I just wrote the function add-registers for binary addition of two n-bit registers in Racket (using bit-add function as a helper):
(define (bit-add x y c)
(values (bitwise-xor x y c) (bitwise-ior (bitwise-and x y)
(bitwise-and x c)
(bitwise-and y c))))
(define (add-registers xs ys)
(let ([carry 0])
(values (reverse (for/list ([b1 (reverse xs)] [b2 (reverse ys)])
(let-values ([(nb nc) (bit-add b1 b2 carry)])
(set! carry nc)
nb)))
carry)))
But I found my code pretty ugly. So I wonder if this could be written more concisely and elegant?
Here's a new version of add-registers that looks somewhat nicer:
(define (add-registers xs ys)
(for/fold ([carry 0] [bs empty])
([b1 (reverse xs)] [b2 (reverse ys)])
(define-values (nb nc) (bit-add b1 b2 carry))
(values nc (cons nb bs))))
Related
I'm trying to write a code for extended Euclidian Algorithm in Scheme for an RSA implementation.
The thing about my problem is I can't write a recursive algorithm where the output of the inner step must be the input of the consecutive outer step. I want it to give the result of the most-outer step but as it can be seen, it gives the result of the most inner one. I wrote a program for this (it is a bit messy but I couldn't find time to edit.):
(define ax+by=1
(lambda (a b)
(define q (quotient a b))
(define r (remainder a b))
(define make-list (lambda (x y)
(list x y)))
(define solution-helper-x-prime (lambda (a b q r)
(if (= r 1) (- 0 q) (solution-helper-x-prime b r (quotient b r) (remainder b r)))
))
(define solution-helper-y-prime (lambda (a b q r)
(if (= r 1) (- r (* q (- 0 q) )) (solution-helper-y-prime b r (quotient b r) (remainder b r))
))
(define solution-first-step (lambda (a b q r)
(if (= r 1) (make-list r (- 0 q))
(make-list (solution-helper-x-prime b r (quotient b r) (remainder b r)) (solution-helper-y-prime b r (quotient b r) (remainder b r))))
))
(display (solution-first-step a b q r))
))
All kinds of help and advice would be greatly appreciated. (P.S. I added a scrrenshot of the instructions that was given to us but I can't see the image. If there is a problem, please let me know.)
This is a Diophantine equation and is a bit tricky to solve. I came up with an iterative solution adapted from this explanation, but had to split the problem in parts - first, obtain the list of quotients by applying the extended Euclidean algorithm:
(define (quotients a b)
(let loop ([a a] [b b] [lst '()])
(if (<= b 1)
lst
(loop b (remainder a b) (cons (quotient a b) lst)))))
Second, go back and solve the equation:
(define (solve x y lst)
(if (null? lst)
(list x y)
(solve y (+ x (* (car lst) y)) (cdr lst))))
Finally, put it all together and determine the correct signs of the solution:
(define (ax+by=1 a b)
(let* ([ans (solve 0 1 (quotients a b))]
[x (car ans)]
[y (cadr ans)])
(cond ((and (= a 0) (= b 1))
(list 0 1))
((and (= a 1) (= b 0))
(list 1 0))
((= (+ (* a (- x)) (* b y)) 1)
(list (- x) y))
((= (+ (* a x) (* b (- y))) 1)
(list x (- y)))
(else (error "Equation has no solution")))))
For example:
(ax+by=1 1027 712)
=> '(-165 238)
(ax+by=1 91 72)
=> '(19 -24)
(ax+by=1 13 13)
=> Equation has no solution
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.
Currently I have
(define filter
(λ (f xs)
(letrec [(filter-tail
(λ (f xs x)
(if (empty? xs)
x
(filter-tail f (rest xs)
(if (f (first xs))
(cons (first xs) x)
'()
)))))]
(filter-tail f xs '() ))))
It should be have as a filter function
However it outputs as
(filter positive? '(-1 2 3))
>> (3 2)
but correct return should be (2 3)
I was wondering if the code is correctly done using tail-recursion, if so then I should use a reverse to change the answer?
I was wondering if the code is correctly done using tail-recursion.
Yes, it is using a proper tail call. You have
(define (filter-tail f xs x) ...)
Which, internally is recursively applied to
(filter-tail f
(some-change-to xs)
(some-other-change-to x))
And, externally it's applied to
(filter-tail f xs '())
Both of these applications are in tail position
I should use a reverse to change the answer?
Yep, there's no way around it unless you're mutating the tail of the list (instead of prepending a head) as you build it. One of the comments you received alluded to this using set-cdr! (see also: Getting rid of set-car! and set-cdr!). There may be other techniques, but I'm unaware of them. I'd love to hear them.
This is tail recursive, requires the output to be reversed. This one uses a named let.
