isolate_peak: Isolate peaks
In majpark21/TSexploreR: Explorative Tools for Time Series

Description Usage Arguments Value See Also Examples

Isolate peaks from a signal based on first (and second derivative). Starting from the tip of the peak, walk left (then right) until derivatives overcome thresholds. When this happens, mark a border of the peak. Individual peaks are delimited by these borders. The rational of using the 2nd derivative is to stop whenever the signal is steady (low 2nd derivative) and evolving slowly (low 1st derivative).

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isolate_peak(y, positions, thresh.order1 = 0, include.boundary = TRUE,
  use.second = FALSE, thresh.order22 = NULL, thresh.order12 = NULL,
  out.type = "data.table")

`y`	A numeric vector, from which to isolate peaks.
`positions`	A vector of integers indicating the index of the tip of the peaks.
`thresh.order1`	Threshold for 1st derivative. Whenever the walk encounters a 1st derivative that is bigger than the threshold, stop and define a peak border. Default to 0, i.e. whenever the signal increases again, stop and define a border.
`include.boundary`	logical. If TRUE, will use beginning/end of the series as valid peak border . If FALSE, when a walk from a peak reaches beginning or end of the series, the peak isolation will be considered as failed.
`use.second`	logical, use 2nd derivative?
`thresh.order22`	If use.second = TRUE. If absolute second derivative is below this threshold, consider the signal as steady. If thresh.order12 is also below its threshold at the same time point, stop and define a border.
`thresh.order12`	If use.second = TRUE. If absolute first derivative is below this threshold, consider the signal as evolving very slowly. If thresh.order22 is also below its threshold at the same time point, stop and define a border.
`One`	of c("data.table","list", "vector"). See Return.

If out.type="data.table", returns a data.table with 2 columns. The first one is the signal, the second is a vector indicating to which peak the portion of the signal belongs to. In this vector, 0 means that the portion of the signal does not belong to any peak, while a number > 0 indicate that it belongs to a peak. 1 indicates the first peak referred in 'positions', 2 the second and so on. If for one of the peaks cannot be properly isolated, its number is skipped. If out.type="vector", returns only the second column of the data.table.

Finally, if out.type="list", returns a list of same length as positions. Each element of the list posseses 4 elements: $start: starting point of the peak; $center: tip of the peak (max amplitude); $end: ending point of the peak; $y: part of the signal comprised between $start and $end.

extract_peak

# Curve coming from real-data:
y <- c(1.114, 1.146, 1.106, 1.049, 1.031, 1.01, 1, 0.992, 0.987, 0.981, 1.009, 1.072, 1.053, 1.018, 0.988,
 0.979, 0.965, 0.958, 0.956, 0.942, 0.939, 0.932, 0.926, 0.922, 0.919, 0.919, 0.916, 0.915, 0.918, 0.916,
 0.913, 0.911, 0.907, 0.908, 0.904, 0.905, 0.9, 0.899, 0.899, 0.905, 0.905, 0.908, 0.913, 0.919, 0.919,
 0.911, 0.922, 0.918, 0.916, 0.915, 0.92, 0.917, 0.915, 0.926, 0.964, 1.099, 1.075, 1.018, 0.999, 0.989,
 0.977, 0.975, 0.964, 0.96, 0.958, 0.945, 0.946, 0.944, 0.944, 0.938, 0.934, 0.936, 0.933, 0.926, 0.921,
 0.923, 0.924, 0.926, 0.929, 0.932, 0.926, 0.932, 0.939, 0.941, 0.976, 1.116, 1.09, 1.053, 1.034, 1.019,
 1.038, 1.104, 1.089, 1.059, 1.027, 1.012, 1.009, 1, 0.991, 0.986, 0.973, 0.969, 0.975, 0.966, 0.961,
 0.96, 0.949, 0.946, 0.943, 0.938, 0.942, 0.937, 0.934, 0.936, 0.941, 0.939, 0.97, 0.932, 0.931, 0.941,
 0.944, 0.949, 0.969, 1.048, 1.052, 1.059, 1.103, 1.083, 1.05, 1.036, 1.015, 1.01, 0.997, 0.995, 0.988,
 0.977, 0.979, 0.977, 0.981, 0.982, 0.976, 0.971, 0.97, 0.965, 0.966, 0.967, 0.967, 0.972, 0.904, 0.966,
 0.978, 0.983, 0.979, 0.975, 0.98, 0.973, 0.968, 0.97, 0.962, 0.966, 0.962, 0.968, 0.964, 0.956, 0.963,
 0.954, 0.958, 0.956, 0.958, 0.952, 0.95, 0.952, 0.946, 0.953, 0.952, 0.952, 0.953, 0.952, 0.954, 0.956)
 
 peaks_pos <- extract_peak(y, method = "bump", bp.winlen = 5, bp.mind = 1, recenter = 2, filter.thresh = 0.05, filter.winlen = 10, detect.early = 10)
 peaks <- isolate_peak(y=y, positions=which(peaks_pos$bump), thresh.order1=0, use.second=FALSE, out.type="list")
 plot(y, type = "b", main = "Points are colored according to their respective peaks.")
 abline(v=which(peaks_pos$bump), lty="dashed", col="red")
 col_ind <- 1
 for(peak in peaks){
   if(!any(is.na(c(peak$start, peak$end)))){
     points(peak$start:peak$end, y[peak$start:peak$end], pch=20, col=palette()[col_ind])
     col_ind <- col_ind+1
   }
 }