CODEWITHSUNDEEP
rdataframeggplot2facetgridextra
fsbmat
fsbmat

Reputation: 301

Graphs side by side using `gridExtra` and multiple facets

I have two databases of different sizes, dt and dt1. I want to use the command grid.arrange from the gridExtra package to display g1 and g2 side by side. If it is possible, I would also like to see g1 and g2 using the facet_grid or facet_wrap command or using gridExtra but with the of facet_grid\facet_wrap visual. I've done a long search on the internet and could not get these graphics using my code below.

set.seed(000)
m <- matrix(rnorm(1000,0,1),1000,1)
dt <- data.frame(m)
names(dt) <- c("X")

library(ggplot2)

g1 <- ggplot(dt, aes(x=X)) 
g1 <- g1+geom_histogram(aes(y=..density..),      # Histogram with density instead of count on y-axis
                        binwidth=.5,
                        colour="black", fill="white",breaks=seq(-2, 2, by = 0.1)) 
g1 <- g1 + stat_function(fun=dnorm,
                         color="black",geom="area", fill="gray", alpha=0.1,
                         args=list(mean=mean(dt$X), 
                                   sd=sd(dt$X)))
g1 <- g1+  geom_vline(aes(xintercept=0, linetype="Valor Verdadeiro"),show.legend =TRUE)
g1 <- g1+  geom_vline(aes(xintercept=mean(dt$X, 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[1])))+ylab("Densidade")
g1 <- g1+  theme(plot.margin=unit(c(0.5, 0.5, 0.5, 0.5), units="line"),
                 legend.position = "top",
                 legend.justification = c(0,0),
                 legend.box.just = "top",
                 legend.margin = margin(0,0,-10,-5),
                 legend.title=element_blank(),
                 legend.direction = "horizontal",
                 legend.background = element_rect(fill="transparent", size=.5, linetype="dotted"))
g1 <- g1+ guides(linetype = guide_legend(override.aes = list(size = 1)))


# Adjust key height and width
g1 = g1 + theme(
  legend.key.height = unit(.6, "cm"),
  legend.key.width = unit(1, "cm"))

# Get the ggplot Grob
gt = ggplotGrob(g1)

# grid.ls(grid.force(gt))  # To get a list of editable grobs

# Edit the relevant keys
library(grid)
gt <- editGrob(grid.force(gt), gPath("key-1-[3,7]-[1,2]"), 
               grep = TRUE, global = TRUE,
               x0 = unit(0, "npc"), y0 = unit(0.5, "npc"), 
               x1 = unit(1, "npc"), y1 = unit(0.5, "npc")) 

# Draw it
grid.newpage()
g1 <- grid.draw(gt)

m1 <- matrix(rnorm(2000,0,1),2000,1)
dt1 <- data.frame(m1)
names(dt1) <- c("Z")
library(ggplot2)

g2 <- ggplot(dt1, aes(x=Z)) 
g2 <- g2+geom_histogram(aes(y=..density..),      # Histogram with density instead of count on y-axis
                        binwidth=.5,
                        colour="black", fill="white",breaks=seq(-2, 2, by = 0.1)) 
g2 <- g2 + stat_function(fun=dnorm,
                         color="black",geom="area", fill="gray", alpha=0.1,
                         args=list(mean=mean(dt1$Z), 
                                   sd=sd(dt1$Z)))
g2 <- g2+  geom_vline(aes(xintercept=0, linetype="Valor Verdadeiro"),show.legend =TRUE)
g2 <- g2+  geom_vline(aes(xintercept=mean(dt1$Z, 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[1])))+ylab("Densidade")
g2 <- g2+  theme(plot.margin=unit(c(0.5, 0.5, 0.5, 0.5), units="line"),
                 legend.position = "top",
                 legend.justification = c(0,0),
                 legend.box.just = "top",
                 legend.margin = margin(0,0,-10,-5),
                 legend.title=element_blank(),
                 legend.direction = "horizontal",
                 legend.background = element_rect(fill="transparent", size=.5, linetype="dotted"))
g2 <- g2+ guides(linetype = guide_legend(override.aes = list(size = 1)))


# Adjust key height and width
g2 = g2 + theme(
  legend.key.height = unit(.6, "cm"),
  legend.key.width = unit(1, "cm"))

# Get the ggplot Grob
gt2 = ggplotGrob(g2)

# grid.ls(grid.force(gt))  # To get a list of editable grobs

# Edit the relevant keys
library(grid)
gt2 <- editGrob(grid.force(gt2), gPath("key-1-[3,7]-[1,2]"), 
                grep = TRUE, global = TRUE,
                x0 = unit(0, "npc"), y0 = unit(0.5, "npc"), 
                x1 = unit(1, "npc"), y1 = unit(0.5, "npc")) 

# Draw it
grid.newpage()
g2 <- grid.draw(gt2)

#library(gridExtra)
#grid.arrange(grid.draw(gt),grid.draw(gt2))

Upvotes: 0

Views: 654

Answers (1)

crlwbm
crlwbm

Reputation: 512

Does this do what you are looking for grid.arrange(gt, gt2, ncol = 2)?

(g1and g2 in your code are both NULL because you they are created by calling grid.draw, which doesn´t return anything)

To use facet_wrap you'll need to get all your data into one dataframe with long format:

library(tidyr)
df <- cbind.data.frame(dt, dt1)
df <- gather(df, key = "db", value = "value")

Then plot:

p <- ggplot(df, aes(x = value)) + 
geom_histogram(aes(y = ..density..), 
               binwidth = .5,
               breaks = seq(-2, 2, by = .1)) +
facet_wrap(~ db)

Upvotes: 1

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