Description Usage Arguments Details Value Author(s) See Also Examples

Find the k-nearest neighbors in one data set for each point in another query data set, using exact or approximate algorithms.

1 |

`X` |
A numeric data matrix where rows are points and columns are dimensions.
This can be missing if |

`query` |
A numeric query matrix where rows are points and columns are dimensions. |

`k` |
An integer scalar specifying the number of nearest neighbors to search for. |

`...` |
Further arguments to pass to specific methods.
This is guaranteed to include |

`BNINDEX` |
A BiocNeighborIndex object containing precomputed index information.
This can be missing if |

`BNPARAM` |
A BiocNeighborParam object specifying the algorithm to use.
This can be missing if |

The class of `BNINDEX`

and `BNPARAM`

will determine dispatch to specific methods.
Only one of these arguments needs to be defined to resolve dispatch.
However, if both are defined, they cannot specify different algorithms.

If `BNINDEX`

is supplied, `X`

does not need to be specified.
In fact, any value of `X`

will be ignored as all necessary information for the search is already present in `BNINDEX`

.
Similarly, any parameters in `BNPARAM`

will be ignored.

If both `BNINDEX`

and `BNPARAM`

are missing, the function will default to the KMKNN algorithm by setting `BNPARAM=KmknnParam()`

.

A list is returned containing `index`

, an integer matrix of neighbor identities;
and `distance`

, a numeric matrix of distances to those neighbors.
See `?"queryKNN-functions"`

for more details.

Aaron Lun

`queryExhaustive`

,
`queryKmknn`

,
`queryVptree`

,
`queryAnnoy`

and `queryHnsw`

for specific methods.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
Y <- matrix(rnorm(100000), ncol=20)
Z <- matrix(rnorm(10000), ncol=20)
str(k.out <- queryKNN(Y, Z, k=10))
str(a.out <- queryKNN(Y, Z, k=10, BNPARAM=AnnoyParam()))
e.dex <- buildExhaustive(Y)
str(k.out2 <- queryKNN(Y,Z, k=10, BNINDEX=e.dex))
str(k.out3 <- queryKNN(Y,Z, k=10, BNINDEX=e.dex, BNPARAM=ExhaustiveParam()))
k.dex <- buildKmknn(Y)
str(k.out2 <- queryKNN(Y,Z, k=10, BNINDEX=k.dex))
str(k.out3 <- queryKNN(Y,Z, k=10, BNINDEX=k.dex, BNPARAM=KmknnParam()))
a.dex <- buildAnnoy(Y)
str(a.out2 <- queryKNN(Y,Z, k=10, BNINDEX=a.dex))
str(a.out3 <- queryKNN(Y,Z, k=10, BNINDEX=a.dex, BNPARAM=AnnoyParam()))
``` |

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