# Load required packages
packages <- c("ggplot2", "tidyverse", "dplyr", "ggpubr", "see")
lapply(packages, function(x) if (!require(x, character.only = TRUE)) install.packages(x))
## Loading required package: ggplot2
## Loading required package: tidyverse
## Warning: package 'lubridate' was built under R version 4.3.3
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ lubridate 1.9.4 ✔ tibble 3.2.1
## ✔ purrr 1.0.2 ✔ tidyr 1.3.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
## Loading required package: ggpubr
##
## Loading required package: see
## Warning: package 'see' was built under R version 4.3.3
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library(ggplot2)
library(tidyverse)
library(dplyr)
library(ggpubr)
library(see)
CAM<-read.csv("Violin_Plot_Data.csv")
## Warning in read.table(file = file, header = header, sep = sep, quote = quote, :
## incomplete final line found by readTableHeader on 'Violin_Plot_Data.csv'
print(CAM)
## F1Performance Repeat1 Repeat2 Repeat3 Repeat4 Repeat5 Repeat6
## 1 SVMWithGradCAMMaps 0.670051 0.701571 0.680628 0.710660 0.648649 0.715686
## 2 SVMWithDeepShapMaps 0.673913 0.610390 0.630872 0.618357 0.662577 0.608696
## Repeat7 Repeat8 Repeat9 Repeat10 Repeat11 Repeat12 Repeat13 Repeat14
## 1 0.713568 0.684932 0.699029 0.687500 0.720812 0.716418 0.666667 0.683417
## 2 0.623529 0.642857 0.607477 0.645833 0.631579 0.660099 0.662420 0.610778
## Repeat15 Repeat16 Repeat17 Repeat18 Repeat19 Repeat20
## 1 0.666667 0.663317 0.691943 0.680412 0.686869 0.686551
## 2 0.701754 0.659091 0.577540 0.666667 0.678571 0.596685
head(CAM)
## F1Performance Repeat1 Repeat2 Repeat3 Repeat4 Repeat5 Repeat6
## 1 SVMWithGradCAMMaps 0.670051 0.701571 0.680628 0.710660 0.648649 0.715686
## 2 SVMWithDeepShapMaps 0.673913 0.610390 0.630872 0.618357 0.662577 0.608696
## Repeat7 Repeat8 Repeat9 Repeat10 Repeat11 Repeat12 Repeat13 Repeat14
## 1 0.713568 0.684932 0.699029 0.687500 0.720812 0.716418 0.666667 0.683417
## 2 0.623529 0.642857 0.607477 0.645833 0.631579 0.660099 0.662420 0.610778
## Repeat15 Repeat16 Repeat17 Repeat18 Repeat19 Repeat20
## 1 0.666667 0.663317 0.691943 0.680412 0.686869 0.686551
## 2 0.701754 0.659091 0.577540 0.666667 0.678571 0.596685
data_long <- CAM %>%
pivot_longer(
cols = starts_with("Repeat"),
names_to = "Repeat",
values_to = "values")
head(data_long)
## # A tibble: 6 × 3
## F1Performance Repeat values
## <chr> <chr> <dbl>
## 1 SVMWithGradCAMMaps Repeat1 0.670
## 2 SVMWithGradCAMMaps Repeat2 0.702
## 3 SVMWithGradCAMMaps Repeat3 0.681
## 4 SVMWithGradCAMMaps Repeat4 0.711
## 5 SVMWithGradCAMMaps Repeat5 0.649
## 6 SVMWithGradCAMMaps Repeat6 0.716
#Full violins
ggplot(data_long, aes(x = F1Performance, y = values, fill = F1Performance)) +
geom_jitter(
position = position_jitter(0.1),
aes(color = F1Performance),
size = 6,
alpha = 0.8
) +
geom_violin(
size = 2,
alpha = 0.5,
draw_quantiles = c(0.25, 0.5, 0.75),
quantile.size = 2
) +
coord_flip() +
scale_fill_manual(values = c("magenta4", "darkorange2")) +
scale_color_manual(values = c("magenta4", "darkorange2")) +
stat_summary(
fun = median,
geom = "point",
shape = 21,
size = 3,
fill = "white",
color = "black",
stroke = 1.5
) +
scale_y_continuous(
limits = c(min(data_long$values), max(data_long$values)),
breaks = seq(min(data_long$values), max(data_long$values), by = 0.02),
labels = scales::number_format(accuracy = 0.02)
) +
theme_minimal() +
theme(
legend.title = element_text(face = "bold", size = 14),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank(),
axis.line.x = element_line(size = 2, color = "black"),
plot.title = element_text(hjust = 0.5, face = "bold"),
panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "grey", linetype = "dashed", size = 1.5),
legend.position = "none"
) +
geom_text(
aes(x = "SVMWithGradCAMMaps", label = "SVM + GRAD-CAM++", y = 0.64),
vjust = -4.5,
color = "darkorange2",
size = 4.5
) +
geom_text(
aes(x = "SVMWithDeepShapMaps", y = 0.6, label = "SVM + Deep SHAP"),
vjust = -3.5,
color = "magenta4",
size = 4.5
) +
ylab("F1") +
ggtitle("Fig.7. Grad-CAM++ saliency maps capture unique predictive information.")
