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script_plots_category_NEW.r
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script_plots_category_NEW.r
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library("ggplot2")
options(stringsAsFactors=FALSE)
library(gtable)
library(grid)
library(gridExtra)
library(egg)
# adjust_feature_name
adjust_feature_name <- function(label_string) {
var <- gsub("\\.", " ", label_string)
var <- gsub("PLT", "(PLT)", var)
var <- gsub("CRP", "(CRP)", var)
var <- gsub("WBC", "(WBC)", var)
var <- gsub("pH", "(pH)", var)
var <- gsub("type of MM", "type of malignant mesothelioma", var)
var <- gsub("C reactive", "C-reactive", var)
var <- gsub(" ", " ", var)
var <- gsub("Lung side", "lung side", var)
return(var)
}
fileName <- "../data/MesotheliomaDataSet_DicleUniversity_updated_names.csv"
mesothelioma_datatable <- read.csv(fileName, header = TRUE, sep =",");
sick_patients_table <- (mesothelioma_datatable[mesothelioma_datatable$class.of.diagnosis==1,])
healthy_patients_table <- (mesothelioma_datatable[mesothelioma_datatable$class.of.diagnosis==0,])
random_number <- sample(1:1000000, 1)
cate_vector <- c(grep("city", colnames(mesothelioma_datatable)), grep("gender", colnames(mesothelioma_datatable)), grep("habit.of.cigarette", colnames(mesothelioma_datatable)), grep("Lung.side", colnames(mesothelioma_datatable)), grep("performance.status", colnames(mesothelioma_datatable)), grep("type.of.MM", colnames(mesothelioma_datatable)))
lun <- length(cate_vector)
fontSize = 10
# Sick patients
require(gridExtra)
outputPdfFileName <- paste("../results/CATEGORY_barplots_sick_patients_vs_", random_number, ".pdf", sep="")
pdf(outputPdfFileName, onefile=FALSE)
i=1
sick_plot_list <- list()
for(index in cate_vector){
temp_df = sick_patients_table
temp_df$CurrentFeature = sick_patients_table[, index]
P_this <- NULL
P_this <- ggplot(temp_df, aes(factor(" "), fill=factor(CurrentFeature))) + geom_bar(stat="count", position="stack") + ylim(0,dim(sick_patients_table)[1]) + labs(x=" ", y=adjust_feature_name(colnames(sick_patients_table[index]))) + theme(axis.text=element_text(size=fontSize), axis.title=element_text(size=fontSize), legend.text=element_text(size=fontSize), legend.title=element_text(size=fontSize), legend.key.size=unit(0.3, "cm")) + coord_flip() + theme(legend.title=element_blank())
if (index == grep("habit.of.cigarette", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("non", "rare", "regular", "frequent"))
}
if (index == grep("gender", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("women", "men"))
}
if (index == grep("performance.status", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("able", "unable"))
}
if (index == grep("Lung.side", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("left", "right", "both"))
}
if (index == grep("type.of.MM", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("T1", "T2/T3", "T4"))
}
sick_plot_list[[length(sick_plot_list) + 1]] <- P_this
i <- i+1
}
# sick_plot_list[[1]] <- sick_plot_list[[1]] + ggtitle("mesothelioma patients: boolean features") + theme(plot.title = element_text(size = fontSize+1, hjust = 0.5))
do.call("ggarrange", c(sick_plot_list, ncol=1))
#grid.arrange(sick_plot_list)
dev.off()
# Healthy patients
require(gridExtra)
outputPdfFileName <- paste("../results/CATEGORY_barplots_healthy_patients_vsy_", random_number, ".pdf", sep="")
pdf(outputPdfFileName, onefile=FALSE)
i=1
healthy_plot_list <- list()
for(index in cate_vector){
temp_df = healthy_patients_table
temp_df$CurrentFeature = healthy_patients_table[, index]
P_this <- NULL
P_this <- ggplot(temp_df, aes(factor(" "), fill=factor(CurrentFeature))) + geom_bar(stat="count", position="stack") + ylim(0,dim(healthy_patients_table)[1]) + labs(x=" ", y=adjust_feature_name(colnames(healthy_patients_table[index]))) + theme(axis.text=element_text(size=fontSize), axis.title=element_text(size=fontSize), legend.text=element_text(size=fontSize), legend.title=element_text(size=fontSize), legend.key.size=unit(0.3, "cm")) + coord_flip() + theme(legend.title=element_blank())
if (index == grep("habit.of.cigarette", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("non", "rare", "regular", "frequent"))
}
if (index == grep("gender", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("women", "men"))
}
if (index == grep("performance.status", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("able", "unable"))
}
if (index == grep("Lung.side", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("left", "right", "both"))
}
if (index == grep("type.of.MM", colnames(mesothelioma_datatable))) {
P_this <- P_this + scale_fill_discrete(labels=c("T1", "T2/T3", "T4"))
}
P_this$width = 20
healthy_plot_list[[length(healthy_plot_list) + 1]] <- P_this
i <- i+1
}
# healthy_plot_list[[1]] <- healthy_plot_list[[1]] + ggtitle("non-mesothelioma patients: boolean features") + theme(plot.title = element_text(size = fontSize+1, hjust = 0.5))
do.call("ggarrange", c(healthy_plot_list, ncol=1))
#grid.arrange(sick_plot_list)
dev.off()