Related
The Y axis labels are offset
The Y axis labels from 100 to the top are aligned to the right, while from 90 to the bottom are aligned to the left. I've looked at many paramaters and I couldn't find one to be causing this. Also, I haven't found anyone else with this same issue.
Here's my code:
test <- ggplot(data,
aes(x=Month, y=Value, color=Name, group=Name, fill=Name))+
geom_line(size=3)+
geom_point(size=5)+
scale_color_manual(values=c("#FBE785","#0F5F00","#FFC300","#1BFFAA"))+
ylab ("")+
xlab ("")+
labs(caption = paste("Fonte: Fred e IBGE.")) +
scale_x_date(date_labels = "%b/%y", breaks = "6 month", expand=c(0,0))+
coord_cartesian(clip = "off")+
theme_minimal() +
guides(fill=guide_legend())+
theme(panel.background = element_rect(fill= "#122929",color = "#122929"),
plot.background = element_rect(fill = "#122929"),
panel.grid.major = element_line(color = "#4D4B55", size =0.1),
panel.grid.minor = element_line(color= "#4D4B55", size =0.1),
panel.grid = element_blank(),
axis.text.y = element_text(vjust = 1, hjust=-1),
axis.text.x = element_text(vjust = -1, hjust=0),
legend.title = element_blank(),
legend.position = "bottom",
legend.key.width = unit(1.5, "cm"),
plot.caption = element_text(family = "Abel",vjust = -1, hjust = 0,colour="#4D4B55", size= 30),
text = element_text(family = "Abel", color = "#4D4B55",size = 35),
plot.margin = margin(1,1,1.5,1.2, "cm"))
ggsave("./test.png", width = 21, height = 15, dpi = 300)
PS: Not sharing the data itself because I guess that's not where the problem is.
Thanks!
Your text is misaligned because of your axis.text.y argument. Change hjust to 1 and it will be properly aligned. I have provided a minimal reproducible example below.
library(tidyverse)
Month <- rep(x = month.abb, times = 10)
Value <- sample(x = 10:120, size = 120, replace = TRUE)
Name <- sample(x = LETTERS[1:4], size = 120, replace = TRUE)
data <- data.frame(Month, Value, Name)
ggplot(data, aes(x = Month, y = Value, color = Name, group = Name, fill = Name)) +
geom_line(size = 1) + geom_point(size = 2) +
theme(axis.text.y = element_text(vjust = 1, hjust = 1)) # <- problem here
I'm making a plot with facets where the length of facet titles vary quite a bit. I am trying to left-align the facet/strip title with hjust, but it seems like hjust adjust differently depending on length of each facet title. Ideally, I would like to align each facet title with the 0 on the axis.
library(ggplot2)
data <- data.frame(q = c(rep("q1", 16), rep("question mucher longer and longer and longer", 16)),
cat = c(rep(paste0("cat", 1:4), times = 8)),
p = rep(25, 32),
group = c(rep(paste0("group", 1:4), each = 4),
c(rep(paste0("group", 1:4), each = 4))))
ggplot(data = data,
aes(x = group, y = p, fill = cat, label = p)) +
geom_bar(stat="identity", position = position_stack(), width=0.6) +
facet_grid(col = vars(q)) +
coord_flip() +
geom_text(position = position_stack(vjust = 0.5), size = 3.5, color= "black") +
xlab("") +
ylab("") +
theme_minimal(base_size=12) +
theme(
legend.position="bottom",
panel.grid.major.y = element_blank(),
panel.grid.major.x = element_line( size=.1, color="gray"),
panel.grid.minor.x = element_line( size=.1, color="gray"),
