plot.rundtw | R Documentation |
Plot the results from rundtw
.
## S3 method for class 'rundtw' plot(x, knn = TRUE, minima = TRUE, scale = c("none", "01", "z"), selDim = 1, lix = 1, Q = NULL, C = NULL, normalize = c("none", "01", "z"), ...)
x |
output from |
knn |
logical, if TRUE ( = default) and the k nearest neighbors were found by |
minima |
logical, if TRUE ( = default) and |
scale |
character, one of c("none", "01", "z"). If "01" or "z" then the detected minima and knn are normed and plotted. |
selDim |
integer vector, default = 1. Set the dimensions to be plotted for multivariate time series |
lix |
list index, integer, default = 1. If |
Q |
time series, default = NULL, either passed as list entry of |
C |
time series, default = NULL, either passed as list entry of |
normalize |
deprecated, use |
... |
additional arguments passed to ggplot() |
Only for those subsequences for which the calculations were finished by rundtw
, the distances are plotted (see the parameters threshold
, k
and early_abandon
of rundtw
).
rundtw
#--- Simulate a query pattern Q and a longer time series C, # and detect rescaled versions of Q in C set.seed(123) Q <- sin(seq(0, 2*pi, length.out = 20)) Q_rescaled <- Q * abs(rnorm(1)) + rnorm(1) C <- c(rnorm(20), Q_rescaled , rnorm(20)) # Force rundtw to finish all calculations and plot the vector of DTW distances ret <- rundtw(Q, C, threshold = NULL, lower_bound = FALSE) ret plot(ret) # Allow early abandoning and lower bounding, and also plot C ret <- rundtw(Q, C, return_QC = TRUE, ws = 5) ret plot(ret) # Get 1 nearest neighbor -> allow early abandon and lower bounding, # and plot C and also plot the scaled detected nearest neighbors ret <- rundtw(Q, C, ws = 5, k = 1, return_QC = TRUE) ret plot(ret, scale = "01") #--- See the help page of rundtw() for further examples.
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