Spiel Grafik von ggplot2 mit mehreren Facetten

Question

Ich baute das Diagramm unten mit dem Befehl grid.arrange aus dem gridExtra Paket, möchte es mit den Visuals der Multi-Facetten-Diagramme verlassen, mit der Probengröße als Facette, ist es möglich?

library(ggplot2) 
library(grid) 
library(utils) 
grid.newpage() 
#Lendo os dados 
dt1 <- read.table("https://cdn.rawgit.com/fsbmat/StackOverflow/master/sim50.txt", header = TRUE) 
attach(dt1) 
#head(dt1) 
dt2 <- read.table("https://cdn.rawgit.com/fsbmat/StackOverflow/master/sim200.txt", header = TRUE) 
attach(dt2) 
#head(dt2) 
dt3 <- read.table("https://cdn.rawgit.com/fsbmat/StackOverflow/master/sim1000.txt", header = TRUE) 
attach(dt3) 
#head(dt3) 
g1 <- ggplot(dt1, aes(x=dt1$gamma0))+coord_cartesian(xlim=c(-1.3,3.3),ylim = c(0,0.63)) + 
    ggtitle("n=50")+ 
    theme(plot.title = element_text(margin = margin(b = 2),size = 6,hjust = 0)) 
g1 <- g1+geom_histogram(aes(y=..density..),  # Histogram with density instead of count on y-axis 
         binwidth=.5, 
         colour="black", fill="white",breaks=seq(-3, 3, by = 0.1)) 
g1 <- g1 + stat_function(fun=dnorm, 
         color="black",geom="area", fill="gray", alpha=0.1, 
         args=list(mean=mean(dt1$gamma0), 
            sd=sd(dt1$gamma0))) 
g1 <- g1+ geom_vline(aes(xintercept=1.23, linetype="Valor Verdadeiro"),show.legend =TRUE) 
g1 <- g1+ geom_vline(aes(xintercept=mean(dt1$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) 
g1 <- g1+ scale_linetype_manual(values=c("dotdash","solid")) # Overlay with transparent density plot 
g1 <- g1+ xlab(expression(paste(gamma[0])))+ylab("") 
g1 <- g1+ theme(plot.margin=unit(c(0.1, 0.1, 0.1, 0.1), units="line"), 
       legend.text=element_text(size=5), 
       legend.position = c(0, 0.97), 
       legend.justification = c("left", "top"), 
       legend.box.just = "left", 
       legend.margin = margin(0,0,0,0), 
       legend.title=element_blank(), 
       legend.direction = "vertical", 
       legend.background = element_rect(colour = NA,fill="transparent", size=.5, linetype="dotted"), 
       legend.key = element_rect(colour = "transparent", fill = NA)) 
g1 <- g1+ guides(linetype = guide_legend(override.aes = list(size = 0.5))) 


# Adjust key height and width 
g1 = g1 + theme(
    legend.key.height = unit(0.3, "cm"), 
    legend.key.width = unit(0.4, "cm")) 

# Get the ggplot Grob 
gt1 = ggplotGrob(g1) 

# Edit the relevant keys 

gt1 <- editGrob(grid.force(gt1), gPath("key-[3,4]-1-[1,2]"), 
       grep = TRUE, global = TRUE, 
       x0 = unit(0, "npc"), y0 = unit(0.5, "npc"), 
       x1 = unit(1, "npc"), y1 = unit(0.5, "npc")) 

################################################### 

g2 <- ggplot(dt2, aes(x=dt2$gamma0))+coord_cartesian(xlim=c(0,3),ylim = c(0,1.26)) + 
    ggtitle("n=200")+ 
    theme(plot.title = element_text(margin = margin(b = 2),size = 6,hjust = 0)) 
g2 <- g2+geom_histogram(aes(y=..density..),  # Histogram with density instead of count on y-axis 
         binwidth=.5, 
         colour="black", fill="white",breaks=seq(-3, 3, by = 0.1)) 
g2 <- g2 + stat_function(fun=dnorm, 
         color="black",geom="area", fill="gray", alpha=0.1, 
         args=list(mean=mean(dt2$gamma0), 
            sd=sd(dt2$gamma0))) 
g2 <- g2+ geom_vline(aes(xintercept=1.23, linetype="Valor Verdadeiro"),show.legend =TRUE) 
g2 <- g2+ geom_vline(aes(xintercept=mean(dt2$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) 
g2 <- g2+ scale_linetype_manual(values=c("dotdash","solid")) # Overlay with transparent density plot 
g2 <- g2+ xlab(expression(paste(gamma[0])))+ylab("") 
g2 <- g2+ theme(plot.margin=unit(c(0.1, 0.1, 0.1, 0.1), units="line"), 
       legend.text=element_text(size=5), 
       legend.position = c(0, 0.97), 
       legend.justification = c("left", "top"), 
       legend.box.just = "left", 
       legend.margin = margin(0,0,0,0), 
       legend.title=element_blank(), 
       legend.direction = "vertical", 
       legend.background = element_rect(colour = NA,fill="transparent", size=.5, linetype="dotted"), 
       legend.key = element_rect(colour = "transparent", fill = NA)) 
g2 <- g2+ guides(linetype = guide_legend(override.aes = list(size = 0.5))) 

