Time series warping envelopes
This function computes the envelopes for DTW lower bound calculations with a Sakoe-Chiba band for a given univariate time series using the streaming algorithm proposed by Lemire (2009).
compute_envelope(x, window.size, error.check = TRUE)
x |
A univariate time series. |
window.size |
Window size for envelope calculation. See details. |
error.check |
Logical indicating whether the function should try to detect inconsistencies and give more informative errors messages. Also used internally to avoid repeating checks. |
The windowing constraint uses a centered window. The calculations expect a value in
window.size that represents the distance between the point considered and one of the edges
of the window. Therefore, if, for example, window.size = 10, the warping for an
observation x_i considers the points between x_{i-10} and x_{i+10}, resulting
in 10(2) + 1 = 21 observations falling within the window.
A list with two elements (lower and upper envelopes respectively): lower and upper.
This envelope is calculated assuming a Sakoe-Chiba constraint for DTW.
Lemire D (2009). “Faster retrieval with a two-pass dynamic-time-warping lower bound .” Pattern Recognition, 42(9), pp. 2169 - 2180. ISSN 0031-3203, doi: 10.1016/j.patcog.2008.11.030, https://www.sciencedirect.com/science/article/pii/S0031320308004925.
data(uciCT) H <- compute_envelope(CharTraj[[1L]], 18L) matplot(do.call(cbind, H), type = "l", col = 2:3) lines(CharTraj[[1L]])
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