Summary
This vignette provides an example of the basic workflow for createVPTS:
Create a VPTS using the BirdScan MR1 example data and create a CSV file,
Read and convert the CSV file to VPTS,
Visualise the time series.
Before we get started
Read Test BirdScanMR1 data
The package ships with a sample data extract from a Birdscan MR1
radar (Sempach, Switzerland), already in the format returned by
extractDbData(). We load it directly from the package’s
extdata folder.
dbData = readRDS(system.file("extdata",
"CH_Sempach_2024_SEP24_25_DataExtract.rds",
package = "birdscanR"
))Step 1: Create VPTS from the BirdScan MR1 example dataset
VPTS CSV files, in line with the ALOFT data standard, can be
generated directly from the echo data with createVPTS().
Note that this function only works on Birdscan MR1 database versions
>= 1.7.0.4, as the variable feature37.speed is required
for the density calculation.
dbName = "CH_Sempach_2024_SEP24_25"
mainOutputDir = file.path(outDir)
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
# Create vpts files
# =============================================================================
vptsDir = createVPTS(
dbName = dbName,
outputDir = mainOutputDir,
echoes = dbData$echoData,
altitudeRange = c(25, 1025),
altitudeBinSize = 50,
timeRange = timeRangeData,
timeBinDuration_sec = 1800,
timeZone = targetTimeZone,
protocolData = dbData$protocolData,
visibilityData = dbData$visibilityData,
siteData = dbData$siteData,
sunriseSunset = dbData$sunriseSunset,
manualBlindTimes = cManualBlindTimes,
saveBlindTimes = FALSE,
blindTimesOutputDir = mainOutputDir,
blindTimeAsMtrZero = NULL,
propObsTimeCutoff = 0.2
)
#> Creating altitude bins..
#> Creating time bins..
#> Warning in createTimeBins(timeRange = timeRange, timeBinDuration_sec =
#> timeBinDuration_sec, : '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..
#> Subsetting echo data..
#> Computing observation times for each timebin..
#> 35 echoes above the defined altitude range, thus excldued from the VPTS calculation.
#> Computing densities in each time-altitude bin..
#> Computing number of animals (n_dbz,), number of birds with speed and direction values (n)mean flux directon (dd, NOTE: not mean circular direction, but mean flux direction taking into account individuals' flight speeds), mean flux speeds (ff, NOTE: not mean ground speed of the individual birds but speed flux size taking into account individual's directions), mean u and v components and mtr-weighted average rcs (rcs) of animal movements in each time-altitude bin..
#> Writing daily VPTS csv files to /tmp/RtmpoVGpFL/vpts..Step 2: Read the CSV-file and convert to VPTS with BioRad::as.vpts()
vpts = read.csv(file.path(vptsDir, "200_vpts_20240924.csv"))
vpts = as.vpts(vpts)
#> Warning in validate_vpts(data): Validation issues found: Type validation failed
#> for radar; Type validation failed for datetime; Type validation failed for w;
#> Type validation failed for sd_vvp; Type validation failed for eta; Type
#> validation failed for dbz; Type validation failed for DBZH; Type validation
#> failed for n_all; Type validation failed for n_dbz_all; Type validation failed
#> for sd_vvp_threshold; Type validation failed for vcp; Type validation failed
#> for source_file
#> Warning in check_multivalue_attributes(data): multiple rcs values found,
#> storing only first (NA) as the functional attribute.