Let's take the following function to get a pair of numbers:
; (range 1 3) --> '(1 2 3)
(define (range a b)
(if (> a b) nil
(cons a (range (+ 1 a) b))))
; generate pair of two numbers with 1 <= i < j <= N
(define (get-pairs n)
(map (lambda (i)
(map (lambda (j) (list i j))
(range 1 (- i 1))))
(range 1 n)))
(get-pairs 2)
; (() ((2 1)))
(get-pairs 3)
(() ((2 1)) ((3 1) (3 2)))
Why does the above produce '() as the first element of the output? Comparing this with python, I would expect it to just give the three pairs, something like:
>>> for i in range(1,3+1): # +1 because the range is n-1 in python
... for j in range(1,i-1+1):
... print (i,j)
...
(2, 1)
(3, 1)
(3, 2)
I suppose maybe it has to do with when i is 1?
(map (lambda (j) (list 1 j)) '())
; ()
Is that just an identity in Scheme that a map with an empty list is always an empty list?
When i is 1, the inner map is over (range 1 0), which is () by your own definition. Since map takes a procedure and a list (or lists) of values, applies the procedure to each value in the list in turn, and returns a list containing the results, mapping any procedure over a list containing no values will return a list containing no values.
It might help to create a simple definition for map to see how this might work. Note that this definition is not fully featured; it only takes a single list argument:
(define (my-map proc xs)
(if (null? xs)
'()
(cons (proc (car xs))
(my-map proc (cdr xs)))))
Here, when the input list is empty, there are no values to map over, so an empty list is returned. Otherwise the procedure proc is applied to the first value in the input list, and the result is consed onto the result of mapping over the rest of the list.
A couple of observations:
First, the empty list is not represented by nil in either standard Scheme or vanilla Racket, and you should not be using it. In the early days of Scheme nil was allowed as a crutch for programmers coming from other lisps, but this has not been the case for a long time. I don't think that it was ever in any of the RnRS standards, but nil may have survived in some specific implementations until maybe R4RS (1991). SICP was from that era. Today you should use '() to represent empty list literals in Scheme so that your code can run on any Scheme implementation. Racket's #lang sicp allows code directly from the book to be run, but that should not keep you from using the common notation. Note that Common Lisp does use nil as a self-evaluating symbol to represent both the empty list, and boolean false. Seeing this in Scheme just doesn't look right today.
Second, you will probably be led astray more often than to wisdom by thinking in terms of Python when trying to understand Scheme code. In this particular case, map is an iteration construct, but it is not the same thing as a for loop. A for loop is usually used for side-effects, but map is used to transform a list. Scheme has a for-each form which is meant to be used for its side-effects, and in that sense is more like a for loop. The Python version that is posted above is not at all like the Scheme version, though. Instead of returning the results in a list, the results are printed. In the Scheme code, when i is 1, the inner mapping is over (range 1 0) --> (). But, in the Python code, when i is 1, the inner loop is over range(1, 1), so the body of this for loop is not executed and nothing is printed.
Better to think carefully about the Scheme code you want to understand, falling back on basic definitions, than to cobble together a model based on Python that has possibly unconsidered corner cases.
Related
write a function in lisp called number(N) that you have to use a nonnegative integer N, and produce the list of all integers from 1 up to and including N.
(defun numbers (N)
(if (<= N 0)
nil
(cons N nil)
(numbers (- N 1)))
I checked some questions, but most of them use loop and range, but this question doesn't allowed me to do this, so I have to use recursion instead:
here is my code, but this code keeps giving me warning:
; caught STYLE-WARNING:
; The variable N is defined but never used.
;
; compilation unit finished
; caught 1 ERROR condition
; caught 1 STYLE-WARNING condition
I think my algorithm is correct ,but because I am new to lisp, I still don't know how to write the function properly. It is grateful if anyone could gave me any help.
IF has generally a common syntax, but there are exceptions
Generally in Lisps like Common Lisp the if operator allows the following syntax:
IF test-form then-form [else-form]
This means that in Lisp usually zero or one else-form are allowed. An example is if in Common Lisp.
In Emacs Lisp multiple else-forms are allowed. Emacs Lisp has the following syntax:
IF test-form then-form else-form*
This means that in Emacs Lisp zero or more else-forms are allowed.
Thus: it's important to mention which language&dialect you are actually using.
Your code
a) Let's assume that you use Common Lisp with its IF syntax.
