bmatchingLibrary Namespace Reference

functions to solve many standard b-matching problems More...

Functions
SparseMatrix< bool > *	bMatchBipartiteMatrixCache (int rows, int cols, double **W, int *brows, int *bcols, int cacheSize, int maxIters, bool verbose=false)
SparseMatrix< bool > *	bMatchBipartiteMatrixSparse (int rows, int cols, double **W, int *brows, int *bcols, int maxIters)
SparseMatrix< bool > *	bMatchBipartiteMatrixSparse (int rows, int cols, double **W, int *brows, int *bcols)
bool **	bMatchBipartiteMatrix (int rows, int cols, double **W, int *brows, int *bcols, int maxIters)
bool **	bMatchBipartiteMatrix (int rows, int cols, double **W, int *brows, int *bcols)
SparseMatrix< bool > *	bMatchBipartiteEuclideanCache (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols, int cacheSize, int maxIters, bool verbose=false)
SparseMatrix< bool > *	bMatchBipartiteEuclideanSparse (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols, int maxIters)
SparseMatrix< bool > *	bMatchBipartiteEuclideanSparse (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols)
bool **	bMatchBipartiteEuclidean (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols, int maxIters)
bool **	bMatchBipartiteEuclidean (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols)
SparseMatrix< bool > *	bMatchBipartiteInnerProductCache (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols, int cacheSize, int maxIters, bool verbose=false)
SparseMatrix< bool > *	bMatchBipartiteInnerProductSparse (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols, int maxIters)
SparseMatrix< bool > *	bMatchBipartiteInnerProductSparse (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols)
bool **	bMatchBipartiteInnerProduct (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols, int maxIters)
bool **	bMatchBipartiteInnerProduct (int rows, int cols, int d, double **X, double **Y, int *brows, int *bcols)
SparseMatrix< bool > *	bMatchMatrixCache (int size, double **W, int *b, int cacheSize, int maxIters, bool verbose=false)
SparseMatrix< bool > *	bMatchMatrixSparse (int size, double **W, int *b, int maxIters)
SparseMatrix< bool > *	bMatchMatrixSparse (int size, double **W, int *b)
bool **	bMatchMatrix (int size, double **W, int *b, int maxIters)
bool **	bMatchMatrix (int size, double **W, int *b)
SparseMatrix< bool > *	bMatchEuclideanCache (int size, int d, double **X, int *b, int cacheSize, int maxIters, bool verbose=false)
SparseMatrix< bool > *	bMatchEuclideanSparse (int size, int d, double **X, int *b, int maxIters)
SparseMatrix< bool > *	bMatchEuclideanSparse (int size, int d, double **X, int *b)
bool **	bMatchEuclidean (int size, int d, double **X, int *b, int maxIters)
bool **	bMatchEuclidean (int size, int d, double **X, int *b)
SparseMatrix< bool > *	bMatchInnerProductCache (int size, int d, double **X, int *b, int cacheSize, int maxIters, bool verbose=false)
SparseMatrix< bool > *	bMatchInnerProductSparse (int size, int d, double **X, int *b, int maxIters)
SparseMatrix< bool > *	bMatchInnerProductSparse (int size, int d, double **X, int *b)
bool **	bMatchInnerProduct (int size, int d, double **X, int *b, int maxIters)
bool **	bMatchInnerProduct (int size, int d, double **X, int *b)
SparseMatrix< bool > *	solveBMatchingSparse (WeightOracle *wo, int *b, int maxIters, bool verbose=false)
bool **	convertToBool (SparseMatrix< bool > *solution)
int *	cat (int *a, int *b, int aSize, int bSize)

---

Detailed Description

functions to solve many standard b-matching problems

Contains helper functions that construct the appropriate objects to solve b-matching and executes the solver using standard weight functions

