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make colorblind-friendly figures [minor]
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@patdumandan
patdumandan committed Nov 1, 2023
1 parent 5f81d5a commit 2a84265
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56 changes: 27 additions & 29 deletions figures.R
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Original file line number Diff line number Diff line change
Expand Up @@ -78,7 +78,7 @@ pp11=ggplot(spdat1)+ geom_line(mapping=aes(x=newmoonnumber, y=abundance, col=spe
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(), axis.line = element_line(colour = "black"))+
facet_wrap(~trt, nrow=2)+
facet_wrap(~trt, nrow=2)+ scale_color_viridis(discrete=TRUE)+
xlab("")+
geom_bracket(
xmin = 280 , xmax = 396, y.position = 60,
Expand All @@ -93,34 +93,34 @@ pp11=ggplot(spdat1)+ geom_line(mapping=aes(x=newmoonnumber, y=abundance, col=spe

##Fig. 2: coefficient overlap####
int_ov=ggdensity(coef_df_PP, x="intercept", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, ylab=F, add="median",xlab=F, size=1
palette=c("#9900cc", "#FFcc00"), rug=T, ylab=F, add="median",xlab=F, size=1
)+geom_vline(xintercept=0)+
scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio=1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

ar1_ov=ggdensity(coef_df_PP, x="beta1", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab=F, size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab=F, size=1, ylab=F
)+geom_vline(xintercept=0)+scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio=1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

ar12_ov=ggdensity(coef_df_PP, x="beta12", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab=F, size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab=F, size=1, ylab=F
)+geom_vline(xintercept=0)+scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio=1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

temp_ov=ggdensity(coef_df_PP, x="temp", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab=F, size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab=F, size=1, ylab=F
)+geom_vline(xintercept=0)+scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio=1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

wprec_ov=ggdensity(coef_df_PP, x="warm_precip", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab=F, size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab=F, size=1, ylab=F
)+geom_vline(xintercept=0)+scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
scale_y_continuous(n.breaks=3)+
theme(aspect.ratio=1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

cprec_ov=ggdensity(coef_df_PP, x="cool_precip", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab=F, size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab=F, size=1, ylab=F
)+geom_vline(xintercept=0)+scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio=1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

Expand Down Expand Up @@ -165,21 +165,21 @@ annotate_figure(pp_predsplot,left = text_grob("C. penicillatus", face = "italic"

##Fig. 4: RMSE####
pp_h1=ggdensity(ppevals1, x="score_diff", color="plot",fill="plot",
palette=c("#69b3a2", "grey"), ylab=F,rug=T, add="median",xlab=F, size=1,
palette=c("#9900cc", "#FFcc00"), ylab=F,rug=T, add="median",xlab=F, size=1,
main="h=1")+geom_vline(xintercept=0)+xlim(-25, 25)+
annotate("text", x=-15, y=0.40, label="non-transferred better fit")+
annotate("text", x=13, y=0.40, label="transferred better fit")+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(axis.text.y = element_blank())

pp_h6=ggdensity(ppevals6, x="score_diff", color="plot",fill="plot",
palette=c("#69b3a2", "grey"), rug=T,ylab=F, add="median", xlab=F,size=1,
palette=c("#9900cc", "#FFcc00"), rug=T,ylab=F, add="median", xlab=F,size=1,
main="h=6")+geom_vline(xintercept=0)+xlim(-25, 25)+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(axis.text.y = element_blank())

pp_h12=ggdensity(ppevals12, x="score_diff", color="plot",fill="plot", size=1,
palette=c("#69b3a2", "grey"),ylab=F, rug=T, add="median", xlab="RMSE difference (non-transferred - transferred)",
palette=c("#9900cc", "#FFcc00"),ylab=F, rug=T, add="median", xlab="RMSE difference (non-transferred - transferred)",
main="h=12")+geom_vline(xintercept=0)+xlim(-25, 25)+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(axis.text.y = element_blank())
Expand All @@ -189,23 +189,22 @@ annotate_figure(pph, top = text_grob("C. penicillatus", face = "italic", size =
left= text_grob("RMSE", size=16, rot=90))

#Brier scores###

ppbr1=ggdensity(pp_briers1, x="brier_diff", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"),ylab=F, rug=T, add="median",xlab=F, size=1,
palette=c("#9900cc", "#FFcc00"),ylab=F, rug=T, add="median",xlab=F, size=1,
main="h=1")+geom_vline(xintercept=0)+xlim(-0.20, .20)+
annotate("text", x=-.12, y=70, label="non-transferred better fit")+
annotate("text", x=0.10, y=70, label="transferred better fit")+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(axis.text.y = element_blank())

ppbr2=ggdensity(pp_briers6, x="brier_diff", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), ylab=F, rug=T, add="median",xlab=F, size=1,
palette=c("#9900cc", "#FFcc00"), ylab=F, rug=T, add="median",xlab=F, size=1,
main="h=6")+geom_vline(xintercept=0)+xlim(-0.20, .20)+
theme(axis.text.y = element_blank())+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))

