tsclustFamily-class | R Documentation |
tsclustFamily
Formal S4 class with a family of functions used in tsclust()
.
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.
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()
).
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 with proxy::dist()
).
If control$distmat
is not NULL
, the function will try to subset it.
If control$symmetric
is TRUE
, centroids
is NULL
, and there is no argument
pairwise
that is TRUE
, only half the distance matrix will be computed.
The function always returns a crossdist
matrix.
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$symmetric
is TRUE
centroids
is NULL
pairwise
is FALSE
or NULL
The distance was registered in proxy::pr_DB with loop = TRUE
A parallel backend with more than 1 worker has been registered with foreach
This symmetric, parallel case makes chunks for parallel workers, but they are not perfectly balanced, so some workers might finish before the others.
The default partitional allcent() function is a closure with the implementations of the
included centroids. The ones for DBA()
, shape_extraction()
and sdtw_cent()
can use
multi-process parallelization with foreach::foreach()
. Its formal arguments are described in
the Centroid Calculation section from tsclust()
.
This class is meant to group together the relevant functions, but they are not linked with
each other automatically. In other words, neither dist
nor allcent
apply preproc
. They
essentially don't know of each other's existence.
dtw_basic()
, dtw_lb()
, gak()
, lb_improved()
, lb_keogh()
, sbd()
, sdtw()
.
## Not run: data(uciCT) # See "GAK" documentation fam <- new("tsclustFamily", dist = "gak") # This is done with symmetric optimizations, regardless of control$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)
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