tsclustFamily-class {dtwclust} | R Documentation |
Class definition for tsclustFamily
Description
Formal S4 class with a family of functions used in tsclust()
.
Details
The custom implementations also handle parallelization.
Since the distance function makes use of proxy, it also supports any extra proxy::dist()
parameters in ...
.
The prototype includes the cluster
function for partitional methods, as well as a pass-through
preproc
function. The initializer expects a control from tsclust-controls. See more below.
Slots
dist
The function to calculate the distance matrices.
allcent
The function to calculate centroids on each iteration.
cluster
The function used to assign a series to a cluster.
preproc
The function used to preprocess the data (relevant for
stats::predict()
).
Distance function
The family's dist() function works like proxy::dist()
but supports parallelization and
optimized symmetric calculations. If you like, you can use the function more or less directly,
but provide a control argument when creating the family (see examples). However, bear in mind
the following considerations.
The second argument is called
centroids
(inconsistent withproxy::dist()
).If
control$distmat
is notNULL
, the function will try to subset it.If
control$symmetric
isTRUE
,centroids
isNULL
, and there is no argumentpairwise
that isTRUE
, only half the distance matrix will be computed.
Note that all distances implemented as part of dtwclust have custom proxy loops that use multi-threading independently of foreach, so see their respective documentation to see what optimizations apply to each one.
For distances not included in dtwclust, the computation can be in parallel using
multi-processing with foreach::foreach()
. If you install and load or attach (see
base::library()
or base::loadNamespace()
) the bigmemory package, the function will
take advantage of said package when all of the following conditions are met, reducing the
overhead of data copying across processes:
-
control$symmetric
isTRUE
-
centroids
isNULL
-
pairwise
isFALSE
orNULL
The distance was registered in proxy::pr_DB with
loop = TRUE
A parallel backend with more than 1 worker has been registered with foreach
This symmetric, parallel case makes chunks for parallel workers, but they are not perfectly balanced, so some workers might finish before the others.
Centroid function
The default partitional allcent() function is a closure with the implementations of the
included centroids. The ones for DBA()
, shape_extraction()
and sdtw_cent()
can use
multi-process parallelization with foreach::foreach()
. Its formal arguments are described in
the Centroid Calculation section from tsclust()
.
Note
This class is meant to group together the relevant functions, but they are not linked with
each other automatically. In other words, neither dist
nor allcent
apply preproc
. They
essentially don't know of each other's existence.
See Also
dtw_basic()
, dtw_lb()
, gak()
, lb_improved()
, lb_keogh()
, sbd()
, sdtw()
.
Examples
## Not run:
data(uciCT)
# See "GAK" documentation
fam <- new("tsclustFamily", dist = "gak")
# This is done with symmetric optimizations, regardless of control$symmetric
crossdist <- fam@dist(CharTraj, window.size = 18L)
# This is done without symmetric optimizations, regardless of control$symmetric
crossdist <- fam@dist(CharTraj, CharTraj, window.size = 18L)
# For non-dtwclust distances, symmetric optimizations only apply
# with an appropriate control AND a single data argument:
fam <- new("tsclustFamily", dist = "dtw",
control = partitional_control(symmetric = TRUE))
fam@dist(CharTraj[1L:5L])
# If you want the fuzzy family, use fuzzy = TRUE
ffam <- new("tsclustFamily", control = fuzzy_control(), fuzzy = TRUE)
## End(Not run)