scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","StrongHidden","ModerateHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:ModerateHidden, names_to = "rate", values_to = "value")
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","NonassociatedHidden","Strong","StrongHidden","Moderate",
"ModerateHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:ModerateHidden, names_to = "rate", values_to = "value")
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","StrongHidden","ModerateHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:ModerateHidden, names_to = "rate", values_to = "value")
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","ModerateHidden","StrongHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:StrongHidden, names_to = "rate", values_to = "value")
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Strong","Moderate",
"ModerateHidden","StrongHidden","NonassociatedHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:StrongHidden, names_to = "rate", values_to = "value")
data_netdiv
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Strong","Moderate",
"ModerateHidden","StrongHidden","NonassociatedHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:NonassociatedHidden, names_to = "rate", values_to = "value")
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","ModerateHidden","StrongHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:StrongHidden, names_to = "rate", values_to = "value")
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#2F4858","#1E84AD",
alpha("#86BBD8",0.5),alpha("#2F4858",0.5),alpha("#1E84AD",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","ModerateHidden","StrongHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(names_to = "rate", values_to = "value")
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","ModerateHidden","StrongHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:StrongHidden, names_to = "rate", values_to = "value")
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Strong","Moderate",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong"
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#2F4858","#1E84AD",
alpha("#86BBD8",0.5),alpha("#2F4858",0.5),alpha("#1E84AD",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
#geom_vline(data=db_mode, aes(xintercept=mode_value),linetype="dashed", size = 0.7, col = "grey95") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#2F4858","#1E84AD",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
#----- Plotting without RevGadgets -----#
data <- read.table("output/coral_association_MuHiSSE_coral_association.log",header=TRUE)
# Removing 10% burnin
data <- data[2003:nrow(data),]
#----- Plotting transition rates -----#
# Filtering evolutionary rates from posterior dataset
data_spe <- data[,grep("speciation.", colnames(data), value = T)]
data_ext <- data[,grep("extinction.", colnames(data), value = T)]
data_netdiv <- data_spe[,1:6] - data_ext[,1:6]
colnames(data_netdiv) <- c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden")
data_netdiv <- data_netdiv %>%
pivot_longer(cols = Nonassociated:StrongHidden, names_to = "rate", values_to = "value")
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#2F4858","#1E84AD",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
ggplot(data_netdiv, aes(x=value, fill=rate)) +
geom_density(size = 0.3, col = "white") +
scale_x_continuous(limits = c(-0.01, 0.25), expand = c(0,0)) +
scale_fill_manual(breaks=c("Nonassociated","Moderate","Strong",
"NonassociatedHidden","ModerateHidden","StrongHidden"),
values = c("#86BBD8","#1E84AD","#2F4858",
alpha("#86BBD8",0.5),alpha("#1E84AD",0.5),alpha("#2F4858",0.5))) +
scale_y_continuous(expand = c(0.01,0.01)) +
theme_bw() +
ylab("Posterior Density") + xlab("Net Diversification (lineages/Ma)") +
theme(text = element_text(size=12),
legend.title = element_blank(),
legend.position = c(.8,.8),
legend.background = element_rect(fill = "transparent", colour = NA),
panel.background = element_rect(fill = "grey95",
colour = "grey95",
linetype = "solid"),
panel.grid.major = element_line(size = 0.5, linetype = 'solid',
colour = "white"),
panel.grid.minor = element_line(size = 0.25, linetype = 'solid',
colour = "white"))
getwd()
ggsave("../../Figures/Siqueira_&_Bellwood_Fig4.pdf", height = 5, width = 6)
#----- Plotting transition rates -----#
# Filtering transition rates from posterior dataset
data_trans <- data[,grep("transition", colnames(data), value = T)]
mat_trans <- matrix(nrow = 3, ncol = 3, dimnames = list(c("Nonassociated","Moderate","Strong"),
c("Nonassociated","Moderate","Strong")))
mat_trans[1,2] <- round(median(data_trans$transition_rates.1.), 5)
mat_trans[1,3] <- round(median(data_trans$transition_rates.2.), 5)
mat_trans[2,1] <- round(median(data_trans$transition_rates.3.), 5)
mat_trans[2,3] <- round(median(data_trans$transition_rates.4.), 5)
mat_trans[3,1] <- round(median(data_trans$transition_rates.5.), 5)
mat_trans[3,2] <- round(median(data_trans$transition_rates.6.), 5)
source("~/Desktop/Ongoing_papers/Coral_association/Scripts/Siqueira_etal_functions.R")
environment(plot.igraph2) <- asNamespace('igraph')
environment(igraph.Arrows2) <- asNamespace('igraph')
g2 <- graph_from_adjacency_matrix(mat_trans, weighted=TRUE,diag=F)
#pdf("../../Figures/Siqueira_&_Bellwood_Fig4b.pdf", height = 8, width = 8)
plot.igraph2(g2, layout = layout.circle,
vertex.size = 50,
vertex.label.cex = 1.2,
vertex.color = cols,
vertex.frame.color = "white",
vertex.width = 2,
vertex.label.color = "grey99",
vertex.label.family = "Helvetica",
edge.color=c(cols[1],cols[3],cols[2],cols[2],cols[1],cols[3]),
edge.width=(E(g2)$weight/max(E(g2)$weight))*25,
edge.arrow.size=(E(g2)$weight/max(E(g2)$weight))*5,
edge.label.family = "Helvetica",
edge.label.cex = 0.8,
edge.curved = 0.5,
rescale = F, axes = F, main = "BLA")
mat_trans
