Merge pull request #1001 from borglab/feature/markdown_values
commit
53b4053c20
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@ -179,9 +179,9 @@ namespace gtsam {
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}
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/* ************************************************************************* */
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std::string DecisionTreeFactor::markdown(
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const KeyFormatter& keyFormatter) const {
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std::stringstream ss;
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string DecisionTreeFactor::markdown(const KeyFormatter& keyFormatter,
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const Names& names) const {
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stringstream ss;
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// Print out header and construct argument for `cartesianProduct`.
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ss << "|";
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@ -200,7 +200,10 @@ namespace gtsam {
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for (const auto& kv : rows) {
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ss << "|";
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auto assignment = kv.first;
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for (auto& key : keys()) ss << assignment.at(key) << "|";
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for (auto& key : keys()) {
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size_t index = assignment.at(key);
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ss << Translate(names, key, index) << "|";
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}
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ss << kv.second << "|\n";
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}
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return ss.str();
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@ -192,9 +192,15 @@ namespace gtsam {
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std::string dot(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
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bool showZero = true) const;
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/// Render as markdown table.
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std::string markdown(
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const KeyFormatter& keyFormatter = DefaultKeyFormatter) const override;
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/**
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* @brief Render as markdown table
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*
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* @param keyFormatter GTSAM-style Key formatter.
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* @param names optional, category names corresponding to choices.
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* @return std::string a markdown string.
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*/
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std::string markdown(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
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const Names& names = {}) const override;
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/// @}
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@ -63,12 +63,13 @@ namespace gtsam {
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/* ************************************************************************* */
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std::string DiscreteBayesNet::markdown(
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const KeyFormatter& keyFormatter) const {
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const KeyFormatter& keyFormatter,
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const DiscreteFactor::Names& names) const {
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using std::endl;
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std::stringstream ss;
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ss << "`DiscreteBayesNet` of size " << size() << endl << endl;
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for(const DiscreteConditional::shared_ptr& conditional: *this)
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ss << conditional->markdown(keyFormatter) << endl;
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ss << conditional->markdown(keyFormatter, names) << endl;
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return ss.str();
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}
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/* ************************************************************************* */
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@ -108,8 +108,8 @@ namespace gtsam {
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/// @{
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/// Render as markdown table.
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std::string markdown(
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const KeyFormatter& keyFormatter = DefaultKeyFormatter) const;
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std::string markdown(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
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const DiscreteFactor::Names& names = {}) const;
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/// @}
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@ -57,13 +57,14 @@ namespace gtsam {
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/* **************************************************************************/
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std::string DiscreteBayesTree::markdown(
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const KeyFormatter& keyFormatter) const {
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const KeyFormatter& keyFormatter,
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const DiscreteFactor::Names& names) const {
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using std::endl;
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std::stringstream ss;
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ss << "`DiscreteBayesTree` of size " << nodes_.size() << endl << endl;
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auto visitor = [&](const DiscreteBayesTreeClique::shared_ptr& clique,
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size_t& indent) {
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ss << "\n" << clique->conditional()->markdown(keyFormatter);
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ss << "\n" << clique->conditional()->markdown(keyFormatter, names);
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return indent + 1;
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};
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size_t indent;
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@ -93,8 +93,8 @@ class GTSAM_EXPORT DiscreteBayesTree
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/// @{
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/// Render as markdown table.
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std::string markdown(
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const KeyFormatter& keyFormatter = DefaultKeyFormatter) const;
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std::string markdown(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
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const DiscreteFactor::Names& names = {}) const;
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/// @}
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};
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@ -282,9 +282,18 @@ size_t DiscreteConditional::sample(size_t parent_value) const {
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return sample(values);
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}
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/* ******************************************************************************** */
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size_t DiscreteConditional::sample() const {
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if (nrParents() != 0)
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throw std::invalid_argument(
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"sample() can only be invoked on no-parent prior");
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DiscreteValues values;
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return sample(values);
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}
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/* ************************************************************************* */
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std::string DiscreteConditional::markdown(
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const KeyFormatter& keyFormatter) const {
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std::string DiscreteConditional::markdown(const KeyFormatter& keyFormatter,
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const Names& names) const {
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std::stringstream ss;
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// Print out signature.
