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#PLot 1
library(ggplot2)
setwd("C:/Users/vhtran/Google Drive/these/diver_selection")
#png(file = "7.png", width = 800, height = 800)
library(readr)
mydata <- read.csv("C:/Users/vhtran/Google Drive/these/diver_selection/dataplot3.csv", sep=";")
ggplot(mydata, aes(x=generations, y=value, colour=group, group=group)) +
  
 
  geom_line(aes(linetype=as.factor(group1),color=as.factor(unit)),size=2) +
  
 
  
  geom_point(aes(fill = group,shape = group))+
  
  
  labs(list(y="value", x="generation"),size=20) +
  theme_bw() + 
  theme(panel.border = element_blank(), panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))+
  
  theme(axis.text.x=element_text(angle=0, hjust=1,size=16),axis.text.y=element_text(angle=0, hjust=1,size=16)) +
  scale_fill_brewer(type="qual", palette=2) +
  scale_color_brewer(type="qual", palette=2) +
  theme(axis.title.x = element_text( size=18))+
  theme(axis.title.y = element_text(size=18))+
  
  #ggtitle("Heritability over time")+
  theme(legend.title=element_blank())+
  guides(color = guide_legend(nrow=3))+
  theme(legend.text = element_text(colour="blue", size = 16))+  
  theme(legend.key.size = unit(2, 'lines'))+
  theme(plot.title = element_text(lineheight=5, face="bold", color="black", size=20))

#dev.off()

#Plot with EBV per week for each line-generation
 library(reshape2)
library(plyr)
mydata_1 <- read.table("C:/Users/vhtran/Google Drive/these/diver_selection/FULL4.dat",quote="\"") 
names(mydata_1)[1]<-"animal"  
names(mydata_1)[2]<-"identif" 
names(mydata_1)[3]<-"bande"  
names(mydata_1)[4]<-"sexe"  
names(mydata_1)[5]<-"lignee"  
names(mydata_1)[6]<-"gener"  
names(mydata_1)[7]<-"loge"  
names(mydata_1)[8]<-"eleve"  
names(mydata_1)[9]<- "pds_dc"  
names(mydata_1)[10]<-"pds_fc"  
names(mydata_1)[11]<-"age"  
names(mydata_1)[12]<-"poidsheb"  
names(mydata_1)[13]<-"poidpre2"  
names(mydata_1)[14]<-"age_dc"  
names(mydata_1)[15]<-"temps"  
names(mydata_1)[16]<-"consoheb"     
names(mydata_1)[17]<-"ADGv"  
names(mydata_1)[18]<-"FCRv"  
names(mydata_1)[19]<-"ADGg"  
names(mydata_1)[20]<-"FCRg"  
names(mydata_1)[21]<-"semaine"  
names(mydata_1)[22]<-"period"  
#mydata$temps=as.numeric(levels(mydata$temps))[mydata$temps]
#number animal
my1=mydata_1[,1:8]
my2=aggregate(my1, list(my1$animal), FUN=head, 1)
my2=arrange(my2,animal)
########################################################################################
# EBV for one records (mean of record)/ 3986 animals
EBV_all <- read.table("EBV_all1309.txt", quote="\"")
test<-melt(EBV_all,id.vars = 'animal')
test1=arrange(test,animal)
test1$EBV=test1$value
EBV_all1=test1[,c("animal","EBV")]
N_animal=length(unique(EBV_all1$animal))
EBV_all1$temps=c(rep(4:13,N_animal))
critere = c("animal")  
mydata_EBV=merge(EBV_all1,my2,by=c(critere))  
#class the animal
mydata_EBV1=arrange(mydata_EBV,animal,temps)  
#results from k-mean trajectory classification
#group A (generation G0-G2)
#group B (generation G3-G7 line HRFI)
#group C (generation G3-G7 line HRFI)
mydata_EBV1$gr=paste(mydata_EBV1$gener,mydata_EBV1$lignee,collapse =NULL)
mydata_EBV1$group =ifelse(mydata_EBV1$gener=="G0"|mydata_EBV1$gener=="G1"|mydata_EBV1$gener=="G2","C",
ifelse(mydata_EBV1$gr=="G3 +"|mydata_EBV1$gr=="G4 +"|mydata_EBV1$gr=="G5 +"|mydata_EBV1$gr=="G6 +"|
         mydata_EBV1$gr=="G7 +","B","A"))
# 
# library(dplyr)
# 
# gd <- mydata_EBV1 %>% 
#         group_by(group,temps) %>% 
#         summarise(
#           EBV.mean = mean(EBV),
#         
#         )
# 
# fix(gd)
# 
# 
# 
# gd$group1=ifelse(gd$group=="A","G0-G2",ifelse(gd$group=="B","G3-G7/HRFI","G3 to G7/LRFI"))
gd <- read.csv("C:/Users/vhtran/Google Drive/these/diver_selection/gd1.csv", sep=";")
gd$temps=gd$temps-3
library(ggplot2)
setwd("C:/Users/vhtran/Google Drive/these/diver_selection")
#png(file = "7.png", width = 800, height = 800)
diver_selec <- read.table("C:/Users/vhtran/Google Drive/these/Sujet2/out.txt", quote="\"")
mydata=diver_selec 
mydata$min=(mydata$EBV.mean-mydata$EBV.sd)
mydata$max=(mydata$EBV.mean+mydata$EBV.sd)
mydata$group1=paste(mydata$gener,mydata$lignee,collapse =NULL)
group=c(rep("C",50),rep("A",10),rep("B",10),rep("A",10),rep("B",10),rep("A",10),rep("B",10),
        rep("A",10),rep("B",10),rep("A",10),rep("B",10))
mydata=cbind(mydata,group)
mydata$temps=mydata$temps-3
mydata_plot=mydata[,c("group","temps","EBV.mean","group1")]
mydata_plot1 = rbind(mydata_plot,gd)
library(ggplot2)
#???pp=ggplot(mydata, aes(x=generations, y=value, colour=group, group=group)) +
  
pp1=  ggplot(mydata_plot1, aes(x=temps, y=EBV.mean, colour=group, group=group1)) +
  