Your code:
(defun numbers (N)
(if (<= N 0)
nil
(cons N nil)
(numbers (- N 1)))
Your code has the problem, that there are more than one else clauses. You need to write a version which has a single else clause.
b) Let's assume that you use Emacs Lisp with its IF syntax with multiple else forms.
Your code:
(defun numbers (N)
(if (<= N 0)
nil
(cons N nil)
(numbers (- N 1)))
Here the (cons N nil) form is allowed, but has no effect. Its return value is not used and it has no side effect. You could delete it and it would make no difference. Again: you would need how to combine its effect with the form (numbers (- N 1)).
Syntax error: missing closing parenthesis
There is another problem in your code. The s-expressions are not complete -> a closing parenthesis is missing:
(defun numbers (N)
(if (<= N 0)
nil
(cons N nil)
(numbers (- N 1)))
As you can see a closing parenthesis is missing at the end.
Thus your code can not be read by Lisp.
There are two ways one generally can avoid this problem:
count the parentheses and set them accordingly
use the editor to count the parentheses
Most people prefer the latter.
The way to think about this is to think about what the algorithm should be:
To compute the numbers from 1 to n:
if n is less than 1 then there are no numbers, so this is the empty list;
otherwise we want a list which looks like (... n), where ... is all the numbers from 1 to n-1.
Note that we want the numbers in forward order: this is going to be critical.
Doing this is slightly difficult in Lisp because we want the number to be at the end of the list, and access to the ends of lists is hard.
Here is the start of a version which builds the list backwards (so this is not the right answer).
(defun numbers (n)
(if (< n 1)
'() ;the empty list
;; n 1 or more, so build a list which is (n . ...)
(cons n <some function involving n>)))
Well, OK, what function should we call recursively? Do we have a function which returns the list we want? Well, yes: it's numbers, with an argument which is one less than n!
(defun numbers (n)
(if (< n 1)
'()
(cons n (numbers (- n 1)))))
And this function works. But it gets the wrong answer: the list is backwards:
> (numbers 10)
(10 9 8 7 6 5 4 3 2 1)
There are two fixes to this problem: the first is to build the list forwards, using append. This version looks like this (remember append wants to append two lists: it doesn't append an element to the end of a list):
(defun numbers (n)
(if (< n 1)
'()
(append (numbers (- n 1)) (list n))))
This gets the right answer:
> (numbers 10)
(1 2 3 4 5 6 7 8 9 10)
but it's a terrible answer: append has to walk all the way down the list (lists in Lisp are chains of conses: there is no fast access to the end of a list), copying it as it goes, to append the new element. So this has absolutely terrible space & time complexity. Programs written like this are why 'Lisp is slow'.
A better approach is to build the list backwards and then reverse it.
(defun numbers (n)
(reverse (numbers-backwards n)))
(defun numbers-backwards (n)
(if (< n 1)
'()
(cons n (numbers-backwards (- n 1)))))
The problem with this, from the homework perspective, might be that using reverse is not allowed. That's OK, we can write it, recursively. The implementation is slightly fiddly, but this is going to help us below.
(defun reverse-list (l)
;; in real life reverse-list-accumulator would be a local function
(reverse-list-accumulator l '()))
(defun reverse-list-accumulator (l accum)
(if (null l)
accum
(reverse-list-accumulator (rest l) (cons (first l) accum))))
The way this works is that reverse-list calls this auxiliary function with an extra argument. The auxiliary function then checks the list, and if it's not empty it calls itself with the tail of the list and the head of the list consed onto the auxiliary argument. If it is empty, it returns the auxiliary argument. It's a little subtle but you can see that this in fact reverses the list.
So now we can write our function using only recursive functions we wrote:
(defun numbers (n)
(reverse-list (numbers-backwards n)))
But now there should be a moment of inspiration: why are we doing this whole
build-it-backwards-and-reverse-it thing? Why don't we just make numbers do the accumulator trick itself! Well, we can do that:
(defun numbers (n)
(numbers-accumulator n '()))
(defun numbers-accumulator (n accum)
(if (< n 1)
accum
(numbers-accumulator (- n 1) (cons n accum))))
And now we don't need to reverse the list, and for added value our
function is 'tail recursive' and will generally be compiled much more
efficiently.
A real-life version of numbers might look more like this, using a local function:
(defun numbers (n)
(labels ((numbers-accumulator (m accum)
(if (< m 1)
accum
(numbers-accumulator (- m 1) (cons m accum)))))
(numbers-accumulator n '())))
Here is a comparison between the version of numbers using append and the above function, on an argument small enough that the append version does not overflow the stack.
> (time (progn (numbers/append 2000) (values)))
Timing the evaluation of (progn (numbers/append 2000) (values))
User time = 0.024
System time = 0.001
Elapsed time = 0.017
Allocation = 32176304 bytes
97 Page faults
> (time (progn (numbers 2000) (values)))
Timing the evaluation of (progn (numbers 2000) (values))
User time = 0.000
System time = 0.000
Elapsed time = 0.001
Allocation = 32000 bytes
0 Page faults
You can see how terrible the append version is, and how good the other one is: this is a 64-bit Lisp, and conses are two words or 16 bytes: it has allocated precisely 2000 cons cells which is the minimum it could do.
Write a Racket function count-occurrences that consumes two lists of symbols and produces a list of
natural numbers measuring how many times items in the first list occur in the second list. For example:
(count-occurrences (list 'a 'b 'a 'q) (list 'r 'a 'b 'e 'b 'g))
=> (list 1 2 1 0)
I've been struggling with this question - how do I use map to do it, since for this question it's specified we can't use recursion.
My original idea was to do the following:
(define (count-occurrences los1 los2)
(map
(length (filter (lambda (x) (symbol=? x (first los1))) los2))
los1))
but using length here can only get us the number 'a occurred, instead of going into recursion. and for abstract functions there can only be one argument for the inside function, so I'm totally lost.
If ... x ... is an open formula, i.e. an expression which references an unbound variable x, wrapping it in a lambda form makes it a function in x, like so:
(lambda (x) ... x ... )
where x becomes bound by that lambda form; a parameter to this so called lambda function, which is to say, an anonymous function introduced by a lambda form.
So, the solution for your troubles is quite simple: recognize that
(length
(filter (lambda (x)
(symbol=? x (first los1)))
los2))
should actually be
(length
(filter (lambda (x)
(symbol=? x y))
los2))
where y refers to each of the elements of los1 in turn, not just the first one; and that it is then an open formula in y – that is to say, y is unbound, free, there. So we must capture it, and make it bound, by ... yes, enclosing this expression in a lambda form, thereby making it a function in y! Like so:
(lambda (y)
(length
(filter (lambda (x)
(symbol=? x y))
los2)))
And this is what gets mapped over los1.
With this simple tweak, your code becomes a correct, working function definition.
Does this fit your requirements and restrictions?
(define (count-occurrences lst1 lst2)
(map (lambda (e1)
(count (lambda (e2) (eq? e1 e2))
lst2))
lst1))
A good way to keep track of keys and values is with a hash-table. While it is possible to write count-occurrences using map and passing a lambda, being explicit may make it easier to see what is going on.
;;; list list -> list
;;;
(define (count-occurrences keys values)
;; Create data structure
(define ht (make-hash))
;; Initialize data structure with keys
;; Set the value of each key to zero
;; Since we have not started counting
(for ([k keys])
(hash-set! ht k 0))
;; Iterate over values and
;; Increment hash table if
;; When value is a key
(for ([v values])
(if (hash-has-key? ht v)
(hash-set! ht v (+ (hash-ref ht v) 1))
null))
;; Iterate over keys and
;; Create list of values
(for/list ([k keys])
(hash-ref ht k)))
Since recursion is prohibited, explicitly looping may make for more maintainable/readable code than an implicit loop. Besides, the variations of for are worth knowing. Hash tables have the advantage that duplicate keys read the same value and there is no need to track the same key twice.
One of the engineering advantages of using for rather than map is that it is easier to reason about the running time. The running time for this code is 2m + n where m is keys and n is values. Solutions using map will typically be m * n. There's nothing inherently wrong with that. But it is worth recognizing.
I have a question regarding finding the largest list in a group of lists in scheme.
For example, we define:
(define manylsts (list (list 9 (list 8 7)) 6 (list 5 (list 4 3 2) 1)))
How would I go about finding the largest list in manylsts?
Thank you
You make a procedure that evaluates to zero if it's argument is not a list. (eg. 9), then if its a list you foldl over the elements using length of the argument as accumulator with a lambda that does max between the recursion of the first argument with the accumulator. It would look something like this:
(define (max-children tree)
(if <??>
(foldl (λ (x acc)
(max <??> (max-children <??>)))
(length <??>)
<??>)
0))
Of course there are many ways of doing this, including explicit recursion, but this was the first thing I though of.
I will answer this question as you asked it.
You said you want to
finding the largest list in manylsts
Since you included a non-listed element inside manylsts you want to have a definition that tells you how big is an element (if is a list).
So I wrote the function elemenlen that returns the length of a list if the given element is a list and 0 otherwise.
(define elemenlen
(λ (a)
(if (list? a) (length a) 0)
))
Then I decided I was going to sort them in order of length and then return the first element. So I need a function that returns a boolean value to use it with sort function included in racket/base.
(define list<
(λ (listA listB)
(< (elemenlen listA) (elemenlen listB))))
(define list>
(λ (listA listB)
(not (list< listA listB))))
The first function returns #t if listA is smaller than listB. The second function returns #t if listA is bigger than listB.
Lastly, biggestElement does the whole trick, sorts the elements in list L in descending order (based on length) and returns the first element.
(define biggestElement
(λ (L)
(car (sort L list>)
)))
The function is used like this:
>(biggestElement '((3 2 1) 1 (1 (2 3) 3))
'(1 (2 3) 3)
That is just one way of doing it, there are other ways of doing it, keep it up and tell us if it helped you.
As you see, I decomposed the big problem into little problems. This is a very handy way of doing your DrRacket homework.
In an effort to find a simple example of CPS which doesn't give me a headache , I came across this Scheme code (Hand typed, so parens may not match) :
(define fact-cps
(lambda(n k)
(cond
((zero? n) (k 1))
(else
(fact-cps (- n 1)
(lambda(v)
(k (* v n))))))))
(define fact
(lambda(n)
(fact-cps n (lambda(v)v)))) ;; (for giggles try (lambda(v)(* v 2)))
(fact 5) => 120
Great, but Scheme isn't Common Lisp, so I took a shot at it:
(defun not-factorial-cps(n k v)
(declare (notinline not-factorial-cps)) ;; needed in clisp to show the trace
(cond
((zerop n) (k v))
((not-factorial-cps (1- n) ((lambda()(setq v (k (* v n))))) v))))
;; so not that simple...
(defun factorial(n)
(not-factorial-cps n (lambda(v)v) 1))
(setf (symbol-function 'k) (lambda(v)v))
(factorial 5) => 120
As you can see, I'm having some problems, so although this works, this has to be wrong. I think all I've accomplished is a convoluted way to do accumulator passing style. So other than going back to the drawing board with this, I had some questions: Where exactly in the Scheme example is the initial value for v coming from? Is it required that lambda expressions only be used? Wouldn't a named function accomplish more since you could maintain the state of each continuation in a data structure which can be manipulated as needed? Is there in particular style/way of continuation passing style in Common Lisp with or without all the macros? Thanks.
The problem with your code is that you call the anonymous function when recurring instead of passing the continuation like in the Scheme example. The Scheme code can easily be made into Common Lisp:
(defun fact-cps (n &optional (k #'values))
(if (zerop n)
(funcall k 1)
(fact-cps (- n 1)
(lambda (v)
(funcall k (* v n))))))
(fact-cps 10) ; ==> 3628800
Since the code didn't use several terms or the implicit progn i switched to if since I think it's slightly more readable. Other than that and the use of funcall because of the LISP-2 nature of Common Lisp it's the identical code to your Scheme version.
Here's an example of something you cannot do tail recursively without either mutation or CPS:
(defun fmapcar (fun lst &optional (k #'values))
(if (not lst)
(funcall k lst)
(let ((r (funcall fun (car lst))))
(fmapcar fun
(cdr lst)
(lambda (x)
(funcall k (cons r x)))))))
(fmapcar #'fact-cps '(0 1 2 3 4 5)) ; ==> (1 1 2 6 24 120)
EDIT
Where exactly in the Scheme example is the initial value for v coming
from?
For every recursion the function makes a function that calls the previous continuation with the value from this iteration with the value from the next iteration, which comes as an argument v. In my fmapcar if you do (fmapcar #'list '(1 2 3)) it turns into
;; base case calls the stacked lambdas with NIL as argument
((lambda (x) ; third iteration
((lambda (x) ; second iteration
((lambda (x) ; first iteration
(values (cons (list 1) x)))
(cons (list 2) x)))
(cons (list 3) x))
NIL)
Now, in the first iteration the continuation is values and we wrap that in a lambda together with consing the first element with the tail that is not computed yet. The next iteration we make another lambda where we call the previous continuation with this iterations consing with the tail that is not computed yet.. At the end we call this function with the empty list and it calls all the nested functions from end to the beginning making the resulting list in the correct order even though the iterations were in oposite order from how you cons a list together.