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@ -317,7 +326,7 @@ std::string DiscreteConditional::markdown(
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ss << "|";
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const_iterator it;
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for(Key parent: parents()) {
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ss << keyFormatter(parent) << "|";
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ss << "*" << keyFormatter(parent) << "*|";
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pairs.emplace_back(parent, cardinalities_.at(parent));
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}
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@ -331,7 +340,10 @@ std::string DiscreteConditional::markdown(
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pairs.rend() - nrParents());
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const auto frontal_assignments = cartesianProduct(slatnorf);
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for (const auto& a : frontal_assignments) {
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for (it = beginFrontals(); it != endFrontals(); ++it) ss << a.at(*it);
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for (it = beginFrontals(); it != endFrontals(); ++it) {
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size_t index = a.at(*it);
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ss << Translate(names, *it, index);
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}
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ss << "|";
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}
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ss << "\n";
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@ -348,8 +360,10 @@ std::string DiscreteConditional::markdown(
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for (const auto& a : assignments) {
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if (count == 0) {
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ss << "|";
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for (it = beginParents(); it != endParents(); ++it)
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ss << a.at(*it) << "|";
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for (it = beginParents(); it != endParents(); ++it) {
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size_t index = a.at(*it);
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ss << Translate(names, *it, index) << "|";
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}
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}
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ss << operator()(a) << "|";
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count = (count + 1) % n;
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@ -162,9 +162,12 @@ public:
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size_t sample(const DiscreteValues& parentsValues) const;
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/// Single value version.
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/// Single parent version.
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size_t sample(size_t parent_value) const;
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/// Zero parent version.
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size_t sample() const;
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/// @}
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/// @name Advanced Interface
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/// @{
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@ -180,8 +183,8 @@ public:
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/// @{
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/// Render as markdown table.
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std::string markdown(
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const KeyFormatter& keyFormatter = DefaultKeyFormatter) const override;
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std::string markdown(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
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const Names& names = {}) const override;
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/// @}
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};
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@ -19,9 +19,20 @@
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#include <gtsam/discrete/DiscreteFactor.h>
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#include <sstream>
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using namespace std;
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namespace gtsam {
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/* ************************************************************************* */
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} // namespace gtsam
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string DiscreteFactor::Translate(const Names& names, Key key, size_t index) {
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if (names.empty()) {
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stringstream ss;
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ss << index;
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return ss.str();
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} else {
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return names.at(key)[index];
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}
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}
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} // namespace gtsam
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@ -89,9 +89,22 @@ public:
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/// @name Wrapper support
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/// @{
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/// Render as markdown table.
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/// Translation table from values to strings.
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using Names = std::map<Key, std::vector<std::string>>;
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/// Translate an integer index value for given key to a string.
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static std::string Translate(const Names& names, Key key, size_t index);
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/**
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* @brief Render as markdown table
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*
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* @param keyFormatter GTSAM-style Key formatter.
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* @param names optional, category names corresponding to choices.
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* @return std::string a markdown string.
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*/
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virtual std::string markdown(
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const KeyFormatter& keyFormatter = DefaultKeyFormatter) const = 0;
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const KeyFormatter& keyFormatter = DefaultKeyFormatter,
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const Names& names = {}) const = 0;
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/// @}
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};
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@ -16,15 +16,17 @@
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* @author Frank Dellaert
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*/
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//#define ENABLE_TIMING
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#include <gtsam/discrete/DiscreteFactorGraph.h>
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#include <gtsam/discrete/DiscreteConditional.h>
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#include <gtsam/discrete/DiscreteBayesTree.h>
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#include <gtsam/discrete/DiscreteConditional.h>
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#include <gtsam/discrete/DiscreteEliminationTree.h>
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#include <gtsam/discrete/DiscreteFactorGraph.h>
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#include <gtsam/discrete/DiscreteJunctionTree.h>
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#include <gtsam/inference/FactorGraph-inst.h>
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#include <gtsam/inference/EliminateableFactorGraph-inst.h>
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#include <boost/make_shared.hpp>
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#include <gtsam/inference/FactorGraph-inst.h>
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using std::vector;
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using std::string;
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using std::map;
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namespace gtsam {
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@ -64,7 +66,7 @@ namespace gtsam {
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}
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/* ************************************************************************* */
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void DiscreteFactorGraph::print(const std::string& s,
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void DiscreteFactorGraph::print(const string& s,
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const KeyFormatter& formatter) const {
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std::cout << s << std::endl;
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std::cout << "size: " << size() << std::endl;
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@ -130,14 +132,15 @@ namespace gtsam {
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}
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/* ************************************************************************* */
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std::string DiscreteFactorGraph::markdown(
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const KeyFormatter& keyFormatter) const {
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string DiscreteFactorGraph::markdown(
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const KeyFormatter& keyFormatter,
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const DiscreteFactor::Names& names) const {
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using std::endl;
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std::stringstream ss;
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ss << "`DiscreteFactorGraph` of size " << size() << endl << endl;
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for (size_t i = 0; i < factors_.size(); i++) {
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ss << "factor " << i << ":\n";
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ss << factors_[i]->markdown(keyFormatter) << endl;
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ss << factors_[i]->markdown(keyFormatter, names) << endl;
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}
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return ss.str();
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}
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@ -24,7 +24,10 @@
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#include <gtsam/discrete/DecisionTreeFactor.h>
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#include <gtsam/discrete/DiscreteBayesNet.h>
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#include <gtsam/base/FastSet.h>
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#include <boost/make_shared.hpp>
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#include <string>
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#include <vector>
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namespace gtsam {
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@ -140,9 +143,15 @@ public:
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/// @name Wrapper support
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/// @{
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/// Render as markdown table.
