Assign threshold categories to Enterococcus data
Usage
anlz_enteromap(
fibdata,
yrsel = NULL,
mosel = NULL,
areasel = NULL,
wetdry = FALSE,
precipdata = NULL,
temporal_window = NULL,
wet_threshold = NULL,
assf = FALSE
)Arguments
- fibdata
data frame of Enterococcus sample data as returned by
enterodataoranlz_fibwetdry- yrsel
optional numeric to filter data by year
- mosel
optional numeric to filter data by month
- areasel
optional character string to filter output by stations in the
long_namecolumn ofenterodata, see details- wetdry
logical; if
TRUE, incorporate wet/dry differences (this will result in a call toanlz_fibwetdry, in which casetemporal_windowandwet_thresholdare required). IfFALSE(default), do not differentiate between wet and dry samples.- precipdata
input data frame as returned by
read_importrain. columns should be: station, date (yyyy-mm-dd), rain (in inches). The objectcatchpreciphas this data from 1995-2023 for select Enterococcus stations. IfNULL, defaults tocatchprecip.- temporal_window
numeric; required if
wetdryisTRUE. number of days precipitation should be summed over (1 = day of sample only; 2 = day of sample + day before; etc.)- wet_threshold
numeric; required if
wetdryisTRUE. inches accumulated through the defined temporal window, above which a sample should be defined as being from a 'wet' time period- assf
logical indicating if the data are further processed as a simple features object with additional columns for
show_enteromap
Value
A data.frame similar to fibdata if assf = FALSE with additional columns describing station categories and optionally filtered by arguments passed to the function. A sf object if assf = TRUE with additional columns for show_enteromap.
Details
This function is based on anlz_fibmap, but is specific to Enterococcus data downloaded via read_importentero. It creates categories for mapping using show_enteromap. Optionally, if samples have been defined as 'wet' or not via anlz_fibwetdry, this can be represented via symbols on the map. Categories based on relevant thresholds are assigned to each observation. The categories are specific to Enterococcus in marine waters (class of 2 or 3M). A station is categorized into one of four ranges defined by the thresholds as noted in the cat column of the output, with corresponding colors appropriate for each range as noted in the col column of the output.
The areasel argument can indicate valid entries in the long_name column of enterodata. For example, use "Old Tampa Bay" for stations in the subwatershed of Old Tampa Bay, where rows in enterodata are filtered based on the the selection. All stations are returned if this argument is set as NULL (default). All valid options for areasel include "Old Tampa Bay", "Hillsborough Bay", "Middle Tampa Bay", "Lower Tampa Bay", "Boca Ciega Bay", or "Manatee River". One to any of the options can be used.
Examples
anlz_enteromap(enterodata, yrsel = 2020, mosel = 9)
#> # A tibble: 39 × 12
#> station long_name yr mo Latitude Longitude entero cat col ind
