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```
##
## Metric to calculate the number of outliers for a Stream of seismic data
##
## Copyright (C) 2012 Mazama Science, Inc.
## by Jonathan Callahan, jonathan@mazamascience.com
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; if not, write to the Free Software
## Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
################################################################################
# The IRIS DMC MUSTANG project keeps track of
#
# - num_spikes
#
# This metric applies the roll_hampel filter from the 'seismicRoll' package.
# See: "Median absolute deviation (MAD) outlier in Time Series"
spikesMetric <- function(st, windowSize=41, thresholdMin=10, selectivity=NA, fixedThreshold=TRUE) {
starttime <- st@requestedStarttime
endtime <- st@requestedEndtime
num_traces <- length(st@traces)
x <- sapply(1:length(st@traces),function(x) { c(st@traces[[x]]@data) })
x <- c(x, recursive=TRUE)
if (length(x) < windowSize) {
stop(paste("spikesMetric: skipping ", st@traces[[1]]@id, "trace length", length(x), "is less than windowSize", windowSize))
}
# Calculate the total number of outliers from all traces
count <- 0
result <- try( outlierIndices <- seismicRoll::findOutliers(x, n=windowSize, thresholdMin=thresholdMin ,selectivity=selectivity, fixedThreshold=fixedThreshold),
silent=TRUE )
if (class(result)[1] != "try-error" ) {
# NOTE: Ignore adjacent outliers when determining the count of spikes.
# NOTE: But be sure there is at least one spike if there is at least one outlier.
if (length(outlierIndices) != 0 ) {
count <- length(which(diff(outlierIndices) > 1)) + 1
}
} else {
stop(paste("spikesMetric: skipping ", st@traces[[1]]@id, geterrmessage()))
}
# Create and return a list of Metric objects
snclq <- st@traces[[1]]@id
m1 <- new("GeneralValueMetric", snclq=snclq, starttime=starttime, endtime=endtime, metricName="num_spikes", elementNames=c("value"), elementValues=count)
return(c(m1))
}
```

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