# Adjust key height and width 
g2 = g2 + theme(
    legend.key.height = unit(0.3, "cm"), 
    legend.key.width = unit(0.4, "cm")) 

# Get the ggplot Grob 
gt2 = ggplotGrob(g2) 

# Edit the relevant keys 

gt2 <- editGrob(grid.force(gt2), gPath("key-[3,4]-1-[1,2]"), 
       grep = TRUE, global = TRUE, 
       x0 = unit(0, "npc"), y0 = unit(0.5, "npc"), 
       x1 = unit(1, "npc"), y1 = unit(0.5, "npc")) 

####################################################### 

g3 <- ggplot(dt3, aes(x=gamma0))+coord_cartesian(xlim=c(0.6,1.8),ylim = c(0,2.6)) + 
    ggtitle("n=1000")+ 
    theme(plot.title = element_text(margin = margin(b = 2),size = 6,hjust = 0)) 
g3 <- g3+geom_histogram(aes(y=..density..),  # Histogram with density instead of count on y-axis 
         binwidth=.5, 
         colour="black", fill="white",breaks=seq(-3, 3, by = 0.1)) 
g3 <- g3 + stat_function(fun=dnorm, 
         color="black",geom="area", fill="gray", alpha=0.1, 
         args=list(mean=mean(dt3$gamma0), 
            sd=sd(dt3$gamma0))) 
g3 <- g3+ geom_vline(aes(xintercept=1.23, linetype="Valor Verdadeiro"),show.legend =TRUE) 
g3 <- g3+ geom_vline(aes(xintercept=mean(dt3$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) 
g3 <- g3+ scale_linetype_manual(values=c("dotdash","solid")) # Overlay with transparent density plot 
g3 <- g3+ xlab(expression(paste(gamma[0])))+ylab("") 
g3 <- g3+ theme(plot.margin=unit(c(0.1, 0.1, 0.1, 0.1), units="line"), 
       legend.text=element_text(size=5), 
       legend.position = c(0, 0.97), 
       legend.justification = c("left", "top"), 
       legend.box.just = "left", 
       legend.margin = margin(0,0,0,0), 
       legend.title=element_blank(), 
       legend.direction = "vertical", 
       legend.background = element_rect(colour = NA,fill="transparent", size=.5, linetype="dotted"), 
       legend.key = element_rect(colour = "transparent", fill = NA)) 
g3 <- g3+ guides(linetype = guide_legend(override.aes = list(size = 0.5))) 


# Adjust key height and width 
g3 = g3 + theme(
    legend.key.height = unit(.3, "cm"), 
    legend.key.width = unit(.4, "cm")) 

# Get the ggplot Grob 
gt3 = ggplotGrob(g3) 

# Edit the relevant keys 

gt3 <- editGrob(grid.force(gt3), gPath("key-[3,4]-1-[1,2]"), 
       grep = TRUE, global = TRUE, 
       x0 = unit(0, "npc"), y0 = unit(0.5, "npc"), 
       x1 = unit(1, "npc"), y1 = unit(0.5, "npc")) 

#################################################### 

library(gridExtra) 
grid.arrange(gt1, gt2, gt3, widths=c(0.3,0.3,0.3), ncol=3) 

Hinweis: Ich möchte die gleiche grafische Darstellung reproduzieren, aber mit der Formatierung des facet_wrap, mit n = 50, n = 200 und n = 1000 als die Facetten.

Answer 1

Ich habe es mit grid.arrange:

library(ggplot2) 
library(grid) 
library(utils) 
grid.newpage() 