strip.text = element_text(face="bold", hjust=0.03)) +
guides(fill = guide_legend(reverse=TRUE)) +
scale_y_continuous(labels=c("0","25","50","75","100 %")) +
geom_hline(yintercept = 0, color = "gray23") +
geom_hline(yintercept = 100, color = "gray23") +
theme(legend.title=element_blank(),
legend.margin=margin(0,0,0,0),
legend.box.margin=margin(-10,0,0,0))
The issue is the expansion of the y scale. Hence, the strip text box expands over the 0 line. To fix your issue use hjust=0 for the strip box text and remove the default expansion on the left (or bottom in your case) of the y scale. To show this clearer I added a red box around the strip text boxes:
library(ggplot2)
ggplot(
data = data,
aes(x = group, y = p, fill = cat, label = p)
) +
geom_bar(stat = "identity", position = position_stack(), width = 0.6) +
facet_grid(col = vars(q)) +
coord_flip() +
geom_text(position = position_stack(vjust = 0.5), size = 3.5, color = "black") +
xlab("") +
ylab("") +
theme_minimal(base_size = 12) +
theme(
legend.position = "bottom",
panel.grid.major.y = element_blank(),
panel.grid.major.x = element_line(size = .1, color = "gray"),
panel.grid.minor.x = element_line(size = .1, color = "gray"),
strip.text = element_text(face = "bold", hjust = 0, margin = margin(0, 0, 0, 0, "pt")),
strip.background.x = element_rect(color = "red")
) +
guides(fill = guide_legend(reverse = TRUE)) +
scale_y_continuous(labels = c("0", "25", "50", "75", "100 %"), expand = c(0, 0, .05, 0)) +
geom_hline(yintercept = 0, color = "gray23") +
geom_hline(yintercept = 100, color = "gray23") +
theme(
legend.title = element_blank(),
legend.margin = margin(0, 0, 0, 0),
legend.box.margin = margin(-10, 0, 0, 0)
)
I have created a ggplot graph with three lines. Each line represents a different column in a data frame and colored in a different color. For some reason, the colors in the final graph are not coordinated to the code.
The data frame:
Scenario 1 Scenario 2 Scenario 3 Years
0.0260 0.0340 0.0366 1
0.0424 0.0562 0.0696 2
0.0638 0.0878 0.1150 3
0.0848 0.1280 0.1578 4
0.1096 0.1680 0.2074 5
0.1336 0.2106 0.2568 6
This is the code:
ggplot(ext2, aes(x = Years))+
geom_line(aes(y = `Scenario 1`, color = "darkblue"))+
geom_line(aes(y = `Scenario 2`, color = "darkred"))+
geom_line(aes(y = `Scenario 3`, color = "darkgreen"))+
xlab("Years")+
ylab("Quasi - extinction probability")+
ggtitle("2 mature individuals")+
geom_segment(aes(x = 45,y = 0.5, xend = 45, yend = 1.1),linetype = "longdash")+
geom_segment(aes(x = 75,y = 0.2, xend = 75, yend = 0.5),linetype = "longdash")+
geom_segment(aes(x = 0,y = 0.5, xend = 100, yend = 0.5),linetype = "longdash")+
geom_segment(aes(x = 0,y = 0.2, xend = 100, yend = 0.2),linetype = "longdash")+
geom_text(x = 20, y = 0.80, label = "CE")+
geom_text(x = 40, y = 0.35, label = "EN")+
scale_colour_manual(values = c("darkblue", "darkred","darkgreen"), labels = c("Scenario 1","Scenario 2","Scenario 3"))+
theme(legend.title = element_blank())+
theme_minimal()
and this is the graph:
Click here to see graph
The problem is that what I defined as 'scenario 3' in the code is actually a representation of 'scenario 2' in the data frame. You can see it according to the values under scenario 2 in the data frame.
