added doc for disceteKey in .h file, formatted in Google style.
Yoonwoo Kim
parent
361f9fa391
commit
7b3ce2fe34
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@ -16,10 +16,10 @@
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* @author Yoonwoo Kim
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*/
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#include <gtsam/discrete/DecisionTreeFactor.h>
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#include <gtsam/base/FastSet.h>
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#include <gtsam/hybrid/HybridValues.h>
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#include <gtsam/discrete/DecisionTreeFactor.h>
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#include <gtsam/discrete/TableFactor.h>
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#include <gtsam/hybrid/HybridValues.h>
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#include <boost/format.hpp>
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#include <utility>
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@ -28,528 +28,527 @@ using namespace std;
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namespace gtsam {
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/* ************************************************************************ */
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TableFactor::TableFactor() {}
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/* ************************************************************************ */
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TableFactor::TableFactor() {}
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/* ************************************************************************ */
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TableFactor::TableFactor(const DiscreteKeys& dkeys,
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const TableFactor& potentials)
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: DiscreteFactor(dkeys.indices()),
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cardinalities_(potentials .cardinalities_) {
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/* ************************************************************************ */
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TableFactor::TableFactor(const DiscreteKeys& dkeys,
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const TableFactor& potentials)
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: DiscreteFactor(dkeys.indices()),
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cardinalities_(potentials.cardinalities_) {
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sparse_table_ = potentials.sparse_table_;
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denominators_ = potentials.denominators_;
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sorted_dkeys_ = discreteKeys();
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sort(sorted_dkeys_.begin(), sorted_dkeys_.end());
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}
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}
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/* ************************************************************************ */
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TableFactor::TableFactor(const DiscreteKeys& dkeys,
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const Eigen::SparseVector<double>& table)
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: DiscreteFactor(dkeys.indices()), sparse_table_(table.size()) {
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sparse_table_ = table;
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double denom = table.size();
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for (const DiscreteKey& dkey : dkeys) {
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cardinalities_.insert(dkey);
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denom /= dkey.second;
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denominators_.insert(std::pair<Key, double>(dkey.first, denom));
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}
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sorted_dkeys_ = discreteKeys();
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sort(sorted_dkeys_.begin(), sorted_dkeys_.end());
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/* ************************************************************************ */
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TableFactor::TableFactor(const DiscreteKeys& dkeys,
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const Eigen::SparseVector<double>& table)
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: DiscreteFactor(dkeys.indices()), sparse_table_(table.size()) {
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sparse_table_ = table;
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double denom = table.size();
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for (const DiscreteKey& dkey : dkeys) {
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cardinalities_.insert(dkey);
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denom /= dkey.second;
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denominators_.insert(std::pair<Key, double>(dkey.first, denom));
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}
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sorted_dkeys_ = discreteKeys();
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sort(sorted_dkeys_.begin(), sorted_dkeys_.end());
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}
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/* ************************************************************************ */
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Eigen::SparseVector<double> TableFactor::Convert(
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/* ************************************************************************ */
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Eigen::SparseVector<double> TableFactor::Convert(
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const std::vector<double>& table) {
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Eigen::SparseVector<double> sparse_table(table.size());
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// Count number of nonzero elements in table and reserving the space.
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const uint64_t nnz = std::count_if(table.begin(), table.end(),
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[](uint64_t i) { return i != 0; });
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sparse_table.reserve(nnz);
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for (uint64_t i = 0; i < table.size(); i++) {
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if (table[i] != 0) sparse_table.insert(i) = table[i];
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Eigen::SparseVector<double> sparse_table(table.size());
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// Count number of nonzero elements in table and reserving the space.
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const uint64_t nnz = std::count_if(table.begin(), table.end(),
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[](uint64_t i) { return i != 0; });
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sparse_table.reserve(nnz);
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for (uint64_t i = 0; i < table.size(); i++) {
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if (table[i] != 0) sparse_table.insert(i) = table[i];
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}
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sparse_table.pruned();
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sparse_table.data().squeeze();
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return sparse_table;
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}
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/* ************************************************************************ */
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Eigen::SparseVector<double> TableFactor::Convert(const std::string& table) {
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// Convert string to doubles.
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std::vector<double> ys;
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std::istringstream iss(table);
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std::copy(std::istream_iterator<double>(iss), std::istream_iterator<double>(),
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std::back_inserter(ys));
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return Convert(ys);
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}
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/* ************************************************************************ */
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bool TableFactor::equals(const DiscreteFactor& other, double tol) const {
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if (!dynamic_cast<const TableFactor*>(&other)) {
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return false;
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} else {
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const auto& f(static_cast<const TableFactor&>(other));
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return sparse_table_.isApprox(f.sparse_table_, tol);
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}
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}
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/* ************************************************************************ */
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double TableFactor::operator()(const DiscreteValues& values) const {
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// a b c d => D * (C * (B * (a) + b) + c) + d
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uint64_t idx = 0, card = 1;
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for (auto it = sorted_dkeys_.rbegin(); it != sorted_dkeys_.rend(); ++it) {
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if (values.find(it->first) != values.end()) {
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idx += card * values.at(it->first);
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}
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sparse_table.pruned();
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sparse_table.data().squeeze();
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return sparse_table;
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card *= it->second;
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}
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return sparse_table_.coeff(idx);
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}
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/* ************************************************************************ */
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Eigen::SparseVector<double> TableFactor::Convert(const std::string& table) {
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// Convert string to doubles.
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std::vector<double> ys;
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std::istringstream iss(table);
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std::copy(std::istream_iterator<double>(iss), std::istream_iterator<double>(),
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std::back_inserter(ys));
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return Convert(ys);
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}
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/* ************************************************************************ */
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bool TableFactor::equals(const DiscreteFactor& other,
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double tol) const {
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if (!dynamic_cast<const TableFactor*>(&other)) {
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return false;
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} else {
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const auto& f(static_cast<const TableFactor&>(other));
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return sparse_table_.isApprox(f.sparse_table_, tol);
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/* ************************************************************************ */
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double TableFactor::findValue(const DiscreteValues& values) const {
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// a b c d => D * (C * (B * (a) + b) + c) + d
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uint64_t idx = 0, card = 1;
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for (auto it = keys_.rbegin(); it != keys_.rend(); ++it) {
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if (values.find(*it) != values.end()) {
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idx += card * values.at(*it);
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}
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card *= cardinality(*it);
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}
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return sparse_table_.coeff(idx);
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}
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/* ************************************************************************ */
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double TableFactor::operator()(const DiscreteValues& values) const {
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// a b c d => D * (C * (B * (a) + b) + c) + d
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uint64_t idx = 0, card = 1;
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for (auto it = sorted_dkeys_.rbegin(); it != sorted_dkeys_.rend(); ++it) {
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if (values.find(it->first) != values.end()) {
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idx += card * values.at(it->first);
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}
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card *= it->second;
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}
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return sparse_table_.coeff(idx);
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/* ************************************************************************ */
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double TableFactor::error(const DiscreteValues& values) const {
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return -log(evaluate(values));
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}
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/* ************************************************************************ */
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double TableFactor::error(const HybridValues& values) const {
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return error(values.discrete());
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}
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/* ************************************************************************ */
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DecisionTreeFactor TableFactor::operator*(const DecisionTreeFactor& f) const {
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return toDecisionTreeFactor() * f;
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}
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/* ************************************************************************ */
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DecisionTreeFactor TableFactor::toDecisionTreeFactor() const {
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DiscreteKeys dkeys = discreteKeys();
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std::vector<double> table;
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for (auto i = 0; i < sparse_table_.size(); i++) {
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table.push_back(sparse_table_.coeff(i));
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}
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DecisionTreeFactor f(dkeys, table);
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return f;
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}
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/* ************************************************************************ */
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double TableFactor::findValue(const DiscreteValues& values) const {
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// a b c d => D * (C * (B * (a) + b) + c) + d
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uint64_t idx = 0, card = 1;
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for (auto it = keys_.rbegin(); it != keys_.rend(); ++it) {
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if (values.find(*it) != values.end()) {
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idx += card * values.at(*it);
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}
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/* ************************************************************************ */
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TableFactor TableFactor::choose(const DiscreteValues parent_assign,
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DiscreteKeys parent_keys) const {
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if (parent_keys.empty()) return *this;
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// Unique representation of parent values.
