I have a little problem to understand do in lisp
I have this code :
(defun iota-b (n)
(do ((x 0 (+1 x))
(u '() (cons x u)))
((> x n) (nreverse u))))
(iota-b 5)
(0 1 2 3 4 5)
In documentation there is the "do" basic template is:
(do (variable-definitions*)
(end-test-form result-form*)
statement*)
I really don't understand where is my body in my function iota-b
For me it's
(u '() (cons x u)))
apparently not, why we put (u '() (cons x u))) in the variable-definitions ?
You have the variable definitions of the form var init [step]
((x 0 (+1 x))
(u '() (cons x u)))
this increments x in every iteration and builds with (cons x u) the u list as (5 4 3 2 1 0).
The end test
(> x n)
The result form
(nreverse u)
reverses the list (5 4 3 2 1 0) to the given result.
And then you have an empty body.
You can of course modify the do loop to
(do ((x 0 (+1 x))
(u '()))
((> x n) (nreverse u))
(setq u (cons x u)))
this will give the same result.
(defun iota-b (n)
(do
; var init step
((x 0 (1+ x)) ; var 1
(u '() (cons x u))) ; var 2
;test result
((> x n) (nreverse u)) ; end ?
; body comes here
; this DO loop example has no body code
; the body code is optional
))
Related
I am just starting to learn Scheme and using cons is a little confusing to me. I have a function duplicate (s number) where s is a list, and number is the number of times the list should be duplicated.
If I enter (duplicate '(1 2) 3), the output should be ((1 2) (1 2) (1 2))
My program looks like this, but when I run it, there is nothing in the output
(define (duplicate s number)
(cond [(null? s) '()]
[(> 0 number) (cons (list s) (duplicate s(- number 1)))]
))
What am I doing wrong here?
We want second input n become zero complete all list.
And we want output is a list so we use cons.
You can build your code by using minimum sample than add more complex data.
If input is (duplicate x 0) we want output is '().
If input is (duplicate x 1) we want output is '(x).
So your code should looks like this
(define (duplicate x n)
(cond
[(= n 0) '()]
[else
(cons x ...)]))
But we already know we want output is '(x) which is (cons x '()).
Obvious '() is (duplicate x 0)'s output. So we add (duplicate x (- n 1)) in second condition.
#lang racket
(define (duplicate x n)
(cond
[(= n 0) '()]
[else
(cons x (duplicate x (- n 1)))]))
;;; TEST
(duplicate '() 0)
(duplicate '() 3)
(duplicate '() 5) ; '(() () () () ())
(duplicate '(1 2) 5) ; '((1 2) (1 2) (1 2) (1 2) (1 2))
Or you can think like this way.
We have employee help us copy document.
employee-1 : We give him a number than he minus 1 than order employee-2 do his job
employee-2 : He copy a document than send message to employee-3
employee-3 : He supervision finish or not (number become zero). If not finish send message to employee-1.
So we want something like this
finish? -> no -> minus-1 -> copy -> finish? -> no -> minus-1 -> ...
#lang racket
(define x 1)
(define result '())
(define (employee-1 n)
(employee-2 (- n 1)))
(define (employee-2 n)
(begin
(set! result (cons x result))
(employee-3 n)))
(define (employee-3 n)
(if (= n 0)
result
(employee-1 n)))
;;; TEST
(employee-3 3) ; '(1 1 1)
Than we combine employee-1 to employee-3
(define x 1)
(define result '())
; (define (employee-1 n) (employee-2 (- n 1)))
(define (employee-2 n)
(begin
(set! result (cons x result))
(employee-3-v2 n)))
(define (employee-3-v2 n)
(if (= n 0)
result
(employee-2 (- n 1))))
;;; TEST
(employee-3-v2 3) ; '(1 1 1)
We use function input replace define global variable. So we have to remove set! and change input parameter.
