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SAM_GrowthData_Alloc.R
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#use latest SamFilter as precusror to this file
# currently SamFilter050916.RData
library(car)
library(MASS)
library(boot)
library(dplyr)
library(plyr)
library(gdata)
library(ggplot2)
library(ggrepel)
library(multcompView)
library(devtools)
library(lubridate)
#######RBIND ALL SUBSETS (function below for unmatch columns)
rbind.match.columns <- function(input1, input2) {
n.input1 <- ncol(input1)
n.input2 <- ncol(input2)
if (n.input2 < n.input1) {
TF.names <- which(names(input2) %in% names(input1))
column.names <- names(input2[, TF.names])
} else {
TF.names <- which(names(input1) %in% names(input2))
column.names <- names(input1[, TF.names])
}
return(rbind(input1[, column.names], input2[, column.names]))
}
#################################################################
# LOAD SAM DATA
load('c:/CloudStor/R_Stuff/SAM/Logistic/SamFilter190916.RData ')
keep(SamFilterCI, SamFilter, SamResults, sure=T)
#recode database subblock errors
SamFilter$SubBlockNo[SamFilter$SubBlockNo==11] <- "11A"
SamFilterCI$SubBlockNo[SamFilterCI$SubBlockNo==11] <- "11A"
#
###### CHOOSE OPTION ########
SamFilterIL<-SamFilter
#SamFilterIL<-SamFilterCI
# #================================================================
# # ADD IN SL DATA from raw SAM database file to SAMfilter
# #================================================================
infileNew <- "c:/CloudStor/R_Stuff/SAM/Logistic/SAMExport2016.csv"
BlckPopNew <- read.csv(infileNew, header=TRUE, sep=',', dec='.', as.is=TRUE)
BlckPopNew$SAM_Date <- as.Date(strptime(as.character(BlckPopNew$SAM_Date), "%d/%m/%Y", tz='AUSTRALIA/HOBART'))
BlckPopNew$SiteCode <- paste(BlckPopNew$SIT_Id,'_',year(BlckPopNew$SAM_Date),'_',month(BlckPopNew$SAM_Date), sep="")
BlckPopNew <- BlckPopNew[order(BlckPopNew$SiteCode,BlckPopNew$SPC_ShellLength),]
BlckPop <- BlckPopNew
SiteCodes<-unique(SamFilter$SiteCode)
pick <- which(BlckPop$SiteCode %in% SiteCodes)
BlckPopFilter<-BlckPop[pick,]
names(BlckPopFilter)[names(BlckPopFilter)=='SIT_StatBlock']<-"BlockNo"
names(BlckPopFilter)[names(BlckPopFilter)=='SIT_SubBlock']<-"SubBlockNo"
#Reformat SublockNo
BlckPopFilter$SubBlockNo<-paste(BlckPopFilter$BlockNo,BlckPopFilter$SubBlockNo, sep="")
SLSubBlockSum<-ddply(BlckPopFilter,.(SubBlockNo), summarize,
SLmax = max(SPC_ShellLength, na.rm=T), SLq95 = quantile(SPC_ShellLength, 0.95, na.rm=T))
#
#Match SLBlockSum to SamFilter by subblock
#
SamFilterIL<-left_join(SamFilterIL,SLSubBlockSum, by = 'SubBlockNo')
rm(BlckPop, BlckPopNew, SLSubBlockSum)
#drop SAM observations with odd low LD50
# OddLook<-subset(SamFilterIL, LD50 < 100 & SLmax > 183)
# OddSiteCodes<-unique(OddLook$SiteCode)
# pick <- which(SamFilterIL$SiteCode %in% OddSiteCodes)
# SamFilterIL<-SamFilterIL[-pick,]
# #================================================================
# # load Growth parameters
# #================================================================
load('c:/CloudStor/R_Stuff/SAM/Logistic/ILResults.RData')
IL.info<-ILResults
names(IL.info)[names(IL.info)=='Latitude']<-"Latitude.IL"
names(IL.info)[names(IL.info)=='Longitude']<-"Longitude.IL"
names(IL.info)[names(IL.info)=='StatBlock']<-"BlockNo.IL"
names(IL.info)[names(IL.info)=='SiteName']<-"GrowthSite"
names(IL.info)[names(IL.info)=='SiteId']<-"SIT_Id"
#Add zone
