# Chapter 6. Lists

You can learn more about working with lists in Chapter 2 of Erlang Programming, Sections 2.10 and 3.5 of Programming Erlang, Section 2.2.5 of Erlang and OTP in Action, and Chapter 1 of Learn You Some Erlang For Great Good!.

## Étude 6-1: Recursive Iteration through a List

In a module named stats, write a function named minimum/1. It takes a list of numbers as its argument and returns the smallest value. This function already exists in the lists module (lists:min/1), but it’s a good exercise in learning about recursion.

Here’s the pseudocode for minimum/1.

• Split the list into the first number and the remainder of the list using the cons operator |.
• Call function minimum/2, which takes a list as its first argument and the "smallest number so far" (the current candidate) as its second argument. Use the remainder of the list (which you extracted in the previous step) as the first argument to minimum/2, and the first item in the list as the second argument.

Here’s the pseudocode for minimum/2.

• When the list passed to minimum/2 is empty, the final result is the current candidate. This stops the recursion.
• If the list passed to minimum/2 is not empty, then see if the head of the list is less than the current candidate.

• If so, call minimum/2 with the tail of the list as the first argument and the list head (the new "smallest number") as the second argument.
• If not, call minimum/2 with the tail of the list as the first argument and the current candidate (still the "smallest number") as the second argument.

Unlike most examples in Introducing Erlang, passing an empty list to this function will make it crash. That’s a reasonable thing to do, as an empty list can’t really be said to have a minimum value.

1> c(stats).
{ok,stats}
2> N = [4, 1, 7, -17, 8, 2, 5].
[4,1,7,-17,8,2,5]
3> stats:minimum(N).
-17
4> stats:minimum([]).
** exception error: no match of right hand side value []
     in function  stats:minimum/1 (stats.erl, line 15)
5> stats:minimum([52.46]).
52.46

See a suggested solution in Appendix A.

## Étude 6-2: Iteration through Lists (More Practice)

Add two more functions to the stats module:

maximum/1, which is just the same as minimum/1, but don’t forget—as I did—to reverse the direction of your test for "smaller" to become a test for "larger." (This function also already exists as lists:max/1.)

range/1, which takes a list of numbers as its argument and returns a list of two numbers: the minimum and maximum entries in the list.

1> c(stats).
{ok,stats}
2> N = [4, 1, 7, -17, 8, 2, 5].
[4,1,7,-17,8,2,5]
3> stats:maximum(N).
8
4> stats:range(N).
[-17,8]

See a suggested solution in Appendix A.

## Étude 6-3: Accumulating the Sum of a List

Add a function julian/1 to the dates module that you wrote in Étude 5-2. Given a string in ISO format ("yyyy-mm-dd"), it returns the Julian date: the day of the year.

Here is some sample output.

1> c(dates).
{ok,dates}
2> dates:julian("2012-12-31").
366
3> dates:julian("2013-12-31").
365
4> dates:julian("2012-02-05").
36
5> dates:julian("2013-02-05").
36
6> dates:julian("1900-03-01").
60
7> dates:julian("2000-03-01").
61
126> dates:julian("2013-01-01").
1

The julian/1 function defines a 12-item list called DaysPerMonth that contains the number of days in each month, splits the date into the year, month, and day (using the date_parts/1 function you wrote in Étude 5-2, and then calls helper function julian/5 (yes, five arguments).

The julian/5 function does all of the work. Its arguments are the year, month, day, the list of days per month, and an accumulated total, which starts at zero. julian/5 takes the head of the days per month list and adds it to the accumulator, and then calls julian/5 again with the tail of the days per month list and the accumulator value as its last two arguments.

Let’s take, as an example, the sequence of calls for April 18, 2013:

julian(2013, 4, 18, [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31], 0).
julian(2013, 4, 18, [28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31], 31).
julian(2013, 4, 18, [31, 30, 31, 30, 31, 31, 30, 31, 30, 31], 59).
julian(2013, 4, 18, [30, 31, 30, 31, 31, 30, 31, 30, 31], 90).

At this point, the accumulator has all the days up through the beginning of April, so the last call to julian/5 just adds the 18 remaining days and yields 108 as its result.