---

Function Documentation

bool ** bmatchingLibrary::bMatchBipartiteEuclidean	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols,
		int	maxIters
	)

solves a bipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchBipartiteEuclidean	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols
	)

solves a bipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteEuclideanCache	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols,
		int	cacheSize,
		int	maxIters,
		bool	verbose = false
	)

solves a bipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	cacheSize	number of entries per row to cache
[in]	maxIters	maximum iterations before aborting optimization
[in]	verbose	whether to print status

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteEuclideanSparse	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols
	)

solves a bipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteEuclideanSparse	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols,
		int	maxIters
	)

solves a bipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchBipartiteInnerProduct	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols,
		int	maxIters
	)

solves a bipartite matching with inner product weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchBipartiteInnerProduct	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols
	)

solves a bipartite matching with inner product weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteInnerProductCache	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols,
		int	cacheSize,
		int	maxIters,
		bool	verbose = false
	)

solves a bipartite matching with inner product weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	cacheSize	number of elements per row to cache
[in]	maxIters	maximum iterations before aborting optimization
[in]	verbose	whether to print status

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteInnerProductSparse	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols,
		int	maxIters
	)

solves a bipartite matching with inner product weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteInnerProductSparse	(	int	rows,
		int	cols,
		int	d,
		double **	X,
		double **	Y,
		int *	brows,
		int *	bcols
	)

solves a bipartite matching with inner product weights given the node descriptors

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node, first bipartition
[in]	Y	node descriptor matrix with each row as vector descriptor of a node, second bipartition
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchBipartiteMatrix	(	int	rows,
		int	cols,
		double **	W,
		int *	brows,
		int *	bcols
	)

solves a bipartite matching given the explicit weight matrix

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	W	weight matrix
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)

Returns:

A boolean matrix containing true for the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchBipartiteMatrix	(	int	rows,
		int	cols,
		double **	W,
		int *	brows,
		int *	bcols,
		int	maxIters
	)

solves a bipartite matching given the explicit weight matrix

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	W	weight matrix
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean matrix containing true for the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteMatrixCache	(	int	rows,
		int	cols,
		double **	W,
		int *	brows,
		int *	bcols,
		int	cacheSize,
		int	maxIters,
		bool	verbose = false
	)

solves a bipartite matching given the explicit weight matrix

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	W	weight matrix
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	cacheSize	number of entries to cache per row
[in]	maxIters	maximum iterations before aborting optimization
[in]	verbose	whether to print status

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteMatrixSparse	(	int	rows,
		int	cols,
		double **	W,
		int *	brows,
		int *	bcols,
		int	maxIters
	)

solves a bipartite matching given the explicit weight matrix

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	W	weight matrix
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchBipartiteMatrixSparse	(	int	rows,
		int	cols,
		double **	W,
		int *	brows,
		int *	bcols
	)

solves a bipartite matching given the explicit weight matrix

Parameters:

[in]	rows	total number of rows (number of nodes in first bipartition)
[in]	cols	total number of columns (number of nodes in second bipartition)
[in]	W	weight matrix
[in]	brows	int vector of target degrees for rows (first bipartition)
[in]	bcols	int vector of target degrees for columns (second bipartition)

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchEuclidean	(	int	size,
		int	d,
		double **	X,
		int *	b,
		int	maxIters
	)

solves a unipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchEuclidean	(	int	size,
		int	d,
		double **	X,
		int *	b
	)

solves a unipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchEuclideanCache	(	int	size,
		int	d,
		double **	X,
		int *	b,
		int	cacheSize,
		int	maxIters,
		bool	verbose = false
	)

solves a unipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes
[in]	cacheSize	number of entries per row to cache
[in]	maxIters	maximum iterations before aborting optimization
[in]	verbose	whether to print status

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchEuclideanSparse	(	int	size,
		int	d,
		double **	X,
		int *	b,
		int	maxIters
	)

solves a unipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchEuclideanSparse	(	int	size,
		int	d,
		double **	X,
		int *	b
	)

solves a unipartite matching with negative Euclidean weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchInnerProduct	(	int	size,
		int	d,
		double **	X,
		int *	b
	)

solves a unipartite matching with negative inner product weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchInnerProduct	(	int	size,
		int	d,
		double **	X,
		int *	b,
		int	maxIters
	)

solves a unipartite matching with negative inner product weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchInnerProductCache	(	int	size,
		int	d,
		double **	X,
		int *	b,
		int	cacheSize,
		int	maxIters,
		bool	verbose = false
	)

solves a unipartite matching with negative inner product weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes
[in]	cacheSize	number of entries per row to cache
[in]	maxIters	maximum iterations before aborting optimization
[in]	verbose	whether to print status

