gtsam 4.2.0
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gtsam::DecisionTree< L, Y > Class Template Reference

Detailed Description

template<typename L, typename Y>
class gtsam::DecisionTree< L, Y >

Decision Tree L = label for variables Y = function range (any algebra), e.g., bool, int, double.

+ Inheritance diagram for gtsam::DecisionTree< L, Y >:

Public Member Functions

Standard Constructors
 DecisionTree ()
 Default constructor (for serialization)
 
 DecisionTree (const Y &y)
 Create a constant.
 
 DecisionTree (const L &label, const Y &y1, const Y &y2)
 Create tree with 2 assignments y1, y2, splitting on variable label
 
 DecisionTree (const LabelC &label, const Y &y1, const Y &y2)
 Allow Label+Cardinality for convenience.
 
 DecisionTree (const std::vector< LabelC > &labelCs, const std::vector< Y > &ys)
 Create from keys and a corresponding vector of values.
 
 DecisionTree (const std::vector< LabelC > &labelCs, const std::string &table)
 Create from keys and string table.
 
template<typename Iterator >
 DecisionTree (Iterator begin, Iterator end, const L &label)
 Create DecisionTree from others.
 
 DecisionTree (const L &label, const DecisionTree &f0, const DecisionTree &f1)
 Create DecisionTree from two others.
 
template<typename X , typename Func >
 DecisionTree (const DecisionTree< L, X > &other, Func Y_of_X)
 Convert from a different value type.
 
template<typename M , typename X , typename Func >
 DecisionTree (const DecisionTree< M, X > &other, const std::map< M, L > &map, Func Y_of_X)
 Convert from a different value type X to value type Y, also transate labels via map from type M to L.
 
Testable
void print (const std::string &s, const LabelFormatter &labelFormatter, const ValueFormatter &valueFormatter) const
 GTSAM-style print.
 
bool equals (const DecisionTree &other, const CompareFunc &compare=&DefaultCompare) const
 
Standard Interface
virtual ~DecisionTree ()=default
 Make virtual.
 
bool empty () const
 Check if tree is empty.
 
bool operator== (const DecisionTree &q) const
 equality
 
const Y & operator() (const Assignment< L > &x) const
 evaluate
 
template<typename Func >
void visit (Func f) const
 Visit all leaves in depth-first fashion.
 
template<typename Func >
void visitLeaf (Func f) const
 Visit all leaves in depth-first fashion.
 
template<typename Func >
void visitWith (Func f) const
 Visit all leaves in depth-first fashion.
 
size_t nrLeaves () const
 Return the number of leaves in the tree.
 
template<typename Func , typename X >
fold (Func f, X x0) const
 Fold a binary function over the tree, returning accumulator.
 
std::set< L > labels () const
 Retrieve all unique labels as a set.
 
DecisionTree apply (const Unary &op) const
 apply Unary operation "op" to f
 
DecisionTree apply (const UnaryAssignment &op) const
 Apply Unary operation "op" to f while also providing the corresponding assignment.
 
DecisionTree apply (const DecisionTree &g, const Binary &op) const
 apply binary operation "op" to f and g
 
DecisionTree choose (const L &label, size_t index) const
 create a new function where value(label)==index It's like "restrict" in Darwiche09book pg329, 330?
 
DecisionTree combine (const L &label, size_t cardinality, const Binary &op) const
 combine subtrees on key with binary operation "op"
 
DecisionTree combine (const LabelC &labelC, const Binary &op) const
 combine with LabelC for convenience
 
void dot (std::ostream &os, const LabelFormatter &labelFormatter, const ValueFormatter &valueFormatter, bool showZero=true) const
 output to graphviz format, stream version
 
void dot (const std::string &name, const LabelFormatter &labelFormatter, const ValueFormatter &valueFormatter, bool showZero=true) const
 output to graphviz format, open a file
 
std::string dot (const LabelFormatter &labelFormatter, const ValueFormatter &valueFormatter, bool showZero=true) const
 output to graphviz format string
 
Advanced Interface
 DecisionTree (const NodePtr &root)
 
template<typename Iterator >
NodePtr compose (Iterator begin, Iterator end, const L &label) const
 

Public Attributes

NodePtr root_
 A DecisionTree just contains the root. TODO(dellaert): make protected.
 

Public Types

using LabelFormatter = std::function< std::string(L)>
 
using ValueFormatter = std::function< std::string(Y)>
 
using CompareFunc = std::function< bool(const Y &, const Y &)>
 
using Unary = std::function< Y(const Y &)>
 Handy typedefs for unary and binary function types.
 
using UnaryAssignment = std::function< Y(const Assignment< L > &, const Y &)>
 
using Binary = std::function< Y(const Y &, const Y &)>
 
using LabelC = std::pair< L, size_t >
 A label annotated with cardinality.
 
using NodePtr = typename Node::Ptr
 ---------------------— Node base class ------------------------—
 

Classes

struct  Choice
 
struct  Leaf
 
struct  Node
 ---------------------— Node base class ------------------------— More...
 

Protected Member Functions

template<typename It , typename ValueIt >
NodePtr create (It begin, It end, ValueIt beginY, ValueIt endY) const
 Internal recursive function to create from keys, cardinalities, and Y values.
 
template<typename M , typename X >
NodePtr convertFrom (const typename DecisionTree< M, X >::NodePtr &f, std::function< L(const M &)> L_of_M, std::function< Y(const X &)> Y_of_X) const
 Convert from a DecisionTree<M, X> to DecisionTree<L, Y>.
 

Static Protected Member Functions

static bool DefaultCompare (const Y &a, const Y &b)
 Default method for comparison of two objects of type Y.
 

Friends

class boost::serialization::access
 Serialization function.
 