For ggplot, the data needs to be in long format before you plot. Then, you can make "Scenarios" (i.e., name) the group, so that you can manually color the individual lines (i.e., with scale_colour_manual).
library(tidyverse)
ext_long <- ext2 %>%
pivot_longer(!Years)
ggplot(ext_long, aes(x = Years, color = name)) +
geom_line(aes(y = value)) +
xlab("Years") +
ylab("Quasi - extinction probability") +
ggtitle("2 mature individuals") +
geom_segment(aes(
x = 45,
y = 0.5,
xend = 45,
yend = 1.1
), linetype = "longdash") +
geom_segment(aes(
x = 75,
y = 0.2,
xend = 75,
yend = 0.5
), linetype = "longdash") +
geom_segment(aes(
x = 0,
y = 0.5,
xend = 100,
yend = 0.5
), linetype = "longdash") +
geom_segment(aes(
x = 0,
y = 0.2,
xend = 100,
yend = 0.2
), linetype = "longdash") +
geom_text(x = 20, y = 0.80, label = "CE") +
geom_text(x = 40, y = 0.35, label = "EN") +
scale_colour_manual(
values = c("darkblue", "darkred", "darkgreen"),
labels = c("Scenario 1", "Scenario 2", "Scenario 3")
) +
theme(legend.title = element_blank()) +
theme_minimal()
Output (only have a small part of the data, which is the reason the lines do not extend across the graph)
Data
ext2 <- structure(
list(
Scenario.1 = c(0.026, 0.0424, 0.0638, 0.0848,
0.1096, 0.1336),
Scenario.2 = c(0.034, 0.0562, 0.0878, 0.128,
0.168, 0.2106),
Scenario.3 = c(0.0366, 0.0696, 0.115, 0.1578,
0.2074, 0.2568),
Years = 1:6
),
class = "data.frame",
row.names = c(NA,-6L)
)
I need to produce a high resolution (1200dpi) image for a journal. However, using cowplot::draw_plot to overlay some insets seems to lower the resolution of the basemap (see resolution of "basemap_test.pdf" vs "cowplot_test.pdf"). There is a similar question here:
The draw_image() function from cowplot results in blurred pdfs
but that one is to do with bringing in outside images; this seems more straightforward, working with a ggplot object in the R environment. Is there a way I can stop the basemap blurring?
snip from basemap pdf
snip from ggdraw pdf
Sorry for the length of the reprex - wanted it as close as possible to my plot
if (!require(pacman)) install.packages('pacman')
library(pacman)
pacman::p_load(tidyverse,cowplot,raster,sf,maptools,fasterize)
eckIV = st_crs("ESRI:54012")
data("wrld_simpl")
wrld = st_as_sf(wrld_simpl) %>%
st_transform(eckIV)
#inset a
a_lims <- c(-9266960,-7503720,4725508,5796774)
a_sf <- st_bbox(extent(a_lims)) %>% st_as_sfc %>% st_sf
#inset b
b_lims <- c(-5203519,-3440279,-3705917,-2634651)
b_sf <- st_bbox(extent(b_lims)) %>% st_as_sfc %>% st_sf
#inset c
c_lims <- c(-43965.2,1719274.8,5759670.1,6830936.1)
c_sf <- st_bbox(extent(c_lims)) %>% st_as_sfc %>% st_sf
#inset d
d_lims <- c(9213988,10977228,3481996,4553262)
d_sf <- st_bbox(extent(d_lims)) %>% st_as_sfc %>% st_sf
insetBoxes <- rbind(a_sf,b_sf,c_sf,d_sf) %>%
st_set_crs(eckIV)
#dummy raster data
rst = raster(ext=extent(wrld),res=30000,crs=eckIV$proj4string)
values(rst) <- runif(n=ncell(rst),0,1)
rst = mask(rst,fasterize(wrld,rst))
