Every operation is a function call
Overview
questions
- How do I make a function？
- How can I test my functions?
- How should I document my code?
Objectives
- Define a function that takes arguments.
- Return a value from a funtion.
- Test a function.
- Set default values for function arguments.
- Explain why we should divide programs into small, single-purpose functions.
Define a Function
some learning
- a function that converts temperatures from Fahrenheit to Celsius
fahrenheit_to_celsius <- function(temp_F) {
temp_C <- (temp_F - 32) * 5 / 9
# return(temp_C)
temp_C
}
# boiling point of water
fahrenheit_to_celsius(212)
-
of course in R, it is not necessary to include return statement. R automatically returns whichever variable is on the last line of the body of the function.
-
some of practice:
best_practice <- c("Write", "programs", "for", "people", "not", "computers")
asterisk <- "***"
# R interprets a variable with a single value as a vector with one element.
highlight <- function(content, wrapper){
tempStr <- c(wrapper, content, wrapper)
# return(tempStr)
tempStr
}
highlight(best_practice, asterisk)
# write a function called edges that returns a vector made up of the first and last elements of its input
dry_principle <- c("Don't", "repeat", "yourself", "or", "others")
edges <- function(inputs){
return(c(inputs[1], inputs[length(inputs)]))
}
edges(dry_principle)
input_1 <- 20
mySum <- function(input_1, input_2 = 10) {
output <- input_1 + input_2
return(output)
}
mySum(input_1 = 1, 3)
# also can be 'mySum(1, 3)'
center <- function(data, midpoint) {
# return a new vector containing the original data centered around the
# midpoint.
# Example: center(c(1, 2, 3), 0) => c(-1, 0, 1)
new_data <- (data - mean(data)) + midpoint
return(new_data)
}
dat <- read.csv(file = "data/inflammation-01.csv", header = FALSE)
centered <- center(dat[, 4], 0)
head(centered)
min(dat[, 4])
mean(dat[, 4])
max(dat[, 4])
mean(centered)
max(centered)
sd(dat[, 4])
sd(centered)
analyze data by plot
analyze <- function(filename) {
# Plots the average, min, and max inflammation over time.
# Input is character string of a csv file.
dat <- read.csv(file = filename, header = FALSE)
avg_day_inflammation <- apply(dat, 2, mean)
plot(avg_day_inflammation)
max_day_inflammation <- apply(dat, 2, max)
plot(max_day_inflammation)
min_day_inflammation <- apply(dat, 2, min)
plot(min_day_inflammation)
}
analyze("data/inflammation-02.csv")