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uint64_t unique = 0;
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uint64_t card = 1;
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for (auto it = keys_.rbegin(); it != keys_.rend(); ++it) {
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if (parent_assign.find(*it) != parent_assign.end()) {
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unique += parent_assign.at(*it) * card;
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card *= cardinality(*it);
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}
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return sparse_table_.coeff(idx);
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}
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/* ************************************************************************ */
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double TableFactor::error(const DiscreteValues& values) const {
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return -log(evaluate(values));
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}
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/* ************************************************************************ */
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double TableFactor::error(const HybridValues& values) const {
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return error(values.discrete());
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}
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// Find child DiscreteKeys
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DiscreteKeys child_dkeys;
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std::sort(parent_keys.begin(), parent_keys.end());
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std::set_difference(sorted_dkeys_.begin(), sorted_dkeys_.end(),
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parent_keys.begin(), parent_keys.end(),
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std::back_inserter(child_dkeys));
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/* ************************************************************************ */
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DecisionTreeFactor TableFactor::operator*(const DecisionTreeFactor& f) const {
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return toDecisionTreeFactor() * f;
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}
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// Create child sparse table to populate.
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uint64_t child_card = 1;
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for (const DiscreteKey& child_dkey : child_dkeys)
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child_card *= child_dkey.second;
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Eigen::SparseVector<double> child_sparse_table_(child_card);
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child_sparse_table_.reserve(child_card);
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/* ************************************************************************ */
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DecisionTreeFactor TableFactor::toDecisionTreeFactor() const {
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DiscreteKeys dkeys = discreteKeys();
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std::vector<double> table;
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for (auto i = 0; i < sparse_table_.size(); i++) {
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table.push_back(sparse_table_.coeff(i));
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// Populate child sparse table.
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for (SparseIt it(sparse_table_); it; ++it) {
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// Create unique representation of parent keys
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uint64_t parent_unique = uniqueRep(parent_keys, it.index());
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// Populate the table
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if (parent_unique == unique) {
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uint64_t idx = uniqueRep(child_dkeys, it.index());
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child_sparse_table_.insert(idx) = it.value();
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}
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DecisionTreeFactor f(dkeys, table);
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}
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child_sparse_table_.pruned();
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child_sparse_table_.data().squeeze();
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return TableFactor(child_dkeys, child_sparse_table_);
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}
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/* ************************************************************************ */
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double TableFactor::safe_div(const double& a, const double& b) {
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// The use for safe_div is when we divide the product factor by the sum
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// factor. If the product or sum is zero, we accord zero probability to the
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// event.
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return (a == 0 || b == 0) ? 0 : (a / b);
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}
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/* ************************************************************************ */
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void TableFactor::print(const string& s, const KeyFormatter& formatter) const {
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cout << s;
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cout << " f[";
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for (auto&& key : keys())
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cout << boost::format(" (%1%,%2%),") % formatter(key) % cardinality(key);
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cout << " ]" << endl;
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for (SparseIt it(sparse_table_); it; ++it) {
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DiscreteValues assignment = findAssignments(it.index());
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for (auto&& kv : assignment) {
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cout << "(" << formatter(kv.first) << ", " << kv.second << ")";
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}
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cout << " | " << it.value() << " | " << it.index() << endl;
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}
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cout << "number of nnzs: " << sparse_table_.nonZeros() << endl;
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}
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/* ************************************************************************ */
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TableFactor TableFactor::apply(const TableFactor& f, Binary op) const {
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if (keys_.empty() && sparse_table_.nonZeros() == 0)
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return f;
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}
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/* ************************************************************************ */
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TableFactor TableFactor::choose(const DiscreteValues parent_assign,
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DiscreteKeys parent_keys) const {
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if (parent_keys.empty()) return *this;
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// Unique representation of parent values.
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uint64_t unique = 0;
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uint64_t card = 1;
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for (auto it = keys_.rbegin(); it != keys_.rend(); ++it) {
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if (parent_assign.find(*it) != parent_assign.end()) {
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unique += parent_assign.at(*it) * card;
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card *= cardinality(*it);
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}
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}
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// Find child DiscreteKeys
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DiscreteKeys child_dkeys;
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std::sort(parent_keys.begin(), parent_keys.end());
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std::set_difference(sorted_dkeys_.begin(), sorted_dkeys_.end(), parent_keys.begin(),
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parent_keys.end(), std::back_inserter(child_dkeys));
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// Create child sparse table to populate.
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uint64_t child_card = 1;
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for (const DiscreteKey& child_dkey : child_dkeys)
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child_card *= child_dkey.second;
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Eigen::SparseVector<double> child_sparse_table_(child_card);
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child_sparse_table_.reserve(child_card);
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// Populate child sparse table.
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for (SparseIt it(sparse_table_); it; ++it) {
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// Create unique representation of parent keys
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uint64_t parent_unique = uniqueRep(parent_keys, it.index());
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// Populate the table
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if (parent_unique == unique) {
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uint64_t idx = uniqueRep(child_dkeys, it.index());
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child_sparse_table_.insert(idx) = it.value();
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}
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}
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child_sparse_table_.pruned();
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child_sparse_table_.data().squeeze();
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return TableFactor(child_dkeys, child_sparse_table_);
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}
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/* ************************************************************************ */
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double TableFactor::safe_div(const double& a, const double& b) {
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// The use for safe_div is when we divide the product factor by the sum
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// factor. If the product or sum is zero, we accord zero probability to the
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// event.
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return (a == 0 || b == 0) ? 0 : (a / b);
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}
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/* ************************************************************************ */
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void TableFactor::print(const string& s, const KeyFormatter& formatter) const {
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cout << s;
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cout << " f[";
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for (auto&& key : keys())
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cout << boost::format(" (%1%,%2%),") % formatter(key) % cardinality(key);
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cout << " ]" << endl;
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for (SparseIt it(sparse_table_); it; ++it) {
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DiscreteValues assignment = findAssignments(it.index());
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for (auto&& kv : assignment) {
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cout << "(" << formatter(kv.first) << ", " << kv.second << ")";
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}
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cout << " | " << it.value() << " | " << it.index() << endl;
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}
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cout << "number of nnzs: " <<sparse_table_.nonZeros() << endl;
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}
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/* ************************************************************************ */
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TableFactor TableFactor::apply(const TableFactor& f, Binary op) const {
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if (keys_.empty() && sparse_table_.nonZeros() == 0)
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return f;
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else if (f.keys_.empty() && f.sparse_table_.nonZeros() == 0)
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return *this;
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// 1. Identify keys for contract and free modes.
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DiscreteKeys contract_dkeys = contractDkeys(f);
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DiscreteKeys f_free_dkeys = f.freeDkeys(*this);
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DiscreteKeys union_dkeys = unionDkeys(f);
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// 2. Create hash table for input factor f
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unordered_map<uint64_t, AssignValList> map_f =
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else if (f.keys_.empty() && f.sparse_table_.nonZeros() == 0)
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return *this;
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// 1. Identify keys for contract and free modes.
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DiscreteKeys contract_dkeys = contractDkeys(f);
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DiscreteKeys f_free_dkeys = f.freeDkeys(*this);
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DiscreteKeys union_dkeys = unionDkeys(f);
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// 2. Create hash table for input factor f
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unordered_map<uint64_t, AssignValList> map_f =
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f.createMap(contract_dkeys, f_free_dkeys);
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// 3. Initialize multiplied factor.
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uint64_t card = 1;
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for (auto u_dkey : union_dkeys) card *= u_dkey.second;
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Eigen::SparseVector<double> mult_sparse_table(card);
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mult_sparse_table.reserve(card);
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// 3. Multiply.
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for (SparseIt it(sparse_table_); it; ++it) {
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uint64_t contract_unique = uniqueRep(contract_dkeys, it.index());
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if (map_f.find(contract_unique) == map_f.end()) continue;
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for (auto assignVal : map_f[contract_unique]) {
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uint64_t union_idx = unionRep(union_dkeys, assignVal.first, it.index());
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mult_sparse_table.insert(union_idx) = op(it.value(), assignVal.second);
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}
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// 3. Initialize multiplied factor.
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uint64_t card = 1;
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for (auto u_dkey : union_dkeys) card *= u_dkey.second;
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Eigen::SparseVector<double> mult_sparse_table(card);
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mult_sparse_table.reserve(card);
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// 3. Multiply.
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for (SparseIt it(sparse_table_); it; ++it) {
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uint64_t contract_unique = uniqueRep(contract_dkeys, it.index());
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if (map_f.find(contract_unique) == map_f.end()) continue;
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for (auto assignVal : map_f[contract_unique]) {
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uint64_t union_idx = unionRep(union_dkeys, assignVal.first, it.index());
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mult_sparse_table.insert(union_idx) = op(it.value(), assignVal.second);
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}
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// 4. Free unused memory.