rst_df = as.data.frame(rst, xy=TRUE)
#basemap
map <- ggplot() +
geom_sf(data=wrld, col=NA) +
geom_raster(data = rst_df, aes(fill = layer, x = x, y = y)) +
geom_sf(data=insetBoxes, fill=NA, size=0.5) +
scale_fill_gradientn(colours=terrain.colors(100),na.value = "transparent") +
theme_void() +
theme(legend.position = "none")
#insets
theme_inset <- theme_void() +
theme(legend.position="none",
panel.border = element_rect(colour = "black", fill = NA))
inset1 <- ggplot() +
geom_sf(data=wrld, col=NA) +
geom_raster(data = rst_df, aes(fill = layer, x = x, y = y)) +
scale_fill_gradientn(colours=terrain.colors(100),na.value = "transparent") +
geom_sf(data=wrld, fill=NA, size=0.1) +
theme_inset +
coord_sf(xlim = c(c_lims[[1]], c_lims[[2]]),
ylim = c(c_lims[[3]], c_lims[[4]]),
expand = FALSE)
inset2 <- ggplot() +
geom_sf(data=wrld, col=NA) +
geom_raster(data = rst_df, aes(fill = layer, x = x, y = y)) +
scale_fill_gradientn(colours=terrain.colors(100),na.value = "transparent") +
geom_sf(data=wrld, fill=NA, size=0.1) +
theme_inset +
coord_sf(xlim = c(d_lims[[1]], d_lims[[2]]),
ylim = c(d_lims[[3]], d_lims[[4]]),
expand = FALSE)
inset3 <- ggplot() +
geom_sf(data=wrld, col=NA) +
geom_raster(data = rst_df, aes(fill = layer, x = x, y = y)) +
scale_fill_gradientn(colours=terrain.colors(100),na.value = "transparent") +
geom_sf(data=wrld, fill=NA, size=0.1) +
theme_inset +
coord_sf(xlim = c(a_lims[[1]], a_lims[[2]]),
ylim = c(a_lims[[3]], a_lims[[4]]),
expand = FALSE)
inset4 <- ggplot() +
geom_sf(data=wrld, col=NA) +
geom_raster(data = rst_df, aes(fill = layer, x = x, y = y)) +
scale_fill_gradientn(colours=terrain.colors(100),na.value = "transparent") +
geom_sf(data=wrld, fill=NA, size=0.1) +
theme_inset +
coord_sf(xlim = c(b_lims[[1]], b_lims[[2]]),
ylim = c(b_lims[[3]], b_lims[[4]]),
expand = FALSE)
#combine
world_map = map %>%
cowplot::ggdraw() +
cowplot::draw_plot(inset1 + theme(plot.background = element_rect(fill = "white", colour = NA)),
width = 0.25,
height = 0.25,
x = 0.75,
y = 0.7) +
cowplot::draw_plot(inset2 + theme(plot.background = element_rect(fill = "white", colour = NA)),
width = 0.25,
height = 0.25,
x = 0.75,
y = 0.4) +
cowplot::draw_plot(inset3 + theme(plot.background = element_rect(fill = "white", colour = NA)),
width = 0.25,
height = 0.25,
x = 0,
y = 0.7) +
cowplot::draw_plot(inset4 + theme(plot.background = element_rect(fill = "white", colour = NA)),
width = 0.25,
height = 0.25,
x = 0,
y = 0.4)
rtn.plot = cowplot::plot_grid(world_map,world_map,ncol=1, labels = letters[1:2])
ggsave(plot=rtn.plot,
filename="cowplot_test.pdf",
width=22,height=18,unit="cm",device="pdf", dpi=1200)
ggsave(plot=map,
filename="basemap_test.pdf",
width=22,height=18,unit="cm",device="pdf", dpi=1200)
I am trying to create a Kaplan-Meier plot with 95% confidence bands plus having the censored data in a table beneath it. I can create the plot, but not the table. I get the error message: Error in grid.draw(both) : object 'both' not found.
