Description Usage Arguments Methods (by generic) Slots Author(s) See Also Examples
Class for TimeWeighted Dynamic Time Warping results.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30  ## S4 method for signature 'ANY'
twdtwMatches(timeseries = NULL, patterns = NULL,
alignments = NULL)
## S4 method for signature 'twdtwMatches'
index(x)
## S4 method for signature 'twdtwMatches'
length(x)
## S4 method for signature 'twdtwMatches'
as.list(x)
## S4 method for signature 'twdtwRaster'
as.list(x)
## S4 method for signature 'twdtwMatches,ANY,ANY,ANY'
x[i, j, drop = TRUE]
## S4 method for signature 'twdtwMatches,numeric,ANY'
x[[i, j, drop = TRUE]]
## S4 method for signature 'twdtwMatches'
labels(object)
## S4 method for signature 'twdtwMatches'
show(object)
## S4 method for signature 'ANY'
is.twdtwMatches(x)

timeseries 
a 
patterns 
a 
alignments 
an object of class list with the TWDTW results with
the same length as 
x 
an object of class twdtwMatches. 
i 
indices of the time series. 
j 
indices of the pattern. 
drop 
if TRUE returns a data.frame, if FALSE returns a list. Default is TRUE. 
object 
an object of class twdtwMatches. 
labels 
a vector with labels of the time series. 
... 
objects of class twdtwMatches. 
twdtwMatches
: Create object of class twdtwMatches.
is.twdtwMatches
: Check if the object belongs to the class twdtwMatches.
timeseries
:An object of class twdtwTimeSeriesclass
with the satellite time series.
pattern
:An object of class twdtwTimeSeriesclass
with the temporal patterns.
alignments
:A list
of TWDTW results with the same length as
the timeseries
. Each element in this list has the following results for each temporal pattern
in patterns
:
from
: a vector with the starting dates of each match in the format "YYYYMMDD",
to
: a vector with the ending dates of each match in the format "YYYYMMDD",
distance
: a vector with TWDTW dissimilarity measure, and
K
: the number of matches of the pattern.
if keep=TRUE
in the twdtwApply
call
the list is extended to include internal structures used during the TWDTW computation:
costMatrix
: cumulative cost matrix,
directionMatrix
: directions of steps that would be taken from each element of matrix,
startingMatrix
: the starting points of each element of the matrix,
stepPattern
: stepPattern
used for the
computation, see package dtw
,
N
: the length of the pattern
,
M
: the length of the time series timeseries
,
timeWeight
: time weight matrix,
localMatrix
: local cost matrix,
matching
: A list whose elements have the matching points for
each match between pattern the time series, such that:
–index1
: a vector with matching points of the pattern, and
–index2
: a vector with matching points of the time series.
Victor Maus, [email protected]
twdtwApply
,
twdtwTimeSeriesclass
, and
twdtwRasterclass
1 2 3 4 5 6 7 8 9 10 11 12  ts = twdtwTimeSeries(timeseries=MOD13Q1.ts.list)
patterns = twdtwTimeSeries(timeseries=MOD13Q1.patterns.list)
matches = twdtwApply(x = ts, y = patterns)
class(matches)
length(matches)
matches
# Creating objects of class twdtwMatches
ts = twdtwTimeSeries(MOD13Q1.ts.list)
patt = twdtwTimeSeries(MOD13Q1.patterns.list)
mat = twdtwApply(ts, patt, weight.fun = logisticWeight(0.1, 100))
mat = twdtwMatches(ts, patterns=patt, alignments=mat)
mat

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