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mult_sparse_table.pruned();
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mult_sparse_table.data().squeeze();
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// 5. Create union keys and return.
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return TableFactor(union_dkeys, mult_sparse_table);
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}
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// 4. Free unused memory.
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mult_sparse_table.pruned();
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mult_sparse_table.data().squeeze();
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// 5. Create union keys and return.
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return TableFactor(union_dkeys, mult_sparse_table);
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}
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/* ************************************************************************ */
|
||||
DiscreteKeys TableFactor::contractDkeys(const TableFactor& f) const {
|
||||
// Find contract modes.
|
||||
DiscreteKeys contract;
|
||||
set_intersection(sorted_dkeys_.begin(), sorted_dkeys_.end(),
|
||||
f.sorted_dkeys_.begin(), f.sorted_dkeys_.end(),
|
||||
back_inserter(contract));
|
||||
return contract;
|
||||
}
|
||||
/* ************************************************************************ */
|
||||
DiscreteKeys TableFactor::contractDkeys(const TableFactor& f) const {
|
||||
// Find contract modes.
|
||||
DiscreteKeys contract;
|
||||
set_intersection(sorted_dkeys_.begin(), sorted_dkeys_.end(),
|
||||
f.sorted_dkeys_.begin(), f.sorted_dkeys_.end(),
|
||||
back_inserter(contract));
|
||||
return contract;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
DiscreteKeys TableFactor::freeDkeys(const TableFactor& f) const {
|
||||
// Find free modes.
|
||||
DiscreteKeys free;
|
||||
set_difference(sorted_dkeys_.begin(), sorted_dkeys_.end(),
|
||||
f.sorted_dkeys_.begin(), f.sorted_dkeys_.end(),
|
||||
back_inserter(free));
|
||||
return free;
|
||||
}
|
||||
/* ************************************************************************ */
|
||||
DiscreteKeys TableFactor::freeDkeys(const TableFactor& f) const {
|
||||
// Find free modes.
|
||||
DiscreteKeys free;
|
||||
set_difference(sorted_dkeys_.begin(), sorted_dkeys_.end(),
|
||||
f.sorted_dkeys_.begin(), f.sorted_dkeys_.end(),
|
||||
back_inserter(free));
|
||||
return free;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
DiscreteKeys TableFactor::unionDkeys(const TableFactor& f) const {
|
||||
// Find union modes.
|
||||
DiscreteKeys union_dkeys;
|
||||
set_union(sorted_dkeys_.begin(), sorted_dkeys_.end(),
|
||||
f.sorted_dkeys_.begin(), f.sorted_dkeys_.end(),
|
||||
back_inserter(union_dkeys));
|
||||
return union_dkeys;
|
||||
}
|
||||
/* ************************************************************************ */
|
||||
DiscreteKeys TableFactor::unionDkeys(const TableFactor& f) const {
|
||||
// Find union modes.
|
||||
DiscreteKeys union_dkeys;
|
||||
set_union(sorted_dkeys_.begin(), sorted_dkeys_.end(), f.sorted_dkeys_.begin(),
|
||||
f.sorted_dkeys_.end(), back_inserter(union_dkeys));
|
||||
return union_dkeys;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
uint64_t TableFactor::unionRep(const DiscreteKeys& union_keys,
|
||||
const DiscreteValues& f_free, const uint64_t idx) const {
|
||||
uint64_t union_idx = 0, card = 1;
|
||||
for (auto it = union_keys.rbegin(); it != union_keys.rend(); it++) {
|
||||
if (f_free.find(it->first) == f_free.end()) {
|
||||
union_idx += keyValueForIndex(it->first, idx) * card;
|
||||
} else {
|
||||
union_idx += f_free.at(it->first) * card;
|
||||
}
|
||||
card *= it->second;
|
||||
/* ************************************************************************ */
|
||||
uint64_t TableFactor::unionRep(const DiscreteKeys& union_keys,
|
||||
const DiscreteValues& f_free,
|
||||
const uint64_t idx) const {
|
||||
uint64_t union_idx = 0, card = 1;
|
||||
for (auto it = union_keys.rbegin(); it != union_keys.rend(); it++) {
|
||||
if (f_free.find(it->first) == f_free.end()) {
|
||||
union_idx += keyValueForIndex(it->first, idx) * card;
|
||||
} else {
|
||||
union_idx += f_free.at(it->first) * card;
|
||||
}
|
||||
return union_idx;
|
||||
card *= it->second;
|
||||
}
|
||||
return union_idx;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
unordered_map<uint64_t, TableFactor::AssignValList> TableFactor::createMap(
|
||||
/* ************************************************************************ */
|
||||
unordered_map<uint64_t, TableFactor::AssignValList> TableFactor::createMap(
|
||||
const DiscreteKeys& contract, const DiscreteKeys& free) const {
|
||||
// 1. Initialize map.
|
||||
unordered_map<uint64_t, AssignValList> map_f;
|
||||
// 2. Iterate over nonzero elements.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
// 3. Create unique representation of contract modes.
|
||||
uint64_t unique_rep = uniqueRep(contract, it.index());
|
||||
// 4. Create assignment for free modes.
|
||||
DiscreteValues free_assignments;
|
||||
for (auto& key : free) free_assignments[key.first]
|
||||
= keyValueForIndex(key.first, it.index());
|
||||
// 5. Populate map.
|
||||
if (map_f.find(unique_rep) == map_f.end()) {
|
||||
map_f[unique_rep] = {make_pair(free_assignments, it.value())};
|
||||
} else {
|
||||
map_f[unique_rep].push_back(make_pair(free_assignments, it.value()));
|
||||
}
|
||||
// 1. Initialize map.
|
||||
unordered_map<uint64_t, AssignValList> map_f;
|
||||
// 2. Iterate over nonzero elements.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
// 3. Create unique representation of contract modes.
|
||||
uint64_t unique_rep = uniqueRep(contract, it.index());
|
||||
// 4. Create assignment for free modes.
|
||||
DiscreteValues free_assignments;
|
||||
for (auto& key : free)
|
||||
free_assignments[key.first] = keyValueForIndex(key.first, it.index());
|
||||
// 5. Populate map.
|
||||
if (map_f.find(unique_rep) == map_f.end()) {
|
||||
map_f[unique_rep] = {make_pair(free_assignments, it.value())};
|
||||
} else {
|
||||
map_f[unique_rep].push_back(make_pair(free_assignments, it.value()));
|
||||
}
|
||||
return map_f;
|
||||
}
|
||||
return map_f;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
uint64_t TableFactor::uniqueRep(const DiscreteKeys& dkeys, const uint64_t idx) const {
|
||||
if (dkeys.empty()) return 0;
|
||||
uint64_t unique_rep = 0, card = 1;
|
||||
for (auto it = dkeys.rbegin(); it != dkeys.rend(); it++) {
|
||||
unique_rep += keyValueForIndex(it->first, idx) * card;
|
||||
card *= it->second;
|
||||
}
|
||||
return unique_rep;
|
||||
/* ************************************************************************ */
|
||||
uint64_t TableFactor::uniqueRep(const DiscreteKeys& dkeys,
|
||||
const uint64_t idx) const {
|
||||
if (dkeys.empty()) return 0;
|
||||
uint64_t unique_rep = 0, card = 1;
|
||||
for (auto it = dkeys.rbegin(); it != dkeys.rend(); it++) {
|
||||
unique_rep += keyValueForIndex(it->first, idx) * card;
|
||||
card *= it->second;
|
||||
}
|
||||
return unique_rep;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
uint64_t TableFactor::uniqueRep(const DiscreteValues& assignments) const {
|
||||
if (assignments.empty()) return 0;
|
||||
uint64_t unique_rep = 0, card = 1;
|
||||
for (auto it = assignments.rbegin(); it != assignments.rend(); it++) {
|
||||
unique_rep += it->second * card;
|
||||
card *= cardinalities_.at(it->first);
|
||||
}
|
||||
return unique_rep;
|
||||
/* ************************************************************************ */
|
||||
uint64_t TableFactor::uniqueRep(const DiscreteValues& assignments) const {
|
||||
if (assignments.empty()) return 0;
|
||||
uint64_t unique_rep = 0, card = 1;
|
||||
for (auto it = assignments.rbegin(); it != assignments.rend(); it++) {
|
||||
unique_rep += it->second * card;
|
||||
card *= cardinalities_.at(it->first);
|
||||
}
|
||||
return unique_rep;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
DiscreteValues TableFactor::findAssignments(const uint64_t idx) const {
|
||||
DiscreteValues assignment;
|
||||
for (Key key : keys_) {
|
||||
assignment[key] = keyValueForIndex(key, idx);
|
||||
}
|
||||
return assignment;
|
||||
/* ************************************************************************ */
|
||||
DiscreteValues TableFactor::findAssignments(const uint64_t idx) const {
|
||||
DiscreteValues assignment;
|
||||
for (Key key : keys_) {
|
||||
assignment[key] = keyValueForIndex(key, idx);
|
||||
}
|
||||
return assignment;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
TableFactor::shared_ptr TableFactor::combine(
|
||||
size_t nrFrontals, Binary op) const {
|
||||
if (nrFrontals > size()) {
|
||||
throw invalid_argument(
|
||||
"TableFactor::combine: invalid number of frontal "
|
||||
"keys " +
|
||||
to_string(nrFrontals) + ", nr.keys=" + std::to_string(size()));
|
||||
}
|
||||
// Find remaining keys.