dt1 <- read.table("https://cdn.rawgit.com/fsbmat/StackOverflow/master/sim50.txt", header = TRUE) 
attach(dt1) 
#head(dt1) 
dt2 <- read.table("https://cdn.rawgit.com/fsbmat/StackOverflow/master/sim200.txt", header = TRUE) 
attach(dt2) 
#head(dt2) 
dt3 <- read.table("https://cdn.rawgit.com/fsbmat/StackOverflow/master/sim1000.txt", header = TRUE) 
attach(dt3) 
#head(dt3) 
g1 <- ggplot(dt1, aes(x=dt1$gamma0))+coord_cartesian(xlim=c(-1.3,3.3),ylim = c(0,0.63)) + 
    theme(plot.title = element_text(margin = margin(b = 2),size = 6,hjust = 0)) 
g1 <- g1+geom_histogram(aes(y=..density..),  # Histogram with density instead of count on y-axis 
         binwidth=.5, 
         colour="black", fill="white",breaks=seq(-3, 3, by = 0.1)) 
g1 <- g1 + stat_function(fun=dnorm, 
         color="black",geom="area", fill="gray", alpha=0.1, 
         args=list(mean=mean(dt1$gamma0), 
            sd=sd(dt1$gamma0))) 
g1 <- g1+ geom_vline(aes(xintercept=1.23, linetype="Valor Verdadeiro"),show.legend =TRUE) 
g1 <- g1+ geom_vline(aes(xintercept=mean(dt1$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) 
g1 <- g1+ scale_linetype_manual(values=c("dotdash","solid")) # Overlay with transparent density plot 
g1 <- g1+ xlab(expression(paste(gamma[0])))+ylab("densidade") 
g1 <- g1+ annotate("rect", xmin = -2, xmax = 3.52, ymin = 0.635, ymax = 0.7, fill="gray") 
g1 <- g1+ annotate("text", x = 1.23, y = 0.65, label = "n=50", size=4) 
g1 <- g1+ theme(plot.margin=unit(c(0.1, 0.1, 0.1, 0.1), units="line"), 
       legend.text=element_text(size=5), 
       legend.position = c(0, 0.97), 
       legend.justification = c("left", "top"), 
       legend.box.just = "left", 
       legend.margin = margin(0,0,0,0), 
       legend.title=element_blank(), 
       legend.direction = "vertical", 
       legend.background = element_rect(colour = NA,fill="transparent", size=.5, linetype="dotted"), 
       legend.key = element_rect(colour = "transparent", fill = NA), 
       axis.text.y=element_blank(), 
       axis.ticks.y=element_blank()) 
g1 <- g1+ guides(linetype = guide_legend(override.aes = list(size = 0.5))) 


# Adjust key height and width 
g1 = g1 + theme(
    legend.key.height = unit(0.3, "cm"), 
    legend.key.width = unit(0.4, "cm")) 

# Get the ggplot Grob 
gt1 = ggplotGrob(g1) 

# Edit the relevant keys 

gt1 <- editGrob(grid.force(gt1), gPath("key-[3,4]-1-[1,2]"), 
       grep = TRUE, global = TRUE, 
       x0 = unit(0, "npc"), y0 = unit(0.5, "npc"), 
       x1 = unit(1, "npc"), y1 = unit(0.5, "npc")) 

################################################### 

g2 <- ggplot(dt2, aes(x=dt2$gamma0))+coord_cartesian(xlim=c(0,3),ylim = c(0,1.26)) + 
    theme(plot.title = element_text(margin = margin(b = 2),size = 6,hjust = 0)) 
g2 <- g2+geom_histogram(aes(y=..density..),  # Histogram with density instead of count on y-axis 
         binwidth=.5, 
         colour="black", fill="white",breaks=seq(-3, 3, by = 0.1)) 
g2 <- g2 + stat_function(fun=dnorm, 
         color="black",geom="area", fill="gray", alpha=0.1, 
         args=list(mean=mean(dt2$gamma0), 
            sd=sd(dt2$gamma0))) 
g2 <- g2+ geom_vline(aes(xintercept=1.23, linetype="Valor Verdadeiro"),show.legend =TRUE) 
g2 <- g2+ geom_vline(aes(xintercept=mean(dt2$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) 
g2 <- g2+ scale_linetype_manual(values=c("dotdash","solid")) # Overlay with transparent density plot 
g2 <- g2+ xlab(expression(paste(gamma[0])))+ylab("") 
g2 <- g2+ annotate("rect", xmin = -2, xmax = 3.5, ymin = 1.27, ymax = 1.8, fill="gray") 
g2 <- g2+ annotate("text", x = 1.23, y = 1.3, label = "n=200", size=4) 

g2 <- g2+ theme(plot.margin=unit(c(0.1, 0.1, 0.1, 0.1), units="line"), 
       legend.text=element_text(size=5), 
       legend.position = c(0, 0.97), 
       legend.justification = c("left", "top"), 
       legend.box.just = "left", 
       legend.margin = margin(0,0,0,0), 
       legend.title=element_blank(), 
       legend.direction = "vertical", 
       legend.background = element_rect(colour = NA,fill="transparent", size=.5, linetype="dotted"), 
       legend.key = element_rect(colour = "transparent", fill = NA), 
       axis.title.y=element_blank(), 
       axis.text.y=element_blank(), 
       axis.ticks.y=element_blank()) 
g2 <- g2+ guides(linetype = guide_legend(override.aes = list(size = 0.5))) 

# Adjust key height and width 
g2 = g2 + theme(
    legend.key.height = unit(0.3, "cm"), 
    legend.key.width = unit(0.4, "cm")) 

