Computes pairwise similarities/distances between two collections of objects (strings, vectors, etc.) using the provided comparator.
pairwise(comparator, x, y, return_matrix = FALSE, ...)# S4 method for Comparator,ANY,missing
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for CppSeqComparator,list,list
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for CppSeqComparator,list,`NULL`
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for StringComparator,vector,vector
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for StringComparator,vector,`NULL`
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for NumericComparator,matrix,vector
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for NumericComparator,vector,matrix
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for Chebyshev,matrix,matrix
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for Chebyshev,matrix,`NULL`
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for Minkowski,matrix,matrix
elementwise(comparator, x, y, ...)
# S4 method for Minkowski,matrix,matrix
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for Minkowski,matrix,`NULL`
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for FuzzyTokenSet,list,list
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for FuzzyTokenSet,vector,`NULL`
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for InVocabulary,vector,vector
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for InVocabulary,vector,`NULL`
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for Lookup,vector,vector
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for Lookup,vector,`NULL`
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for MongeElkan,list,list
pairwise(comparator, x, y, return_matrix = FALSE, ...)
# S4 method for MongeElkan,list,`NULL`
pairwise(comparator, x, y, return_matrix = FALSE, ...)
If both x and y are specified, every object in x is compared with
every object in y using the comparator, and the resulting scores are
returned in a size(x) by size(y) matrix.
If only x is specified, then the objects in x are compared with
themselves using the comparator, and the resulting scores are returned in a
size(x) by size(y) matrix.
By default, the matrix is represented as an instance of the
PairwiseMatrix class, which is more space-efficient for symmetric
comparators when y is not specified. However, if return_matrix = TRUE,
the matrix is returned as an ordinary matrix instead.
a comparator used to compare the objects, which is a
sub-class of Comparator.
a collection of objects to compare, typically stored as entries
in an atomic vector, rows in a matrix, or entries in a list. The required
format depends on the type of comparator. y may be omitted or set to
NULL to compare objects in x.
a logical of length 1. If FALSE (default), the pairwise
similarities/distances will be returned as a PairwiseMatrix
which is more space-efficient for symmetric comparators. If TRUE, a
standard matrix is returned instead.
other parameters passed on to other methods.
comparator = Comparator,x = ANY,y = missing: Compute a pairwise comparator when y
comparator = CppSeqComparator,x = list,y = list: Specialization for CppSeqComparator where x
and y are lists of sequences (vectors) to compare.
comparator = CppSeqComparator,x = list,y = NULL: Specialization for CppSeqComparator where x is
a list of sequences (vectors) to compare.
comparator = StringComparator,x = vector,y = vector: Specialization for StringComparator where x
and y are vectors of strings to compare.
comparator = StringComparator,x = vector,y = NULL: Specialization for StringComparator where x
is a vector of strings to compare.
comparator = NumericComparator,x = matrix,y = vector: Specialization for NumericComparator where x
is a matrix of rows (interpreted as vectors) to compare with a vector y.
comparator = NumericComparator,x = vector,y = matrix: Specialization for NumericComparator where x
is a vector to compare with a matrix y of rows (interpreted as vectors).
comparator = Chebyshev,x = matrix,y = matrix: Specialization for Chebyshev where x and y
matrices of rows (interpreted as vectors) to compare.
comparator = Chebyshev,x = matrix,y = NULL: Specialization for Minkowski where x is a matrix
of rows (interpreted as vectors) to compare among themselves.
comparator = Minkowski,x = matrix,y = matrix: Specialization for a Minkowski where x and y
matrices of rows (interpreted as vectors) to compare.
comparator = Minkowski,x = matrix,y = matrix: Specialization for a Minkowski where x and y
matrices of rows (interpreted as vectors) to compare.
comparator = Minkowski,x = matrix,y = NULL: Specialization for Minkowski where x is a matrix
of rows (interpreted as vectors) to compare among themselves.
comparator = FuzzyTokenSet,x = list,y = list: Specialization for FuzzyTokenSet where x and y are
lists of token vectors to compare.
comparator = FuzzyTokenSet,x = vector,y = NULL: Specialization for FuzzyTokenSet where x is a list of token
vectors to compare among themselves.
comparator = InVocabulary,x = vector,y = vector: Specialization for InVocabulary where x and y
are vectors of strings to compare.
comparator = InVocabulary,x = vector,y = NULL: Specialization for InVocabulary where x is a
vector of strings to compare among themselves.
comparator = Lookup,x = vector,y = vector: Specialization for a Lookup where x and y are
vectors of strings to compare
comparator = Lookup,x = vector,y = NULL: Specialization for Lookup where x is a vector of
strings to compare among themselves
comparator = MongeElkan,x = list,y = list: Specialization for MongeElkan where x and y are
lists of token vectors to compare.
comparator = MongeElkan,x = list,y = NULL: Specialization for MongeElkan where x is a list
of token vectors to compare among themselves.
## Computing the distances between a query point y (a 3D numeric vector)
## and a set of reference points x
x <- rbind(c(1,0,1), c(0,0,0), c(-1,2,-1))
y <- c(10, 5, 10)
pairwise(Manhattan(), x, y)
## Computing the pairwise similarities among a set of strings
x <- c("Benjamin", "Ben", "Benny", "Bne", "Benedict", "Benson")
comparator <- DamerauLevenshtein(similarity = TRUE, normalize = TRUE)
pairwise(comparator, x, return_matrix = TRUE) # return an ordinary matrix
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