|
||||
DiscreteKeys remain_dkeys;
|
||||
uint64_t card = 1;
|
||||
for (auto i = nrFrontals; i < keys_.size(); i++) {
|
||||
remain_dkeys.push_back(discreteKey(i));
|
||||
card *= cardinality(keys_[i]);
|
||||
}
|
||||
// Create combined table.
|
||||
Eigen::SparseVector<double> combined_table(card);
|
||||
combined_table.reserve(sparse_table_.nonZeros());
|
||||
// Populate combined table.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
uint64_t idx = uniqueRep(remain_dkeys, it.index());
|
||||
double new_val = op(combined_table.coeff(idx), it.value());
|
||||
combined_table.coeffRef(idx) = new_val;
|
||||
/* ************************************************************************ */
|
||||
TableFactor::shared_ptr TableFactor::combine(size_t nrFrontals,
|
||||
Binary op) const {
|
||||
if (nrFrontals > size()) {
|
||||
throw invalid_argument(
|
||||
"TableFactor::combine: invalid number of frontal "
|
||||
"keys " +
|
||||
to_string(nrFrontals) + ", nr.keys=" + std::to_string(size()));
|
||||
}
|
||||
// Find remaining keys.
|
||||
DiscreteKeys remain_dkeys;
|
||||
uint64_t card = 1;
|
||||
for (auto i = nrFrontals; i < keys_.size(); i++) {
|
||||
remain_dkeys.push_back(discreteKey(i));
|
||||
card *= cardinality(keys_[i]);
|
||||
}
|
||||
// Create combined table.
|
||||
Eigen::SparseVector<double> combined_table(card);
|
||||
combined_table.reserve(sparse_table_.nonZeros());
|
||||
// Populate combined table.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
uint64_t idx = uniqueRep(remain_dkeys, it.index());
|
||||
double new_val = op(combined_table.coeff(idx), it.value());
|
||||
combined_table.coeffRef(idx) = new_val;
|
||||
}
|
||||
// Free unused memory.
|
||||
combined_table.pruned();
|
||||
combined_table.data().squeeze();
|
||||
return std::make_shared<TableFactor>(remain_dkeys, combined_table);
|
||||
}
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
TableFactor::shared_ptr TableFactor::combine(
|
||||
const Ordering& frontalKeys, Binary op) const {
|
||||
if (frontalKeys.size() > size()) {
|
||||
throw invalid_argument(
|
||||
"TableFactor::combine: invalid number of frontal "
|
||||
"keys " +
|
||||
std::to_string(frontalKeys.size()) + ", nr.keys=" +
|
||||
std::to_string(size()));
|
||||
}
|
||||
// Find remaining keys.
|
||||
DiscreteKeys remain_dkeys;
|
||||
uint64_t card = 1;
|
||||
for (Key key : keys_) {
|
||||
if (std::find(frontalKeys.begin(), frontalKeys.end(), key) ==
|
||||
frontalKeys.end()) {
|
||||
remain_dkeys.emplace_back(key, cardinality(key));
|
||||
card *= cardinality(key);
|
||||
}
|
||||
}
|
||||
// Create combined table.
|
||||
Eigen::SparseVector<double> combined_table(card);
|
||||
combined_table.reserve(sparse_table_.nonZeros());
|
||||
// Populate combined table.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
uint64_t idx = uniqueRep(remain_dkeys, it.index());
|
||||
double new_val = op(combined_table.coeff(idx), it.value());
|
||||
combined_table.coeffRef(idx) = new_val;
|
||||
}
|
||||
// Free unused memory.
|
||||
combined_table.pruned();
|
||||
combined_table.data().squeeze();
|
||||
return std::make_shared<TableFactor>(remain_dkeys, combined_table);
|
||||
/* ************************************************************************ */
|
||||
TableFactor::shared_ptr TableFactor::combine(const Ordering& frontalKeys,
|
||||
Binary op) const {
|
||||
if (frontalKeys.size() > size()) {
|
||||
throw invalid_argument(
|
||||
"TableFactor::combine: invalid number of frontal "
|
||||
"keys " +
|
||||
std::to_string(frontalKeys.size()) +
|
||||
", nr.keys=" + std::to_string(size()));
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
size_t TableFactor::keyValueForIndex(Key target_key, uint64_t index) const {
|
||||
// http://phrogz.net/lazy-cartesian-product
|
||||
return (index / denominators_.at(target_key)) % cardinality(target_key);
|
||||
// Find remaining keys.
|
||||
DiscreteKeys remain_dkeys;
|
||||
uint64_t card = 1;
|
||||
for (Key key : keys_) {
|
||||
if (std::find(frontalKeys.begin(), frontalKeys.end(), key) ==
|
||||
frontalKeys.end()) {
|
||||
remain_dkeys.emplace_back(key, cardinality(key));
|
||||
card *= cardinality(key);
|
||||
}
|
||||
}
|
||||
// Create combined table.
|
||||
Eigen::SparseVector<double> combined_table(card);
|
||||
combined_table.reserve(sparse_table_.nonZeros());
|
||||
// Populate combined table.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
uint64_t idx = uniqueRep(remain_dkeys, it.index());
|
||||
double new_val = op(combined_table.coeff(idx), it.value());
|
||||
combined_table.coeffRef(idx) = new_val;
|
||||
}
|
||||
// Free unused memory.
|
||||
combined_table.pruned();
|
||||
combined_table.data().squeeze();
|
||||
return std::make_shared<TableFactor>(remain_dkeys, combined_table);
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
std::vector<std::pair<DiscreteValues, double>> TableFactor::enumerate()
|
||||
const {
|
||||
// Get all possible assignments
|
||||
std::vector<std::pair<Key, size_t>> pairs = discreteKeys();
|
||||
// Reverse to make cartesian product output a more natural ordering.
|
||||
std::vector<std::pair<Key, size_t>> rpairs(pairs.rbegin(), pairs.rend());
|
||||
const auto assignments = DiscreteValues::CartesianProduct(rpairs);
|
||||
// Construct unordered_map with values
|
||||
std::vector<std::pair<DiscreteValues, double>> result;
|
||||
for (const auto& assignment : assignments) {
|
||||
result.emplace_back(assignment, operator()(assignment));
|
||||
}
|
||||
return result;
|
||||
}
|
||||
/* ************************************************************************ */
|
||||
size_t TableFactor::keyValueForIndex(Key target_key, uint64_t index) const {
|
||||
// http://phrogz.net/lazy-cartesian-product
|
||||
return (index / denominators_.at(target_key)) % cardinality(target_key);
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
DiscreteKeys TableFactor::discreteKeys() const {
|
||||
DiscreteKeys result;
|
||||
for (auto&& key : keys()) {
|
||||
DiscreteKey dkey(key, cardinality(key));
|
||||
if (std::find(result.begin(), result.end(), dkey) == result.end()) {
|
||||
result.push_back(dkey);
|
||||
}
|
||||
}
|
||||
return result;
|
||||
/* ************************************************************************ */
|
||||
std::vector<std::pair<DiscreteValues, double>> TableFactor::enumerate() const {
|
||||
// Get all possible assignments
|
||||
std::vector<std::pair<Key, size_t>> pairs = discreteKeys();
|
||||
// Reverse to make cartesian product output a more natural ordering.
