stomp_par | R Documentation |
Computes the Matrix Profile and Profile Index for Univariate Time Series.
stomp_par( ..., window_size, exclusion_zone = getOption("tsmp.exclusion_zone", 1/2), verbose = getOption("tsmp.verbose", 2), n_workers = 2 ) stomp( ..., window_size, exclusion_zone = getOption("tsmp.exclusion_zone", 1/2), verbose = getOption("tsmp.verbose", 2) )
... |
a |
window_size |
an |
exclusion_zone |
a |
verbose |
an |
n_workers |
an |
The Matrix Profile, has the potential to revolutionize time series data mining because of its
generality, versatility, simplicity and scalability. In particular it has implications for time
series motif discovery, time series joins, shapelet discovery (classification), density
estimation, semantic segmentation, visualization, rule discovery, clustering etc. verbose
changes how much information is printed by this function; 0
means nothing, 1
means text, 2
adds the progress bar, 3
adds the finish sound. exclusion_zone
is used to avoid trivial
matches; if a query data is provided (join similarity), this parameter is ignored.
Returns a MatrixProfile
object, a list
with the matrix profile mp
, profile index pi
left and right matrix profile lmp
, rmp
and profile index lpi
, rpi
, window size w
and
exclusion zone ez
.
stomp_par()
: Parallel version.
stomp()
: Single thread version.
Zhu Y, Zimmerman Z, Senobari NS, Yeh CM, Funning G. Matrix Profile II : Exploiting a Novel Algorithm and GPUs to Break the One Hundred Million Barrier for Time Series Motifs and Joins. Icdm. 2016 Jan 22;54(1):739-48.
Website: http://www.cs.ucr.edu/~eamonn/MatrixProfile.html
Other matrix profile computations:
mstomp_par()
,
scrimp()
,
stamp_par()
,
tsmp()
,
valmod()
mp <- stomp(mp_toy_data$data[1:200, 1], window_size = 30, verbose = 0) #' # using threads mp <- stomp_par(mp_toy_data$data[1:400, 1], window_size = 30, verbose = 0) ref_data <- mp_toy_data$data[, 1] query_data <- mp_toy_data$data[, 2] # self similarity mp <- stomp(ref_data, window_size = 30) # join similarity mp2 <- stomp(ref_data, query_data, window_size = 30)
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