R/process_pandn_data.R

In ERICNorthEast/ERIC_Data_Proc: Functions for data processing and validation

#' Filter data to just protected & notable species
#'
#' @param pandn_data data to process
#' @param DR_config list of config values
#' @param optional_desigs optional designations selected by the user
#'
#' @return
#' @export
#'
#' @examples
#' options <- c("DURHAM_DESIGS","NP_DESIGS","TV_DESIGS"  )
#' config_keys <- c("locationCol","abundanceCol","commentCol","recorderCol","speciesCol","lastCol","dateCol","distanceCol","colCount","DROutputCols","DROutputColsWithDist","DRColNames","DRColNamesWithDist","FEP_DESIG","WNIO1_DESIG","WNIO2_DESIG","WNIO81_DESIG","WNIO82_DESIG","WNIO5_DESIG","WALES_DESIG","NORTH_DESIGS","NP_DESIGS","SCOT_DESIGS","TV_DESIGS","DURHAM_DESIGS")

#' locationCol <- 9
#' abundanceCol <- 5
#' commentCol <- 7
#' recorderCol <- 8
#' speciesCol <- 3
#' lastCol <- 14
#' dateCol <- 10
#' distanceCol <- 12
#' colCount <- 15

#' DROutputCols <- c("All.Design","Taxon.grou", "Taxon.Lati","Taxon.Comm", "Obs.Abunda", "Determinat","Obs.Commen","Sample.Rec",  "Sample.Loc",  "Sample.Dat","Sample.Spa","Survey.Run","Survey.Nam","Info")
#' DROutputColsWithDist <- c("All.Design","Taxon.grou", "Taxon.Lati","Taxon.Comm", "Obs.Abunda", "Determinat","Obs.Commen","Sample.Rec",  "Sample.Loc",  "Sample.Dat","Sample.Spa","distance","Survey.Run","Survey.Nam","Info")
#' DRColNames <- c("Designations","Taxon group","Latin Name","Common Name","Abundances","Determination Type","Comments","Recorder","Location Name","Date","Grid Reference","Survey Run By","Survey Name","Additional Information")
#' DRColNamesWithDist <- c("Designations","Taxon group","Latin Name","Common Name","Abundances","Determination Type","Comments","Recorder","Location Name","Date","Grid Reference","Approx. Distance(m)","Survey Run By","Survey Name","Additional Information")

#' FEP_DESIG <- "FEP-001"
#' WNIO1_DESIG <- "W(NI)O-Sch1_part1"
#' WNIO2_DESIG <- "W(NI)O-Sch1_part2"
#' WNIO81_DESIG <- "W(NI)O-Sch8_part1"
#' WNIO82_DESIG <- "W(NI)O-Sch8_part2"
#' WNIO5_DESIG <- "W(NI)O-Sch5"
#' WALES_DESIG <- "Wales_NERC_S.42"

#' NORTH_DESIGS <- 'pandn_data$All.Design== "Northumberland BAP" |  pandn_data$All.Design=="FEP-001, Northumberland NP BAP"'
#' NP_DESIGS <- 'pandn_data$All.Design=="FEP-001, Northumberland NP BAP"'
#' SCOT_DESIGS <- 'pandn_data$All.Design== "Scottish_Biodiversity_List" | pandn_data$All.Design== "Scottish_Biodiversity_List, W(NI)O-Sch1_part1" |pandn_data$All.Design== "Scottish_Biodiversity_List, Wales_NERC_S.42" |pandn_data$All.Design== "FEP-001, Scottish_Biodiversity_List"'
#' TV_DESIGS <- 'pandn_data$All.Design=="Tees Valley BAP" | pandn_data$All.Design=="Tees Valley BAP, " | pandn_data$All.Design=="Tees Valley BAP, FEP-001" | pandn_data$All.Design=="Tees Valley BAP, Tees Valley BAP" | pandn_data$All.Design=="Tees Valley BAP, Tees Valley BAP, W(NI)O-Sch8_part1, Wales_NERC_S.42" | pandn_data$All.Design=="Tees Valley BAP, W(NI)O-Sch8_part1, Wales_NERC_S.42"'
#' DURHAM_DESIGS <- 'pandn_data$All.Design=="Durham BAP"'

#' config_values <- list(locationCol,abundanceCol,commentCol,recorderCol,speciesCol,lastCol,dateCol,distanceCol,colCount, DROutputCols,DROutputColsWithDist,DRColNames,DRColNamesWithDist,FEP_DESIG,WNIO1_DESIG,WNIO2_DESIG,WNIO81_DESIG,WNIO82_DESIG,WNIO5_DESIG,WALES_DESIG,    NORTH_DESIGS,NP_DESIGS,SCOT_DESIGS,TV_DESIGS,DURHAM_DESIGS)

#' config_pairs <- list()                     # Create empty list
#' for(i in 1:length(config_keys)) {              # Add key/value pairs in for-loop
  #' config_pairs[config_keys[i]] <- config_values[i]
  #' }

#'a <- c('','BirdsDir-A2.2')
#'b <- c('','')
#'c <- c('','')
#'d <- c('insect - butterfly','bird')
#'e <- c('Pieris rapae','Turdus merula')
#'f <- c('Small White','Blackbird')
#'g <- c('Mike Jeffries','Alnwick Wildlife Group')
#'h <- c('Morpeth Town','Morpeth Town')
#'i <- c('04/09/2010','04/09/2010')
#'j <- c('NZ18X','NZ18X')
#'k <- c('Butterfly Conservation','Alnwick Wildlife Group')
#'l <- c('Butterfly Conservation','Alnwick Wildlife Group')
#'m <- c('2 Count','1 Count')
#'n <- c('Considered Correct','Considered Correct')
#'o <- c(419000,419000)
#'p <- c(585000,585000)
#'q <- c(1000,1000)
#'r <- c('layer','layer')
#'s <- c('path','path')

#'df <- data.frame(a,b,c,d,e,f,a,g,h,h,i,j,k,l,m,n,o,p,q,r,s)


#'names(df) <- c('All.Design', 'Wildlife..', 'Wildlife_1', 'Taxon.grou', 'Taxon.Lati', 'Taxon.Comm', 'Obs.Commen', 'Sample.Rec', 'Sample.Loc', 'Sample.L_1', 'Sample.Dat', 'Sample.Spa', 'Survey.Run', 'Survey.Nam', 'Obs.Abunda', 'Determinat', 'Central_Ea', 'Central_No', 'Buffer', 'layer', 'path')
#' data <- change_recorder_col_names(df)
#' pandn_data <- process_pandn_data(df,config_pairs,options)
process_pandn_data <- function(pandn_data,DR_config,optional_desigs){

  # #For the P&N data remove the designations we'd delete manually
  filtered_data <- remove_manual_desigs(pandn_data,DR_config)

  # And the optional ones
  filtered_data <- remove_optional_desigs(filtered_data,optional_desigs,DR_config)

  return(filtered_data)
}