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#!/usr/bin/env Rscript
# Parse arguments (filename, column number, min, max, bins)
args <- commandArgs(trailingOnly = TRUE)
filename <- args[1]
# start_row <- as.numeric(args[2])
start_row <- 2
col_num <- as.numeric(args[2])
# Optional min and max values (positions 3 and 4)
user_min <- ifelse(length(args) >= 3, as.numeric(args[3]), NA)
user_max <- ifelse(length(args) >= 4, as.numeric(args[4]), NA)
# Number of bins now at the end (position 5)
num_bins <- ifelse(length(args) >= 5, as.numeric(args[5]), 20) # Default to 20 bins if not specified
# Read the CSV file (assuming it has a header)
data <- read.csv(filename, header = TRUE)
# Extract the data
plot_data <- data[start_row:nrow(data), col_num]
# Convert to numeric
plot_data <- as.numeric(as.character(plot_data))
plot_data <- plot_data[!is.na(plot_data)]
# Determine range bounds
data_min <- min(plot_data)
data_max <- max(plot_data)
range_min <- ifelse(is.na(user_min), data_min, user_min)
range_max <- ifelse(is.na(user_max), data_max, user_max)
# Calculate percentage of samples within the range
count_in_range <- sum(plot_data >= range_min & plot_data <= range_max)
total_count <- length(plot_data)
percent_in_range <- (count_in_range / total_count) * 100
# Output to command line
cat(sprintf("%.2f%% of samples are within the range [%.2f, %.2f]\n",
percent_in_range, range_min, range_max))
# Set up graphics
windows(width = 8, height = 6)
# Create the histogram
hist(plot_data,
breaks = num_bins,
main = paste("Histogram of Column", col_num),
xlab = "Value",
col = "lightblue",
border = "black")
# Add vertical lines for min and max if provided by user
if(!is.na(user_min)) {
abline(v = user_min, col = "red", lwd = 2, lty = 2)
}
if(!is.na(user_max)) {
abline(v = user_max, col = "red", lwd = 2, lty = 2)
}
# Add basic statistics including standard deviation
stats_text <- paste0("n = ", length(plot_data), "\n",
"min = ", sprintf("%.2f", data_min), "\n",
"max = ", sprintf("%.2f", data_max), "\n",
"mean = ", sprintf("%.2f", mean(plot_data)), "\n",
"median = ", sprintf("%.2f", median(plot_data)), "\n",
"sd = ", sprintf("%.2f", sd(plot_data)), "\n",
sprintf("%.2f%% in [%.2f, %.2f]",
percent_in_range, range_min, range_max))
text_x <- par("usr")[1] + 0.05 * (par("usr")[2] - par("usr")[1])
text_y <- par("usr")[4] - 0.1 * (par("usr")[4] - par("usr")[3])
text(text_x, text_y, stats_text, adj = c(0, 1))
# Add text to instruct user
mtext("Close this window using the X button when done", side = 1, line = 4, col = "red")
# Tell user what to do
cat("Histogram displayed. Close the window manually when done viewing.\n")
cat("Usage: Rscript hist.r filename.csv column_number [min] [max] [bins]\n")
# Keep the script running until the window is closed
Sys.sleep(1000) # Keep script running for a long time
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