IL.info$Zone[IL.info$BlockNo %in% c(seq(13,30,1)) | IL.info$SIT_Id %in% c("588")]<- "E"
IL.info$Zone[IL.info$BlockNo %in% c(seq(6,12,1))] <- "CW"
IL.info$Zone[IL.info$BlockNo %in% c(seq(7,12,1))] <- "W"
IL.info$Zone[IL.info$BlockNo %in% c("5") | IL.info$SIT_Id %in% c("316")]<- "N"
IL.info$Zone[IL.info$BlockNo %in% c(1, 2, 3, 4,47, 48, 49,39, 40)] <- "N"
IL.info$Zone[IL.info$BlockNo %in% c(seq(32, 38,1),seq(41,46,1), seq(50,57,1))] <- "BS"
IL.info<-droplevels(subset(IL.info, SIT_Id != "266"))#Louisa Bay
IL.info<-droplevels(subset(IL.info, SIT_Id != "171"))#Sterile Island
IL.info<-droplevels(subset(IL.info, SIT_Id != "172"))#Actaeon Island
# IL.info<-droplevels(subset(IL.info, SIT_Id != "461"))# One Tree Point
# IL.info<-droplevels(subset(IL.info, SIT_Id != "764"))#Duck holes
IL.info<-droplevels(subset(IL.info, SIT_Id != "480"))#Gagens Point
IL.info<-droplevels(subset(IL.info, SIT_Id != "478"))#Middle Grounds
IL.info<-droplevels(subset(IL.info, SIT_Id != "337"))#Southerly Bottom
IL.info<-droplevels(subset(IL.info, SIT_Id != "813"))#George III
IL.info$L95<-as.numeric(as.character(IL.info$L95))
IL.info$L50<-as.numeric(as.character(IL.info$L50))
IL.info$MaxDL<-as.numeric(as.character(IL.info$MaxDL))
IL.info$MaxSig<-as.numeric(as.character(IL.info$MaxSig))
# #================================================================
# # Match SAM and Growth ID's
# #================================================================
SamFilterIL$SIT_Id<-as.character(SamFilterIL$SIT_Id)
SAM.IL<-left_join(SamFilterIL,IL.info[,c(1:6)], by = 'SIT_Id')
SAMSites<-subset(SAM.IL, is.na(MaxDL))
SAMSites<-SAMSites[,1:34]
SAMGwthSites<-subset(SAM.IL, !is.na(MaxDL))
rm(SAM.IL)
Gwth.Id<-unique(SAMGwthSites$SIT_Id)
combinedDF<-left_join(SAMGwthSites[,c(6,17,21,22,24,28:31,33,35:39)],IL.info[,c(1:11)], by = 'SIT_Id')
write.csv(combinedDF, file='GrwthSAMmatched.csv')
# # ================== LM =================================
boxcox(SAMGwthSites$LD50~SAMGwthSites$L50)
fit<-lm(LD50~L50, data=SAMGwthSites)
summary(fit)
anova(fit)
par(mfrow = c(2,2))
plot(fit)
par(mfrow = c(1,1))
# view the data l50 by ld50
ggplot(data = SAMGwthSites, aes(x=L50, y=LD50)) +
xlab(bquote(''~L50['']~'(mm)')) + ylab(bquote(''~LM['50%']~'(mm)'))+
geom_smooth(method=lm, se=F, color='grey', fullrange=F, size=1.2, color='black')+
geom_text_repel(aes(label=GrowthSite), size=3)+
geom_errorbar(aes(ymin=SAMGwthSites$Ld50BootL95, ymax=SAMGwthSites$Ld50BootU95),
width=.2)+
geom_point(aes(colour=Zone), size=3)+
#ggtitle(paste(dum$SubBlockNo, FishYear))+
#labs(title= Yeardum$SubBlockNo, size=10)+
#geom_histogram(binwidth=50)+
theme_bw()+
#scale_color_identity()+ #this makes sure the color follows the color argument above in aes()
theme(legend.position=c(0.1, 0.8))+
theme(legend.title=element_blank())+
theme(legend.text = element_text(size=14))+
theme(axis.title.x = element_text(size=14),
axis.text.x = element_text(size=14))+
theme(axis.title.y = element_text(size=14),
axis.text.y = element_text(size=14))
# #drop SAM observations with odd low LD50
# OddLook<-subset(SAMGwthSites, L50 < 110 & LD50 > 120)
# OddSiteCodes<-unique(OddLook$SiteCode)
# pick <- which(SamFilterIL$SiteCode %in% OddSiteCodes)
# SamFilterIL<-SamFilterIL[-pick,]
#
# #================================================================
# #
# # Growth data allocation with zone
# #
# #================================================================
#############################