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> <chr> <chr>
#> 1 21FLHILL_W… Old Tamp… 2020 9 28.0 -82.6 380 130 … #EE7… Ente…
#> 2 21FLHILL_W… Old Tamp… 2020 9 28.0 -82.6 380 130 … #EE7… Ente…
#> 3 21FLHILL_W… Old Tamp… 2020 9 28.0 -82.6 490 130 … #EE7… Ente…
#> 4 21FLHILL_W… Old Tamp… 2020 9 28.0 -82.6 725 130 … #EE7… Ente…
#> 5 21FLPDEM_W… Old Tamp… 2020 9 28.0 -82.7 703 130 … #EE7… Ente…
#> 6 21FLPDEM_W… Old Tamp… 2020 9 27.9 -82.7 10 < 35 #2DC… Ente…
#> 7 21FLPDEM_W… Old Tamp… 2020 9 27.9 -82.7 1990 > 999 #CC3… Ente…
#> 8 21FLPDEM_W… Old Tamp… 2020 9 27.9 -82.7 171 130 … #EE7… Ente…
#> 9 21FLTPA_WQ… Old Tamp… 2020 9 27.9 -82.6 908 130 … #EE7… Ente…
#> 10 21FLHILL_W… Hillsbor… 2020 9 27.9 -82.4 1 < 35 #2DC… Ente…
#> # ℹ 29 more rows
#> # ℹ 2 more variables: indnm <chr>, conc <dbl>
# differentiate wet/dry samples in that time frame
anlz_enteromap(enterodata, yrsel = 2020, mosel = 9, wetdry = TRUE,
temporal_window = 2, wet_threshold = 0.5)
#> # A tibble: 39 × 13
#> station long_name yr mo Latitude Longitude entero cat col ind
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> <chr> <chr>
#> 1 21FLHILL_W… Old Tamp… 2020 9 28.0 -82.6 380 130 … #EE7… Ente…
#> 2 21FLHILL_W… Old Tamp… 2020 9 28.0 -82.6 380 130 … #EE7… Ente…
#> 3 21FLHILL_W… Old Tamp… 2020 9 28.0 -82.6 490 130 … #EE7… Ente…
#> 4 21FLHILL_W… Old Tamp… 2020 9 28.0 -82.6 725 130 … #EE7… Ente…
#> 5 21FLPDEM_W… Old Tamp… 2020 9 28.0 -82.7 703 130 … #EE7… Ente…
#> 6 21FLPDEM_W… Old Tamp… 2020 9 27.9 -82.7 10 < 35 #2DC… Ente…
#> 7 21FLPDEM_W… Old Tamp… 2020 9 27.9 -82.7 1990 > 999 #CC3… Ente…
#> 8 21FLPDEM_W… Old Tamp… 2020 9 27.9 -82.7 171 130 … #EE7… Ente…
#> 9 21FLTPA_WQ… Old Tamp… 2020 9 27.9 -82.6 908 130 … #EE7… Ente…
#> 10 21FLHILL_W… Hillsbor… 2020 9 27.9 -82.4 1 < 35 #2DC… Ente…
#> # ℹ 29 more rows
#> # ℹ 3 more variables: indnm <chr>, conc <dbl>, wet_sample <lgl>
# as sf object
anlz_enteromap(enterodata, assf = TRUE)
#> Simple feature collection with 5596 features and 14 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -82.74598 ymin: 27.49433 xmax: -82.38168 ymax: 28.02571
#> Geodetic CRS: WGS 84
#> # A tibble: 5,596 × 15
#> station long_name yr mo Latitude Longitude entero cat col ind
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <fct> <chr> <chr>
#> 1 21FLHILL_W… Old Tamp… 2001 1 28.0 -82.6 80 35 -… #E9C… Ente…
#> 2 21FLHILL_W… Old Tamp… 2001 2 28.0 -82.6 360 130 … #EE7… Ente…
#> 3 21FLHILL_W… Old Tamp… 2001 3 28.0 -82.6 3900 > 999 #CC3… Ente…
#> 4 21FLHILL_W… Old Tamp… 2001 4 28.0 -82.6 20 < 35 #2DC… Ente…
#> 5 21FLHILL_W… Old Tamp… 2001 7 28.0 -82.6 1300 > 999 #CC3… Ente…
#> 6 21FLHILL_W… Old Tamp… 2001 8 28.0 -82.6 260 130 … #EE7… Ente…
#> 7 21FLHILL_W… Old Tamp… 2001 9 28.0 -82.6 420 130 … #EE7… Ente…
#> 8 21FLHILL_W… Old Tamp… 2001 10 28.0 -82.6 520 130 … #EE7… Ente…
#> 9 21FLHILL_W… Old Tamp… 2001 11 28.0 -82.6 60 35 -… #E9C… Ente…
#> 10 21FLHILL_W… Old Tamp… 2001 12 28.0 -82.6 340 130 … #EE7… Ente…
#> # ℹ 5,586 more rows
#> # ℹ 5 more variables: grp <fct>, conc <dbl>, wet_sample <fct>,
#> # geometry <POINT [°]>, lab <chr>