; (define x 1)
; (define result '())
; (define (employee-1 n) (employee-2 (- n 1)))
(define (employee-2-v2 n x result)
(employee-3-v2 n x (cons x result)))
(define (employee-3-v2 n x result)
(if (= n 0)
result
(employee-2-v2 (- n 1) x result)))
;;; TEST
(employee-3-v2 3 1 '()) ; '(1 1 1)
Than we combine employee-2-v2 to employee-3-v2. Remember we have to change input parameter.
(define (employee-3-v3 n x result)
(if (= n 0)
result
(employee-3-v3 (- n 1) x (cons x result))))
;;; TEST
(employee-3-v3 3 'x '()) ; '(x x x)
Now we want remove not necessary input parameter result.
(define (employee-3-v4 n x)
(if (= n 0)
'()
(cons x (employee-3-v4 (- n 1) x))))
;;; TEST
(build-list 10 (λ (n) (employee-3-v4 n 'x)))
#|
output:
'(()
(x)
(x x)
(x x x)
(x x x x)
(x x x x x)
(x x x x x x)
(x x x x x x x)
(x x x x x x x x)
(x x x x x x x x x))
|#
I'm working on this project in Scheme and these errors on these three particular methods have me very stuck.
Method #1:
; Returns the roots of the quadratic formula, given
; ax^2+bx+c=0. Return only real roots. The list will
; have 0, 1, or 2 roots. The list of roots should be
; sorted in ascending order.
; a is guaranteed to be non-zero.
; Use the quadratic formula to solve this.
; (quadratic 1.0 0.0 0.0) --> (0.0)
; (quadratic 1.0 3.0 -4.0) --> (-4.0 1.0)
(define (quadratic a b c)
(if
(REAL? (sqrt(- (* b b) (* (* 4 a) c))))
((let ((X (/ (+ (* b -1) (sqrt(- (* b b) (* (* 4 a) c)))) (* 2 a)))
(Y (/ (- (* b -1) (sqrt(- (* b b) (* (* 4 a) c)))) (* 2 a))))
(cond
((< X Y) (CONS X (CONS Y '())))
((> X Y) (CONS Y (CONS X '())))
((= X Y) (CONS X '()))
)))#f)
Error:
assertion-violation: attempt to call a non-procedure [tail-call]
('(0.0) '())
1>
assertion-violation: attempt to call a non-procedure [tail-call]
('(-4.0 1.0) '())
I'm not sure what it is trying to call. (0.0) and (-4.0 1.0) is my expected output so I don't know what it is trying to do.
Method #2:
;Returns the list of atoms that appear anywhere in the list,
;including sublists
; (flatten '(1 2 3) --> (1 2 3)
; (flatten '(a (b c) ((d e) f))) --> (a b c d e f)
(define (flatten lst)
(cond
((NULL? lst) '())
((LIST? lst) (APPEND (CAR lst) (flatten(CDR lst))))
(ELSE (APPEND lst (flatten(CDR lst))))
)
)
Error: assertion-violation: argument of wrong type [car]
(car 3)
3>
assertion-violation: argument of wrong type [car]
(car 'a)
I'm not sure why this is happening, when I'm checking if it is a list before I append anything.
Method #3
; Returns the value that results from:
; item1 OP item2 OP .... itemN, evaluated from left to right:
; ((item1 OP item2) OP item3) OP ...
; You may assume the list is a flat list that has at least one element
; OP - the operation to be performed
; (accumulate '(1 2 3 4) (lambda (x y) (+ x y))) --> 10
; (accumulate '(1 2 3 4) (lambda (x y) (* x y))) --> 24
; (accumulate '(1) (lambda (x y) (+ x y))) --> 1
(define (accumulate lst OP)
(define f (eval OP (interaction-environment)))
(cond
((NULL? lst) '())
((NULL? (CDR lst)) (CAR lst))
(ELSE (accumulate(CONS (f (CAR lst) (CADR lst)) (CDDR lst)) OP))
)
)
Error:
syntax-violation: invalid expression [expand]
#{procedure 8664}
5>
syntax-violation: invalid expression [expand]
#{procedure 8668}
6>
syntax-violation: invalid expression [expand]
#{procedure 8672}
7>
syntax-violation: invalid expression [expand]
#{procedure 1325 (expt in scheme-level-1)}
This one I have no idea what this means, what is expand?
