I was asked to write a procedure that computes elements of Pascal's triangle by means of a recursive process. I may create a procedure that returns a single row in the triangle or a number within a particular row.
Here is my solution:
(define (f n)
(cond ((= n 1) '(1))
(else
(define (func i n l)
(if (> i n)
l
(func (+ i 1) n (cons (+ (convert (find (- i 1) (f (- n 1))))
(convert (find i (f (- n 1)))))
l))))
(func 1 n '()))))
(define (find n l)
(define (find i n a)
(if (or (null? a) (<= n 0))
'()
(if (>= i n)
(car a)
(find (+ i 1) n (cdr a)))))
(find 1 n l))
(define (convert l)
(if (null? l)
0
(+ l 0)))
This seems to work fine but it gets really inefficient to find elements of a larger row starting with (f 8). Is there a better procedure that solves this problem by means of a recursive process?
Also, how would I write it, if I want to use an iterative process (tail-recursion)?
There are several ways to optimize the algorithm, one of the best would be to use dynamic programming to efficiently calculate each value. Here is my own solution to a similar problem, which includes references to better understand this approach - it's a tail-recursive, iterative process. The key point is that it uses mutation operations for updating a vector of precomputed values, and it's a simple matter to adapt the implementation to print a list for a given row:
(define (f n)
(let ([table (make-vector n 1)])
(let outer ([i 1])
(when (< i n)
(let inner ([j 1] [previous 1])
(when (< j i)
(let ([current (vector-ref table j)])
(vector-set! table j (+ current previous))
(inner (add1 j) current))))
(outer (add1 i))))
(vector->list table)))
Alternatively, and borrowing from #Sylwester's solution we can write a purely functional tail-recursive iterative version that uses lists for storing the precomputed values; in my tests this is slower than the previous version:
(define (f n)
(define (aux tr tc prev acc)
(cond ((> tr n) '())
((and (= tc 1) (= tr n))
prev)
((= tc tr)
(aux (add1 tr) 1 (cons 1 acc) '(1)))
(else
(aux tr
(add1 tc)
(cdr prev)
(cons (+ (car prev) (cadr prev)) acc)))))
(if (= n 1)
'(1)
(aux 2 1 '(1 1) '(1))))
Either way it works as expected for larger inputs, it'll be fast for n values in the order of a couple of thousands:
(f 10)
=> '(1 9 36 84 126 126 84 36 9 1)
There are a number of soluitons presented already, and they do point out that usign dynamic programming is a good option here. I think that this can be written a bit more simply though. Here's what I'd do as a straightforward list-based solution. It's based on the observation that if row n is (a b c d e), then row n+1 is (a (+ a b) (+ b c) (+ c d) (+ d e) e). An easy easy to compute that is to iterate over the tails of (0 a b c d e) collecting ((+ 0 a) (+ a b) ... (+ d e) e).
(define (pascal n)
(let pascal ((n n) (row '(1)))
(if (= n 0) row
(pascal (- n 1)
(maplist (lambda (tail)
(if (null? (cdr tail)) 1
(+ (car tail)
(cadr tail))))
(cons 0 row))))))
(pascal 0) ;=> (1)
(pascal 1) ;=> (1 1)
(pascal 2) ;=> (1 2 1)
(pascal 3) ;=> (1 3 3 1)
(pascal 4) ;=> (1 4 6 4 1)
This made use of an auxiliary function maplist:
(define (maplist function list)
(if (null? list) list
(cons (function list)
(maplist function (cdr list)))))
(maplist reverse '(1 2 3))
;=> ((3 2 1) (3 2) (3))
Related
I am trying to create Pascal's Triangle using recursion. My code is:
(define (pascal n)
(cond
( (= n 1)
list '(1))
(else (append (list (pascal (- n 1))) (list(add '1 (coresublist (last (pascal (- n 1))))))
)))) ;appends the list from pascal n-1 to the new generated list
(define (add s lst) ;adds 1 to the beginning and end of the list
(append (list s) lst (list s))
)
(define (coresublist lst) ;adds the subsequent numbers, takes in n-1 list
(cond ((= (length lst) 1) empty)
(else
(cons (+ (first lst) (second lst)) (coresublist (cdr lst)))
)))
When I try to run it with:
(display(pascal 3))
I am getting an error that says:
length: contract violation
expected: list?
