I am simply trying to make this average function to be tail recursive. I have managed to get my function to work and that took some considerable effort. Afterwards I went to ask my professor if my work was satisfactory and he informed me that
my avg function was not tail recursive
avg did not produce the correct output for lists with more than one element
I have been playing around with this code for the past 2 hours and have hit a bit of a wall. Can anyone help me to identify what I am not understanding here.
Spoke to my professor he was != helpful
(defun avg (aList)
(defun sumup (aList)
(if (equal aList nil) 0
; if aList equals nil nothing to sum
(+ (car aList) (sumup (cdr aList)) )
)
)
(if
(equal aList nil) 0
; if aList equals nil length dosent matter
(/ (sumup aList) (list-length aList) )
)
)
(print (avg '(2 4 6 8 19))) ;39/5
my expected results for my test are commented right after it 39/5
So this is what I have now
(defun avg (aList &optional (sum 0) (length 0))
(if aList
(avg (cdr aList) (+ sum (car aList))
(+ length 1))
(/ sum length)))
(print (avg '(2 4 6 8 19))) ;39/5
(defun avg (list &optional (sum 0) (n 0))
(cond ((null list) (/ sum n))
(t (avg (cdr list)
(+ sum (car list))
(+ 1 n)))))
which is the same like:
(defun avg (list &optional (sum 0) (n 0))
(if (null list)
(/ sum n)
(avg (cdr list)
(+ sum (car list))
(+ 1 n))))
or more similar for your writing:
(defun avg (list &optional (sum 0) (n 0))
(if list
(avg (cdr list)
(+ sum (car list))
(+ 1 n))
(/ sum n)))
(defun avg (lst &optional (sum 0) (len 0))
(if (null lst)
(/ sum len)
(avg (cdr lst) (incf sum (car lst)) (1+ len))))
You could improve your indentation here by putting the entire if-then/if-else statement on the same line, because in your code when you call the avg function recursively the indentation bleeds into the next line. In the first function you could say that if the list if null (which is the base case of the recursive function) you can divide the sum by the length of the list. If it is not null, you can obviously pass the cdr of the list, the sum so far by incrementing it by the car of the list, and then increment the length of the list by one. Normally it would not be wise to use the incf or 1+ functions because they are destructive, but in this case they will only have a localized effect because they only impact the optional sum and len parameters for this particular function, and not the structure of the original list (or else I would have passed a copy of the list).
Another option would be to use a recursive local function, and avoid the optional parameters and not have to compute the length of the list on each recursive call. In your original code it looks like you were attempting to use a local function within the context of your avg function, but you should use the "labels" Special operator to do that, and not "defun":
(defun avg (lst)
(if (null lst)
0
(labels ((find-avg (lst sum len)
(if (null lst)
(/ sum len)
(find-avg (cdr lst) (incf sum (car lst)) len))))
(find-avg lst 0 (length lst))))
I'm not 100% sure if your professor would want the local function to be tail-recursive or if he was referring to the global function (avg), but that is how you could also make the local function tail-recursive if that is an acceptable remedy as well. It's actually more efficient in some ways, although it requires more lines of code. In this case a lambda expression could also work, BUT since they do not have a name tail-recursion is not possibly, which makes the labels Special operator is useful for local functions if tail-recursion is mandatory.
Related
I'm creating a tail recursive function that evaluates a polynomial by passing a list of coefficients and an x value.
example: evaluate x^3 + 2x^2 + 5, so the user would pass the list '(5 0 2 1) and an x like 1 in a functional call (poly '(5 0 2 1) 1).
I can't figure out why i'm getting the following error:
if: bad syntax in: (if (null? (cdr lst)) (+ total (car lst))
eval-poly-tail-helper ((cdr lst) x (+ (* (expt x n) (car lst)) total)
(+ 1 n)))
(define (poly lst x)
(poly-assistant lst x 0 0))
(define (poly-assistant lst x total n)
(if (null? (cdr lst))
(+ total (car lst))
poly-assistant((cdr lst) x (+ (* (expt x n) (car lst)) total) (+ 1 n))))
You need a left paren before poly-assistant in the last line.
In Scheme, function applications start with a left paren. And if takes 2 or 3 operands.
Use a better editor (e.g. emacs) able to match parenthesis.
The two left parenthesis before cdr looks suspicious. You might need only one.
Learn to use your Scheme debugger, or at least add debugging prints.
I'm trying to write a simple procedure for finding the n:th prime but I don't think I understand how to reference variables correctly in racket.