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchInnerProductSparse	(	int	size,
		int	d,
		double **	X,
		int *	b,
		int	maxIters
	)

solves a unipartite matching with negative inner product weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchInnerProductSparse	(	int	size,
		int	d,
		double **	X,
		int *	b
	)

solves a unipartite matching with negative inner product weights given the node descriptors

Parameters:

[in]	size	total number of nodes
[in]	d	dimensionality of descriptor vectors
[in]	X	node descriptor matrix with each row as vector descriptor of a node
[in]	b	int vector of target degrees for all nodes

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchMatrix	(	int	size,
		double **	W,
		int *	b,
		int	maxIters
	)

solves a unipartite matching given explicit weight matrix

Parameters:

[in]	size	total number of nodes
[in]	W	weight matrix
[in]	b	int vector of target degrees for each node
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

bool ** bmatchingLibrary::bMatchMatrix	(	int	size,
		double **	W,
		int *	b
	)

solves a unipartite matching given explicit weight matrix

Parameters:

[in]	size	total number of nodes
[in]	W	weight matrix
[in]	b	int vector of target degrees for each node

Returns:

A boolean matrix containing true at the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchMatrixCache	(	int	size,
		double **	W,
		int *	b,
		int	cacheSize,
		int	maxIters,
		bool	verbose = false
	)

solves a unipartite matching given explicit weight matrix

Parameters:

[in]	size	total number of nodes
[in]	W	weight matrix
[in]	b	int vector of target degrees for each node
[in]	maxIters	maximum iterations before aborting optimization
[in]	cacheSize	number of entries per row to cache
[in]	verbose	whether to print status

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchMatrixSparse	(	int	size,
		double **	W,
		int *	b,
		int	maxIters
	)

solves a unipartite matching given explicit weight matrix

Parameters:

[in]	size	total number of nodes
[in]	W	weight matrix
[in]	b	int vector of target degrees for each node
[in]	maxIters	maximum iterations before aborting optimization

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

SparseMatrix< bool > * bmatchingLibrary::bMatchMatrixSparse	(	int	size,
		double **	W,
		int *	b
	)

solves a unipartite matching given explicit weight matrix

Parameters:

[in]	size	total number of nodes
[in]	W	weight matrix
[in]	b	int vector of target degrees for each node

Returns:

A boolean SparseMatrix containing the matched elements of the b-matching adjacency matrix

int * bmatchingLibrary::cat	(	int *	a,
		int *	b,
		int	aSize,
		int	bSize
	)

concatonates two vectors

Parameters:

[in]	a	first vector
[in]	b	second vector
[in]	aSize	length of a
[in]	bSize	length of b

Returns:

a new vector of length (aSize + bSize) containing a copy of a concatenated with a copy of b

bool ** bmatchingLibrary::convertToBool

(

SparseMatrix< bool > *

solution  )

converts a SparseMatrix object to a full boolean matrix

Parameters:

[in]

solution

pointer to solution SparseMatrix

Returns:

the b-matching adjacency matrix as a boolean matrix

SparseMatrix< bool > * bmatchingLibrary::solveBMatchingSparse	(	WeightOracle *	wo,
		int *	b,
		int	maxIters,
		bool	verbose = false
	)

solves a b-matching given the weight oracle and degree constraints

Parameters:

[in]	wo	weight oracle for edge weights of graph
[in]	b	int vector of target degrees for nodes
[in]	maxIters	maximum iterations before aborting optimization
[in]	verbose	whether to print status

Returns:

A boolean SparseMatrix containing matched elements of the b-matching adjacency matrix