I have found the following piece of code that it makes permutation in Scheme. I mean if I enter like arguments \'(1 2 3) it will give me:
((1 2 3) (1 3 2) (
Let's pick this apart, going from the inside out. Fix lst
and apply the inner expression to one of its elements.
> (define lst '(1 2 3))
> (define i 1)
> (permute (remove i lst))
((2 3) (3 2))
Looks good: the inner expression removes and element and generates permutations of the remainder of the list, recursively. Now map
the lambda
over these permutations:
> (map (lambda (j) (cons i j)) (permute (remove i lst)))
((1 2 3) (1 3 2))
So the inner map
produces all permutations that start with some i
, which we've set to 1
here.
The outer map
makes sure all permutations are generated by considering all elements of lst
as the first element.
> (map (lambda (i) (map (lambda (j) (cons i j))
> (permute (remove i lst))))
> lst)
(((1 2 3) (1 3 2)) ((2 1 3) (2 3 1)) ((3 1 2) (3 2 1)))
But this generates lists with too much nesting. Applying append
flattens a list of lists,
> (append '(1 2) '(3 4) '(5 6))
(1 2 3 4 5 6)
> (apply append '((1 2) (3 4) (5 6)))
(1 2 3 4 5 6)
so we get a flat list of permutations out.
I've always found it easier to understand the algorithm on a higher level before diving into an implementation and trying to understand what's happening there. So the question is: what are the permutations of a list, and how would you find them?
The permutations of a single element list are evidently just the list itself.
The permutations of (a b)
are the set [(a b) (b a)]
.
The permutations of (a b c)
are the set
[(a b c) (a c b) (b c a) (b a c) (c a b) (c b a)]
In general there are n! permutations of a list of length n - we have n choices for the first element, and once we've picked that, (n-1) choices for the second element, (n-2) for the third element, and so on. This decrease in the degrees of freedom as we fix more and more of the first elements of the list is very suggestive: maybe we can represent the finding the permutations of a list of length n in terms of the permutations of a list of length (n - 1), and so on until we reach the permutations of a single-element list.
It turns out that the permutations of a list a precisely the set [element prepended to the permutations of list \ element, for every element in list].
Looking at the (a b c)
case confirms that this is
true - we have a
preceding (b c)
and (c b)
, which are the
permutations of (b c)
, b
preceding (a c)
and (c a)
and so on. This
operation of prepending the element to the sublist could be defined as
(define (prepend j)
(cons element j))
and the operation of doing it for all the
permutations of the sublist would then be (map prepend (permute
sublist))
. Now, defining a new prepend function for each element is
maybe overkill - especially since they all have the same form. So a
better approach is just to use a lambda, which captures the value of
the element under consideration. The desired operation is
then (map (lambda (j) (cons element j)) (permute sublist))
. Now, we
want to apply this operation to each element of the list, and the way to
do that is using another map, giving:
(map (lambda (element)
(lambda (j) (cons element j) (permute sublist)))
list)
Now, this looks good, but there is a problem: each stage of the recursion takes single
elements and turns them into a list. That's fine for lists of length 1,
but for longer lists it repeats for every recursive call, and we get
very deeply nested lists. What we really want to do is to put all
these lists on the same footing, which is exactly what the (apply append ...)
takes care of. And that's almost all of that line. The only
thing missing is how the sublist is generated in the first place. But
that's easy as well - we'll just use remove
, so that sublist = (remove element list)
. Putting everything together, and we have
(apply append (map (lambda (i)
(lambda (j) (cons i j))
(permute (remove i lst)))
lst))
The base case takes care of the length = 1 case, and all of the others can be found from there