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std::string markdown(
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const KeyFormatter& keyFormatter = DefaultKeyFormatter) const;
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/**
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* @brief Render as markdown table
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*
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* @param keyFormatter GTSAM-style Key formatter.
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* @param names optional, a map from Key to category names.
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* @return std::string a (potentially long) markdown string.
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*/
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std::string markdown(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
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const DiscreteFactor::Names& names = {}) const;
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/// @}
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}; // \ DiscreteFactorGraph
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@ -98,7 +98,7 @@ class GTSAM_EXPORT DiscretePrior : public DiscreteConditional {
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* sample
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* @return sample from conditional
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*/
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size_t sample() const { return Base::sample({}); }
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size_t sample() const { return Base::sample(); }
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/// @}
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};
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@ -52,6 +52,8 @@ virtual class DecisionTreeFactor : gtsam::DiscreteFactor {
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std::vector<std::pair<DiscreteValues, double>> enumerate() const;
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string markdown(const gtsam::KeyFormatter& keyFormatter =
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gtsam::DefaultKeyFormatter) const;
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string markdown(const gtsam::KeyFormatter& keyFormatter,
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std::map<gtsam::Key, std::vector<std::string>> names) const;
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};
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#include <gtsam/discrete/DiscreteConditional.h>
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@ -84,10 +86,13 @@ virtual class DiscreteConditional : gtsam::DecisionTreeFactor {
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size_t solve(const gtsam::DiscreteValues& parentsValues) const;
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size_t sample(const gtsam::DiscreteValues& parentsValues) const;
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size_t sample(size_t value) const;
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size_t sample() const;
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void solveInPlace(gtsam::DiscreteValues @parentsValues) const;
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void sampleInPlace(gtsam::DiscreteValues @parentsValues) const;
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string markdown(const gtsam::KeyFormatter& keyFormatter =
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gtsam::DefaultKeyFormatter) const;
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string markdown(const gtsam::KeyFormatter& keyFormatter,
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std::map<gtsam::Key, std::vector<std::string>> names) const;
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};
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#include <gtsam/discrete/DiscretePrior.h>
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@ -101,7 +106,6 @@ virtual class DiscretePrior : gtsam::DiscreteConditional {
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double operator()(size_t value) const;
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std::vector<double> pmf() const;
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size_t solve() const;
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size_t sample() const;
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};
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#include <gtsam/discrete/DiscreteBayesNet.h>
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@ -130,6 +134,8 @@ class DiscreteBayesNet {
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gtsam::DiscreteValues sample() const;
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string markdown(const gtsam::KeyFormatter& keyFormatter =
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gtsam::DefaultKeyFormatter) const;
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string markdown(const gtsam::KeyFormatter& keyFormatter,
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std::map<gtsam::Key, std::vector<std::string>> names) const;
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};
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#include <gtsam/discrete/DiscreteBayesTree.h>
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@ -164,6 +170,8 @@ class DiscreteBayesTree {
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string markdown(const gtsam::KeyFormatter& keyFormatter =
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gtsam::DefaultKeyFormatter) const;
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string markdown(const gtsam::KeyFormatter& keyFormatter,
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std::map<gtsam::Key, std::vector<std::string>> names) const;
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};
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#include <gtsam/inference/DotWriter.h>
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@ -211,6 +219,8 @@ class DiscreteFactorGraph {
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string markdown(const gtsam::KeyFormatter& keyFormatter =
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gtsam::DefaultKeyFormatter) const;
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string markdown(const gtsam::KeyFormatter& keyFormatter,
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std::map<gtsam::Key, std::vector<std::string>> names) const;
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};
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} // namespace gtsam
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@ -119,6 +119,27 @@ TEST(DecisionTreeFactor, markdown) {
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EXPECT(actual == expected);
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}
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/* ************************************************************************* */
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// Check markdown representation with a value formatter.