ppbr3=ggdensity(pp_briers12, x="brier_diff", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"),ylab=F, rug=T, add="median", size=1,
palette=c("#9900cc", "#FFcc00"),ylab=F, rug=T, add="median", size=1,
main="h=12", xlab="Brier score difference (non-transferred - transferred)")+
geom_vline(xintercept=0)+xlim(-0.2, 0.2)+
theme(axis.text.y = element_blank())+
Expand All @@ -219,38 +218,38 @@ annotate_figure(ppbh, top = text_grob("C. penicillatus", face = "italic", size =

##Fig. 2: coefficient overlap####
pbint_ov=ggdensity(coef_df_PB, x="intercept", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab="intercept", size=1
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab="intercept", size=1
)+geom_vline(xintercept=0)+ylab("")+
scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio = 1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

pbar1_ov=ggdensity(coef_df_PB, x="beta1", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab="AR (1)", size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab="AR (1)", size=1, ylab=F
)+geom_vline(xintercept=0)+
scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio = 1, axis.text.x = element_text(angle=90), axis.text.y = element_blank())

pbar12_ov=ggdensity(coef_df_PB, x="beta12", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab=" AR (12)", size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab=" AR (12)", size=1, ylab=F
)+geom_vline(xintercept=0)+
scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio = 1, axis.text.x = element_text(angle=90), axis.text.y = element_blank())

pbtemp_ov=ggdensity(coef_df_PB, x="temp", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab="mean temperature (lag=1)", size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab="mean temperature (lag=1)", size=1, ylab=F
)+geom_vline(xintercept=0)+
scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio = 1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

pbwprec_ov=ggdensity(coef_df_PB, x="warm_precip", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab="warm precipitation", size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab="warm precipitation", size=1, ylab=F
)+geom_vline(xintercept=0)+
scale_y_continuous(n.breaks=3)+
scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio = 1,axis.text.x = element_text(angle=90), axis.text.y = element_blank())

pbcprec_ov=ggdensity(coef_df_PB, x="cool_precip", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab="cool precipitation", size=1, ylab=F
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab="cool precipitation", size=1, ylab=F
)+geom_vline(xintercept=0)+
scale_x_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(aspect.ratio = 1, axis.text.x = element_text(angle=90), axis.text.y = element_blank())
Expand Down Expand Up @@ -295,22 +294,21 @@ pb_predsplot=ggarrange(pbpreds_plot1, pbpreds_plot2, common.legend = T, ncol=1,
annotate_figure(pb_predsplot,left = text_grob("C. baileyi", face = "italic", size = 16, rot=90))

##Fig. 4: RMSE####
pb_h1=ggdensity(pbevals1, x="score_diff", color="plot",fill="plot",
palette=c("#69b3a2", "grey"), rug=T, ylab=F,add="median",xlab=F, size=1,
pb_h1=ggdensity(pbevals1, x="score_diff", fill="plot", color="plot",
palette=c("#9900cc", "#FFcc00"), rug=T, ylab=F,add="median",xlab=F, size=1,
main="h=1")+geom_vline(xintercept=0)+xlim(-45, 45)+
annotate("text", x=-28, y=0.12, label="non-transferred better fit")+
annotate("text", x=26, y=0.12, label="transferred better fit")+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(axis.text.y = element_blank())

pb_h6=ggdensity(pbevals6, x="score_diff", color="plot",fill="plot",
palette=c("#69b3a2", "grey"), rug=T, ylab=F, add="median", xlab=F,size=1,
main="h=6")+geom_vline(xintercept=0)+xlim(-45, 45)+
pb_h6=ggdensity(pbevals6, x="score_diff", fill="plot", color="plot",
palette=c("#9900cc", "#FFcc00"), rug=T, ylab=F,add="median",xlab=F, size=1, main="h=6")+geom_vline(xintercept=0)+xlim(-45, 45)+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+
theme(axis.text.y = element_blank())

pb_h12=ggdensity(pbevals12, x="score_diff", color="plot",fill="plot", size=1,ylab=F,
palette=c("#69b3a2", "grey"), rug=T, add="median", xlab="RMSE difference (non-transferred - transferred)",
palette=c("#9900cc", "#FFcc00"), rug=T, add="median", xlab="RMSE difference (non-transferred - transferred)",
main="h=12")+geom_vline(xintercept=0)+xlim(-45, 45)+
theme(axis.text.y = element_blank())+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))
Expand All @@ -322,19 +320,19 @@ annotate_figure(pbhh, top = text_grob("C. baileyi", face = "italic", size = 16),
#Brier scores###