given: 1
I am looking for someone to help me fix this code (not write me entirely new code that does Pascal's Triangle). Thanks in advance! The output for pascal 3 should be:
(1) (1 1) (1 2 1)
We should start with the recursive definition for a value inside Pascals' triangle, which is usually expressed in terms of two parameters (row and column):
(define (pascal x y)
(if (or (zero? y) (= x y))
1
(+ (pascal (sub1 x) y)
(pascal (sub1 x) (sub1 y)))))
There are more efficient ways to implement it (see Wikipedia), but it will work fine for small values. After that, we just have to build the sublists. In Racket, this is straightforward using iterations, but feel free to implement it with explicit recursion if you wish:
(define (pascal-triangle n)
(for/list ([x (in-range 0 n)])
(for/list ([y (in-range 0 (add1 x))])
(pascal x y))))
It'll work as expected:
(pascal-triangle 3)
=> '((1) (1 1) (1 2 1))
I am trying to build the built-in procedure build-list in Racket.
The built-in function works like this:
(build-list 10 (lambda (x) (* x x)))
>> '(0 1 4 9 16 25 36 49 64 81)
My implementation is a recursive definition for a recursive procedure:
(define (my-build-list-recur list-len proc)
(if (= list-len 0)
'()
(cons (proc (sub1 list-len)) (my-build-list-recur (sub1 list-len) proc))))
When I call my implementation, I have:
(my-build-list-recur 10 (lambda (x) (* x x)))
>> '(81 64 49 36 25 16 9 4 1 0)
As you might have seen, I get the same result, but in a reverse order.
What can I do to have the result in the same order as the native function?
P.S.: I have done an implementation using a recursive definition for an iterative procedure which works perfectly. I am struggling now to generate the same result with the totally recursive procedure. I already know how to solve this doubt with long tail recursion.
This is my implementation with long tail recursion:
(define (my-build-list list-len proc)
(define (iter list-len accu n)
(if (= (length accu) list-len)
(reverse accu)
(iter list-len (cons (proc n) accu) (add1 n))))
;(trace iter)
(iter list-len '() 0))
Ok so you're looking for an answer that does not use state variables and a tail call. You want for a recursive procedure that also evolves a recursive process. Not sure why you want this other than just to see how the definition would differ. You should also read about tail recursion modulo cons (here, and on wikipedia) – it's relevant to this question.
;; recursive procedure, recursive process
(define (build-list n f)
(define (aux m)
(if (equal? m n)
empty
(cons (f m) (aux (add1 m)))))
(aux 0))
(build-list 5 (λ (x) (* x x)))
;; => '(0 1 4 9 16)
Notice how the aux call is no longer in tail position – ie, cons cannot finish evaluating until it has evaluated the aux call in its arguments. The process will look something like this, evolving on the stack:
(cons (f 0) ...)
(cons (f 0) (cons (f 1) ...))
(cons (f 0) (cons (f 1) (cons (f 2) ...)))
(cons (f 0) (cons (f 1) (cons (f 2) (cons (f 3) ...))))
(cons (f 0) (cons (f 1) (cons (f 2) (cons (f 3) (cons (f 4) ...)))))
(cons (f 0) (cons (f 1) (cons (f 2) (cons (f 3) (cons (f 4) empty)))))
(cons (f 0) (cons (f 1) (cons (f 2) (cons (f 3) (cons (f 4) '())))))
(cons (f 0) (cons (f 1) (cons (f 2) (cons (f 3) '(16)))))
(cons (f 0) (cons (f 1) (cons (f 2) '(9 16))))
(cons (f 0) (cons (f 1) '(4 9 16)))
(cons (f 0) '(1 4 9 16))
'(0 1 4 9 16)
You'll see that the cons calls are left hanging open until ... is filled in. And the last ... isn't filled in with empty until m is equal to n.