|
||||
std::vector<std::pair<Key, size_t>> rpairs(pairs.rbegin(), pairs.rend());
|
||||
const auto assignments = DiscreteValues::CartesianProduct(rpairs);
|
||||
// Construct unordered_map with values
|
||||
std::vector<std::pair<DiscreteValues, double>> result;
|
||||
for (const auto& assignment : assignments) {
|
||||
result.emplace_back(assignment, operator()(assignment));
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
DiscreteKeys TableFactor::discreteKeys() const {
|
||||
DiscreteKeys result;
|
||||
for (auto&& key : keys()) {
|
||||
DiscreteKey dkey(key, cardinality(key));
|
||||
if (std::find(result.begin(), result.end(), dkey) == result.end()) {
|
||||
result.push_back(dkey);
|
||||
}
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
// Print out header.
|
||||
/* ************************************************************************ */
|
||||
string TableFactor::markdown(const KeyFormatter& keyFormatter,
|
||||
const Names& names) const {
|
||||
stringstream ss;
|
||||
|
||||
// Print out header.
|
||||
/* ************************************************************************ */
|
||||
string TableFactor::markdown(const KeyFormatter& keyFormatter,
|
||||
const Names& names) const {
|
||||
stringstream ss;
|
||||
ss << "|";
|
||||
for (auto& key : keys()) {
|
||||
ss << keyFormatter(key) << "|";
|
||||
}
|
||||
ss << "value|\n";
|
||||
|
||||
// Print out header.
|
||||
// Print out separator with alignment hints.
|
||||
ss << "|";
|
||||
for (size_t j = 0; j < size(); j++) ss << ":-:|";
|
||||
ss << ":-:|\n";
|
||||
|
||||
// Print out all rows.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
DiscreteValues assignment = findAssignments(it.index());
|
||||
ss << "|";
|
||||
for (auto& key : keys()) {
|
||||
ss << keyFormatter(key) << "|";
|
||||
size_t index = assignment.at(key);
|
||||
ss << DiscreteValues::Translate(names, key, index) << "|";
|
||||
}
|
||||
ss << "value|\n";
|
||||
|
||||
// Print out separator with alignment hints.
|
||||
ss << "|";
|
||||
for (size_t j = 0; j < size(); j++) ss << ":-:|";
|
||||
ss << ":-:|\n";
|
||||
|
||||
// Print out all rows.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
DiscreteValues assignment = findAssignments(it.index());
|
||||
ss << "|";
|
||||
for (auto& key : keys()) {
|
||||
size_t index = assignment.at(key);
|
||||
ss << DiscreteValues::Translate(names, key, index) << "|";
|
||||
}
|
||||
ss << it.value() << "|\n";
|
||||
}
|
||||
return ss.str();
|
||||
ss << it.value() << "|\n";
|
||||
}
|
||||
return ss.str();
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
string TableFactor::html(const KeyFormatter& keyFormatter,
|
||||
const Names& names) const {
|
||||
stringstream ss;
|
||||
/* ************************************************************************ */
|
||||
string TableFactor::html(const KeyFormatter& keyFormatter,
|
||||
const Names& names) const {
|
||||
stringstream ss;
|
||||
|
||||
// Print out preamble.
|
||||
ss << "<div>\n<table class='TableFactor'>\n <thead>\n";
|
||||
// Print out preamble.
|
||||
ss << "<div>\n<table class='TableFactor'>\n <thead>\n";
|
||||
|
||||
// Print out header row.
|
||||
// Print out header row.
|
||||
ss << " <tr>";
|
||||
for (auto& key : keys()) {
|
||||
ss << "<th>" << keyFormatter(key) << "</th>";
|
||||
}
|
||||
ss << "<th>value</th></tr>\n";
|
||||
|
||||
// Finish header and start body.
|
||||
ss << " </thead>\n <tbody>\n";
|
||||
|
||||
// Print out all rows.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
DiscreteValues assignment = findAssignments(it.index());
|
||||
ss << " <tr>";
|
||||
for (auto& key : keys()) {
|
||||
ss << "<th>" << keyFormatter(key) << "</th>";
|
||||
size_t index = assignment.at(key);
|
||||
ss << "<th>" << DiscreteValues::Translate(names, key, index) << "</th>";
|
||||
}
|
||||
ss << "<th>value</th></tr>\n";
|
||||
ss << "<td>" << it.value() << "</td>"; // value
|
||||
ss << "</tr>\n";
|
||||
}
|
||||
ss << " </tbody>\n</table>\n</div>";
|
||||
return ss.str();
|
||||
}
|
||||
|
||||
// Finish header and start body.
|
||||
ss << " </thead>\n <tbody>\n";
|
||||
|
||||
// Print out all rows.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
DiscreteValues assignment = findAssignments(it.index());
|
||||
ss << " <tr>";
|
||||
for (auto& key : keys()) {
|
||||
size_t index = assignment.at(key);
|
||||
ss << "<th>" << DiscreteValues::Translate(names, key, index) << "</th>";
|
||||
}
|
||||
ss << "<td>" << it.value() << "</td>"; // value
|
||||
ss << "</tr>\n";
|
||||
}
|
||||
ss << " </tbody>\n</table>\n</div>";
|
||||
return ss.str();
|
||||
/* ************************************************************************ */
|
||||
TableFactor TableFactor::prune(size_t maxNrAssignments) const {
|
||||
const size_t N = maxNrAssignments;
|
||||
|
||||
// Get the probabilities in the TableFactor so we can threshold.
|
||||
vector<pair<Eigen::Index, double>> probabilities;
|
||||
|
||||
// Store non-zero probabilities along with their indices in a vector.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
probabilities.emplace_back(it.index(), it.value());
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
TableFactor TableFactor::prune(size_t maxNrAssignments) const {
|
||||
const size_t N = maxNrAssignments;
|
||||
// The number of probabilities can be lower than max_leaves.
|
||||
if (probabilities.size() <= N) return *this;
|
||||
|
||||
// Get the probabilities in the TableFactor so we can threshold.
|
||||
vector<pair<Eigen::Index, double>> probabilities;
|
||||
|
||||
// Store non-zero probabilities along with their indices in a vector.
|
||||
for (SparseIt it(sparse_table_); it; ++it) {
|
||||
probabilities.emplace_back(it.index(), it.value());
|
||||
}
|
||||
|
||||
// The number of probabilities can be lower than max_leaves.
|
||||
if (probabilities.size() <= N) return *this;
|
||||
|
||||
// Sort the vector in descending order based on the element values.
|
||||
sort(probabilities.begin(), probabilities.end(), [] (
|
||||
const std::pair<Eigen::Index, double>& a,
|
||||
const std::pair<Eigen::Index, double>& b) {
|
||||
return a.second > b.second;
|
||||
});
|
||||
|
||||
// Keep the largest N probabilities in the vector.
|
||||
if (probabilities.size() > N) probabilities.resize(N);
|
||||
// Sort the vector in descending order based on the element values.
|
||||
sort(probabilities.begin(), probabilities.end(),
|
||||
[](const std::pair<Eigen::Index, double>& a,
|
||||
const std::pair<Eigen::Index, double>& b) {
|
||||
return a.second > b.second;
|
||||
});
|
||||
|
||||
// Create pruned sparse vector.
|
||||
Eigen::SparseVector<double> pruned_vec(sparse_table_.size());
|
||||
pruned_vec.reserve(probabilities.size());
|
||||
// Keep the largest N probabilities in the vector.
|
||||
if (probabilities.size() > N) probabilities.resize(N);
|
||||
|
||||
// Populate pruned sparse vector.
|
||||
for (const auto& prob : probabilities) {
|
||||
pruned_vec.insert(prob.first) = prob.second;
|
||||
}
|
||||
// Create pruned sparse vector.
|
||||
Eigen::SparseVector<double> pruned_vec(sparse_table_.size());
|
||||
pruned_vec.reserve(probabilities.size());
|
||||
|
||||
// Create pruned decision tree factor and return.
|
||||
return TableFactor(this->discreteKeys(), pruned_vec);
|
||||
// Populate pruned sparse vector.
|
||||
for (const auto& prob : probabilities) {
|
||||
pruned_vec.insert(prob.first) = prob.second;
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
// Create pruned decision tree factor and return.
|
||||
return TableFactor(this->discreteKeys(), pruned_vec);
|
||||
}
|
||||
|
||||
/* ************************************************************************ */
|
||||
} // namespace gtsam
|
||||
|
|
|
|||
|
|
@ -23,8 +23,8 @@
|
|||
|
||||
#include <Eigen/Sparse>
|
||||
#include <algorithm>
|
||||
#include <memory>
|
||||
#include <map>
|
||||
#include <memory>
|
||||
#include <stdexcept>
|
||||
#include <string>
|
||||
#include <utility>
|
||||
|
|
@ -32,287 +32,296 @@
|
|||
|
||||
namespace gtsam {
|
||||
|
||||
class HybridValues;
|
||||
class HybridValues;
|
||||
|
||||
/**
|
||||
* A discrete probabilistic factor optimized for sparsity.
