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Copy pathAIS_allSiteCOVIDchange.R
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AIS_allSiteCOVIDchange.R
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#CHANGE IN NEARBY VESSEL USE
#-----------------------------------------------------------------------------------------
tDir = "E:\\RESEARCH\\SanctSound\\"
dirAIS = paste0(tDir,"data")
Fpattern = "_2018_10_to_2020_11.csv" # "_2018_10_to_2021_04.csv"
nFilesAIS = length( list.files(path=dirAIS,pattern = Fpattern, full.names=TRUE, recursive = TRUE))
inFilesAIS = ( list.files(path=dirAIS,pattern = Fpattern, full.names=TRUE, recursive = TRUE))
x = strsplit(inFilesAIS,"_")
sanctsAIS = unique(sapply( x, "[", 2 ))
#combine AIS files
multmerge = function(path){
filenames = list.files(path=path, pattern = Fpattern, full.names=TRUE, recursive = TRUE)
rbindlist(lapply(filenames, fread))
}
AIS <- multmerge(dirAIS)
sitesAIS = unique(AIS$LOC_ID)
cat(length(sitesAIS), " number of sites with AIS data", "\n")
rm(x)
#re-name sites
AIS$LOC_ID[AIS$LOC_ID=="PM08"] = "PHRB"
sitesAIS = unique(AIS$LOC_ID)
AIS$DAY = as.Date(AIS$DATE,format = "%m/%d/%Y")
AIS$MTH = month(AIS$DAY )
AIS$YR = year(AIS$DAY )
AIS = AIS[ AIS$YR >2018, ]
AIS$ALL_UV = AIS$LOA_S_UV+AIS$LOA_M_UV+AIS$LOA_L_UV+AIS$LOA_NA_UV
AIS$ALL_HR = AIS$LOA_S_OPHRS+AIS$LOA_M_OPHRS+AIS$LOA_L_OPHRS+AIS$LOA_NA_OPHRS
tmpHRm = as.data.frame( aggregate(AIS$ALL_HR, by=list(AIS$MTH,AIS$LOC_ID,AIS$YR), mean, na.rm=T) )
tmpUVm = as.data.frame( aggregate(AIS$ALL_UV, by=list(AIS$MTH,AIS$LOC_ID,AIS$YR), mean, na.rm=T) )
tmpHRs = as.data.frame( aggregate(AIS$ALL_HR, by=list(AIS$MTH,AIS$LOC_ID,AIS$YR), sum, na.rm=T) )
tmpUVs = as.data.frame( aggregate(AIS$ALL_UV, by=list(AIS$MTH,AIS$LOC_ID,AIS$YR), sum, na.rm=T) )
#smean operational hours
ggplot(tmpHRm, aes(as.factor(Group.1), Group.2, fill=as.numeric(as.character(x )) ) ) +
geom_tile()+
scale_fill_gradient2(low = "darkgreen", mid = "white", high = "darkred")+
theme( legend.title = element_blank() ) +
facet_grid(~Group.3)
ggplot(tmpUVm, aes(as.factor(Group.1), Group.2, fill=as.numeric(as.character(x )) ) ) +
geom_tile()+
scale_fill_gradient2(low = "white", high = "purple")+
theme( legend.title = element_blank() ) +
facet_grid(~Group.3)
#CHANGE IN MONTHLY MEAN OPERATIONAL HOURS
HRM = as.data.frame( spread(tmpHRm, Group.3, x))
HRM$Diff = HRM$`2020`- HRM$`2019`
ggplot(HRM, aes(as.factor(Group.1), Group.2, fill=as.numeric(as.character(Diff )) ) ) +
geom_tile()+
scale_fill_gradient2(low = "darkgreen", mid = "white", high = "darkred")+
theme( legend.title = element_blank() )
UVM = as.data.frame( spread(tmpUVm, Group.3, x))
UVM$Diff = UVM$`2020`- UVM$`2019`
ggplot(UVM, aes(as.factor(Group.1), Group.2, fill=as.numeric(as.character(Diff )) ) ) +
geom_tile()+
scale_fill_gradient2(low = "darkgreen", mid = "white", high = "darkred")+
xlab("")+ ylab("")+
theme_minimal() +
theme( legend.title = element_blank() )