If you don't like the inner aux procedure, you can use a default parameter, but this does leak some of the private API to the public API. Maybe it's useful to you and/or maybe you don't really care.
;; recursive procedure, recursive process
(define (build-list n f (m 0))
(if (equal? m n)
'()
(cons (f m) (build-list n f (add1 m)))))
;; still only apply build-list with 2 arguments
(build-list 5 (lambda (x) (* x x)))
;; => '(0 1 4 9 16)
;; if a user wanted, they could start `m` at a different initial value
;; this is what i mean by "leaked" private API
(build-list 5 (lambda (x) (* x x) 3)
;; => '(9 16)
Stack-safe implementations
Why you'd specifically want a recursive process (one which grows the stack) is strange, imo, especially considering how easy it is to write a stack-safe build-list procedure which doesn't grow the stack. Here's some recursive procedures with a linear iterative processes.
The first one is extremely simple but does leak a little bit of private API using the acc parameter. You could easily fix this using an aux procedure like we did in the first solution.
;; recursive procedure, iterative process
(define (build-list n f (acc empty))
(if (equal? 0 n)
acc
(build-list (sub1 n) f (cons (f (sub1 n)) acc))))
(build-list 5 (λ (x) (* x x)))
;; => '(0 1 4 9 16)
Check out the evolved process
(cons (f 4) empty)
(cons (f 3) '(16))
(cons (f 2) '(9 16))
(cons (f 1) '(4 9 16))
(cons (f 0) '(1 4 9 16))
;; => '(0 1 4 9 16)
This is insanely better because it can constantly reuse one stack frame until the entire list is built. As an added advantage, we don't need to keep a counter that goes from 0 up to n. Instead, we build the list backwards and count from n-1 to 0.
Lastly, here's another recursive procedure that evolves a linear iterative process. It utilizes a named-let and continuation passing style. The loop helps prevent leaking the API this time.
;; recursive procedure, iterative process
(define (build-list n f)
(let loop ((m 0) (k identity))
(if (equal? n m)
(k empty)
(loop (add1 m) (λ (rest) (k (cons (f m) rest)))))))
(build-list 5 (λ (x) (* x x)))
;; => '(0 1 4 9 16)
It cleans up a little tho if you use compose and curry:
;; recursive procedure, iterative process
(define (build-list n f)
(let loop ((m 0) (k identity))
(if (equal? n m)
(k empty)
(loop (add1 m) (compose k (curry cons (f m)))))))
(build-list 5 (λ (x) (* x x)))
;; => '(0 1 4 9 16)
The process evolved from this procedure is slightly different, but you'll notice that it also doesn't grow the stack, creating a sequence of nested lambdas on the heap instead. So this would be sufficient for sufficiently large values of n:
(loop 0 identity) ; k0
(loop 1 (λ (x) (k0 (cons (f 0) x))) ; k1
(loop 2 (λ (x) (k1 (cons (f 1) x))) ; k2
(loop 3 (λ (x) (k2 (cons (f 2) x))) ; k3
(loop 4 (λ (x) (k3 (cons (f 3) x))) ; k4
(loop 5 (λ (x) (k4 (cons (f 4) x))) ; k5
(k5 empty)
(k4 (cons 16 empty))
(k3 (cons 9 '(16)))
(k2 (cons 4 '(9 16)))
(k1 (cons 1 '(4 9 16)))
(k0 (cons 0 '(1 4 9 16)))
(identity '(0 1 4 9 16))
'(0 1 4 9 16)
I am writing a function to count the number of ways to make change in scheme given a list of denominations and an amount. My code is as follows, but it does not work as intended. Should I be using cons instead of the + operator? Should the third line down's base case be the empty list?
