Nothing
###############################################################################################
#Reads in the triennial survey data and filters the data into what is necessary
#It reads in catch and station data and makes sure only the species necessary are kept
#### may want to keep NA (blank in Excel) to select the zero tows
#removeCAN is a flag if you want tows in Canadian waters removed
# need the file called foreign_hauls.csv (with option to specify a different name)
#
#Written by Allan Hicks
#Necessary column names
# SPECIES_CODE
# WEIGHT in kg
# DISTANCE_FISHED is in km
# NET_WIDTH is in m
###############################################################################
ReadInBiomass.EWC.fn <- function(dataFile,directory,species=c(NA),removeCAN=T,verbose=F,foreignfile="foreign_hauls.csv") {
dat <- read.csv(paste(directory,dataFile,sep="\\"))
totRows <- nrow(dat)
if("SPECIES_CODE" %in% names(dat)){
dat <- dat[dat$SPECIES_CODE %in% species,]
if(verbose) {cat(nrow(dat),"rows kept out of",totRows,"after filtering by species\n")}
}else{
if(verbose) {cat("no column in dataFile for 'SPECIES_CODE'. Keeping all columns: n =",nrow(dat),"\n")}
}
totRows <- nrow(dat)
if(removeCAN) {
foreignHauls <- read.csv(file.path(directory,foreignfile))
foreignInd <- !(dat$HAULJOIN %in% foreignHauls$HAULJOIN)
dat <- dat[foreignInd,]
if(verbose) {cat(sum(foreignInd),"rows kept (or",sum(!foreignInd),"removed) out of",totRows,"after removing foreign hauls\n")}
}
#calculate the density (kg/km^2) using net width and distance fished
dat$areaFished <- dat$DISTANCE_FISHED*(dat$NET_WIDTH/1000)
tmp <- sum(is.na(dat$areaFished))
if(tmp>0 | verbose) {cat("There are",tmp,"instances where area swept could not be calculated due to missing values.\n")}
dat$kgPerKm2 <- dat$WEIGHT/dat$areaFished
dat$kgPerKm2[is.na(dat$kgPerKm2)&!is.na(dat$areaFished)] <- 0 #the tows with no observation of the species
return(dat)
}
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