What I want is for the inner procedure sieve-iter to add primes to the list primlst which is in the namespace of sieve but I get an infinite loop. My guess is that primlst within sieve-iter is causing issues.
(define (sieve n) ;; returns the n:th prime (n>0)
(let [(primlst '(2))
(cand 3)]
(define (sieve-iter i lst)
(cond ((null? lst) (and (cons i primlst) (sieve-iter (+ i 2) primlst))) ;;prime
((= (length primlst) n) (car primlst)) ;;end
((= (modulo i (car lst)) 0) (sieve-iter (+ i 2) primlst)) ;;non-prime
(#t (sieve-iter n (cdr lst))))) ;;unclear if prime
(sieve-iter cand primlst)))
Any help is appreciated!
First of all, you shouldn't refer to primlist at all within the sieve-iter function. Instead, you should refer to lst.
Second of all, you appear to be mistaken on the effect of this expression:
(and (cons i primlst) (sieve-iter (+ i 2) primlst))
You seem to be interpreting that as meaning "Add i to the primlist and then start the next iteration."
(cons i primlist) changes nothing. Instead, it creates a new list consisting of primlist with i in front of it and then evaluates to that value. The original primlist (which should have been lst anyway) is left untouched.
Also, and is for Boolean logic, not for stringing commands together. It evaluates each of its subexpressions separately until it finds one that evaluates to #f and then it stops.
You should replace that whole expression with this:
(sieve-iter (+ i 2) (cons i lst))
...which passes the new list created by cons to the next run of sieve-iter.
Your trying to do too much in one function, let prime-iter just worry about the iteration to build up the list of primes. Make another internal function to recurse down the existing primes to test the new candidate.
(define (sieve n) ;; returns the n:th prime (n>0)
(define (sieve-iter i lst remaining)
(cond ;((null? lst) (and (cons i primlst) (sieve-iter (+ i 2) primlst))) ;;should never be null, we are building the list up
((<= remaining 0) (car lst)) ;;checking length every time gets expensive added a variable to the function
((sieve-prime? i lst) ;;if prime add to lst and recurse on next i
(sieve-iter (+ i 2) (cons i lst) (- remaining 1)))
(else
(sieve-iter (+ i 2) lst remaining)))) ; else try next
(define (sieve-prime? i lst)
(cond ((null? lst) #t)
((= 0 (modulo i (car lst))) #f)
(else (sieve-prime? i (cdr lst)))))
(let ((primlst '(2)) ;;you generally don't modify these,
(cand 3)) ;mostly they just bind values to name for convenience or keep from having to re-calculate the same thing more than once
(sieve-iter cand primlst (- n 1))))
You could have used set! to modify primlist where it was before, but the procedure is no longer obviously a pure function.
There is another low-handing optimization possible here, when calling sieve-prime? filter the lst argument to remove values larger than the square root of i.
I am totally new to Lisp.
How to find the difference between elements in an arithmetic progression series?
e.g.
(counted-by-N '(20 10 0))
Return -10
(counted-by-N '(20 10 5))
(counted-by-N '(2))
(counted-by-N '())
Returns Nil
In Python/C and other languages, it is very straightforward... Kinda stuck here in Lisp.
My pseudo algorithm would be something like this:
function counted-by-N(L):
if len(L) <= 1:
return Nil
else:
diff = L[second] - L[first]
for (i = second; i < len(L) - 1; i++):
if L[i+1] - L[i] != diff
return Nil
return diff
Current work:
(defun count-by-N (L)
(if (<= (length L) 1) Nil
(
(defvar diff (- (second L) (first L)))
; How to do the loop part?
))
)
(flet ((by-n (list &aux
(e1 (first list))
(e2 (second list))
(difference (and e1 e2 (- e2 e1))))
(and difference
(loop for (one two) on list
while (and one two)
when (/= (- two one) difference)
do (return-from by-n nil)))
difference))
(by-n '(20 10 0)))
or
(flet ((by-n (list &aux
(e1 (first list))
(e2 (second list))
(difference (and e1 e2 (- e2 e1))))
(when difference
(loop for (one two) on list
while (and one two)
when (/= (- two one) difference)
do (return-from by-n nil))
difference)))
(by-n '(20 10 0)))
As far as you said on the second answer the best choice you have to do this example is implement it recursively.
Example Using List Processing (good manners)
That way, you have some ways to do this example on the recursively and simple way:
(defun count-by-N-1 (lst)
(if (equal NIL lst)
NIL
(- (car (cdr lst)) (car lst))
)
(count-by-N-1 (cdr lst))
)
On this first approach of the function count-by-N-1 I am using the simple car and cdr instructions to simplify the basics of Common Lisp List transformations.