You know you are doing the last call when you have "used up" the first month-1 items in the list of days per month. That happens when the month number is greater than (13 - length(days_per_month_list)). Hint: use a guard.

Of course, there’s still the problem of leap years. You can handle it in either julian/5 or julian/1.

If you want to do the work in julian/5, then for non-leap years, the last call to julian/5 adds the number of days in the target month. For leap years, the function must add the number of days in the target month plus one—but only if the month is after February.

If you want to do the work in julian/5, use a case to assign either 28 or 29 to a variable named DaysInFeb (depending on whether the year is a leap year), and then use that variable instead of 28 when you construct your original days per month list.

I’ll give you the code for the is_leap_year/1 function for free; it returns true if the given year is a leap year, false otherwise.

is_leap_year(Year) ->
(Year rem 4 == 0 andalso Year rem 100 /= 0)
orelse (Year rem 400 == 0).

See suggested solutions in Appendix A.

## Interlude: "Mistakes were made."

As I was writing the next two études, I tried, despite the examples in the book, to avoid using lists:reverse/1. I thought, "Why can’t I add items to the end of a list using the cons (vertical bar; |) notation?" Here’s why.

I decided to do a simple task: take a list of numbers and return a list consisting of the squares of the numbers. I tried adding new items to the end of the list with this code:

-module(bad_code).
-export([squares/1]).

squares(Numbers) -> squares(Numbers, []).

squares([], Result) -> Result;

squares([H | T], Result) -> squares(T, [Result | H * H ]).

The resulting list was in the correct order, but it was an improper list.

1> c(bad_code).
{ok,bad_code}
2> bad_code:squares([9, 4.22, 5]).
[[[[]|81]|17.8084]|25]

That didn’t work. Wait a minute—the book said that the right hand side of the cons (|) operator should be a list. "OK, you want a list?" I thought. "I’ve got your list right here." (See the last line of the code, where I wrap the new item in square brackets.)

squares2(Numbers) -> squares2(Numbers, []).

squares2([], Result) -> Result;

squares2([H | T], Result) -> squares2(T, [Result | [H * H] ]).

There. That should do the trick.

6> c(bad_code).
{ok,bad_code}
7> bad_code:squares2([9, 4.22, 5]).
[[[[],81],17.8084],25]

The result was better, but only slightly better. I didn’t have an improper list any more, but now I had a list of list of list of lists. I could fix the problem by changing one line to flatten the final result.

squares2([], Result) -> lists:flatten(Result);

That worked, but it wasn’t a satisfying solution.

In light of all of this, I decided to use lists:reverse/1 and write the code to generate a proper, non-nested list.

-module(good_code).
-export([correct_squares/1]).

correct_squares(Numbers) -> correct_squares(Numbers, []).

correct_squares([], Result) -> lists:reverse(Result);

correct_squares([H | T], Result) ->
correct_squares(T, [H * H | Result]).
1> c(good_code).
{ok,good_code}
2> good_code:correct_squares([9, 4.22, 5]).
[81,17.8084,25]

Success at last! The moral of the story?

• RTFM (Read the Fabulous Manual).
• Believe what you read.
• If you don’t believe what you read, try it and find out.
• Don’t worry if you make this sort of mistake. You won’t be the first person to do so, and you certainly won’t be the last.
• When using cons, "lists come last."

OK. Back to work.

## Étude 6-4: Lists of Lists

Dentists check the health of your gums by checking the depth of the "pockets" at six different locations around each of your 32 teeth. The depth is measured in millimeters. If any of the depths is greater than or equal to four millimeters, that tooth needs attention. (Thanks to Dr. Patricia Lee, DDS, for explaining this to me.)

Your task is to write a module named teeth and a function named alert/1. The function takes a list of 32 lists of six numbers as its input. If a tooth isn’t present, it is represented by the list [0] instead of a list of six numbers. The function produces a list of the tooth numbers that require attention. The numbers must be in ascending order.

Here’s a set of pocket depths for a person who has had her upper wisdom teeth, numbers 1 and 16, removed. Just copy and paste it.

