`R`

Tip: use `seqi()`

for indexing.

`R`

‘s “`1:0`

trap” is a mal-feature that confuses newcomers and is a reliable source of bugs. This note will show how to use `seqi()`

to write more reliable code and document intent.

The issue is, contrary to expectations (formed in working with other programming languages) the sequence `1:0`

is not empty. It is instead a decreasing sequence. Data scientists typically work in many languages, so we should expect differences. However having a sequence builder that returns empty when the bounds cross is a common useful tool for controlling loops and other indexing tasks.

We have written about this before. The usual defense is that it is the same as `seq(1, 0)`

, but I see that more as a doubling-down than an argument. Also due to odd behavior when iterating over vectors or lists with class-attributes, we sometimes must introduce indices (as it isn’t always safe to directly iterate over contents in `R`

).

What this means is in `R`

there is no common safe, succinct way to write index vector or loops where one of the end-points is passed in as an argument. For example the following simple example is incorrect.

# sum reciprocals of squares of positive integers from 1 up to k # converges to pi^2/6 sum_sq_recip_k <- function(k) { sum(1/((1:k)^2)) } # should be zero, as the convention 1 up to -1 is the empty set sum_sq_recip_k(-1) # [1] Inf

There are plenty of ways to write reversed sequences (such as `rev(0:1)`

), so writing reversed sequences isn’t a great unmet need. Previously we recommended using `seq_len()`

as a solution. This is still good, however that only directly addressed upper-bound issues. For general ranges (where perhaps the lower-bound is the parameter) we still have a problem.

`Python`

is one of the most popular programming languages, and it supplies a convenient function for the common task of iterating over increasing ranges of integers.

# Python code [k for k in range(3, 5)] # Out[1]: [3, 4] [k for k in range(5, 3)] # Out[2]: []

Now of course different programming languages made different choices. However, in my opinion, writing possibly empty sequences parametrically is a common programming need and it is nice to have this be convenient.

Our current advice to `R`

users is use `wrapr::seqi()`

which stands for “sequence, increasing integer(s)”. We needed such a capability when translating `C++`

code to `R`

code for our `RcppDynProg`

example (otherwise we would have to put guards around the loops so they don’t activate on what should be empty sequences).

`seqi()`

is used as follows.

library("wrapr") # print 3, 4, and then 5 for(i in seqi(3, 5)) { print(i) } #> [1] 3 #> [1] 4 #> [1] 5 # empty for(i in seqi(5, 2)) { print(i) }

This is clear, safe, and documents intent. It is a non-negotiable fact that in `R`

`base::seq(1,0)`

is `[1, 0]`

. Well, `wrapr::seqi(1,0)`

is `[]`

.

Categories: Uncategorized

### jmount

Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.

Thought provoking for a novice like me.

But I think “It is a non-negotiable fact that in R base::seq(1,0) is [0, 1]” is a negotiable fact (or a typo).

In my version of R, base::seq(1,0) is [1, 0].

Typo on my part, I’ll fix it.