pbbr1=ggdensity(pb_briers1, x="brier_diff", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T,ylab=F, add="median",xlab=F, size=1,
palette=c("#9900cc", "#FFcc00"), rug=T,ylab=F, add="median",xlab=F, size=1,
main="h=1")+geom_vline(xintercept=0)+xlim(-0.4, 0.4)+
annotate("text", x=-0.25, y=13, label="non-transferred better fit")+
annotate("text", x=.25, y=13, label="transferred better fit")+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+theme(axis.text.y = element_blank())

pbbr2=ggdensity(pb_briers6, x="brier_diff", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T, add="median",xlab=F,ylab=F, size=1,
palette=c("#9900cc", "#FFcc00"), rug=T, add="median",xlab=F,ylab=F, size=1,
main="h=6")+geom_vline(xintercept=0)+xlim(-0.4, 0.4)+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+theme(axis.text.y = element_blank())

pbbr3=ggdensity(pb_briers12, x="brier_diff", color="treatment",fill="treatment",
palette=c("#69b3a2", "grey"), rug=T,ylab=F, add="median", size=1,
palette=c("#9900cc", "#FFcc00"), rug=T,ylab=F, add="median", size=1,
main="h=12", xlab="Brier score difference (non-transferred - transferred)")+
geom_vline(xintercept=0)+xlim(-0.4, 0.4)+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))+theme(axis.text.y = element_blank())
Expand Down
32 changes: 25 additions & 7 deletions supplementary_stuff.R
View file
Original file line number Diff line number Diff line change
Expand Up @@ -18,35 +18,35 @@ length(ppm_na$newmoonnumber)/length(ppm$newmoonnumber)*100

c1=ggplot(coef_df_PP, aes(x=intercept, y=temp, col=treatment))+geom_point()+theme_classic()+
geom_smooth(method="lm")+ylab("mean temp (lag=1)")+xlab("")+
ggtitle(expression(italic("C. penicillatus")))+scale_color_manual(values=c(control="#69b3a2", removal="grey"))+
ggtitle(expression(italic("C. penicillatus")))+scale_color_manual(values=c(control="#9900cc", removal="#FFcc00"))+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))

c2=ggplot(coef_df_PP, aes(x=intercept, y=warm_precip, col=treatment))+geom_point()+theme_classic()+
geom_smooth(method="lm")+ylab("warm precipitation")+
scale_color_manual(values=c(control="#69b3a2", removal="grey"))+xlab("")+
scale_color_manual(values=c(control="#9900cc", removal="#FFcc00"))+xlab("")+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))

c3=ggplot(coef_df_PP, aes(x=intercept, y=cool_precip, col=treatment))+geom_point()+theme_classic()+
geom_smooth(method="lm")+ylab("cool precipitation")+
scale_color_manual(values=c(control="#69b3a2", removal="grey"))+
scale_color_manual(values=c(control="#9900cc", removal="#FFcc00"))+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))

ggarrange(c1,c2,c3, common.legend = T, nrow=3, legend="bottom")

#PB
z1=ggplot(coef_df_PB, aes(x=intercept, y=temp, col=treatment))+geom_point()+theme_classic()+
geom_smooth(method="lm")+ylab("mean temp (lag=1)")+xlab("")+
ggtitle(expression(italic("C. baileyi")))+scale_color_manual(values=c(control="#69b3a2", removal="grey"))+
ggtitle(expression(italic("C. baileyi")))+scale_color_manual(values=c(control="#9900cc", removal="#FFcc00"))+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))

z2=ggplot(coef_df_PB, aes(x=intercept, y=warm_precip, col=treatment))+geom_point()+theme_classic()+
geom_smooth(method="lm")+ylab("warm precipitation")+
scale_color_manual(values=c(control="#69b3a2", removal="grey"))+xlab("")+
scale_color_manual(values=c(control="#9900cc", removal="#FFcc00"))+xlab("")+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))

z3=ggplot(coef_df_PB, aes(x=intercept, y=cool_precip, col=treatment))+geom_point()+theme_classic()+
geom_smooth(method="lm")+ylab("cool precipitation")+
scale_color_manual(values=c(control="#69b3a2", removal="grey"))+
scale_color_manual(values=c(control="#9900cc", removal="#FFcc00"))+
scale_y_continuous(n.breaks=3, labels = scales::label_number(accuracy = 0.01))

ggarrange(z1,z2,z3, common.legend = T, nrow=3, legend="bottom")
Expand Down Expand Up @@ -368,4 +368,22 @@ rolling_mod=function(split) {
distr = "nbinom",
xreg = analysis_set[,3:5],
link = "log")
}
}

#run before building rolling origin bject
n_moons_yr=13
n_yrs=5
n_moons_train=n_moons_yr*n_yrs
n_moons_test=n_moons_yr*1

#run before making forecasts

#PP
m=rep(seq(1:39), each=13) #no.of splits
code1="same"
code2="switched"

#PB
m=rep(seq(1:42), each=13)
code1="same"
code2="switched"

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