(define (change k l)
(cond ((= k 0) 1)
((or (< k 0) (null? l)) 0)
(else (+ (change k (cdr l))
(change (- k (car l))
(cdr l))))))
Test:
(change 11 (list 1 5 10 25))
If the returned value is just a number then forget about cons and '() for building the output, and only use car, cdr, null? for processing the input. Other than that, be aware that there's a small mistake in the last line of your code, here's the fixed version:
(define (change k l)
(cond ((= k 0) 1)
((or (< k 0) (null? l)) 0)
(else
(+ (change k (cdr l))
(change (- k (car l)) l))))) ; don't do (cdr l) here
Now it works as expected:
(change 11 (list 1 5 10 25))
=> 4
The professor showed us a drawn-out method to find all permutations of a list, i.e. (a b c) => ((a b c) (a c b) (b a c) (b c a) (c b a) (c a b)), but she said it could be done much more efficiently with foldl or map.
Totally new to the functional mindset. I cannot figure this out for the life of me.
There are scheme versions (you mensioned "foldl" so there is haskell version too on this page) on http://rosettacode.org/wiki/Permutations#Scheme:
(define (insert l n e)
(if (= 0 n)
(cons e l)
(cons (car l)
(insert (cdr l) (- n 1) e))))
(define (seq start end)
(if (= start end)
(list end)
(cons start (seq (+ start 1) end))))
(define (permute l)
(if (null? l)
'(())
(apply append (map (lambda (p)
(map (lambda (n)
(insert p n (car l)))
(seq 0 (length p))))
(permute (cdr l))))))
How about this one?
#lang racket
(define l '(apple banana cheese desk))
(remove-duplicates (for/list ([i 1000000]) (shuffle l)))
Naturally, you'll want to increase the constant for long lists....
(#nothelpfulsorry)
Given a recursive function in scheme how do I change that function to tail recursive, and then how would I implement it using streams? Are there patterns and rules that you follow when changing any function in this way?
Take this function as an example which creates a list of numbers from 2-m (this is not tail recursive?)
Code:
(define listupto
(lambda (m)
(if (= m 2)
'(2)
(append (listupto (- m 1)) (list m)))))
I'll start off by explaining your example. It is definitely not tail recursive. Think of how this function executes. Each time you append you must first go back and make the recursive call until you hit the base case, and then you pull your way back up.
This is what a trace of you function would look like:
(listupto 4)
| (append (listupto(3)) '4)
|| (append (append (listupto(2)) '(3)) '(4))
||| (append (append '(2) '(3)) '(4))
|| (append '(2 3) '(4))
| '(2 3 4)
'(2 3 4)
Notice the V-pattern you see pulling in and then out of the recursive calls. The goal of tail recursion is to build all of the calls together, and only make one execution. What you need to do is pass an accumulator along with your function, this way you can only make one append when your function reaches the base case.
Here is the tail recursive version of your function:
(define listupto-tail
(lambda (m)
(listupto m '())))
# Now with the new accumulator parameter!
(define listupto
(lambda (m accu)
(if (= m 2)
(append '(2) accu)
(listupto (- m 1) (append (list m) accu)))))
If we see this trace, it will look like this:
(listupto 4)
| (listupto (3) '(4)) # m appended with the accu, which is the empty list currently
|| (listupto (2) '(3 4)) # m appended with accu, which is now a list with 4
||| (append '(2) '(3 4))
'(2 3 4)
Notice how the pattern is different, and we don't have to traverse back through the recursive calls. This saves us pointless executions. Tail recursion can be a difficult concept to grasp I suggest taking a look here. Chapter 5 has some helpful sections in it.
Generally to switch to a tail recursive form you transform the code so that it takes an accumulator parameter which builds the result up and is used as the final return value. This is generally a helper function which your main function delegates too.
