使用多个方面播放 ggplot2 的图形
Play graphic of ggplot2 using multiple facets
我使用 gridExtra 包中的命令 grid.arrange 构建了下面的图表，希望它保留多方面图表的视觉效果，使用样本大小作为方面，是可能吗？
library(ggplot2)
library(grid)
library(utils)
grid.newpage()
#Lendo os dados
dt1 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim50.txt", header = TRUE)
attach(dt1)
#head(dt1)
dt2 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim200.txt", header = TRUE)
attach(dt2)
#head(dt2)
dt3 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/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$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE)
g3 <- g3+ scale_linetype_manual(values=c("dotdash","solid")) # Overlay with transparent density plot
g3 <- g3+ xlab(expression(paste(gamma[0])))+ylab("")
g3 <- g3+ theme(plot.margin=unit(c(0.1, 0.1, 0.1, 0.1), units="line"),
legend.text=element_text(size=5),
legend.position = c(0, 0.97),
legend.justification = c("left", "top"),
legend.box.just = "left",
legend.margin = margin(0,0,0,0),
legend.title=element_blank(),
legend.direction = "vertical",
legend.background = element_rect(colour = NA,fill="transparent", size=.5, linetype="dotted"),
legend.key = element_rect(colour = "transparent", fill = NA))
g3 <- g3+ guides(linetype = guide_legend(override.aes = list(size = 0.5)))
# Adjust key height and width
g3 = g3 + theme(
legend.key.height = unit(.3, "cm"),
legend.key.width = unit(.4, "cm"))
# Get the ggplot Grob
gt3 = ggplotGrob(g3)
# Edit the relevant keys
gt3 <- editGrob(grid.force(gt3), gPath("key-[3,4]-1-[1,2]"),
grep = TRUE, global = TRUE,
x0 = unit(0, "npc"), y0 = unit(0.5, "npc"),
x1 = unit(1, "npc"), y1 = unit(0.5, "npc"))
####################################################
library(gridExtra)
grid.arrange(gt1, gt2, gt3, widths=c(0.3,0.3,0.3), ncol=3)
注意：我想重现相同的图形，但使用 facet_wrap 的格式，使用 n = 50、n = 200 和 n = 1000 作为构面。
(i) rbind 三个 data.frames 在一起，并给它一个将出现在 facet_wrap 标签上的类型，即 n=50、n=200 和 n=1000
dat <- list(dt1, dt2, dt3) %>% setNames(c("dt1", "dt2", "dt3"))
dat <- ldply(names(dat), function(x) dat[[x]] %>% mutate(type = x %>% as.factor))
levels(dat$type) <- c("n=50", "n=200", "n=1000")
(ii) 用 facet_wrap(~type)
绘制图形
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$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) +
scale_linetype_manual(values=c("dotdash","solid")) +
facet_wrap(~type, scales="free")
- 请注意，我删除了您的主题元素和轴设置，因为它们对于每个 data.frame 使用而言都过于自定义。
我使用 grid.arrange:
library(ggplot2)
library(grid)
library(utils)
grid.newpage()
dt1 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim50.txt", header = TRUE)
attach(dt1)
#head(dt1)
dt2 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim200.txt", header = TRUE)
attach(dt2)
#head(dt2)
dt3 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim1000.txt", header = TRUE)
attach(dt3)
#head(dt3)
g1 <- ggplot(dt1, aes(x=dt1$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)
我使用 gridExtra 包中的命令 grid.arrange 构建了下面的图表，希望它保留多方面图表的视觉效果，使用样本大小作为方面，是可能吗？
library(ggplot2)
library(grid)
library(utils)
grid.newpage()
#Lendo os dados
dt1 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim50.txt", header = TRUE)
attach(dt1)
#head(dt1)
dt2 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim200.txt", header = TRUE)
attach(dt2)
#head(dt2)
dt3 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/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$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE)
g3 <- g3+ scale_linetype_manual(values=c("dotdash","solid")) # Overlay with transparent density plot
g3 <- g3+ xlab(expression(paste(gamma[0])))+ylab("")
g3 <- g3+ theme(plot.margin=unit(c(0.1, 0.1, 0.1, 0.1), units="line"),
legend.text=element_text(size=5),
legend.position = c(0, 0.97),
legend.justification = c("left", "top"),
legend.box.just = "left",
legend.margin = margin(0,0,0,0),
legend.title=element_blank(),
legend.direction = "vertical",
legend.background = element_rect(colour = NA,fill="transparent", size=.5, linetype="dotted"),
legend.key = element_rect(colour = "transparent", fill = NA))
g3 <- g3+ guides(linetype = guide_legend(override.aes = list(size = 0.5)))
# Adjust key height and width
g3 = g3 + theme(
legend.key.height = unit(.3, "cm"),
legend.key.width = unit(.4, "cm"))
# Get the ggplot Grob
gt3 = ggplotGrob(g3)
# Edit the relevant keys
gt3 <- editGrob(grid.force(gt3), gPath("key-[3,4]-1-[1,2]"),
grep = TRUE, global = TRUE,
x0 = unit(0, "npc"), y0 = unit(0.5, "npc"),
x1 = unit(1, "npc"), y1 = unit(0.5, "npc"))
####################################################
library(gridExtra)
grid.arrange(gt1, gt2, gt3, widths=c(0.3,0.3,0.3), ncol=3)
注意：我想重现相同的图形，但使用 facet_wrap 的格式，使用 n = 50、n = 200 和 n = 1000 作为构面。
(i) rbind 三个 data.frames 在一起，并给它一个将出现在 facet_wrap 标签上的类型，即 n=50、n=200 和 n=1000
dat <- list(dt1, dt2, dt3) %>% setNames(c("dt1", "dt2", "dt3"))
dat <- ldply(names(dat), function(x) dat[[x]] %>% mutate(type = x %>% as.factor))
levels(dat$type) <- c("n=50", "n=200", "n=1000")
(ii) 用 facet_wrap(~type)
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$gamma0, na.rm=T), linetype="Valor Estimado"),show.legend =TRUE) +
scale_linetype_manual(values=c("dotdash","solid")) +
facet_wrap(~type, scales="free")
- 请注意，我删除了您的主题元素和轴设置，因为它们对于每个 data.frame 使用而言都过于自定义。
我使用 grid.arrange:
library(ggplot2)
library(grid)
library(utils)
grid.newpage()
dt1 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim50.txt", header = TRUE)
attach(dt1)
#head(dt1)
dt2 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim200.txt", header = TRUE)
attach(dt2)
#head(dt2)
dt3 <- read.table("https://cdn.rawgit.com/fsbmat/Whosebug/master/sim1000.txt", header = TRUE)
attach(dt3)
#head(dt3)
g1 <- ggplot(dt1, aes(x=dt1$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)