implement a min-heap to record the top N probabilities for pruning

release/4.3a0
Varun Agrawal 2024-11-06 16:37:04 -05:00
parent d21f191219
commit 9666725473
1 changed files with 60 additions and 14 deletions

View File

@ -349,13 +349,67 @@ namespace gtsam {
: DiscreteFactor(keys.indices(), keys.cardinalities()), : DiscreteFactor(keys.indices(), keys.cardinalities()),
AlgebraicDecisionTree<Key>(keys, table) {} AlgebraicDecisionTree<Key>(keys, table) {}
/**
* @brief Min-Heap class to help with pruning.
* The `top` element is always the smallest value.
*/
class MinHeap {
std::vector<double> v_;
public:
/// Default constructor
MinHeap() {}
/// Push value onto the heap
void push(double x) {
v_.push_back(x);
std::make_heap(v_.begin(), v_.end(), std::greater<double>{});
}
/// Push value `x`, `n` number of times.
void push(double x, size_t n) {
v_.insert(v_.end(), n, x);
std::make_heap(v_.begin(), v_.end(), std::greater<double>{});
}
/// Pop the top value of the heap.
double pop() {
std::pop_heap(v_.begin(), v_.end(), std::greater<double>{});
double x = v_.back();
v_.pop_back();
return x;
}
/// Return the top value of the heap without popping it.
double top() { return v_.at(0); }
/**
* @brief Print the heap as a sequence.
*
* @param s A string to prologue the output.
*/
void print(const std::string& s = "") {
std::cout << (s.empty() ? "" : s + " ");
for (size_t i = 0; i < v_.size() - 1; i++) {
std::cout << v_.at(i) << ",";
}
std::cout << v_.at(v_.size() - 1) << std::endl;
}
/// Return true if heap is empty.
bool empty() const { return v_.empty(); }
/// Return the size of the heap.
size_t size() const { return v_.size(); }
};
/* ************************************************************************ */ /* ************************************************************************ */
DecisionTreeFactor DecisionTreeFactor::prune(size_t maxNrAssignments) const { DecisionTreeFactor DecisionTreeFactor::prune(size_t maxNrAssignments) const {
const size_t N = maxNrAssignments; const size_t N = maxNrAssignments;
// Set of all keys // Set of all keys
std::set<Key> allKeys(keys().begin(), keys().end()); std::set<Key> allKeys(keys().begin(), keys().end());
std::vector<double> min_heap; MinHeap min_heap;
auto op = [&](const Assignment<Key>& a, double p) { auto op = [&](const Assignment<Key>& a, double p) {
// Get all the keys in the current assignment // Get all the keys in the current assignment
@ -377,25 +431,17 @@ namespace gtsam {
} }
if (min_heap.empty()) { if (min_heap.empty()) {
for (size_t i = 0; i < std::min(nrAssignments, N); ++i) { min_heap.push(p, std::min(nrAssignments, N));
min_heap.push_back(p);
}
std::make_heap(min_heap.begin(), min_heap.end(),
std::greater<double>{});
} else { } else {
// If p is larger than the smallest element, // If p is larger than the smallest element,
// then we insert into the max heap. // then we insert into the max heap.
if (p > min_heap.at(0)) { if (p > min_heap.top()) {
for (size_t i = 0; i < std::min(nrAssignments, N); ++i) { for (size_t i = 0; i < std::min(nrAssignments, N); ++i) {
if (min_heap.size() == N) { if (min_heap.size() == N) {
std::pop_heap(min_heap.begin(), min_heap.end(), min_heap.pop();
std::greater<double>{});
min_heap.pop_back();
} }
min_heap.push_back(p); min_heap.push(p);
std::make_heap(min_heap.begin(), min_heap.end(),
std::greater<double>{});
} }
} }
} }
@ -403,7 +449,7 @@ namespace gtsam {
}; };
this->visitWith(op); this->visitWith(op);
double threshold = min_heap.at(0); double threshold = min_heap.top();
// Now threshold the decision tree // Now threshold the decision tree
size_t total = 0; size_t total = 0;