Example Using List Processing Shortcuts (best implementation)
However you can resume by using some shortcuts of the car and cdr instructions like when you want to do a a car of a cdr, like I did on this example:
(defun count-by-N-2 (lst)
(if (equal NIL lst)
NIL
(- (cadr lst) (car lst))
)
(count-by-N-2 (cdr lst))
)
If you have some problems to understand this kind of questions using basic instructions of Common Lisp List transformation as well as car and cdr, you still can choose the first, second and rest approach. However I recommend you to see some of this basic instructions first:
http://www.gigamonkeys.com/book/they-called-it-lisp-for-a-reason-list-processing.html
Example Using Accessors (best for understand)
(defun count-by-N-3 (lst)
(if (equal NIL lst)
NIL
(- (first (rest lst)) (first lst))
)
(count-by-N-3 (rest lst))
)
This last one, the one that I will explain more clearly since it is the most understandable, you will do a recursion list manipulation (as in the others examples), and like the others, until the list is not NIL it will get the first element of the rest of the list and subtract the first element of the same list. The program will do this for every element till the list is "clean". And at last returns the list with the subtracted values.
That way if you read and study the similarities between using first, second and rest approach against using car and cdr, you easily will understand the both two first examples that I did put here.
Here is my final answer of this question which uses recursion:
(defun diff (N)
(- (second N) (first N))
)
(defun count-by-N (L)
(cond
((null L) nil)
((= (length L) 1) nil)
((= (length L) 2) (diff L))
((= (diff L) (diff (rest L))) (count-by-N (rest L)))
(T nil)
)
)
I'm trying to have the following program work, but for some reason it keeps telling me that my input doesnt contain the correct amount of arguments, why? here is the program
(define (sum f lst)
(cond
((null? lst)
0)
((pair? (car lst))
(+(f(sum (f car lst))) (f(sum (f cdr lst)))))
(else
(+ (f(car lst)) (f(sum (f cdr lst)))))))
and here is my input: (sum (lambda (x) (* x x)) '(1 2 3))
Thanks!
btw I take no credit for the code, Im just having fun with this one (http://groups.engin.umd.umich.edu/CIS/course.des/cis400/scheme/listsum.htm)
You're indeed passing the wrong number of arguments to the procedures sum and f, notice that the expressions (sum (f car lst)), (sum (f cdr lst)) are wrong, surely you meant (sum f (car lst)), (sum f (cdr lst)) - you don't want to apply f (a single-parameter procedure) to the two parameters that you're passing, and sum expects two arguments, but only one is passed. Try this instead:
(define (sum f lst)
(cond ((null? lst)
0)
((pair? (car lst))
(+ (sum f (car lst)) (sum f (cdr lst))))
(else
(+ (f (car lst)) (sum f (cdr lst))))))
More important: you're calling the f procedure in the wrong places. Only one call is needed in the last line, for the case when (car lst) is just a number and not a list - in the other places, both (car lst) and (cdr lst) are lists that need to be traversed; simply pass f around as a parameter taking care of correctly advancing the recursion.
Let's try the corrected procedure with a more interesting input - as it is, the procedure is capable of finding the sum of a list of arbitrarily nested lists:
(sum (lambda (x) (* x x)) '(1 (2) (3 (4)) 5))
> 55
You should take a look at either The Little Schemer or How to Design Programs, both books will teach you how to structure the solution for this kind of recursive problems over lists of lists.
I'm new to Scheme (via Racket) and (to a lesser extent) functional programming, and could use some advise on the pros and cons of accumulation via variables vs recursion. For the purposes of this example, I'm trying to calculate a moving average. So, for a list '(1 2 3 4 5), the 3 period moving average would be '(1 2 2 3 4). The idea is that any numbers before the period are not yet part of the calculation, and once we reach the period length in the set, we start averaging the subset of the list according the chosen period.
So, my first attempt looked something like this:
(define (avg lst)
(cond
[(null? lst) '()]
[(/ (apply + lst) (length lst))]))
(define (make-averager period)
(let ([prev '()])
(lambda (i)
(set! prev (cons i prev))
(cond
[(< (length prev) period) i]
[else (avg (take prev period))]))))
(map (make-averager 3) '(1 2 3 4 5))
> '(1 2 2 3 4)
This works. And I like the use of map. It seems composible and open to refactoring. I could see in the future having cousins like:
(map (make-bollinger 5) '(1 2 3 4 5))
(map (make-std-deviation 2) '(1 2 3 4 5))
etc.
