Hailstone sequence: Difference between revisions
→Vectorization solution: Improved syntax.
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The previous solution is entirely satisfactory and may be more efficient than the following solution. However, problems like these are a great chance to show off the strength of R's vectorization. Also, this lets us show off how the <- syntax can do multiple variable assignments in one line. Observe how short the following code is:
<lang rsplus>###Task 1:
collatz <- function(n)
{
lastIndex <- 1
output <- lastEntry <- n
while(lastEntry != 1)
{
#Each branch updates lastEntry, lastIndex, and appends a new element to the end of output.
#Note that the return value of lastIndex <- lastIndex + 1 is lastIndex + 1.
#You may be surprised that output can be appended to despite starting as just a single number.
#If so, recall that R's numerics are vectors, meaning that output<-n created a vector of length 1.
#It's ugly, but efficient.
if(lastEntry %% 2
else
}
output
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###Task 2:
#Notice how easy it is to access the required elements:
twentySeven <- collatz(27)
cat("The first four elements are:", twentySeven[1:4], "and the last four are:", twentySeven[length(twentySeven) - 3:0], "\n")
###Task 3:
#Notice how a several line long loop can be avoided with R's sapply or Vectorize:
seqLenghts <- sapply(
longest <- which.max(seqLenghts)
#Equivalently, line 1 could have been: seqLenghts <- sapply(Vectorize(collatz)(1:99999), length).
#Another good option would be seqLenghts <- lengths(Vectorize(collatz)(1:99999)).</lang>
{{out}}
<pre>The first four elements are: 27 82 41 124 and the last four are: 8 4 2 1 ▼
▲The first four elements are: 27 82 41 124 and the last four are: 8 4 2 1
▲[1] "The longest sequence before the 100000th is found at n=77031. It has length 351."
=={{header|Racket}}==
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