library(survival)
library(ggplot2)
library(GGally)
library(gtable)
data(lung)
sf.sex <- survfit(Surv(time, status) ~ sex, data = lung)
pl.sex <- ggsurv(sf.sex) +
geom_ribbon(aes(ymin=low,ymax=up,fill=group),alpha=0.3) +
guides(fill=guide_legend("sex"))
pl.sex
tbl <- ggplot(df_nums, aes(x = Time, y = factor(variable), colour = variable,+
label=value)) +
geom_text() +
theme_bw() +
theme(panel.grid.major = element_blank(),+
legend.position = "none",+
plot.background = element_blank(), +
panel.grid.major = element_blank(),+
panel.grid.minor = element_blank(),+
panel.border = element_blank(),+
legend.position="none",+
axis.line = element_blank(),+
axis.text.x = element_blank(),+
axis.text.y = element_text(size=15, face="bold", color = 'black'),+
axis.ticks=element_blank(),+
axis.title.x = element_blank(),+
axis.title.y = element_blank(),+
plot.title = element_blank()) +
scale_y_discrete(breaks=c("Group.A", "Group.B"), labels=c("Group A", "Group B"))
both = rbind(ggplotGrob(g), ggplotGrob(tbl), size="last")
panels <- both$layout$t[grep("panel", both$layout$name)]
both$heights[panels] <- list(unit(1,"null"), unit(2, "lines"))
both <- gtable_add_rows(both, heights = unit(1,"line"), 8)
both <- gtable_add_grob(both, textGrob("Number at risk", hjust=0, x=0), t=9, l=2, r=4)
grid.newpage()
grid.draw(both)
I solved the problem by using the Rcmdrplugin KMggplot2 The code is generated by the plugin after selecting the data and variables.
library(survival, pos=18)
data(lung, package="survival")
lung <- within(lung, {
sex <- factor(sex, labels=c('male','female'))
})
ggthemes_data <- ggthemes::ggthemes_data
require("ggplot2")
.df <- na.omit(data.frame(x = lung$time, y = lung$status, z = lung$sex))
.df <- .df[do.call(order, .df[, c("z", "x"), drop = FALSE]), , drop = FALSE]
.fit <- survival::survfit(survival::Surv(time = x, event = y, type = "right") ~ z,
.df)
.pval <- plyr::ddply(.df, plyr::.(),
function(x) {
data.frame(
x = 0, y = 0, df = 1,
chisq = survival::survdiff(
survival::Surv(time = x, event = y, type = "right") ~ z, x
)$chisq
)})
.pval$label <- paste0(
"paste(italic(p), \" = ",
signif(1 - pchisq(.pval$chisq, .pval$df), 3),
"\")"
)
.fit <- data.frame(x = .fit$time, y = .fit$surv, nrisk = .fit$n.risk, nevent =
.fit$n.event, ncensor= .fit$n.censor, upper = .fit$upper, lower = .fit$lower)
.df <- .df[!duplicated(.df[,c("x", "z")]), ]
.df <- .fit <- data.frame(.fit, .df[, c("z"), drop = FALSE])
.med <- plyr::ddply(.fit, plyr::.(z), function(x) {
data.frame(
median = min(subset(x, y < (0.5 + .Machine$double.eps^0.5))$x)
)})
.df <- .fit <- rbind(unique(data.frame(x = 0, y = 1, nrisk = NA, nevent = NA,
ncensor = NA, upper = 1, lower = 1, .df[, c("z"), drop = FALSE])), .fit)
.cens <- subset(.fit, ncensor == 1)
.tmp1 <- data.frame(as.table(by(.df, .df[, c("z"), drop = FALSE], function(d)
max(d$nrisk, na.rm = TRUE))))
.tmp1$x <- 0
.nrisk <- .tmp1
for (i in 1:9) {.df <- subset(.fit, x < 100 * i); .tmp2 <-
data.frame(as.table(by(.df, .df[, c("z"), drop = FALSE], function(d) if
(all(is.na(d$nrisk))) NA else min(d$nrisk - d$nevent - d$ncensor, na.rm = TRUE))));
.tmp2$x <- 100 * i; .tmp2$Freq[is.na(.tmp2$Freq)] <- .tmp1$Freq[is.na(.tmp2$Freq)];
.tmp1 <- .tmp2; .nrisk <- rbind(.nrisk, .tmp2)}
.nrisk$y <- rep(seq(0.075, 0.025, -0.05), 10)
