N * M = number of samples taken
const int M = TEST_SAMPLES;
// Test the average results of applying our distribution algorithm for entity connection relationships.
T tree(N*10);
int j = 17;
for (int i = 0; i < N; i++) {
tree.insert(j, j);
j = permutei(j, N);
}
std::vector<int> pick_count(N, 0);
for (int i = 0; i < N * M; i++) {
int p = tree.random_select(rng);
pick_count.at(p)++;
}
ASSERT(pick_count[0] == 0, "'0' should not be picked!");
// for i>0, normalize and output:
for (int i = 1; i < N; i += INCREMENT) {
printf("For %d: %.4f\n", i,pick_count[i] * SCALE_FACTOR / double(i));
}
StatCalc stats;
for (int i = 1; i < N; i++) {
stats.add_element(pick_count[i] * SCALE_FACTOR / double(i));
}
stats.print_summary();
}
static void measure_heap() {
PERF_TIMER2("measure_heap");
T tree;
const int N = TEST_SIZE * TEST_SAMPLES;
int j = N/2;
for (int i = 0; i < N; i++) {
tree.push(j);
j = permutei(j, N);
if ((j+i) % 52 == 0) {
tree.pop();
}
if (tree.size() > 100) {
while (!tree.empty()) {
tree.pop();
}
}
}
while (!tree.empty()) {
tree.pop();
}
}