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning in geom_violin(size = 2, alpha = 0.5, draw_quantiles = c(0.25, 0.5, :
## Ignoring unknown parameters: `quantile.size`
## Warning: The `size` argument of `element_line()` is deprecated as of ggplot2 3.4.0.
## ℹ Please use the `linewidth` argument instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_point()`).
#Half Violins
ggplot(data_long, aes(x = F1Performance, y = values, fill = F1Performance)) +
geom_jitter(
position = position_jitter(0.1),
aes(color = F1Performance),
size = 6,
alpha = 0.8
) +
geom_violinhalf(
size = 2,
alpha = 0.5,
draw_quantiles = c(0.25, 0.5, 0.75),
quantile.size = 2
) +
coord_flip() +
scale_fill_manual(values = c("magenta4", "darkorange2")) +
scale_color_manual(values = c("magenta4", "darkorange2")) +
stat_summary(
fun = median,
geom = "point",
shape = 21,
size = 3,
fill = "white",
color = "black",
stroke = 1.5
) +
scale_y_continuous(
limits = c(min(data_long$values), max(data_long$values)),
breaks = seq(min(data_long$values), max(data_long$values), by = 0.02),
labels = scales::number_format(accuracy = 0.02)
) +
theme_minimal() +
theme(
legend.title = element_text(face = "bold", size = 14),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank(),
axis.line.x = element_line(size = 2, color = "black"),
plot.title = element_text(hjust = 0.5, face = "bold"),
panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "grey", linetype = "dashed", size = 1.5),
legend.position = "none"
) +
geom_text(
aes(
x = "SVMWithGradCAMMaps",
label = "SVM + GRAD-CAM++",
y = 0.64
),
vjust = -4.5,
color = "darkorange2",
size = 4.5
) +
geom_text(
aes(
x = "SVMWithDeepShapMaps",
y = 0.6,
label = "SVM + Deep SHAP"
),
vjust = -3.5,
color = "magenta4",
size = 4.5
) +
ylab("F1") +
ggtitle("Fig. 7. Grad-CAM++ saliency maps capture unique predictive information.")
## Warning in geom_violinhalf(size = 2, alpha = 0.5, draw_quantiles = c(0.25, : Ignoring unknown parameters: `size`, `draw_quantiles`, and `quantile.size`
## Removed 1 row containing missing values or values outside the scale range
## (`geom_point()`).
#Box and Violin
ggplot(data_long, aes(x = F1Performance, y = values, fill = F1Performance)) +
geom_jitter(
position = position_jitter(0.1),
aes(color = F1Performance),
size = 6,
alpha = 0.8
) +
geom_violinhalf(
size = 2,
alpha = 0.5,
draw_quantiles = c(0.25, 0.5, 0.75),
quantile.size = 2
) +
geom_boxplot(
aes(color = F1Performance),
width = 0.4,
alpha = 0.3,
outlier.shape = NA
) +
coord_flip() +
scale_fill_manual(values = c("magenta4", "darkorange2")) +
scale_color_manual(values = c("magenta4", "darkorange2")) +
stat_summary(
fun = median,
geom = "point",
shape = 21,
size = 3,
fill = "white",
color = "black",
stroke = 1.5
) +
scale_y_continuous(
limits = c(min(data_long$values), max(data_long$values)),
breaks = seq(min(data_long$values), max(data_long$values), by = 0.02),
labels = scales::number_format(accuracy = 0.02)
) +
theme_minimal() +
theme(
legend.title = element_text(face = "bold", size = 14),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
axis.title.y = element_blank(),
axis.line.x = element_line(size = 2, color = "black"),
plot.title = element_text(hjust = 0.5, face = "bold"),
panel.grid.major.y = element_blank(),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_line(color = "grey", linetype = "dashed", size = 1.5),
legend.position = "none"
) +
geom_text(
aes(x = "SVMWithGradCAMMaps", label = "SVM + GRAD-CAM++", y = 0.64),
vjust = -4.5,
color = "darkorange2",
size = 4.5
) +
geom_text(
aes(x = "SVMWithDeepShapMaps", y = 0.6, label = "SVM + Deep SHAP"),
vjust = -3.5,
color = "magenta4",
size = 4.5
) +
ylab("F1") +
ggtitle("Fig.7. Grad-CAM++ saliency maps capture unique predictive information.")
## Warning in geom_violinhalf(size = 2, alpha = 0.5, draw_quantiles = c(0.25, : Ignoring unknown parameters: `size`, `draw_quantiles`, and `quantile.size`
## Removed 1 row containing missing values or values outside the scale range
## (`geom_point()`).
