library(adaptNP)
library(dplyr) # recommended for the examples
#> Warning: package 'dplyr' was built under R version 4.5.2
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
# to add: get data
data = Esthwaite_Buoy_HiRes # pre-loaded data
criteria = '(Temp4m > 18) | (SPFD >800)'
flag_event(data,criteria)
#> # A tibble: 126,472 × 24
#> TIMESTAMP RECORD AirTemp WindDir WindSpd CMP6 SPFD PonselTemp
#> <dttm> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 2025-04-29 21:06:00 0 12.9 55.7 0 0 0.0253 14.7
#> 2 2025-04-29 21:08:00 1 12.9 61.7 1.87 0 0.0126 14.7
#> 3 2025-04-29 21:10:00 2 12.8 39.9 1.88 0 0.0379 14.7
#> 4 2025-04-29 21:12:00 3 12.6 43.1 1.47 0 0.0442 14.7
#> 5 2025-04-29 21:14:00 4 12.8 55.8 1.59 0 0.0506 14.7
#> 6 2025-04-29 21:16:00 5 12.7 66.6 1.69 0 0.0379 14.7
#> 7 2025-04-29 21:18:00 6 12.6 63.2 1.80 0 0.0569 14.7
#> 8 2025-04-29 21:20:00 7 12.5 63.0 2.01 0 -0.0126 14.7
#> 9 2025-04-29 21:22:00 8 12.4 63.0 2.04 0 0.0442 14.7
#> 10 2025-04-29 21:26:00 0 12.3 59.1 0 0 0.0316 14.7
#> # ℹ 126,462 more rows
#> # ℹ 16 more variables: PonselCond <dbl>, Temp_RH <dbl>, RH <dbl>, Temp1m <dbl>,
#> # Temp2m <dbl>, Temp3m <dbl>, Temp4m <dbl>, Temp5m <dbl>, Temp6m <dbl>,
#> # Temp7m <dbl>, Temp8m <dbl>, Temp9m <dbl>, Temp10m <dbl>, Temp11m <dbl>,
#> # Temp12m <dbl>, event_flag <lgl>