addItemsCol
,
getAllNNsCol
and getAllNNsListCol
are the
column-based equivalents of addItems
,
getAllNNs
and getAllNNsList
, respectively.
Note that the returned nearest neighbor data from
getAllNNsCol
and getAllNNsListCol
are
also stored by column, i.e. the matrices have dimensions
k x n
where k
is the number of neighbors, and
n
the number of items in the data being searched.byrow
has
been added to hnsw_knn
, hnsw_build
and
hnsw_search
. By default this is set to TRUE
and indicates that the items in the input matrix are found in each row.
To pass column-stored items, set byrow = FALSE
. Any
matrices returned by hnsw_search
and hnsw_knn
will now follow the convention provided by the value of
byrow
: i.e. if byrow = FALSE
, the matrices
contain nearest neighbor information in each column.getItems
, which returns a matrix of the
data vectors in the index with the specified integer identifiers. From a
feature request made by d4tum (https://github.com/jlmelville/rcpphnsw/issues/18).progress
parameter in the functional interface no
longer does anything. When verbose = TRUE
, a progress bar
is no longer shown.setNumThreads
method if using the object-based API, and the
n_threads
parameter in the hnsw_*
function
API. For finer control, a setGrainSize
and
grain_size
option is also available in the object and
function interface respectively. Thank you to Dmitriy Selivanov for a lot of
the work on this.verbose = TRUE
now has incurs substantially
less computational overhead associated with calculating the progress
bar. Thank you to Samuel
Granjeaud for spotting the problem and coming up with various
solutions.progress
. By default this is set to
"bar"
and will show the progress bar when
verbose = TRUE
. If you want a more terse output, set
progress = NULL
. progress = NULL
will
eventually be the default setting: for now, verbose = TRUE
will get you the progress bar by default for backwards
compatibility.markDeleted
, that will remove an object
from being retrieved from the index.resizeIndex
, that allows the index to be
increased without having to save and reload the index.size
is available for the index objects
and reports the number of items added to the index.hnsw_search
would stop
if the number of
rows in the input matrix was smaller than k
. This check has
been removed. Note that the correct behavior is to ensure that
k
is smaller than or equal to index$size()
where index
is the index you are searching. Because the
size()
method is new to this version, to preserve
compatibility with old indexes, this check hasn’t been added to
hnsw_search
. If this matters to you, manually compare
index$size()
with k
before running
hnsw_search
. An error will be thrown if k
neighbors can’t be found in the index. Thank you to Yuxing Liao for spotting this and
the pull request to remove the check.Initial release.