SAMSite.BS<-droplevels(subset(SAMSites, Zone == 'BS'))
SAMSite.Z<-droplevels(subset(SAMSites, Zone != 'BS'))
Zones<-unique(SAMSite.Z$Zone)
#####
if (exists("SAMjoin"))
rm(SAMjoin)
for(z in Zones){
Samchoice<-subset(SAMSites, Zone == z)
ILchoice<-subset(SAMGwthSites, Zone == z)
Samchoice$match<-sapply(Samchoice$LD50,function(x)which.min(abs(x - ILchoice$LD50)))
Samchoice$match<-as.numeric(Samchoice$match)
ILchoice$match<-1:nrow(ILchoice)
Zonejoin<-left_join(Samchoice,ILchoice[,c(6,37:42)], by = 'match')
if (exists("SAMjoin"))
SAMjoin <- rbind(SAMjoin, Zonejoin)
else
SAMjoin <- Zonejoin
}
names(SAMjoin)[names(SAMjoin)=='LD50.x']<-"LD50"
names(SAMjoin)[names(SAMjoin)=='LD50.y']<-"GrowthLD50"
#TREAT BSZ grwth data as mean values as no direct matches by SIT_ID
BS.IL.Info<-droplevels(subset(IL.info, SIT_Id == "315"))
BSjoin<-left_join(SAMSite.BS, BS.IL.Info[,c(2:6,12)], by = 'Zone')
BSjoin$GrowthLD50<-NA
SAMGwthOutPut<-rbind.match.columns(SAMjoin, BSjoin)
SAMILResults<-rbind.match.columns(SAMGwthSites,SAMGwthOutPut)
# GrwthAllocations<-SAMjoin[,c(6, 18, 21, 22,29, 36,41)]
# E_GrwthAllocations<-droplevels(subset(GrwthAllocations, Zone =='E'))
#
# write.csv(GrwthAllocations, file='GrwthAllocations.csv')
########GROWTH ALLOCATION OPTIONS NOT USED###############
# 1. #ALLOCATE THE GROWTH DATA BY LD50 without zone retrictions
# SAMSite.Z$match<-sapply(SAMSite.Z$LD50,function(x)which.min(abs(x - SAMGwthSites$LD50)))
# SAMGwthSites$match<-c(1:20)
# SAMjoin<-left_join(SAMSite.Z,SAMGwthSites[,c(6,35:41)], by = 'match')
# names(SAMjoin)[names(SAMjoin)=='LD50.x']<-"LD50"
# names(SAMjoin)[names(SAMjoin)=='LD50.y']<-"GrowthLD50"
# 2. #ALLOCATE GROWTH DATA ONLY KEEPING MAXIMUM REULST FOR EACH MATCH OF GROWTH AND SAM
#SAMGwthSites<-do.call(rbind,lapply(split(SAMGwthSites,SAMGwthSites$SIT_Id),function(chunk) chunk[which.min(chunk$LD50),]))
# 3. #ALLOCATE GROWTH DATA VIA Producing LD50t for each of the growth data from Growth data with matching LD50range < 5 mm
# fit2<-lm(LD50~L50, data=SAMGwthSites)
# summary(fit2)
#
# anova(fit2)
# par(mfrow = c(2,2))
# plot(fit2)
# par(mfrow = c(1,1))
# #shapiro.test(fit2)
#
#
# IL.info$LD50t<-fit2$coef[1]+fit2$coef[2]*IL.info$L50
#
# # #================================================================
# # #
# # # Growth data allocation with zone
# # #
# # #================================================================
# #############################
# SAMSite.BS<-droplevels(subset(SamFilter, Zone == 'BS'))
# SAMSite.Z<-droplevels(subset(SamFilter, Zone != 'BS'))
#
# Zones<-unique(SAMSite.Z$Zone)
# #####
# if (exists("SAMjoin"))
# rm(SAMjoin)
#
# for(z in Zones){
# Samchoice<-subset(SamFilter, Zone == z)
# ILchoice<-subset(IL.info, Zone == z)
# Samchoice$match<-sapply(Samchoice$LD50,function(x)which.min(abs(x - ILchoice$LD50t)))
# Samchoice$match<-as.numeric(Samchoice$match)
# ILchoice$match<-1:nrow(ILchoice)
#
# Zonejoin<-left_join(Samchoice,ILchoice[,c(2:5,7,14)], by = 'match')
#
# if (exists("SAMjoin"))
# SAMjoin <- rbind(SAMjoin, Zonejoin)
# else
# SAMjoin <- Zonejoin
# }
#
# #TREAT BSZ grwth data as mean values as no direct matches by SIT_ID
# BS.IL.Info<-droplevels(subset(IL.info, SIT_Id == "315"))
# BSjoin<-left_join(SAMSite.BS, BS.IL.Info[,c(2:6,12)], by = 'Zone')
#
#
#
# SAMGwthOutPut<-rbind.match.columns(SAMjoin, BSjoin)
#
# SAMILResults<-SAMGwthOutPut
#