.plot <- ggplot(data = .fit, aes(x = x, y = y, colour = z)) +
RcmdrPlugin.KMggplot2::geom_stepribbon(data = .fit, aes(x = x, ymin = lower, ymax =
upper, fill = z), alpha = 0.25, colour = "transparent", show.legend = FALSE, kmplot
= TRUE) + geom_step(size = 1.5) +
geom_linerange(data = .cens, aes(x = x, ymin = y,
ymax = y + 0.02), size = 1.5) +
geom_text(data = .pval, aes(y = y, x = x, label =
label), colour = "black", hjust = 0, vjust = -0.5, parse = TRUE, show.legend =
FALSE, size = 14 * 0.282, family = "sans") +
geom_vline(data = .med, aes(xintercept
= median), colour = "black", lty = 2) + scale_x_continuous(breaks = seq(0, 900, by
= 100), limits = c(0, 900)) +
scale_y_continuous(limits = c(0, 1), expand = c(0.01,0)) + scale_colour_brewer(palette = "Set1") + scale_fill_brewer(palette = "Set1") +
xlab("Time from entry") + ylab("Proportion of survival") + labs(colour = "sex") +
ggthemes::theme_calc(base_size = 14, base_family = "sans") + theme(legend.position
= c(1, 1), legend.justification = c(1, 1))
.nrisk$y <- ((.nrisk$y - 0.025) / (max(.nrisk$y) - 0.025) + 0.5) * 0.5
.plot2 <- ggplot(data = .nrisk, aes(x = x, y = y, label = Freq, colour = z)) +
geom_text(size = 14 * 0.282, family = "sans") + scale_x_continuous(breaks = seq(0,900, by = 100), limits = c(0, 900)) +
scale_y_continuous(limits = c(0, 1)) +
scale_colour_brewer(palette = "Set1") + ylab("Proportion of survival") +
RcmdrPlugin.KMggplot2::theme_natrisk(ggthemes::theme_calc, 14, "sans")
.plot3 <- ggplot(data = subset(.nrisk, x == 0), aes(x = x, y = y, label = z, colour = z)) +
geom_text(hjust = 0, size = 14 * 0.282, family = "sans") +
scale_x_continuous(limits = c(-5, 5)) + scale_y_continuous(limits = c(0, 1)) +
scale_colour_brewer(palette = "Set1") +
RcmdrPlugin.KMggplot2::theme_natrisk21(ggthemes::theme_calc, 14, "sans")
.plotb <- ggplot(.df, aes(x = x, y = y)) + geom_blank() +
RcmdrPlugin.KMggplot2::theme_natriskbg(ggthemes::theme_calc, 14, "sans")
grid::grid.newpage(); grid::pushViewport(grid::viewport(layout =
grid::grid.layout(2, 2, heights = unit(c(1, 3), c("null", "lines")), widths =
unit(c(4, 1), c("lines", "null")))));
print(.plotb, vp =
grid::viewport(layout.pos.row = 1:2, layout.pos.col = 1:2));
print(.plot , vp =
grid::viewport(layout.pos.row = 1 , layout.pos.col = 1:2));
print(.plot2, vp =
grid::viewport(layout.pos.row = 2 , layout.pos.col = 1:2));
print(.plot3, vp =
grid::viewport(layout.pos.row = 2 , layout.pos.col = 1 ));
.plot <- recordPlot()
print(.plot)
Here's a start (code below)
I guess you can create the table need and replace it by the random.table
# install.packages("ggplot2", dependencies = TRUE)
# install.packages("RGraphics", dependencies = TRUE)
# install.packages("gridExtra", dependencies = TRUE)
# install.packages("survival", dependencies = TRUE)
require(ggplot2)
library(RGraphics)
library(gridExtra)
library(survival)
# Plot
data(lung)
sf.sex <- survfit(Surv(time, status) ~ sex, data = lung)
pl.sex <- ggsurv(sf.sex) +
geom_ribbon(aes(ymin=low,ymax=up,fill=group),alpha=0.3) +
guides(fill=guide_legend("sex"))
# Table
random.table <- data.frame("CL 95"=rnorm(5),n=runif(5,1,3))
pl.table <- tableGrob(random.table)
# Arrange the plots on the same page
grid.arrange(pl.sex, pl.table, ncol=1)