But, it's not in the spirit of Scheme (right?) because I'm accumulating with side effects. So I rewrote it to look like this:
(define (moving-average l period)
(let loop ([l l] [acc '()])
(if (null? l)
l
(let* ([acc (cons (car l) acc)]
[next
(cond
[(< (length acc) period) (car acc)]
[else (avg (take acc period))])])
(cons next (loop (cdr l) acc))))))
(moving-average '(1 2 3 4 5) 3)
> '(1 2 2 3 4)
Now, this version is more difficult to grok at first glance. So I have a couple questions:
Is there a more elegant way to express the recursive version using some of the built in iteration constructs of racket (like for/fold)? Is it even tail recursive as written?
Is there any way to write the first version without the use of an accumulator variable?
Is this type of problem part of a larger pattern for which there are accepted best practices, especially in Scheme?
It's a little strange to me that you're starting before the first of the list but stopping sharply at the end of it. That is, you're taking the first element by itself and the first two elements by themselves, but you don't do the same for the last element or the last two elements.
That's somewhat orthogonal to the solution for the problem. I don't think the accumulator is making your life any easier here, and I would write the solution without it:
#lang racket
(require rackunit)
;; given a list of numbers and a period,
;; return a list of the averages of all
;; consecutive sequences of 'period'
;; numbers taken from the list.
(define ((moving-average period) l)
(cond [(< (length l) period) empty]
[else (cons (mean (take l period))
((moving-average period) (rest l)))]))
;; compute the mean of a list of numbers
(define (mean l)
(/ (apply + l) (length l)))
(check-equal? (mean '(4 4 1)) 3)
(check-equal? ((moving-average 3) '(1 3 2 7 6)) '(2 4 5))
Well, as a general rule, you want to separate the manner in which you recurse and/or iterate from the content of the iteration steps. You mention fold in your question, and this points in the right step: you want some form of higher-order function that will handle the list traversal mechanics, and call a function you supply with the values in the window.
I cooked this up in three minutes; it's probably wrong in many ways, but it should give you an idea:
;;;
;;; Traverse a list from left to right and call fn with the "windows"
;;; of the list. fn will be called like this:
;;;
;;; (fn prev cur next accum)
;;;
;;; where cur is the "current" element, prev and next are the
;;; predecessor and successor of cur, and accum either init or the
;;; accumulated result from the preceeding call to fn (like
;;; fold-left).
;;;
;;; The left-edge and right-edge arguments specify the values to use
;;; as the predecessor of the first element of the list and the
;;; successor of the last.
;;;
;;; If the list is empty, returns init.
;;;
(define (windowed-traversal fn left-end right-end init list)
(if (null? list)
init
(windowed-traversal fn
(car list)
right-end
(fn left-end
(car list)
(if (null? (cdr list))
right-end
(second list))
init)
(cdr list))))
(define (moving-average list)
(reverse!
(windowed-traversal (lambda (prev cur next list-accum)
(cons (avg (filter true? (list prev cur next)))
list-accum))
#f
#f
'()
list)))
Alternately, you could define a function that converts a list into n-element windows and then map average over the windows.
(define (partition lst default size)
(define (iter lst len result)
(if (< len 3)
(reverse result)
(iter (rest lst)
(- len 1)
(cons (take lst 3) result))))
(iter (cons default (cons default lst))
(+ (length lst) 2)
empty))
(define (avg lst)
(cond
[(null? lst) 0]
[(/ (apply + lst) (length lst))]))
(map avg (partition (list 1 2 3 4 5) 0 3))
Also notice that the partition function is tail-recursive, so it doesn't eat up stack space -- this is the point of result and the reverse call. I explicitly keep track of the length of the list to avoid either repeatedly calling length (which would lead to O(N^2) runtime) or hacking together a at-least-size-3 function. If you don't care about tail recursion, the following variant of partition should work:
(define (partition lst default size)
(define (iter lst len)
(if (< len 3)
empty
(cons (take lst 3)
(iter (rest lst)
(- len 1)))))
(iter (cons default (cons default lst))
(+ (length lst) 2)))
Final comment - using '() as the default value for an empty list could be dangerous if you don't explicitly check for it. If your numbers are greater than 0, 0 (or -1) would probably work better as a default value - they won't kill whatever code is using the value, but are easy to check for and can't appear as a legitimate average