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Calculates minute-resolution summaries of clicks

fp_summarize.Rd

Calculates minute-resolution summaries of clicks

Usage

fp_summarize(x)

Arguments

x

data.table where each row is a click, as the "clicks" element in the list object returned by fp_read(). Each row must minimally have a POSIXct column time. The return value of fp_read() is also accepted with a warning, provided that the clicks data.table is present .

Value

A data.table with three or four columns:

  • time: POSIXct timestamp of the start of the 1-minute time chunk, in YYYY-mm-dd HH:MM format

  • dpm: detection-positive-minutes, 1 if at least one click is registered during the time chunk; 0 otherwise.

  • bpm: buzz-positive-minutes, 1 if at least one feeding buzz is registered during the time chunk, 0 otherwise. Note that bpm is only available if there is a 'buzz' column in the clicks data.table, e.g. from first calling fp_find_buzzes()

See also

fp_find_buzzes(), lubridate::floor_date()

Examples

# first read some FPOD data
fn <- fp_example("gullars_period1.FP3")
dat <- fp_read(fn)

# extract porpoise clicks of quality Hi and Mod
nbhf <- dat$clicks[species == "NBHF" & quality_level >= 2]

# get a simple summary, with timestamp, degC and dpm.
dpm <- fp_summarize(nbhf)

# If we also wanted buzz-positive-minutes, we could do this first.
nbhf$buzz <- fp_find_buzzes(nbhf, method = "clicks")

# This time, when we call fp_summarize, it should detect that there's a
# buzz column, and automatically calculate feeding-positive-minutes as well.
dpm <- fp_summarize(nbhf)

# Once we have DPMs, we can easily aggregate these into coarser time chunks
dpm_per_hour <- dpm[, .(dpm = sum(dpm)),
    .(date = as.POSIXct(trunc(time, unit = "hours")))] # per hour
dpm_per_day <- dpm[, .(dpm = sum(dpm)),
    .(date = as.Date(time))] # per day
dpm_per_month <- dpm[, .(dpm = sum(dpm)),
    .(date = as.POSIXct(trunc(time, unit = "months")))] # per month