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TEST(DecisionTreeFactor, markdownWithValueFormatter) {
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DiscreteKey A(12, 3), B(5, 2);
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DecisionTreeFactor f(A & B, "1 2 3 4 5 6");
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string expected =
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"|A|B|value|\n"
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"|:-:|:-:|:-:|\n"
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"|Zero|-|1|\n"
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"|Zero|+|2|\n"
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"|One|-|3|\n"
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"|One|+|4|\n"
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"|Two|-|5|\n"
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"|Two|+|6|\n";
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auto keyFormatter = [](Key key) { return key == 12 ? "A" : "B"; };
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DecisionTreeFactor::Names names{{12, {"Zero", "One", "Two"}},
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{5, {"-", "+"}}};
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string actual = f.markdown(keyFormatter, names);
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EXPECT(actual == expected);
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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@ -187,7 +187,7 @@ TEST(DiscreteBayesNet, markdown) {
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"|1|0.01|\n"
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"\n"
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" *P(Smoking|Asia)*:\n\n"
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"|Asia|0|1|\n"
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"|*Asia*|0|1|\n"
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"|:-:|:-:|:-:|\n"
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"|0|0.8|0.2|\n"
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"|1|0.7|0.3|\n\n";
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|
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@ -143,7 +143,7 @@ TEST(DiscreteConditional, markdown_multivalued) {
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A | B = "2/88/10 2/20/78 33/33/34 33/33/34 95/2/3");
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string expected =
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" *P(a1|b1)*:\n\n"
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"|b1|0|1|2|\n"
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"|*b1*|0|1|2|\n"
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"|:-:|:-:|:-:|:-:|\n"
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"|0|0.02|0.88|0.1|\n"
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"|1|0.02|0.2|0.78|\n"
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@ -161,17 +161,19 @@ TEST(DiscreteConditional, markdown) {
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DiscreteConditional conditional(A, {B, C}, "0/1 1/3 1/1 3/1 0/1 1/0");
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string expected =
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" *P(A|B,C)*:\n\n"
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"|B|C|0|1|\n"
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"|*B*|*C*|T|F|\n"
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"|:-:|:-:|:-:|:-:|\n"
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"|0|0|0|1|\n"
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"|0|1|0.25|0.75|\n"
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"|0|2|0.5|0.5|\n"
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"|1|0|0.75|0.25|\n"
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"|1|1|0|1|\n"
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"|1|2|1|0|\n";
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vector<string> names{"C", "B", "A"};
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auto formatter = [names](Key key) { return names[key]; };
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string actual = conditional.markdown(formatter);
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"|-|Zero|0|1|\n"
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"|-|One|0.25|0.75|\n"
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"|-|Two|0.5|0.5|\n"
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"|+|Zero|0.75|0.25|\n"
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"|+|One|0|1|\n"
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"|+|Two|1|0|\n";
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vector<string> keyNames{"C", "B", "A"};
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auto formatter = [keyNames](Key key) { return keyNames[key]; };
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||||
DecisionTreeFactor::Names names{
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{0, {"Zero", "One", "Two"}}, {1, {"-", "+"}}, {2, {"T", "F"}}};
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string actual = conditional.markdown(formatter, names);
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||||
EXPECT(actual == expected);
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}
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||||
|
||||
|
|
|
@ -28,6 +28,8 @@ static const DiscreteKey X(0, 2);
|
|||
/* ************************************************************************* */
|
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TEST(DiscretePrior, constructors) {
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DiscretePrior actual(X % "2/3");
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EXPECT_LONGS_EQUAL(1, actual.nrFrontals());
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||||
EXPECT_LONGS_EQUAL(0, actual.nrParents());
|
||||
DecisionTreeFactor f(X, "0.4 0.6");
|
||||
DiscretePrior expected(f);
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||||
EXPECT(assert_equal(expected, actual, 1e-9));
|
||||
|
@ -41,12 +43,18 @@ TEST(DiscretePrior, operator) {
|
|||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST(DiscretePrior, to_vector) {
|
||||
TEST(DiscretePrior, pmf) {
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||||
DiscretePrior prior(X % "2/3");
|
||||
vector<double> expected {0.4, 0.6};
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||||
EXPECT(prior.pmf() == expected);
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
TEST(DiscretePrior, sample) {
|
||||
DiscretePrior prior(X % "2/3");
|
||||
prior.sample();
|
||||
}
|
||||
|
||||
/* ************************************************************************* */
|
||||
int main() {
|
||||
TestResult tr;
|
||||
|
|
|
@ -86,8 +86,8 @@ class GTSAM_EXPORT Constraint : public DiscreteFactor {
|
|||
/// @{
|
||||
|
||||
/// Render as markdown table.