Something of the form:
(define listupto
(lambda (m)
(listupto-helper m '())))
(define listupto-helper
(lambda (m l)
(if (= m 2)
(append '(2) l)
(listupto-helper (- m 1) (append (list m) l)))))
As the comments point out, the helper function can be replaced with a named let which is apparently (haven't done much/enough Scheme!) more idiomatic (and as the comments suggest cons is much better than creating a list and appending.
(define listupto
(lambda (n)
(let loop ((m n) (l '()))
(if (= m 2)
(append '(2) l)
(loop (- m 1) (cons m l))))))
You also ask about streams. You can find a SICP styled streams used e.g. here or here which have a from-By stream builder defined:
;;;; Stream Implementation
(define (head s) (car s))
(define (tail s) ((cdr s)))
(define-syntax s-cons
(syntax-rules ()
((s-cons h t) (cons h (lambda () t)))))
;;;; Stream Utility Functions
(define (from-By x s)
(s-cons x (from-By (+ x s) s)))
Such streams creation relies on macros, and they must be accessed by special means:
(define (take n s)
(cond ; avoid needless tail forcing for n == 1 !
((= n 1) (list (head s))) ; head is already forced
((> n 1) (cons (head s) (take (- n 1) (tail s))))
(else '())))
(define (drop n s)
(cond
((> n 0) (drop (- n 1) (tail s)))
(else s)))
But they aren't persistent, i.e. take and drop recalculate them on each access. One way to make streams persistent is to have a tailing closure surgically altering the last cons cell on access:
(1 . <closure>)
(1 . (2 . <closure>))
....
like this:
(define (make-stream next this state)
(let ((tcell (list (this state)))) ; tail sentinel cons cell
(letrec ((g (lambda ()
(set! state (next state))
(set-cdr! tcell (cons (this state) g))
(set! tcell (cdr tcell))
tcell)))
(set-cdr! tcell g)
tcell)))
(define (head s) (car s))
(define (tail s)
(if (or (pair? (cdr s))
(null? (cdr s)))
(cdr s)
((cdr s))))
We can now use it like this
(define a (make-stream (lambda (i) (+ i 1)) (lambda (i) i) 1))
;Value: a
a
;Value 13: (1 . #[compound-procedure 14])
(take 3 a)
;Value 15: (1 2 3)
a
;Value 13: (1 2 3 . #[compound-procedure 14])
(define b (drop 4 a))
;Value: b
b
;Value 16: (5 . #[compound-procedure 14])
a
;Value 13: (1 2 3 4 5 . #[compound-procedure 14])
(take 4 a)
;Value 17: (1 2 3 4)
a
;Value 13: (1 2 3 4 5 . #[compound-procedure 14])
Now, what does (make-stream (lambda (i) (list (cadr i) (+ (car i) (cadr i)))) car (list 0 1)) define?
update: in Daniel Friedman's 1994 slides "The Joys of Scheme, Cont'd" we find simpler implementation of these "memoized streams" (as they are called there), making the tail function itself store the forced stream in the tail sentinel, as
(define (tail s)
(if (or (pair? (cdr s))
(null? (cdr s)))
(cdr s)
(let ((n ((cdr s))))
(set-cdr! s n)
(cdr s))))
;; can be used as e.g. (https://ideone.com/v6pzDt)
(define fibs
(let next-fib ((a 0) (b 1))
(s-cons a (next-fib b (+ a b)))))
Here's a tail recursive form -
(define (listupto n)
(let run
((m 0)
(return identity))
(if (> m n)
(return null)
(run (add1 m)
(lambda (r) (return (cons m r)))))))
(listupto 9)
; '(0 1 2 3 4 5 6 7 8 9)
And here it is as a stream -
(define (listupto n)
(let run
((m 0))
(if (> m n)
empty-stream
(stream-cons m
(run (add1 m))))))
(stream->list (listupto 9))
; '(0 1 2 3 4 5 6 7 8 9)