|
||||
* Uses sparse_table_ to store only the nonzero probabilities.
|
||||
* Computes the assigned value for the key using the ordering which the
|
||||
* nonzero probabilties are stored in. (lazy cartesian product)
|
||||
*
|
||||
* @ingroup discrete
|
||||
*/
|
||||
class GTSAM_EXPORT TableFactor : public DiscreteFactor {
|
||||
protected:
|
||||
/// Map of Keys and their cardinalities.
|
||||
std::map<Key, size_t> cardinalities_;
|
||||
/// SparseVector of nonzero probabilities.
|
||||
Eigen::SparseVector<double> sparse_table_;
|
||||
|
||||
private:
|
||||
/// Map of Keys and their denominators used in keyValueForIndex.
|
||||
std::map<Key, size_t> denominators_;
|
||||
/// Sorted DiscreteKeys to use internally.
|
||||
DiscreteKeys sorted_dkeys_;
|
||||
|
||||
/**
|
||||
* A discrete probabilistic factor optimized for sparsity.
|
||||
* Uses sparse_table_ to store only the nonzero probabilities.
|
||||
* Computes the assigned value for the key using the ordering which the
|
||||
* nonzero probabilties are stored in. (lazy cartesian product)
|
||||
*
|
||||
* @ingroup discrete
|
||||
* @brief Uses lazy cartesian product to find nth entry in the cartesian
|
||||
* product of arrays in O(1)
|
||||
* Example)
|
||||
* v0 | v1 | val
|
||||
* 0 | 0 | 10
|
||||
* 0 | 1 | 21
|
||||
* 1 | 0 | 32
|
||||
* 1 | 1 | 43
|
||||
* keyValueForIndex(v1, 2) = 0
|
||||
* @param target_key nth entry's key to find out its assigned value
|
||||
* @param index nth entry in the sparse vector
|
||||
* @return TableFactor
|
||||
*/
|
||||
class GTSAM_EXPORT TableFactor : public DiscreteFactor {
|
||||
protected:
|
||||
std::map<Key, size_t> cardinalities_; /// Map of Keys and their cardinalities.
|
||||
Eigen::SparseVector<double> sparse_table_; /// SparseVector of nonzero probabilities.
|
||||
|
||||
private:
|
||||
std::map<Key, size_t> denominators_; /// Map of Keys and their denominators used in keyValueForIndex.
|
||||
DiscreteKeys sorted_dkeys_; /// Sorted DiscreteKeys to use internally.
|
||||
|
||||
/**
|
||||
* @brief Uses lazy cartesian product to find nth entry in the cartesian product of arrays in O(1)
|
||||
* Example)
|
||||
* v0 | v1 | val
|
||||
* 0 | 0 | 10
|
||||
* 0 | 1 | 21
|
||||
* 1 | 0 | 32
|
||||
* 1 | 1 | 43
|
||||
* keyValueForIndex(v1, 2) = 0
|
||||
* @param target_key nth entry's key to find out its assigned value
|
||||
* @param index nth entry in the sparse vector
|
||||
* @return TableFactor
|
||||
*/
|
||||
size_t keyValueForIndex(Key target_key, uint64_t index) const;
|
||||
size_t keyValueForIndex(Key target_key, uint64_t index) const;
|
||||
|
||||
DiscreteKey discreteKey(size_t i) const {
|
||||
return DiscreteKey(keys_[i], cardinalities_.at(keys_[i]));
|
||||
/**
|
||||
* @brief Return ith key in keys_ as a DiscreteKey
|
||||
* @param i ith key in keys_
|
||||
* @return DiscreteKey
|
||||
* */
|
||||
DiscreteKey discreteKey(size_t i) const {
|
||||
return DiscreteKey(keys_[i], cardinalities_.at(keys_[i]));
|
||||
}
|
||||
|
||||
/// Convert probability table given as doubles to SparseVector.
|
||||
static Eigen::SparseVector<double> Convert(const std::vector<double>& table);
|
||||
|
||||
/// Convert probability table given as string to SparseVector.
|
||||
static Eigen::SparseVector<double> Convert(const std::string& table);
|
||||
|
||||
public:
|
||||
// typedefs needed to play nice with gtsam
|
||||
typedef TableFactor This;
|
||||
typedef DiscreteFactor Base; ///< Typedef to base class
|
||||
typedef std::shared_ptr<TableFactor> shared_ptr;
|
||||
typedef Eigen::SparseVector<double>::InnerIterator SparseIt;
|
||||
typedef std::vector<std::pair<DiscreteValues, double>> AssignValList;
|
||||
using Binary = std::function<double(const double, const double)>;
|
||||
|
||||
public:
|
||||
/** The Real ring with addition and multiplication */
|
||||
struct Ring {
|
||||
static inline double zero() { return 0.0; }
|
||||
static inline double one() { return 1.0; }
|
||||
static inline double add(const double& a, const double& b) { return a + b; }
|
||||
static inline double max(const double& a, const double& b) {
|
||||
return std::max(a, b);
|
||||
}
|
||||
|
||||
/// Convert probability table given as doubles to SparseVector.
|
||||
static Eigen::SparseVector<double> Convert(const std::vector<double>& table);
|
||||
|
||||
/// Convert probability table given as string to SparseVector.
|
||||
static Eigen::SparseVector<double> Convert(const std::string& table);
|
||||
|
||||
public:
|
||||
// typedefs needed to play nice with gtsam
|
||||
typedef TableFactor This;
|
||||
typedef DiscreteFactor Base; ///< Typedef to base class
|
||||
typedef std::shared_ptr<TableFactor> shared_ptr;
|
||||
typedef Eigen::SparseVector<double>::InnerIterator SparseIt;
|
||||
typedef std::vector<std::pair<DiscreteValues, double>> AssignValList;
|
||||
using Binary = std::function<double(const double, const double)>;
|
||||
|
||||
public:
|
||||
/** The Real ring with addition and multiplication */
|
||||
struct Ring {
|
||||
static inline double zero() { return 0.0; }
|
||||
static inline double one() { return 1.0; }
|
||||
static inline double add(const double& a, const double& b) { return a + b; }
|
||||
static inline double max(const double& a, const double& b) {
|
||||
return std::max(a, b);
|
||||
}
|
||||
static inline double mul(const double& a, const double& b) { return a * b; }
|
||||
static inline double div(const double& a, const double& b) {
|
||||
return (a == 0 || b == 0) ? 0 : (a / b);
|
||||
}
|
||||
static inline double id(const double& x) { return x; }
|
||||
};
|
||||
|
||||
/// @name Standard Constructors
|
||||
/// @{
|
||||
|
||||
/** Default constructor for I/O */
|
||||
TableFactor();
|
||||
|
||||
/** Constructor from DiscreteKeys and TableFactor */
|
||||
TableFactor(const DiscreteKeys& keys, const TableFactor& potentials);
|
||||
|
||||
/** Constructor from sparse_table */
|
||||
TableFactor(const DiscreteKeys& keys,
|
||||
const Eigen::SparseVector<double>& table);
|
||||
|
||||
/** Constructor from doubles */
|
||||
TableFactor(const DiscreteKeys& keys, const std::vector<double>& table)
|
||||
: TableFactor(keys, Convert(table)) {}
|
||||
|
||||
/** Constructor from string */
|
||||
TableFactor(const DiscreteKeys& keys, const std::string& table)
|
||||
: TableFactor(keys, Convert(table)) {}
|
||||
|
||||
/// Single-key specialization
|
||||
template <class SOURCE>
|
||||
TableFactor(const DiscreteKey& key, SOURCE table)
|
||||
: TableFactor(DiscreteKeys{key}, table) {}
|
||||
|
||||
/// Single-key specialization, with vector of doubles.
|
||||
TableFactor(const DiscreteKey& key, const std::vector<double>& row)
|
||||
: TableFactor(DiscreteKeys{key}, row) {}
|
||||
|
||||
|
||||
/// @}
|
||||
/// @name Testable
|
||||
/// @{
|
||||
|
||||
/// equality
|
||||
bool equals(const DiscreteFactor& other, double tol = 1e-9) const override;
|
||||
|
||||
// print
|
||||
void print(
|
||||
const std::string& s = "TableFactor:\n",
|
||||
const KeyFormatter& formatter = DefaultKeyFormatter) const override;
|
||||
|
||||
// /// @}
|
||||
// /// @name Standard Interface
|
||||
// /// @{
|
||||
|
||||
/// Calculate probability for given values `x`,
|
||||
/// is just look up in TableFactor.