|
||||
std::string markdown(
|
||||
const KeyFormatter& keyFormatter = DefaultKeyFormatter) const override {
|
||||
std::string markdown(const KeyFormatter& keyFormatter = DefaultKeyFormatter,
|
||||
const Names& names = {}) const override {
|
||||
return (boost::format("`Constraint` on %1% variables\n") % (size())).str();
|
||||
}
|
||||
|
||||
|
|
|
@ -115,7 +115,7 @@ void runLargeExample() {
|
|||
// Do brute force product and output that to file
|
||||
if (scheduler.nrStudents() == 1) { // otherwise too slow
|
||||
DecisionTreeFactor product = scheduler.product();
|
||||
product.dot("scheduling-large", false);
|
||||
product.dot("scheduling-large", DefaultKeyFormatter, false);
|
||||
}
|
||||
|
||||
// Do exact inference
|
||||
|
|
|
@ -115,7 +115,7 @@ void runLargeExample() {
|
|||
// Do brute force product and output that to file
|
||||
if (scheduler.nrStudents() == 1) { // otherwise too slow
|
||||
DecisionTreeFactor product = scheduler.product();
|
||||
product.dot("scheduling-large", false);
|
||||
product.dot("scheduling-large", DefaultKeyFormatter, false);
|
||||
}
|
||||
|
||||
// Do exact inference
|
||||
|
|
|
@ -139,7 +139,7 @@ void runLargeExample() {
|
|||
// Do brute force product and output that to file
|
||||
if (scheduler.nrStudents() == 1) { // otherwise too slow
|
||||
DecisionTreeFactor product = scheduler.product();
|
||||
product.dot("scheduling-large", false);
|
||||
product.dot("scheduling-large", DefaultKeyFormatter, false);
|
||||
}
|
||||
|
||||
// Do exact inference
|
||||
|
|
|
@ -50,7 +50,7 @@ class TestDiscreteConditional(GtsamTestCase):
|
|||
"0/1 1/3 1/1 3/1 0/1 1/0")
|
||||
expected = \
|
||||
" *P(A|B,C)*:\n\n" \
|
||||
"|B|C|0|1|\n" \
|
||||
"|*B*|*C*|0|1|\n" \
|
||||
"|:-:|:-:|:-:|:-:|\n" \
|
||||
"|0|0|0|1|\n" \
|
||||
"|0|1|0.25|0.75|\n" \
|
||||
|
|
|
@ -6,7 +6,7 @@ All Rights Reserved
|
|||
See LICENSE for the license information
|
||||
|
||||
Unit tests for Discrete Priors.
|
||||
Author: Varun Agrawal
|
||||
Author: Frank Dellaert
|
||||
"""
|
||||
|
||||
# pylint: disable=no-name-in-module, invalid-name
|
||||
|
@ -42,6 +42,11 @@ class TestDiscretePrior(GtsamTestCase):
|
|||
expected = np.array([0.4, 0.6])
|
||||
np.testing.assert_allclose(expected, prior.pmf())
|
||||
|
||||
def test_sample(self):
|
||||
prior = DiscretePrior(X, "2/3")
|
||||
actual = prior.sample()
|
||||
self.assertIsInstance(actual, int)
|
||||
|
||||
def test_markdown(self):
|
||||
"""Test the _repr_markdown_ method."""
|
||||
|
||||
|
|
Loading…
Reference in New Issue