# Get the ggplot Grob 
gt2 = ggplotGrob(g2) 

# Edit the relevant keys 

gt2 <- editGrob(grid.force(gt2), gPath("key-[3,4]-1-[1,2]"), 
       grep = TRUE, global = TRUE, 
       x0 = unit(0, "npc"), y0 = unit(0.5, "npc"), 
       x1 = unit(1, "npc"), y1 = unit(0.5, "npc")) 

####################################################### 

g3 <- ggplot(dt3, aes(x=gamma0))+coord_cartesian(xlim=c(0.6,1.8),ylim = c(0,2.6)) + 
    theme(plot.title = element_text(margin = margin(b = 2),size = 6,hjust = 0)) 
g3 <- g3+geom_histogram(aes(y=..density..),  # Histogram with density instead of count on y-axis 
         binwidth=.5, 
         colour="black", fill="white",breaks=seq(-3, 3, by = 0.1)) 
g3 <- g3 + stat_function(fun=dnorm, 
         color="black",geom="area", fill="gray", alpha=0.1, 
         args=list(mean=mean(dt3$gamma0), 
            sd=sd(dt3$gamma0))) 
g3 <- g3+ geom_vline(aes(xintercept=1.23, linetype="Valor Verdadeiro"),show.legend =TRUE) 
g3 <- g3+ geom_vline(aes(xintercept=mean(dt3$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) 
g3 <- g3+ scale_linetype_manual(values=c("dotdash","solid")) # Overlay with transparent density plot 
g3 <- g3+ labs(x=expression(paste(gamma[0])), y="") 
g3 <- g3+ annotate("rect", xmin = -2, xmax = 1.875, ymin = 2.62, ymax = 3, fill="gray") 
g3 <- g3+ annotate("text", x = 1.23, y = 2.68, label = "n=1000", size=4) 
g3 <- g3+ theme(plot.margin=unit(c(0.1, 0.1, 0.1, 0.1), units="line"), 
       legend.text=element_text(size=5), 
       legend.position = c(0, 0.97), 
       legend.justification = c("left", "top"), 
       legend.box.just = "left", 
       legend.margin = margin(0,0,0,0), 
       legend.title=element_blank(), 
       legend.direction = "vertical", 
       legend.background = element_rect(colour = NA,fill="transparent", size=.5, linetype="dotted"), 
       legend.key = element_rect(colour = "transparent", fill = NA), 
       axis.title.y=element_blank(), 
       axis.text.y=element_blank(), 
       axis.ticks.y=element_blank()) 
g3 <- g3+ guides(linetype = guide_legend(override.aes = list(size = 0.5))) 


# Adjust key height and width 
g3 = g3 + theme(
    legend.key.height = unit(.3, "cm"), 
    legend.key.width = unit(.4, "cm")) 

# Get the ggplot Grob 
gt3 = ggplotGrob(g3) 

# Edit the relevant keys 

gt3 <- editGrob(grid.force(gt3), gPath("key-[3,4]-1-[1,2]"), 
       grep = TRUE, global = TRUE, 
       x0 = unit(0, "npc"), y0 = unit(0.5, "npc"), 
       x1 = unit(1, "npc"), y1 = unit(0.5, "npc")) 

#################################################### 

library(gridExtra) 
grid.arrange(gt1, gt2, gt3, widths=c(0.1,0.1,0.1), ncol=3) 

Answer 2

(i) die drei rbind data.frames zusammen und geben ihm eine Art, die auf dem Etikett facet_wrap, dh n=50, n=200 und n=1000

dat <- list(dt1, dt2, dt3) %>% setNames(c("dt1", "dt2", "dt3")) 
dat <- ldply(names(dat), function(x) dat[[x]] %>% mutate(type = x %>% as.factor)) 
levels(dat$type) <- c("n=50", "n=200", "n=1000") 

(ii) Zeichnen der Graphen mit facet_wrap(~type)

erscheint

ggplot(dat, aes(x=gamma0)) + 
    geom_histogram(aes(y=..density..), binwidth=.5, colour="black", fill="white",breaks=seq(-3, 3, by = 0.1)) + 
    stat_function(fun=dnorm, color="black",geom="area", fill="gray", alpha=0.1, args=list(mean=mean(dt1$gamma0), sd=sd(dt1$gamma0))) + 
    geom_vline(aes(xintercept=1.23, linetype="Valor Verdadeiro"),show.legend =TRUE) + 
    geom_vline(aes(xintercept=mean(dt1$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) + 
    scale_linetype_manual(values=c("dotdash","solid")) + 
    facet_wrap(~type, scales="free") 

• Beachten Sie, dass ich die Designelemente und Achseneinstellungen entfernt habe, da sie für jeden verwendeten Datenrahmen zu individuell angepasst wurden.