Trasform impulsive dataframe (100 ms samples) in dataframe (1s samples)
Source:R/OpeNoise.R
dfImpulsiveTrasform.RdReturns a dataframe (1s samples)
Examples
#data("dataset_impulsive1")
#data("dataset_impulsive2")
dfImpulsiveTrasform(dfImpulsive = dataset_impulsive1,
statistic = energetic.mean)[1:5, ]
#> date LAeq LZeq.6.3 LZeq.8.0 LZeq.10.0 LZeq.12.5 LZeq.16.0
#> 36 2022-04-28 09:04:35 35.3 34.5 30.3 37.0 44.9 39.7
#> 37 2022-04-28 09:04:36 37.2 35.8 36.0 40.7 45.7 38.6
#> 38 2022-04-28 09:04:37 36.8 38.0 37.4 40.8 40.2 40.1
#> 39 2022-04-28 09:04:38 32.1 42.2 28.9 37.2 40.4 41.2
#> 40 2022-04-28 09:04:39 30.2 39.3 35.7 42.2 45.1 43.8
#> LZeq.20.0 LZeq.25.0 LZeq.31.5 LZeq.40.0 LZeq.50.0 LZeq.63.0 LZeq.80.0
#> 36 38.0 38.9 36.4 36.5 34.4 34.7 28.7
#> 37 36.5 42.0 40.5 34.5 36.0 37.3 33.7
#> 38 35.3 42.1 43.1 37.7 35.5 33.2 34.6
#> 39 39.5 38.5 38.7 35.3 32.1 29.8 27.0
#> 40 37.2 39.1 34.5 36.9 33.9 30.7 29.9
#> LZeq.100 LZeq.125 LZeq.160 LZeq.200 LZeq.250 LZeq.315 LZeq.400 LZeq.500
#> 36 45.5 25.8 24.9 19.5 19.7 24.2 23.1 20.7
#> 37 46.4 38.5 29.9 27.1 28.8 28.6 29.2 25.1
#> 38 45.9 42.7 35.5 26.6 26.8 28.3 26.6 26.4
#> 39 45.9 25.5 23.7 19.9 23.7 22.4 26.7 21.0
#> 40 46.1 28.2 24.8 19.7 18.2 19.6 20.9 21.8
#> LZeq.630 LZeq.800 LZeq.1000 LZeq.1250 LZeq.1600 LZeq.2000 LZeq.2500
#> 36 23.1 18.3 16.9 16.5 17.7 20.6 19.7
#> 37 28.0 25.8 26.4 26.4 28.4 24.1 24.5
#> 38 26.3 24.7 21.7 24.5 22.8 22.9 22.3
#> 39 23.0 22.2 24.2 22.9 22.8 22.4 19.5
#> 40 17.9 15.6 14.6 14.8 15.4 14.0 13.9
#> LZeq.3150 LZeq.4000 LZeq.5000 LZeq.6300 LZeq.8000 LZeq.10000 LZeq.12500
#> 36 20.5 16.7 15.3 14.0 13.3 12.7 12.1
#> 37 24.7 22.0 20.2 17.4 16.9 17.5 17.6
#> 38 22.0 20.5 19.3 18.8 17.9 17.8 17.1
#> 39 16.5 15.3 13.1 11.6 11.3 10.1 10.4
#> 40 14.8 13.9 12.5 10.7 12.7 14.6 14.1
#> LZeq.16000 LZeq.20000 LZFmin.6.3 LZFmin.8.0 LZFmin.10.0 LZFmin.12.5
#> 36 10.6 6.3 34.9 23.6 37.4 41.1
#> 37 13.2 7.6 35.3 35.3 40.0 45.3
#> 38 12.0 6.7 37.5 36.5 40.3 40.2
#> 39 7.6 5.1 41.8 30.8 36.9 38.4
#> 40 15.1 6.7 39.2 34.3 41.0 44.4
#> LZFmin.16.0 LZFmin.20.0 LZFmin.25.0 LZFmin.31.5 LZFmin.40.0 LZFmin.50.0
#> 36 40.6 35.5 36.1 34.8 32.8 33.2
#> 37 37.8 36.8 41.2 39.5 33.8 35.1
#> 38 39.2 34.4 41.3 42.0 36.8 34.9
#> 39 39.9 38.1 38.3 39.2 34.4 31.2
#> 40 43.5 36.2 38.4 33.3 36.6 33.2
#> LZFmin.63.0 LZFmin.80.0 LZFmin.100 LZFmin.125 LZFmin.160 LZFmin.200
#> 36 32.9 26.1 45.3 26.2 21.7 20.1
#> 37 34.4 32.3 46.0 35.3 28.1 26.1
#> 38 34.8 33.0 45.7 40.5 33.3 25.3
#> 39 29.5 27.8 45.7 28.0 23.6 18.9
#> 40 29.3 28.7 45.9 26.6 23.8 19.4
#> LZFmin.250 LZFmin.315 LZFmin.400 LZFmin.500 LZFmin.630 LZFmin.800
#> 36 16.6 22.8 19.1 18.7 21.0 14.7
#> 37 27.3 27.1 27.8 24.1 26.6 24.1
#> 38 24.9 26.3 24.9 25.1 25.3 23.7
#> 39 21.8 21.1 24.7 19.4 21.2 20.6
#> 40 17.2 18.1 20.3 21.0 17.7 15.1
#> LZFmin.1000 LZFmin.1250 LZFmin.1600 LZFmin.2000 LZFmin.2500 LZFmin.3150
#> 36 15.3 17.3 18.6 18.6 17.6 18.6
#> 37 23.9 23.3 25.0 21.4 22.0 22.7
#> 38 20.9 23.3 23.6 22.0 21.4 21.7
#> 39 21.7 20.2 20.0 21.0 17.9 16.2
#> 40 14.4 14.9 15.0 14.9 15.0 14.5
#> LZFmin.4000 LZFmin.5000 LZFmin.6300 LZFmin.8000 LZFmin.10000 LZFmin.12500
#> 36 15.3 14.1 13.0 12.2 11.6 11.0
#> 37 19.7 18.4 16.1 15.4 15.4 15.2
#> 38 20.0 18.7 18.0 17.3 17.5 17.0
#> 39 14.7 12.7 11.5 11.1 10.0 10.0
#> 40 13.7 12.3 10.6 11.3 12.1 11.6
#> LZFmin.16000 LZFmin.20000
#> 36 9.2 5.7
#> 37 11.0 6.4
#> 38 12.2 6.9
#> 39 7.3 5.0
#> 40 11.6 5.5