Example: Arithmetic Operations for Rational Numbers
Suppose we want to do arithmetic with rational numbers. We want to be able to add, subtract, multiply, and divide them and to test whether two rational numbers are equal.
Let us begin by assuming that we already have a way of constructing a rational number from a numerator and a denominator. We also assume that, given a rational number, we have a way of extracting (or selecting) its numerator and its denominator. Let us further assume that the constructor and selectors are available as functions:
(make-rat <n> <d>)
returns the rational number whose numerator is the integer<n>
and whose denominator is the integer<d>
.(numer <x>)
returns the numerator of the rational number<x>
.(denom <x>)
returns the denominator of the rational number<x>
.
We are using here a powerful strategy of synthesis: wishful thinking. We haven't yet said how a rational number is represented, or how the functions numer/1
, denom/1
, and make-rat/2
should be implemented. Even so, if we did have these three functions, we could then add, subtract, multiply, divide, and test equality by using the following relations:
We can express these rules as functions:
(defun add-rat (x y)
(make-rat (+ (* (numer x) (denom y))
(* (numer y) (denom x)))
(* (denom x) (denom y))))
(defun sub-rat (x y)
(make-rat (- (* (numer x) (denom y))
(* (numer y) (denom x)))
(* (denom x) (denom y))))
(defun mul-rat (x y)
(make-rat (* (numer x) (numer y))
(* (denom x) (denom y))))
(defun div-rat (x y)
(make-rat (* (numer x) (denom y))
(* (denom x) (numer y))))
(defun equal-rat? (x y)
(== (* (numer x) (denom y))
(* (numer y) (denom x))))
Now we have the operations on rational numbers defined in terms of the selector and constructor functions numer/1
, denom/1
, and make-rat/2
. But we haven't yet defined these. What we need is some way to glue together a numerator and a denominator to form a rational number.
Now we have the operations on rational numbers defined in terms of the selector and constructor functions numer/1
, denom/1
, and make-rat/2
. But we haven't yet defined these. What we need is some way to glue together a numerator and a denominator to form a rational number.
Pairs
To enable us to implement the concrete level of our data abstraction, our language provides a compound structure called a pair, which can be constructed with the primitive function cons/2
. This function takes two arguments and returns a compound data object that contains the two arguments as parts. Given a pair, we can extract the parts using the primitive functions car/1
and cdr/1
.1 Thus, we can use cons/2
, car/1
, and cdr/1
as follows:
> (set x (cons 1 2))
(1 . 2)
> (car x)
1
> (cdr x)
2
Notice that a pair is a data object that can be given a name and manipulated, just like a primitive data object. Moreover, cons/2
can be used to form pairs whose elements are pairs, and so on:
> (set x (cons 1 2))
(1 . 2)
> (set y (cons 3 4))
(3 . 4)
> (set z (cons x y))
((1 . 2) 3 . 4)
> (car (car z))
1
> (car (cdr z))
3
In the section Hierarchical Data and the Closure Property we will see how this ability to combine pairs means that pairs can be used as general-purpose building blocks to create all sorts of complex data structures. The single compound-data primitive pair, implemented by the functions cons/2
, car/1
, and cdr/1
, is the only glue we need. Data objects constructed from pairs are called list-structured data.
Representing rational numbers
Pairs offer a natural way to complete the rational-number system. Simply represent a rational number as a pair of two integers: a numerator and a denominator. Then make-rat/2
, numer/1
, and denom/1
and are readily implemented as follows:1
(defun make-rat (x y)
(cons x y))
(defun numer (rat)
(car rat))
(defun denom (rat)
(cdr rat))
However, LFE pattern matching provides another possibility for implementating numer/1
and denom/1
. Without using car
or cdr
, we can match the numerator and denomenator in function arguments itself, without making a call in the body of the function.
(defun numer
(((cons x _))
x))
(defun denom
(((cons _ y))
y))
Though nothing obvious is gained through the use of pattern matching here2, this is a good opportunity to see its usage again, after the introduction in the first chapter.
In order to display the results of our computations, we can print rational numbers by printing the numerator, a slash, and the denominator:4
(defun print-rat (rat)
(io:format "~p/~p~n" (list (numer rat)
(denom rat))))
Now we can try our rational-number functions:
> (set one-half (make-rat 1 2))
(1 . 2)
> (print-rat one-half)
1/2
ok
> (set one-third (make-rat 1 3))
(1 . 3)
> (print-rat (add-rat one-half one-third))
5/6
ok
> (print-rat (mul-rat one-half one-third))
1/6
ok
> (print-rat (add-rat one-third one-third))
6/9
ok
As the final example shows, our rational-number implementation does not reduce rational numbers to lowest terms. We can remedy this by changing make-rat/2
. If we have a gcd/2
function like the one in the section Greatest Common Divisors that produces the greatest common divisor of two integers, we can use gcd/2
to reduce the numerator and the denominator to lowest terms before constructing the pair:
(defun make-rat (n d)
(let ((g (gcd n d)))
(cons (trunc (/ n g))
(trunc (/ d g)))))
Now we have
> (print-rat (add-rat one-third one-third))
2/3
ok
as desired. This modification was accomplished by changing the constructor make-rat/2
without changing any of the functions (such as add-rat/2
and mul-rat/2
) that implement the actual operations.
1. The namecons
stands for "construct." The namescar
andcdr
derive from the original implementation of Lisp on the IBM 704. That machine had an addressing scheme that allowed one to reference the "address" and "decrement" parts of a memory location.car
stands for "Contents of Address part of Register" andcdr
(pronounced "could-er" or "cudder") stands for "Contents of Decrement part of Register." ↩
2. In fact, something is lost: about 2 seconds. Arguably, this could be within a margin of uncertainty, though the results are consistent. The timing was performed upon the LFE author's 2009 MacBook Air using(set counts (lists:seq 1 10000))
and(/ (lists:sum (lists:map (lambda (_) (element 1 (timer:tc #'numer/1 (list one-half)))) counts)) (length counts))
. Without pattern matching, results ranged between 7 and 8 seconds; with pattern matching, results ranged from 8 to 11 seconds. ↩