queryDistance | R Documentation |
Query a reference dataset to determine the distance to the k-th nearest neighbor of each point in a query dataset.
queryDistance(
X,
query,
k,
num.threads = 1,
subset = NULL,
transposed = FALSE,
...,
BNPARAM = NULL
)
X |
The reference dataset to be queried.
This should be a numeric matrix where rows correspond to reference points and columns correspond to variables (i.e., dimensions).
Alternatively, a prebuilt BiocNeighborIndex object from |
query |
A numeric matrix of query points, containing the same number of columns as |
k |
A positive integer scalar specifying the number of nearest neighbors to retrieve. Alternatively, an integer vector of length equal to the number of points in All |
num.threads |
Integer scalar specifying the number of threads to use for the search. |
subset |
An integer, logical or character vector indicating the rows of |
transposed |
A logical scalar indicating whether |
... |
Further arguments to pass to |
BNPARAM |
A BiocNeighborParam object specifying how the index should be constructed.
If |
If multiple queries are to be performed to the same X
, it may be beneficial to build the index from X
with buildIndex
.
The resulting pointer object can be supplied as X
to multiple queryKNN
calls, avoiding the need to repeat index construction in each call.
Numeric vector of length equal to the number of points in query
(or subset
, if provided),
containing the distance from each point to its k
-th nearest neighbor.
This is equivalent to but more memory efficient than using queryKNN
and subsetting to the last distance.
Aaron Lun
buildIndex
, to build an index ahead of time.
Y <- matrix(rnorm(100000), ncol=20)
Z <- matrix(rnorm(20000), ncol=20)
out <- queryDistance(Y, query=Z, k=5)
head(out)
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