|
||||
double evaluate(const DiscreteValues& values) const {
|
||||
return operator()(values);
|
||||
static inline double mul(const double& a, const double& b) { return a * b; }
|
||||
static inline double div(const double& a, const double& b) {
|
||||
return (a == 0 || b == 0) ? 0 : (a / b);
|
||||
}
|
||||
static inline double id(const double& x) { return x; }
|
||||
};
|
||||
|
||||
/// Evaluate probability distribution, sugar.
|
||||
double operator()(const DiscreteValues& values) const override;
|
||||
/// @name Standard Constructors
|
||||
/// @{
|
||||
|
||||
/// Calculate error for DiscreteValues `x`, is -log(probability).
|
||||
double error(const DiscreteValues& values) const;
|
||||
/** Default constructor for I/O */
|
||||
TableFactor();
|
||||
|
||||
/// multiply two TableFactors
|
||||
TableFactor operator*(const TableFactor& f) const {
|
||||
return apply(f, Ring::mul);
|
||||
};
|
||||
/** Constructor from DiscreteKeys and TableFactor */
|
||||
TableFactor(const DiscreteKeys& keys, const TableFactor& potentials);
|
||||
|
||||
/// multiple with DecisionTreeFactor
|
||||
DecisionTreeFactor operator*(const DecisionTreeFactor& f) const override;
|
||||
/** Constructor from sparse_table */
|
||||
TableFactor(const DiscreteKeys& keys,
|
||||
const Eigen::SparseVector<double>& table);
|
||||
|
||||
static double safe_div(const double& a, const double& b);
|
||||
/** Constructor from doubles */
|
||||
TableFactor(const DiscreteKeys& keys, const std::vector<double>& table)
|
||||
: TableFactor(keys, Convert(table)) {}
|
||||
|
||||
size_t cardinality(Key j) const { return cardinalities_.at(j); }
|
||||
/** Constructor from string */
|
||||
TableFactor(const DiscreteKeys& keys, const std::string& table)
|
||||
: TableFactor(keys, Convert(table)) {}
|
||||
|
||||
/// divide by factor f (safely)
|
||||
TableFactor operator/(const TableFactor& f) const {
|
||||
return apply(f, safe_div);
|
||||
}
|
||||
/// Single-key specialization
|
||||
template <class SOURCE>
|
||||
TableFactor(const DiscreteKey& key, SOURCE table)
|
||||
: TableFactor(DiscreteKeys{key}, table) {}
|
||||
|
||||
/// Convert into a decisiontree
|
||||
DecisionTreeFactor toDecisionTreeFactor() const override;
|
||||
/// Single-key specialization, with vector of doubles.
|
||||
TableFactor(const DiscreteKey& key, const std::vector<double>& row)
|
||||
: TableFactor(DiscreteKeys{key}, row) {}
|
||||
|
||||
/// Generate TableFactor from TableFactor
|
||||
// TableFactor toTableFactor() const override { return *this; }
|
||||
/// @}
|
||||
/// @name Testable
|
||||
/// @{
|
||||
|
||||
/// Create a TableFactor that is a subset of this TableFactor
|
||||
TableFactor choose(const DiscreteValues assignments,
|
||||
DiscreteKeys parent_keys) const;
|
||||
/// equality
|
||||
bool equals(const DiscreteFactor& other, double tol = 1e-9) const override;
|
||||
|
||||
/// Create new factor by summing all values with the same separator values
|
||||
shared_ptr sum(size_t nrFrontals) const {
|
||||
return combine(nrFrontals, Ring::add);
|
||||
}
|
||||
// print
|
||||
void print(
|
||||
const std::string& s = "TableFactor:\n",
|
||||
const KeyFormatter& formatter = DefaultKeyFormatter) const override;
|
||||
|
||||
/// Create new factor by summing all values with the same separator values
|
||||
shared_ptr sum(const Ordering& keys) const {
|
||||
return combine(keys, Ring::add);
|
||||
}
|
||||
// /// @}
|
||||
// /// @name Standard Interface
|
||||
// /// @{
|
||||
|
||||
/// Create new factor by maximizing over all values with the same separator.
|
||||
shared_ptr max(size_t nrFrontals) const {
|
||||
return combine(nrFrontals, Ring::max);
|
||||
}
|
||||
/// Calculate probability for given values `x`,
|
||||
/// is just look up in TableFactor.
|
||||
double evaluate(const DiscreteValues& values) const {
|
||||
return operator()(values);
|
||||
}
|
||||
|
||||
/// Create new factor by maximizing over all values with the same separator.
|
||||
shared_ptr max(const Ordering& keys) const {
|
||||
return combine(keys, Ring::max);
|
||||
}
|
||||
/// Evaluate probability distribution, sugar.
|
||||
double operator()(const DiscreteValues& values) const override;
|
||||
|
||||
/// @}
|
||||
/// @name Advanced Interface
|
||||
/// @{
|
||||
/// Calculate error for DiscreteValues `x`, is -log(probability).
|
||||
double error(const DiscreteValues& values) const;
|
||||
|
||||
/**
|
||||
* Apply binary operator (*this) "op" f
|
||||
* @param f the second argument for op
|
||||
* @param op a binary operator that operates on TableFactor
|
||||
*/
|
||||
TableFactor apply(const TableFactor& f, Binary op) const;
|
||||
/// multiply two TableFactors
|
||||
TableFactor operator*(const TableFactor& f) const {
|
||||
return apply(f, Ring::mul);
|
||||
};
|
||||
|
||||
/// Return keys in contract mode.
|
||||
DiscreteKeys contractDkeys(const TableFactor& f) const;
|
||||
|
||||
/// Return keys in free mode.
|
||||
DiscreteKeys freeDkeys(const TableFactor& f) const;
|
||||
/// multiple with DecisionTreeFactor
|
||||
DecisionTreeFactor operator*(const DecisionTreeFactor& f) const override;
|
||||
|
||||
/// Return union of DiscreteKeys in two factors.
|
||||
DiscreteKeys unionDkeys(const TableFactor& f) const;
|
||||
static double safe_div(const double& a, const double& b);
|
||||
|
||||
/// Create unique representation of union modes.
|
||||
uint64_t unionRep(const DiscreteKeys& keys,
|
||||
const DiscreteValues& assign, const uint64_t idx) const;
|
||||
|
||||
/// Create a hash map of input factor with assignment of contract modes as
|
||||
/// keys and vector of hashed assignment of free modes and value as values.
|
||||
std::unordered_map<uint64_t, AssignValList> createMap(
|
||||
size_t cardinality(Key j) const { return cardinalities_.at(j); }
|
||||
|
||||
/// divide by factor f (safely)
|
||||
TableFactor operator/(const TableFactor& f) const {
|
||||
return apply(f, safe_div);
|
||||
}
|
||||
|
||||
/// Convert into a decisiontree
|
||||
DecisionTreeFactor toDecisionTreeFactor() const override;
|
||||
|
||||
/// Generate TableFactor from TableFactor
|
||||
// TableFactor toTableFactor() const override { return *this; }
|
||||
|
||||
/// Create a TableFactor that is a subset of this TableFactor
|
||||
TableFactor choose(const DiscreteValues assignments,
|
||||
DiscreteKeys parent_keys) const;
|
||||
|
||||
/// Create new factor by summing all values with the same separator values
|
||||
shared_ptr sum(size_t nrFrontals) const {
|
||||
return combine(nrFrontals, Ring::add);
|
||||
}
|
||||
|
||||
/// Create new factor by summing all values with the same separator values
|
||||
shared_ptr sum(const Ordering& keys) const {
|
||||
return combine(keys, Ring::add);
|
||||
}
|
||||
|
||||
/// Create new factor by maximizing over all values with the same separator.
|
||||
shared_ptr max(size_t nrFrontals) const {
|
||||
return combine(nrFrontals, Ring::max);
|
||||
}
|
||||
|
||||
/// Create new factor by maximizing over all values with the same separator.