  
 
geom_line(aes(linetype=group1, size = group1)) +  
  
   scale_linetype_manual(values=c("solid","solid","solid","solid",rep(c("solid","solid"),2),
                                  rep(c("dotted","twodash"),5))) +
   scale_size_manual(values=c(3,3,3,rep(0.5,15)))+
  
  
 # geom_line(data = gd) +
  
  geom_point(aes(fill = group1,shape = group1),   # Shape depends on cond
             size = 4) +        # Large points
  
  scale_shape_manual(values=c(1,1,1,1,5,6,7,8,rep(c(9,9,10,10,11,11,12,12,13,13),1))) +
 
  
 
 scale_x_continuous(breaks=1:10) +
labs(list(y="EBV (kg feed/kg gain)", x="Week"),size=24) +
  theme_bw() + 
  theme(panel.border = element_blank(), panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))+
  
  theme(axis.text.x=element_text(angle=0, hjust=1,size=24),axis.text.y=element_text(angle=0, hjust=1,size=24)) +
  scale_fill_brewer(type="qual", palette=2) +
  scale_color_brewer(type="qual", palette=2) +
  theme(axis.title.x = element_text( size=24))+
  theme(axis.title.y = element_text(size=24))+
  
  #ggtitle("Heritability over time")+
  theme(legend.title=element_blank())+
  guides(color = guide_legend(nrow=3))+
  theme(legend.text = element_text(colour="blue", size = 20))+  
  theme(legend.key.size = unit(2, 'lines'))+
  theme(plot.title = element_text(lineheight=5, face="bold", color="black", size=20))
library(RColorBrewer)
myColors <- c("blue","red","green")
names(myColors) <- levels(mydata$group)
# myline=c("dotdash","solid", "dotted","dotdash","solid", "dotted")
# names(myline) <- levels(mydata$group)
# 
colScale <- scale_colour_manual(name = "group",values = myColors)
# lineScale <- scale_colour_manual(name = "group",values = myline)
#png(file="EBV_gene_week1.png",width=1800,height=1200,res=100)
pp1+colScale 

Scale for 'colour' is already present. Adding another scale for 'colour', which will replace the existing
scale.

#dev.off()

# CUREVES SBV FOR GENERATIONS
library(ggplot2)
mydata<- read.csv("C:/Users/vhtran/Google Drive/these/diver_selection/dataplot3.csv", sep=";")
mydata=mydata[1:32,]
pp1=  ggplot(mydata, aes(x=generations, y=value, colour=group, group=group)) + 
  
  
  
geom_line(aes(linetype=group), # Line type depends on cond
          size = 1) +
  
  #geom_point(aes(fill = group,shape = group1),  
             geom_point(aes(fill = group,shape = group),size = 3) +
             
             # Shape depends on cond
                     # Large points
  
  
  
  scale_linetype_manual(values=c("dotted","dotted","solid", "solid")) +
  scale_shape_manual(values=c(8,8,1,1)) +
  
  #geom_line(data=dataplot, aes(x=generations, y=value, group=group,col=as.factor(group1),linetype=as.factor(group), scale_fill_manual(values=c("blue","red"))))
  
  #geom_line(aes(linetype=as.factor(group),color=as.factor(group)),size=2) +
  
  #geom_errorbar(aes(ymin=min, ymax=max, colour=group,linetype=group), width=.4,
  #  position=position_dodge(0.05))+
  
  
  
  
# scale_colour_manual(name="Error Bars",values=cols, guide = guide_legend(fill = NULL,colour = NULL)) + 
# scale_fill_manual(values=cols, guide="none") +
 #scale_x_continuous(breaks=1:10) +
  
  labs(list(y=" kg feed/kg gain ", x="Week"),size=18) +
  theme_bw() + 
  theme(panel.border = element_blank(), panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))+
  
  theme(axis.text.x=element_text(angle=0, hjust=1,size=18),axis.text.y=element_text(angle=0, hjust=1,size=18)) +
  scale_fill_brewer(type="qual", palette=2) +
  scale_color_brewer(type="qual", palette=2) +
  theme(axis.title.x = element_text( size=18))+
  theme(axis.title.y = element_text(size=18))+
  
  #ggtitle("Heritability over time")+
  theme(legend.title=element_blank())+
  guides(color = guide_legend(nrow=3))+
  theme(legend.text = element_text(colour="blue", size = 16))+  
  theme(legend.key.size = unit(2,'lines'))+
  theme(plot.title = element_text(lineheight=5, face="bold", color="black", size=16))
library(RColorBrewer)
myColors <- c("red","blue","red","blue","red","blue")
names(myColors) <- levels(mydata$group)
myline=c("dotdash","solid", "dotted","dotdash","solid", "dotted")
names(myline) <- levels(mydata$group)
colScale <- scale_colour_manual(name = "group",values = myColors)
lineScale <- scale_colour_manual(name = "group",values = myline)
#png(file="EBV_genkk.png",width=1000,height=800,res=100)
pp1+colScale 

Scale for 'colour' is already present. Adding another scale for 'colour', which will replace the existing
scale.

#dev.off()
#+lineScale