PocketDepths = [[0], [2,2,1,2,2,1], [3,1,2,3,2,3],
[3,1,3,2,1,2], [3,2,3,2,2,1], [2,3,1,2,1,1],
[3,1,3,2,3,2], [3,3,2,1,3,1], [4,3,3,2,3,3],
[3,1,1,3,2,2], [4,3,4,3,2,3], [2,3,1,3,2,2],
[1,2,1,1,3,2], [1,2,2,3,2,3], [1,3,2,1,3,3], [0],
[3,2,3,1,1,2], [2,2,1,1,3,2], [2,1,1,1,1,2],
[3,3,2,1,1,3], [3,1,3,2,3,2], [3,3,1,2,3,3],
[1,2,2,3,3,3], [2,2,3,2,3,3], [2,2,2,4,3,4],
[3,4,3,3,3,4], [1,1,2,3,1,2], [2,2,3,2,1,3],
[3,4,2,4,4,3], [3,3,2,1,2,3], [2,2,2,2,3,3],
[3,2,3,2,3,2]].

And here’s the output:

1> c(teeth).
{ok,teeth}
2> teeth:alert(PocketDepths).
[9,11,25,26,29]

See a suggested solution in Appendix A.

## Étude 6-5: Random Numbers; Generating Lists of Lists

How do you think I got the numbers for the teeth in the preceding étude? Do you really think I made up and typed all 180 of them? No, of course not. Instead, I wrote an Erlang program to create the list of lists for me, and that’s what you’ll do in this étude.

In order to create the data for the teeth, I had to generate random numbers with Erlang’s random module. Try generating a random number uniformly distributed between 0 and 1.0 by typing this in erl:

1> random:uniform().
0.4435846174457203

Now, exit erl, restart, and type the same command again. You’ll get the same number. In order to ensure that you get different sets of random numbers, you have to seed the random number generator with a three-tuple. The easiest way to get a different seed every time you run the program is to use the now/0 built-in function, which returns a different three-tuple every time you call it.

1> now().
{1356,887000,432535}
2> now().
{1356,887002,15527}
3> now().
{1356,887003,831752}

Exit erl, restart, it and try these commands. Do this a couple of times to convince yourself that you really get different random numbers. Don’t worry about the undefined; that’s just Erlang’s way of telling you that the random number generator wasn’t seeded before.

1> random:seed(now()).
undefined
2> random:uniform().
0.27846009966109264

If you want to generate a random integer between 1 and N, use uniform/1; thus random:uniform(10) will generate a random integer from 1 to 10.

Functions that use random numbers have side effects; unlike the sin or sqrt function, which always gives you the same numbers for the same input, functions that use random numbers should always give you different numbers for the same input. Since these functions aren’t "pure," it’s best to isolate them in a module of their own.

In this étude, create a module named non_fp, and write a function generate_teeth/2. This function has a string consisting of the characters T and F for its first argument. A T in the string indicates that the tooth is present, and a F indicates a missing tooth. In Erlang, a string is a list of characters, so you can treat this string just as you would any other list. Remember to refer to individual characters as $T and $F.

The second argument is a floating point number between 0 and 1.0 that indicates the probability that a tooth will be a good tooth.

These are the helper functions I needed:

generate_teeth/3

The first two arguments are the same as for generate_teeth/2; the third argument is the accumulated list. When the first argument is an empty list, the function yields the reverse of the accumulated list.

Hint: use pattern matching to figure out whether a tooth is present or not. For a non-present tooth, add [0] to the accumulated list; for a tooth that is present, create a list of six numbers by calling generate_tooth/1 with the probability of a good tooth as its argument.

generate_tooth/1

This generates the list of numbers for a single tooth. It generates a random number between 0 and 1. If that number is less than the probability of a good tooth, it sets the "base depth" to 2, otherwise it sets the base depth to 3.

The function then calls generate_tooth/3 with the base depth, the number 6, and an empty list as its arguments.

generate_tooth/3
The first argument is the base depth, the second is the number of items left to generate, and the third argument is the accumulated list. When the number of items hits zero, the function is finished. Otherwise, it adds a random integer between -1 and 1 to the base depth, adds it to the accumulated list, and does a recursive call with one less item.

See a suggested solution in Appendix A.