|
||||
shared_ptr max(const Ordering& keys) const {
|
||||
return combine(keys, Ring::max);
|
||||
}
|
||||
|
||||
/// @}
|
||||
/// @name Advanced Interface
|
||||
/// @{
|
||||
|
||||
/**
|
||||
* Apply binary operator (*this) "op" f
|
||||
* @param f the second argument for op
|
||||
* @param op a binary operator that operates on TableFactor
|
||||
*/
|
||||
TableFactor apply(const TableFactor& f, Binary op) const;
|
||||
|
||||
/// Return keys in contract mode.
|
||||
DiscreteKeys contractDkeys(const TableFactor& f) const;
|
||||
|
||||
/// Return keys in free mode.
|
||||
DiscreteKeys freeDkeys(const TableFactor& f) const;
|
||||
|
||||
/// Return union of DiscreteKeys in two factors.
|
||||
DiscreteKeys unionDkeys(const TableFactor& f) const;
|
||||
|
||||
/// Create unique representation of union modes.
|
||||
uint64_t unionRep(const DiscreteKeys& keys, const DiscreteValues& assign,
|
||||
const uint64_t idx) const;
|
||||
|
||||
/// Create a hash map of input factor with assignment of contract modes as
|
||||
/// keys and vector of hashed assignment of free modes and value as values.
|
||||
std::unordered_map<uint64_t, AssignValList> createMap(
|
||||
const DiscreteKeys& contract, const DiscreteKeys& free) const;
|
||||
|
||||
/// Create unique representation
|
||||
uint64_t uniqueRep(const DiscreteKeys& keys, const uint64_t idx) const;
|
||||
|
||||
/// Create unique representation with DiscreteValues
|
||||
uint64_t uniqueRep(const DiscreteValues& assignments) const;
|
||||
/// Create unique representation
|
||||
uint64_t uniqueRep(const DiscreteKeys& keys, const uint64_t idx) const;
|
||||
|
||||
/// Find DiscreteValues for corresponding index.
|
||||
DiscreteValues findAssignments(const uint64_t idx) const;
|
||||
|
||||
/// Find value for corresponding DiscreteValues.
|
||||
double findValue(const DiscreteValues& values) const;
|
||||
/// Create unique representation with DiscreteValues
|
||||
uint64_t uniqueRep(const DiscreteValues& assignments) const;
|
||||
|
||||
/**
|
||||
* Combine frontal variables using binary operator "op"
|
||||
* @param nrFrontals nr. of frontal to combine variables in this factor
|
||||
* @param op a binary operator that operates on TableFactor
|
||||
* @return shared pointer to newly created TableFactor
|
||||
*/
|
||||
shared_ptr combine(size_t nrFrontals, Binary op) const;
|
||||
/// Find DiscreteValues for corresponding index.
|
||||
DiscreteValues findAssignments(const uint64_t idx) const;
|
||||
|
||||
/**
|
||||
* Combine frontal variables in an Ordering using binary operator "op"
|
||||
* @param nrFrontals nr. of frontal to combine variables in this factor
|
||||
* @param op a binary operator that operates on TableFactor
|
||||
* @return shared pointer to newly created TableFactor
|
||||
*/
|
||||
shared_ptr combine(const Ordering& keys, Binary op) const;
|
||||
/// Find value for corresponding DiscreteValues.
|
||||
double findValue(const DiscreteValues& values) const;
|
||||
|
||||
/// Enumerate all values into a map from values to double.
|
||||
std::vector<std::pair<DiscreteValues, double>> enumerate() const;
|
||||
/**
|
||||
* Combine frontal variables using binary operator "op"
|
||||
* @param nrFrontals nr. of frontal to combine variables in this factor
|
||||
* @param op a binary operator that operates on TableFactor
|
||||
* @return shared pointer to newly created TableFactor
|
||||
*/
|
||||
shared_ptr combine(size_t nrFrontals, Binary op) const;
|
||||
|
||||
/// Return all the discrete keys associated with this factor.
|
||||
DiscreteKeys discreteKeys() const;
|
||||
/**
|
||||
* Combine frontal variables in an Ordering using binary operator "op"
|
||||
* @param nrFrontals nr. of frontal to combine variables in this factor
|
||||
* @param op a binary operator that operates on TableFactor
|
||||
* @return shared pointer to newly created TableFactor
|
||||
*/
|
||||
shared_ptr combine(const Ordering& keys, Binary op) const;
|
||||
|
||||
/**
|
||||
* @brief Prune the decision tree of discrete variables.
|
||||
*
|
||||
* Pruning will set the values to be "pruned" to 0 indicating a 0
|
||||
* probability. An assignment is pruned if it is not in the top
|
||||
* `maxNrAssignments` values.
|
||||
*
|
||||
* A violation can occur if there are more
|
||||
* duplicate values than `maxNrAssignments`. A violation here is the need to
|
||||
* un-prune the decision tree (e.g. all assignment values are 1.0). We could
|
||||
* have another case where some subset of duplicates exist (e.g. for a tree
|
||||
* with 8 assignments we have 1, 1, 1, 1, 0.8, 0.7, 0.6, 0.5), but this is
|
||||
* not a violation since the for `maxNrAssignments=5` the top values are (1,
|
||||
* 0.8).
|
||||
*
|
||||
* @param maxNrAssignments The maximum number of assignments to keep.
|
||||
* @return TableFactor
|
||||
*/
|
||||
TableFactor prune(size_t maxNrAssignments) const;
|
||||
/// Enumerate all values into a map from values to double.
|
||||
std::vector<std::pair<DiscreteValues, double>> enumerate() const;
|
||||
|
||||
/// @}
|
||||
/// @name Wrapper support
|
||||
/// @{
|
||||
/// Return all the discrete keys associated with this factor.
|
||||
DiscreteKeys discreteKeys() const;
|
||||
|
||||
/**
|
||||
* @brief Render as markdown table
|
||||
*
|
||||
* @param keyFormatter GTSAM-style Key formatter.
|
||||
* @param names optional, category names corresponding to choices.
|
||||
* @return std::string a markdown string.
|
||||
*/
|
||||
std::string markdown(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
|
||||
const Names& names = {}) const override;
|
||||
/**
|
||||
* @brief Prune the decision tree of discrete variables.
|
||||
*
|
||||
* Pruning will set the values to be "pruned" to 0 indicating a 0
|
||||
* probability. An assignment is pruned if it is not in the top
|
||||
* `maxNrAssignments` values.
|
||||
*
|
||||
* A violation can occur if there are more
|
||||
* duplicate values than `maxNrAssignments`. A violation here is the need to
|
||||
* un-prune the decision tree (e.g. all assignment values are 1.0). We could
|
||||
* have another case where some subset of duplicates exist (e.g. for a tree
|
||||
* with 8 assignments we have 1, 1, 1, 1, 0.8, 0.7, 0.6, 0.5), but this is
|
||||
* not a violation since the for `maxNrAssignments=5` the top values are (1,
|
||||
* 0.8).
|
||||
*
|
||||
* @param maxNrAssignments The maximum number of assignments to keep.
|
||||
* @return TableFactor
|
||||
*/
|
||||
TableFactor prune(size_t maxNrAssignments) const;
|
||||
|
||||
/**
|
||||
* @brief Render as html table
|
||||
*
|
||||
* @param keyFormatter GTSAM-style Key formatter.
|
||||
* @param names optional, category names corresponding to choices.
|
||||
* @return std::string a html string.
|
||||
*/
|
||||
std::string html(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
|
||||
const Names& names = {}) const override;
|
||||
/// @}
|
||||
/// @name Wrapper support
|
||||
/// @{
|
||||
|
||||
/**
|
||||
* @brief Render as markdown table
|
||||
*
|
||||
* @param keyFormatter GTSAM-style Key formatter.
|
||||
* @param names optional, category names corresponding to choices.
|
||||
* @return std::string a markdown string.
|
||||
*/
|
||||
std::string markdown(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
|
||||
const Names& names = {}) const override;
|
||||
|
||||
/**
|
||||
* @brief Render as html table
|
||||
*
|
||||
* @param keyFormatter GTSAM-style Key formatter.
|
||||
* @param names optional, category names corresponding to choices.
|
||||
* @return std::string a html string.
|
||||
*/
|
||||
std::string html(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
|
||||
const Names& names = {}) const override;
|
||||
|
||||
/// @}
|
||||
/// @name HybridValues methods.
|
||||
|
|
@ -325,7 +334,7 @@ namespace gtsam {
|
|||
double error(const HybridValues& values) const override;
|
||||
|
||||
/// @}
|
||||
};
|
||||
};
|
||||
|
||||
// traits
|
||||
template <>
|
||||
|
|
|
|||
Loading…
Reference in New Issue