(define (filter f xs)
(let loop ([ys '()]
[xs xs])
(cond [(empty? xs) (reverse ys)]
[(f (car xs)) (loop (cons (car xs) ys) (cdr xs))]
[else (loop ys (cdr xs))])))
(filter positive? '(-1 2 3)) ;=> '(2 3)
Here's another one using a left fold. The output still has to be reversed.
(define (filter f xs)
(reverse (foldl (λ (x ys) (if (f x) (cons x ys) ys))
'()
xs)))
(filter positive? '(-1 2 3)) ;=> '(2 3)
With the "difference-lists" technique and curried functions, we can have
(define (fold c z xs)
(cond ((null? xs) z)
(else (fold c (c (car xs) z) (cdr xs)))))
(define (comp f g) (lambda (x) ; ((comp f g) x)
(f (g x))))
(define (cons1 x) (lambda (y) ; ((cons1 x) y)
(cons x y)))
(define (filter p xs)
((fold (lambda (x k)
(if (p x)
(comp k (cons1 x)) ; nesting's on the left
k))
(lambda (x) x) ; the initial continuation, IC
xs)
'()))
(display (filter (lambda (x) (not (zero? (remainder x 2)))) (list 1 2 3 4 5)))
This builds
comp
/ \
comp cons1 5
/ \
comp cons1 3
/ \
IC cons1 1
and applies '() to it, constructing the result list in the efficient right-to-left order, so there's no need to reverse it.
First, fold builds the difference-list representation of the result list in a tail recursive manner by composing the consing functions one-by-one; then the resulting function is applied to '() and is reduced, again, in tail-recursive manner, by virtues of the comp function-composition definition, because the composed functions are nested on the left, as fold is a left fold, processing the list left-to-right:
( (((IC+k1)+k3)+k5) '() ) ; writing `+` for `comp`
=> ( ((IC+k1)+k3) (k5 '()) ) ; and `kI` for the result of `(cons1 I)`
<= ( ((IC+k1)+k3) l5 ) ; l5 = (list 5)
=> ( (IC+k1) (k3 l5) )
<= ( (IC+k1) l3 ) ; l3 = (cons 3 l5)
=> ( IC (k1 l3) )
<= ( IC l1 ) ; l1 = (cons 1 l3)
<= l1
The size of the function built by fold is O(n), just like the interim list would have, with the reversal.
In order to implement derivative of given polynomial, I need to factorize the polynomial, i.e., (* 3 x y) should be the product of 3 and (* x y).
So I implemented a function multiplicand to get the second factor of a product:
(define (multiplicand p)
(let ((second-factor (cdr (cdr p))))
(if (pair? second-factor) (cons '* second-factor)
second-factor)))
and the test code is
(multiplicand '(* x y))
But the output is '(* y). It seems that the condition (pair? second-factor) equals #true with second-factor values 'y.
Can anybody help me with this, thanks a lot.
Bear in mind that (cdr (cdr ...)) is returning a list (not an element!), so pair? will return true if the list has enough elements (three or more). Perhaps you were aiming for something like this?
(define (multiplicand p)
(if (null? (cdddr p)) ; assuming list has at least 3 elements
p
`(* ,(second p) (* ,(third p) ,(fourth p)))))
(multiplicand '(* x y))
=> (* x y)
(multiplicand '(* 3 x y))
=> (* 3 (* x y))
Manipulating symbolic expressions is what match is made for:
(define (multiplicand p)
(match p
[(list '* m n) n]
[_ (error 'multiplicand (~a "expected product, got: " p))]))
How can I implement the Extended Euclidean algorithm? Here's my first attempt:
(define ex-gcd a b
; gcd(a,b) = a * x+ b * y
; gcd(a,b)-> always will be 1
output: (x.y)
)
The algorithm is right here in Wikipedia, you just have to adapt it to only return Bézout coefficients, the car part of the returned cons-cell will be x, and the cdr will be y:
(define (extended-gcd a b)
(let loop ([s 0] [t 1] [r b]
[old-s 1] [old-t 0] [old-r a])
(if (zero? r)
(cons old-s old-t)
(let ((q (quotient old-r r)))
(loop (- old-s (* q s))
(- old-t (* q t))
(- old-r (* q r))
s t r)))))
It's easy to test it using Bézout's identity, use different values for a and b and verify that it works as advertised:
(define (test a b)
(let* ((ans (extended-gcd a b))
(x (car ans))
(y (cdr ans)))
(= (gcd a b) (+ (* a x) (* b y)))))
(test 384 256)
=> #t
Notice that the algorithm calculated other values, by changing what you return you can also obtain the following:
Bézout coefficients: old_s, old_t
Greatest common divisor: old_r
Quotients by the gcd: t, s