Member Typedef Documentation

◆ NodePtr

template<typename L , typename Y >
using gtsam::DecisionTree< L, Y >::NodePtr = typename Node::Ptr

---------------------— Node base class ------------------------—

A function is a shared pointer to the root of a DT

Constructor & Destructor Documentation

◆ DecisionTree() [1/2]

template<typename L , typename Y >
template<typename X , typename Func >
gtsam::DecisionTree< L, Y >::DecisionTree ( const DecisionTree< L, X > &  other,
Func  Y_of_X 
)

Convert from a different value type.

Template Parameters
XThe previous value type.
Parameters
otherThe DecisionTree to convert from.
Y_of_XFunctor to convert from value type X to type Y.

◆ DecisionTree() [2/2]

template<typename L , typename Y >
template<typename M , typename X , typename Func >
gtsam::DecisionTree< L, Y >::DecisionTree ( const DecisionTree< M, X > &  other,
const std::map< M, L > &  map,
Func  Y_of_X 
)

Convert from a different value type X to value type Y, also transate labels via map from type M to L.

Template Parameters
MPrevious label type.
XPrevious value type.
Parameters
otherThe decision tree to convert.
L_of_MMap from label type M to type L.
Y_of_XFunctor to convert from type X to type Y.

Member Function Documentation

◆ apply()

template<typename L , typename Y >
DecisionTree< L, Y > gtsam::DecisionTree< L, Y >::apply ( const UnaryAssignment &  op) const

Apply Unary operation "op" to f while also providing the corresponding assignment.

Apply unary operator with assignment.

Parameters
opFunction which takes Assignment<L> and Y as input and returns object of type Y.
Returns
DecisionTree

◆ convertFrom()

template<typename L , typename Y >
template<typename M , typename X >
DecisionTree< L, Y >::NodePtr gtsam::DecisionTree< L, Y >::convertFrom ( const typename DecisionTree< M, X >::NodePtr f,
std::function< L(const M &)>  L_of_M,
std::function< Y(const X &)>  Y_of_X 
) const
protected

Convert from a DecisionTree<M, X> to DecisionTree<L, Y>.

Template Parameters
MThe previous label type.
XThe previous value type.
Parameters
fThe node pointer to the root of the previous DecisionTree.
L_of_MFunctor to convert from label type M to type L.
Y_of_XFunctor to convert from value type X to type Y.
Returns
NodePtr

◆ fold()

template<typename L , typename Y >
template<typename Func , typename X >
X gtsam::DecisionTree< L, Y >::fold ( Func  f,
x0 
) const

Fold a binary function over the tree, returning accumulator.

Template Parameters
Xtype for accumulator.
Parameters
fbinary function: Y * X -> X returning an updated accumulator.
x0initial value for accumulator.
Returns
X final value for accumulator.
Note
X is always passed by value.
Due to pruning, leaves might not exhaust choices.

Example: auto add = [](const double& y, double x) { return y + x; }; double sum = tree.fold(add, 0.0);

◆ labels()

template<typename L , typename Y >
std::set< L > gtsam::DecisionTree< L, Y >::labels ( ) const

Retrieve all unique labels as a set.

Get (partial) labels by performing a visit.

This method performs a depth-first search to go to every leaf and records the keys assignment which leads to that leaf. Since the tree can be pruned, there might be a leaf at a lower depth which results in a partial assignment (i.e. not all keys are specified).

E.g. given a tree with 3 keys, there may be a branch where the 3rd key has the same values for all the leaves. This leads to the branch being pruned so we get a leaf which is arrived at by just the first 2 keys and their assignments.

◆ print()

template<typename L , typename Y >
void gtsam::DecisionTree< L, Y >::print ( const std::string &  s,
const LabelFormatter &  labelFormatter,
const ValueFormatter &  valueFormatter 
) const

GTSAM-style print.

Parameters
sPrefix string.
labelFormatterFunctor to format the node label.
valueFormatterFunctor to format the node value.

◆ visit()

template<typename L , typename Y >
template<typename Func >
void gtsam::DecisionTree< L, Y >::visit ( Func  f) const

Visit all leaves in depth-first fashion.

Parameters
f(side-effect) Function taking the value of the leaf node.
Note
Due to pruning, the number of leaves may not be the same as the number of assignments. E.g. if we have a tree on 2 binary variables with all values being 1, then there are 2^2=4 assignments, but only 1 leaf.

Example: int sum = 0; auto visitor = [&](int y) { sum += y; }; tree.visit(visitor);

◆ visitLeaf()

template<typename L , typename Y >
template<typename Func >
void gtsam::DecisionTree< L, Y >::visitLeaf ( Func  f) const

Visit all leaves in depth-first fashion.

Parameters
f(side-effect) Function taking the leaf node pointer.
Note
Due to pruning, the number of leaves may not be the same as the number of assignments. E.g. if we have a tree on 2 binary variables with all values being 1, then there are 2^2=4 assignments, but only 1 leaf.

Example: int sum = 0; auto visitor = [&](const Leaf& leaf) { sum += leaf.constant(); }; tree.visitLeaf(visitor);

◆ visitWith()

template<typename L , typename Y >
template<typename Func >
void gtsam::DecisionTree< L, Y >::visitWith ( Func  f) const

Visit all leaves in depth-first fashion.

Parameters
f(side-effect) Function taking an assignment and a value.
Note
Due to pruning, the number of leaves may not be the same as the number of assignments. E.g. if we have a tree on 2 binary variables with all values being 1, then there are 2^2=4 assignments, but only 1 leaf.

Example: int sum = 0; auto visitor = [&](const Assignment<L>& assignment, int y) { sum += y; }; tree.visitWith(visitor);


The documentation for this class was generated from the following files: