How do I make the substitution? I tried to trace but I don't really get what is going on...
the code:
(define (repeated f n)
(if (zero? n)
identity
(lambda (x) ((repeated f (- n 1)) (f x)))))
f is a function and n is an integer that gives the number of times we should apply f.
....can someone help me to interpret it. I know it returns several procedures and i want to believe that it goes f(f(f(x)))
okey i will re-ask this question but in different manner, because i didn't really get an answer last time. consider this code
(define (repeated f n)
(if (zero? n)
identity
(lambda (x) ((repeated f (- n 1)) (f x)))))
where n is a positive integer and f is an arbitrary function: how does scheme operate on this code lets say we give (repeated f 2). what will happen? this is what think:
(f 2)
(lambda (x) ((repeated f (- 2 1)) (f x))))
(f 1)
(lambda (x) ((lambda (x) ((repeated f (- 1 1)) (f x)))) (f x))))
(f 0)
(lambda (x) ((lambda (x) (identity (f x)))) (f x))))
> (lambda (x) ((lambda (x) (identity (f x)))) (f x))))
> (lambda (x) ((lambda (x) ((f x)))) (f x))))
here is were i get stuck first i want it to go (f(f(x)) but now i will get (lambda x ((f x) (f x)) , the parentheses is certaintly wrong , but i think you understand what i mean. What is wrong with my arguments on how the interpreter works
Your implementation actually delays the further recursion and return a procedure whose body will create copies of itself to fulfill the task at runtime.
Eg. (repeated double 4) ==> (lambda (x) ((repeated double (- 4 1)) (double x)))
So when calling it ((repeated double 4) 2) it runs ((repeated double (- 4 1)) (double 2)))
where the operand part evaluates to (lambda (x) ((repeated double (- 3 1)) (double x))) and so on making the closures at run time so the evaluation becomes equal to this, but in stages during runtime..
((lambda (x) ((lambda (x) ((lambda (x) ((lambda (x) ((lambda (x) (identity x)) (double x))) (double x))) (double x))) (double x))) 2)
A different way of writing the same functionality would be like this:
(define (repeat fun n)
(lambda (x)
(let repeat-loop ((n n)
(x x))
(if (<= n 0)
x
(repeat-loop (- n 1) (fun x))))))
(define (double x) (+ x x))
((repeat double 4) 2) ; ==> 32
You've got a function that takes a function f and an non-negative integer n and returns the function fn, i.e., f(f(f(…f(n)…). Depending on how you think of your recursion, this could be implemented straightforwardly in either of two ways. In both cases, if n is 0, then you just need a function that returns its argument, and that function is the identity function. (This is sort of by convention, in the same way that x0 = 1. It does make sense when it's considered in more depth, but that's probably out of scope for this question.)
How you handle the recursive case is where you have some options. The first option is to think of fn(x) as f(fn-1(x)), where you call f with the result of calling fn-1 with x:
(define (repeated f n)
(if (zero? n)
identity
(lambda (x)
(f ((repeated f (- n 1)) x)))))
The other option is to think of fn(x) as fn-1(f(x)) where _fn-1 gets called with the result of f(x).
(define (repeated f n)
(if (zero? n)
identity
(lambda (x)
((repeated f (- n 1)) (f x)))))
In either case, the important thing to note here is that in Scheme, a form like
(function-form arg-form-1 arg-form-2 ...)
is evaluated by evaluating function-form to produce a value function-value (which should be a function) and evaluating each arg-form-i to produce values arg-value-i, and then calling _function-value_ with the arg-values. Since (repeated ...) produces a function, it's suitable as a function-form:
(f ((repeated f (- n 1)) x))
; |--- f^{n-1} ------|
; |---- f^{n-1}(x) ------|
;|------f(f^{n-1}(x)) ------|
((repeated f (- n 1)) (f x))
; |--- f^{n-1} ------|
;|---- f^{n-1}(f(x))--------|
Based on Will Ness's comment, it's worth pointing out that while these are somewhat natural ways to decompose this problem (i.e., based on the equalities fn(x) = fn-1(f(x)) = f(fn-1(x))), it's not necessarily the most efficient. These solutions both require computing some intermediate function objects to represent fn-1 that require a fair amount of storage, and then some computation on top of that. Computing fn(x) directly is pretty straightforward and efficient with, e.g., repeat:
(define (repeat f n x)
(let rep ((n n) (x x))
(if (<= n 0)
x
(rep (- n 1) (f x)))))
A more efficient version of repeated, then, simply curries the x argument of repeat:
(define (repeated f n)
(lambda (x)
(repeat f n x)))
This should have better run time performance than either of the other implementations.
Danny. I think that if we work repeated with small values of n (0, 1 and 2) will be able to see how the function translates to f(f(f(...(x))). I assume that identity's implementation is (define (identity x) x) (i.e. returns its only parameter as is), and that the "then" part of the if should be (identity f).
(repeated f 0) ;should apply f only once, no repetition
-> (identity f)
-> f
(repeated f 1) ;expected result is f(f(x))
-> (lambda (x) ((repeated f 0) (f x)))
-> (lambda (x) (f (f x))) ;we already know that (repeated f 0) is f
(repeated f 2) ;expected result is f(f(f(x)))
-> (lambda (x) ((repeated f 1) (f x)))
-> (lambda (x) (f (f (f x)))) ; we already know that (repeated f 1) if f(f(x))
... and so on.
Equational reasoning would be very helpful here. Imagine lambda calculus-based language with Haskell-like syntax, practically a combinatory calculus.
Here, parentheses are used just for grouping of expressions (not for function calls, which have no syntax at all – just juxtaposition): f a b c is the same as ((f a) b) c, the same as Scheme's (((f a) b) c). Definitions like f a b = ... are equivalent to (define f (lambda (a) (lambda (b) ...))) (and shortcut for (lambda (a) ...) is (\a-> ...).
Scheme's syntax just obscures the picture here. I don't mean parentheses, but being forced to explicit lambdas instead of just equations and freely shifting the arguments around:
f a b = \c -> .... === f a b c = .... ; `\ ->` is for 'lambda'
Your code is then nearly equivalent to
repeated f n x ; (define (repeated f n)
| n <= 0 = x ; (if (zero? n) identity
| otherwise = repeated f (n-1) (f x) ; (lambda (x)
; ((repeated f (- n 1)) (f x)))))
(read | as "when"). So
repeated f 2 x = ; ((repeated f 2) x) = ((\x-> ((repeated f 1) (f x))) x)
= repeated f 1 (f x) ; = ((repeated f 1) (f x))
= repeated f 0 (f (f x)) ; = ((\y->((repeated f 0) (f y))) (f x))
= f (f x) ; = ((\z-> z) (f (f x)))
; = (f (f x))
The above reduction sequence leaves out the particulars of environment frames creation and chaining in Scheme, but it all works out pretty much intuitively. f is the same f, n-1 where n=2 is 1 no matter when we perform the subtraction, etc..
Related
I want to solve the scheme problem
I define the code two, three, sq, plus
two is f(f(x)) // three is f(f(f(x)))
sq is square function ex ((two sq)3) is 81
plus is
(define (plus m n)
(lambda (f) (lambda (x) (m f (n f x))
I don't know why wrong that please let me know
You are confusing arity of functions. three and two are not functions of two parameters. They are functions that take a parameter and return a function. That returned function again takes a parameter.
Try the evaluating the following:
(let ((inc (lambda (x) (+ x 1))))
(list ((three inc) 0)
((two inc) 0)))
Your plus should be:
(define (plus m n)
(lambda (f) (lambda (x) ((m f) ((n f) x)))))
Now this should give you (3 2 5)
(let ((inc (lambda (x) (+ x 1))))
(list ((three inc) 0)
((two inc) 0)
(((plus two three) inc) 0)))
The code to repeat a function in Scheme is the following:
(define (repeat f n)
(if (= n 1)
f
(lambda (x) (f ((repeat f (- n 1)) x)))))
But I don't manage to understand how the recursion here works with the lambda(x) and so on.
Can someone explain this with an example like (repeat f 3)?
Thank you
Using the substitution method and working "upwards":
(repeat f 1)
--> f
which is equivalent to (lambda (x) (f x)), if f is a unary function.
And then,
(repeat f 2)
--> (lambda (x) (f ((repeat f 1) x)))
--> (lambda (x) (f (f x)))
and
(repeat f 3)
--> (lambda (x) (f ((repeat f 2) x)))
[through name change in the "inner" lambda]
--> (lambda (x) (f ((lambda (y) (f (f y))) x)))
[through ((lambda (y) (f (f y))) x) --> (f (f x))]
--> (lambda (x) (f (f (f x))))
The thing to realize is that this repeat function doesn't actually call f n times. It returns a new function that will call f n times. You can see this in the base case: when (= n 1), it simply returns f, it doesn't execute (f).
(repeat f (- n 1)) calls repeat recursively to get a function that calls f one less time. lambda is then used to construct a new function that calls this new function and then calls f to make the total n calls.
I'm trying to edit the current program I have
(define (sumofnumber n)
(if (= n 0)
1
(+ n (sumofnumber (modulo n 2 )))))
so that it returns the sum of an n number of positive squares. For example if you inputted in 3 the program would do 1+4+9 to get 14. I have tried using modulo and other methods but it always goes into an infinite loop.
The base case is incorrect (the square of zero is zero), and so is the recursive step (why are you taking the modulo?) and the actual operation (where are you squaring the value?). This is how the procedure should look like:
(define (sum-of-squares n)
(if (= n 0)
0
(+ (* n n)
(sum-of-squares (- n 1)))))
A definition using composition rather than recursion. Read the comments from bottom to top for the procedural logic:
(define (sum-of-squares n)
(foldl + ; sum the list
0
(map (lambda(x)(* x x)) ; square each number in list
(map (lambda(x)(+ x 1)) ; correct for range yielding 0...(n - 1)
(range n))))) ; get a list of numbers bounded by n
I provide this because you are well on your way to understanding the idiom of recursion. Composition is another of Racket's idioms worth exploring and often covered after recursion in educational contexts.
Sometimes I find composition easier to apply to a problem than recursion. Other times, I don't.
You're not squaring anything, so there's no reason to expect that to be a sum of squares.
Write down how you got 1 + 4 + 9 with n = 3 (^ is exponentiation):
1^2 + 2^2 + 3^2
This is
(sum-of-squares 2) + 3^2
or
(sum-of-squares (- 3 1)) + 3^2
that is,
(sum-of-squares (- n 1)) + n^2
Notice that modulo does not occur anywhere, nor do you add n to anything.
(And the square of 0 is 0 , not 1.)
You can break the problem into small chunks.
1. Create a list of numbers from 1 to n
2. Map a square function over list to square each number
3. Apply + to add all the numbers in squared list
(define (sum-of-number n)
(apply + (map (lambda (x) (* x x)) (sequence->list (in-range 1 (+ n 1))))))
> (sum-of-number 3)
14
This is the perfect opportunity for using the transducers technique.
Calculating the sum of a list is a fold. Map and filter are folds, too. Composing several folds together in a nested fashion, as in (sum...(filter...(map...sqr...))), leads to multiple (here, three) list traversals.
But when the nested folds are fused, their reducing functions combine in a nested fashion, giving us a one-traversal fold instead, with the one combined reducer function:
(define (((mapping f) kons) x acc) (kons (f x) acc)) ; the "mapping" transducer
(define (((filtering p) kons) x acc) (if (p x) (kons x acc) acc)) ; the "filtering" one
(define (sum-of-positive-squares n)
(foldl ((compose (mapping sqr) ; ((mapping sqr)
(filtering (lambda (x) (> x 0)))) ; ((filtering {> _ 0})
+) 0 (range (+ 1 n)))) ; +))
; > (sum-of-positive-squares 3)
; 14
Of course ((compose f g) x) is the same as (f (g x)). The combined / "composed" (pun intended) reducer function is created just by substituting the arguments into the definitions, as
((mapping sqr) ((filtering {> _ 0}) +))
=
( (lambda (kons)
(lambda (x acc) (kons (sqr x) acc)))
((filtering {> _ 0}) +))
=
(lambda (x acc)
( ((filtering {> _ 0}) +)
(sqr x) acc))
=
(lambda (x acc)
( ( (lambda (kons)
(lambda (x acc) (if ({> _ 0} x) (kons x acc) acc)))
+)
(sqr x) acc))
=
(lambda (x acc)
( (lambda (x acc) (if (> x 0) (+ x acc) acc))
(sqr x) acc))
=
(lambda (x acc)
(let ([x (sqr x)] [acc acc])
(if (> x 0) (+ x acc) acc)))
which looks almost as something a programmer would write. As an exercise,
((filtering {> _ 0}) ((mapping sqr) +))
=
( (lambda (kons)
(lambda (x acc) (if ({> _ 0} x) (kons x acc) acc)))
((mapping sqr) +))
=
(lambda (x acc)
(if (> x 0) (((mapping sqr) +) x acc) acc))
=
(lambda (x acc)
(if (> x 0) (+ (sqr x) acc) acc))
So instead of writing the fused reducer function definitions ourselves, which as every human activity is error-prone, we can compose these reducer functions from more atomic "transformations" nay transducers.
Works in DrRacket.
I am really new to scheme functional programming. I recently came across Y-combinator function in lambda calculus, something like this Y ≡ (λy.(λx.y(xx))(λx.y(xx))). I wanted to implement it in scheme, i searched alot but i didn't find any implementation which exactly matches the above given structure. Some of them i found are given below:
(define Y
(lambda (X)
((lambda (procedure)
(X (lambda (arg) ((procedure procedure) arg))))
(lambda (procedure)
(X (lambda (arg) ((procedure procedure) arg)))))))
and
(define Y
(lambda (r)
((lambda (f) (f f))
(lambda (y)
(r (lambda (x) ((y y) x)))))))
As you can see, they dont match with the structure of this Y ≡ (λy.(λx.y(xx))(λx.y(xx))) combinator function. How can I implement it in scheme in exactly same way?
In a lazy language like Lazy Racket you can use the normal order version, but not in any of the applicative order programming languages like Scheme. They will just go into an infinite loop.
The applicative version of Y is often called a Z combinator:
(define Z
(lambda (f)
((lambda (g) (g g))
(lambda (g)
(f (lambda args (apply (g g) args)))))))
Now the first thing that happens when this is applied is (g g) and since you can always substitute a whole application with the expansion of it's body the body of the function can get rewritten to:
(define Z
(lambda (f)
((lambda (g)
(f (lambda args (apply (g g) args))))
(lambda (g)
(f (lambda args (apply (g g) args)))))))
I haven't really changed anything. It's just a little more code that does exactly the same. Notice this version uses apply to support multiple argument functions. Imagine the Ackermann function:
(define ackermann
(lambda (m n)
(cond
((= m 0) (+ n 1))
((= n 0) (ackermann (- m 1) 1))
(else (ackermann (- m 1) (ackermann m (- n 1)))))))
(ackermann 3 6) ; ==> 509
This can be done with Z like this:
((Z (lambda (ackermann)
(lambda (m n)
(cond
((= m 0) (+ n 1))
((= n 0) (ackermann (- m 1) 1))
(else (ackermann (- m 1) (ackermann m (- n 1))))))))
3
6) ; ==> 509
Notice the implementations is exactly the same and the difference is how the reference to itself is handled.
EDIT
So you are asking how the evaluation gets delayed. Well the normal order version looks like this:
(define Y
(lambda (f)
((lambda (g) (g g))
(lambda (g) (f (g g))))))
If you look at how this would be applied with an argument you'll notice that Y never returns since before it can apply f in (f (g g)) it needs to evaluate (g g) which in turn evaluates (f (g g)) etc. To salvage that we don't apply (g g) right away. We know (g g) becomes a function so we just give f a function that when applied will generate the actual function and apply it. If you have a function add1 you can make a wrapper (lambda (x) (add1 x)) that you can use instead and it will work. In the same manner (lambda args (apply (g g) args)) is the same as (g g) and you can see that by just applying substitution rules. The clue here is that this effectively stops the computation at each step until it's actually put into use.
I'm trying to create a function that wraps itself n times using a function called repeat
(define (repeat f n)
(if (= n 1)
f
(repeat (lambda (x) (f x)) (- n 1))))
((repeat inc 5) 2)
I'm expecting the result to be equal to
(inc (inc (inc (inc (inc 2))))) ; 7
But my result is 3
What am I doing wrong?
To be clear, I want repeat to return a function that accepts a single argument. f should not be applied until the return value of repeat is called with an argument.
e.g.,
(define inc5 (repeat inc 5))
(inc5 2) ; => 7
p.s.,
This is related but not identical to exercise 1.43 in SICP. I've solved the problem as it is presented there, but I'm curious if it can be solved this way too.
The problem with your definition is that (lambda (x) (f x)) is the same as f, i.e., your repeat repeats only once.
I think what you need is
(define (repeat f n)
(if (= n 1)
f
(lambda (x) (f ((repeat f (- n 1)) x)))))
PS. Note that you are using Scheme syntax under the Common Lisp tag; you might want to update one or the other.
Lets take a look at a similar function.
(define (repeat-exp fn ct)
(if (= ct 1)
fn
(repeat `(lambda (x) (,fn x)) (- ct 1))))
Calling it will get you
> (repeat-exp inc 5)
'(lambda (x)
((lambda (x)
((lambda (x)
((lambda (x)
((lambda (x)
(#<procedure:inc> x))
x))
x))
x))
x))
>
As you can see, your initial function only gets called once; in the innermost evaluation. If you want it to get called at each level, you need to call it there too.
(define (repeat-exp2 fn ct)
(if (= ct 1)
fn
`(lambda (x)
(,fn (,(repeat-exp2 fn (- ct 1)) x)))))
> (repeat-exp2 inc 5)
'(lambda (x)
(#<procedure:inc>
((lambda (x)
(#<procedure:inc>
((lambda (x)
(#<procedure:inc>
((lambda (x)
(#<procedure:inc>
(#<procedure:inc> x)))
x)))
x)))
x)))
>
Now you can write the numeric equivalent.
(define (repeat2 fn ct)
(if (= ct 1)
fn
(lambda (x)
(fn ((repeat2 fn (- ct 1)) x)))))
which should do what you wanted initially.
> (repeat2 inc 5)
#<procedure>
> ((repeat2 inc 5) 2)
7