Is it required that lambda expressions only be used? Wouldn't a named
function accomplish more since you could maintain the state of each
continuation in a data structure which can be manipulated as needed?
I use a named function (values) to start it off, however every iteration of fact-cps has it's own free variable n and k which is unique for that iteration. That is the data structure used and for it to be a named function you'd need to use flet or labels in the very same scope as the anonymous lambda functions are made. Since you are applying previous continuation in your new closure you need to build a new one every time.
Is there in particular style/way of continuation passing style in
Common Lisp with or without all the macros?
It's the same except for the dual namespace. You need to either funcall or apply. Other than that you do it as in any other language.
I have to define a variadic function in Scheme that takes the following form:
(define (n-loop procedure [a list of pairs (x,y)]) where the list of pairs can be any length.
Each pair specifies a lower and upper bound. That is, the following function call: (n-loop (lambda (x y) (inspect (list x y))) (0 2) (0 3)) produces:
(list x y) is (0 0)
(list x y) is (0 1)
(list x y) is (0 2)
(list x y) is (1 0)
(list x y) is (1 1)
(list x y) is (1 2)
Obviously, car and cdr are going to have to be involved in my solution. But the stipulation that makes this difficult is the following. There are to be no assignment statements or iterative loops (while and for) used at all.
I could handle it using while and for to index through the list of pairs, but it appears I have to use recursion. I don't want any code solutions, unless you feel it is necessary for explanation, but does anyone have a suggestion as to how this might be attacked?
The standard way to do looping in Scheme is to use tail recursion. In fact, let's say you have this loop:
(do ((a 0 b)
(b 1 (+ a b))
(i 0 (+ i 1)))
((>= i 10) a)
(eprintf "(fib ~a) = ~a~%" i a))
This actually get macro-expanded into something like the following:
(let loop ((a 0)
(b 1)
(i 0))
(cond ((>= i 10) a)
(else (eprintf "(fib ~a) = ~a~%" i a)
(loop b (+ a b) (+ i 1)))))
Which, further, gets macro-expanded into this (I won't macro-expand the cond, since that's irrelevant to my point):
(letrec ((loop (lambda (a b i)
(cond ((>= i 10) a)
(else (eprintf "(fib ~a) = ~a~%" i a)
(loop b (+ a b) (+ i 1)))))))
(loop 0 1 0))
You should be seeing the letrec here and thinking, "aha! I see recursion!". Indeed you do (specifically in this case, tail recursion, though letrec can be used for non-tail recursions too).
Any iterative loop in Scheme can be rewritten as that (the named let version is how loops are idiomatically written in Scheme, but if your assignment won't let you use named let, expand one step further and use the letrec). The macro-expansions I've described above are straightforward and mechanical, and you should be able to see how one gets translated to the other.
Since your question asked how about variadic functions, you can write a variadic function this way:
(define (sum x . xs)
(if (null? xs) x
(apply sum (+ x (car xs)) (cdr xs))))
(This is, BTW, a horribly inefficient way to write a sum function; I am just using it to demonstrate how you would send (using apply) and receive (using an improper lambda list) arbitrary numbers of arguments.)
Update
Okay, so here is some general advice: you will need two loops:
an outer loop, that goes through the range levels (that's your variadic stuff)
an inner loop, that loops through the numbers in each range level
In each of these loops, think carefully about:
what the starting condition is
what the ending condition is
what you want to do at each iteration
whether there is any state you need to keep between iterations
In particular, think carefully about the last point, as that is how you will nest your loops, given an arbitrary number of nesting levels. (In my sample solution below, that's what the cur variable is.)
After you have decided on all these things, you can then frame the general structure of your solution. I will post the basic structure of my solution below, but you should have a good think about how you want to go about solving the problem, before you look at my code, because it will give you a good grasp of what differences there are between your solution approach and mine, and it will help you understand my code better.
Also, don't be afraid to write it using an imperative-style loop first (like do), then transforming it to the equivalent named let when it's all working. Just reread the first section to see how to do that transformation.
All that said, here is my solution (with the specifics stripped out):
(define (n-loop proc . ranges)
(let outer ((cur ???)
(ranges ranges))
(cond ((null? ranges) ???)
(else (do ((i (caar ranges) (+ i 1)))
((>= i (cadar ranges)))
(outer ??? ???))))))
Remember, once you get this working, you will still need to transform the do loop into one based on named let. (Or, you may have to go even further and transform both the outer and inner loops into their letrec forms.)