Plots a time series of MTR values as a bar plot. For each bar the spread (first and third Quartile) is shown as error bars as well as the numbers of echoes. Periods with no observation are indicated with grey, negative bars.
Usage
plotLongitudinalMTR(
mtr,
maxMTR,
timeRange = NULL,
targetTimeZone = "Etc/GMT0",
plotClass = "allClasses",
propObsTimeCutoff = 0.2,
plotSpread = TRUE,
filePath = NULL
)Arguments
- mtr
data frame with MTR values created by
computeMTR().- maxMTR
optional numeric variable, fixes the maximum value of the y-Scale of the plot to the given value. If negative or not set, the y-Scale is auto-scaled.
- timeRange
optional list of string vectors length 2, start and end time of the time ranges that should be plotted. The date/time format is “yyyy-MM-dd hh:mm”.
- targetTimeZone
"Etc/GMT0" String specifying the target time zone. Default is "Etc/GMT0".
- plotClass
character string with the class of which the MTR data should be plotted. If not set or set to “allClasses”, MTR of all classes will be plotted.
- propObsTimeCutoff
numeric between 0 and 1. If the MTR is computed per day and night, time bins with a proportional observation time smaller than propObsTimeCutoff are ignored when combining the time bins. If the MTR is computed for each time bin, the parameter is ignored.
- plotSpread
logical, choose if the spread (first and third quartile) should be plotted.
- filePath
character string, path of the directory where the plot should be saved.
savePlotToFile()is used to save the plots as png files with an auto-generated filename.
See also
Other plot functions:
createTimeRangeForPlot(),
plotExploration()
Examples
# \donttest{
# Load example data
# ===========================================================================
dbData = readRDS(system.file("extdata",
"CH_Sempach_2024_SEP24_25_DataExtract.rds",
package = "birdscanR"
))
dbName = "CH_Sempach_2024_SEP24_25"
targetTimeZone = "Etc/GMT0"
timeRangeData = c("2024-09-24 00:00", "2024-09-25 23:59")
# Set manual blind times to NULL (no manual blind times)
# ===========================================================================
cManualBlindTimes = NULL
# Compute migration traffic rate
# ===========================================================================
classSelection.mtr = c("passerine_type")
mtrData = computeMTR(
dbName = dbName,
echoes = dbData$echoData,
classSelection = classSelection.mtr,
altitudeRange = c(25, 1025),
altitudeBinSize = 50,
timeRange = timeRangeData,
timeBinDuration_sec = 1800,
timeZone = targetTimeZone,
sunriseSunset = dbData$sunriseSunset,
sunOrCivil = "civil",
protocolData = dbData$protocolData,
visibilityData = dbData$visibilityData,
manualBlindTimes = cManualBlindTimes,
saveBlindTimes = FALSE,
blindTimesOutputDir = getwd(),
blindTimeAsMtrZero = NULL,
propObsTimeCutoff = 0,
computePerDayNight = FALSE,
computeAltitudeDistribution = TRUE
)
#> Creating altitude bins..
#> Creating time bins..
#> Warning: 'createTimeBins()' was called with an input time range that ends later than 2 days before the last sunrise/sunset in the sunriseSunset dataset. The end of the timerange was adjusted to the last date in the sunriseSunset dataset - 2 days.
#> Calculating blind times..
#> Computing observation times for each timebin..
#> 93 echoes above the defined altitude range, thus excldued from the MTR calculation.
# Make Plot
# ===========================================================================
timeRangePlot = list(
c("2024-09-24 00:00", "2024-09-24 23:59"),
c("2024-09-25 00:00", "2024-09-25 23:59")
)
plotLongitudinalMTR(
mtr = mtrData,
maxMTR = -1,
timeRange = timeRangePlot,
targetTimeZone = "Etc/GMT0",
plotClass = "allClasses",
propObsTimeCutoff = 0.2,
plotSpread = TRUE,
filePath = tempdir()
)
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
#> Warning: Removed 1 row containing missing values or values outside the scale range
#> (`geom_col()`).
# }