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Merge pull request #1953 from borglab/discrete-table-conditional
TableFactor and TableDistribution
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| Original file line number | Diff line number | Diff line change |
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| /* ---------------------------------------------------------------------------- | ||
| * GTSAM Copyright 2010, Georgia Tech Research Corporation, | ||
| * Atlanta, Georgia 30332-0415 | ||
| * All Rights Reserved | ||
| * Authors: Frank Dellaert, et al. (see THANKS for the full author list) | ||
| * See LICENSE for the license information | ||
| * -------------------------------------------------------------------------- */ | ||
|
|
||
| /** | ||
| * @file TableDistribution.cpp | ||
| * @date Dec 22, 2024 | ||
| * @author Varun Agrawal | ||
| */ | ||
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| #include <gtsam/base/Testable.h> | ||
| #include <gtsam/base/debug.h> | ||
| #include <gtsam/discrete/Ring.h> | ||
| #include <gtsam/discrete/Signature.h> | ||
| #include <gtsam/discrete/TableDistribution.h> | ||
| #include <gtsam/hybrid/HybridValues.h> | ||
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| #include <algorithm> | ||
| #include <cassert> | ||
| #include <random> | ||
| #include <set> | ||
| #include <stdexcept> | ||
| #include <string> | ||
| #include <utility> | ||
| #include <vector> | ||
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| using namespace std; | ||
| using std::pair; | ||
| using std::stringstream; | ||
| using std::vector; | ||
| namespace gtsam { | ||
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| /// Normalize sparse_table | ||
| static Eigen::SparseVector<double> normalizeSparseTable( | ||
| const Eigen::SparseVector<double>& sparse_table) { | ||
| return sparse_table / sparse_table.sum(); | ||
| } | ||
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| /* ************************************************************************** */ | ||
| TableDistribution::TableDistribution(const TableFactor& f) | ||
| : BaseConditional(f.keys().size(), f.discreteKeys(), ADT(nullptr)), | ||
| table_(f / (*std::dynamic_pointer_cast<TableFactor>( | ||
| f.sum(f.keys().size())))) {} | ||
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| /* ************************************************************************** */ | ||
| TableDistribution::TableDistribution(const DiscreteKeys& keys, | ||
| const std::vector<double>& potentials) | ||
| : BaseConditional(keys.size(), keys, ADT(nullptr)), | ||
| table_(TableFactor( | ||
| keys, normalizeSparseTable(TableFactor::Convert(keys, potentials)))) { | ||
| } | ||
|
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| /* ************************************************************************** */ | ||
| TableDistribution::TableDistribution(const DiscreteKeys& keys, | ||
| const std::string& potentials) | ||
| : BaseConditional(keys.size(), keys, ADT(nullptr)), | ||
| table_(TableFactor( | ||
| keys, normalizeSparseTable(TableFactor::Convert(keys, potentials)))) { | ||
| } | ||
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| /* ************************************************************************** */ | ||
| void TableDistribution::print(const string& s, | ||
| const KeyFormatter& formatter) const { | ||
| cout << s << " P( "; | ||
| for (const_iterator it = beginFrontals(); it != endFrontals(); ++it) { | ||
| cout << formatter(*it) << " "; | ||
| } | ||
| cout << "):\n"; | ||
| table_.print("", formatter); | ||
| cout << endl; | ||
| } | ||
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| /* ************************************************************************** */ | ||
| bool TableDistribution::equals(const DiscreteFactor& other, double tol) const { | ||
| auto dtc = dynamic_cast<const TableDistribution*>(&other); | ||
| if (!dtc) { | ||
| return false; | ||
| } else { | ||
| const DiscreteConditional& f( | ||
| static_cast<const DiscreteConditional&>(other)); | ||
| return table_.equals(dtc->table_, tol) && | ||
| DiscreteConditional::BaseConditional::equals(f, tol); | ||
| } | ||
| } | ||
|
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| /* ****************************************************************************/ | ||
| DiscreteFactor::shared_ptr TableDistribution::sum(size_t nrFrontals) const { | ||
| return table_.sum(nrFrontals); | ||
| } | ||
|
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| /* ****************************************************************************/ | ||
| DiscreteFactor::shared_ptr TableDistribution::sum(const Ordering& keys) const { | ||
| return table_.sum(keys); | ||
| } | ||
|
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| /* ****************************************************************************/ | ||
| DiscreteFactor::shared_ptr TableDistribution::max(size_t nrFrontals) const { | ||
| return table_.max(nrFrontals); | ||
| } | ||
|
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| /* ****************************************************************************/ | ||
| DiscreteFactor::shared_ptr TableDistribution::max(const Ordering& keys) const { | ||
| return table_.max(keys); | ||
| } | ||
|
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| /* ****************************************************************************/ | ||
| DiscreteFactor::shared_ptr TableDistribution::operator/( | ||
| const DiscreteFactor::shared_ptr& f) const { | ||
| return table_ / f; | ||
| } | ||
|
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| /* ************************************************************************ */ | ||
| DiscreteValues TableDistribution::argmax() const { | ||
| uint64_t maxIdx = 0; | ||
| double maxValue = 0.0; | ||
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| Eigen::SparseVector<double> sparseTable = table_.sparseTable(); | ||
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| for (SparseIt it(sparseTable); it; ++it) { | ||
| if (it.value() > maxValue) { | ||
| maxIdx = it.index(); | ||
| maxValue = it.value(); | ||
| } | ||
| } | ||
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| return table_.findAssignments(maxIdx); | ||
| } | ||
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| /* ****************************************************************************/ | ||
| void TableDistribution::prune(size_t maxNrAssignments) { | ||
| table_ = table_.prune(maxNrAssignments); | ||
| } | ||
|
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| /* ****************************************************************************/ | ||
| size_t TableDistribution::sample(const DiscreteValues& parentsValues) const { | ||
| static mt19937 rng(2); // random number generator | ||
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| DiscreteKeys parentsKeys; | ||
| for (auto&& [key, _] : parentsValues) { | ||
| parentsKeys.push_back({key, table_.cardinality(key)}); | ||
| } | ||
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| // Get the correct conditional distribution: P(F|S=parentsValues) | ||
| TableFactor pFS = table_.choose(parentsValues, parentsKeys); | ||
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| // TODO(Duy): only works for one key now, seems horribly slow this way | ||
| if (nrFrontals() != 1) { | ||
| throw std::invalid_argument( | ||
| "TableDistribution::sample can only be called on single variable " | ||
| "conditionals"); | ||
| } | ||
| Key key = firstFrontalKey(); | ||
| size_t nj = cardinality(key); | ||
| vector<double> p(nj); | ||
| DiscreteValues frontals; | ||
| for (size_t value = 0; value < nj; value++) { | ||
| frontals[key] = value; | ||
| p[value] = pFS(frontals); // P(F=value|S=parentsValues) | ||
| if (p[value] == 1.0) { | ||
| return value; // shortcut exit | ||
| } | ||
| } | ||
| std::discrete_distribution<size_t> distribution(p.begin(), p.end()); | ||
| return distribution(rng); | ||
| } | ||
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| } // namespace gtsam |
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