Any help would be greatly appreciated
code has (let () ...) which clearly evaluates to list? so the extra parentheses seems odd. ((let () +) 1 2) ; ==> 3 works because the let evaluates to a procedure, but if you try ((cons 1 '()) 1 2) you should get an error saying something like application: (1) is not a procedure since (1) isn't a procedure. Also know that case insensitivity is deprecated so CONS and REAL? are not future proof.
append concatenates lists. They have to be lists. In the else you know since lst is not list? that lst cannot be an argument of append. cons might be what you are looking for. Since lists are abstraction magic in Scheme I urge you to get comfortable with pairs. When I read (1 2 3) I see (1 . (2 . (3 . ()))) or perhaps (cons 1 (cons 2 (cons 3 '()))) and you should too.
eval is totally inappropriate in this code. If you pass (lambda (x y) (+ x y)) which evaluates to a procedure to OP you can do (OP 1 2). Use OP directly.
I am trying to build a 6-tuple store on top of wiredtiger. The tuples can be described as follow:
(graph, subject, predicate, object, alive, transaction)
Every tuple stored in the database is unique.
Queries are like regular SPARQL queries except that the database store 6 tuples.
Zero of more elements of a tuple can be variable. Here is an example query that allows to retrieve all changes introduces by a particular transaction P4X432:
SELECT ?graph ?subject ?predicate ?object ?alive
WHERE
{
?graph ?subject ?predicate ?object ?alive "P4X432"
}
Considering all possible patterns ends up with considering all combinations of:
(graph, subject, predicate, object, alive, transaction)
That is given by the following function:
def combinations(tab):
out = []
for i in range(1, len(tab) + 1):
out.extend(x for x in itertools.combinations(tab, i))
assert len(out) == 2**len(tab) - 1
return out
Where:
print(len(combinations(('graph', 'subject', 'predicate', 'object', 'alive', 'transaction'))))
Display:
63
That is there 63 combinations of the 6-tuples. I can complete each indices with the missing tuple item, e.g. the following combination:
('graph', 'predicate', 'transaction')
Will be associated with the following index:
('graph', 'predicate', 'transaction', 'subject', 'alive', 'object')
But I know there is a smaller subset of all permutations of the 6-tuple that has the following property:
A set of n-permutations of {1, 2, ..., n} where all combinations of {1, 2, ..., n} are prefix-permutation of at least one element of the set.
Otherwise said, all combinations have a permutation that is prefix of one element of the set.
I found using a brute force algorithm a set of size 25 (inferior to 63) that has that property:
((5 0 1 2 3 4) (4 5 0 1 2 3) (3 4 5 0 1 2) (2 3 4 5 0 1) (1 2 3 4 5 0) (0 1 2 3 4 5) (0 2 1 3 4 5) (0 3 2 1 5 4) (0 4 3 1 5 2) (0 4 2 3 1 5) (2 1 5 3 0 4) (3 2 1 5 0 4) (3 1 4 5 0 2) (3 1 5 4 2 0) (3 0 1 4 2 5) (3 5 2 0 1 4) (4 3 1 0 2 5) (4 2 1 5 3 0) (4 1 0 2 5 3) (4 5 2 1 0 3) (5 4 1 2 3 0) (5 3 0 1 4 2) (5 2 1 3 4 0) (5 1 2 4 0 3) (5 0 2 4 3 1))
Here is the r7rs scheme program I use to compute that solution:
(define-library (indices)
(export indices)
(export permutations)
(export combination)
(export combinations)
(export run)
(import (only (chezscheme) trace-define trace-lambda random trace-let))
(import (scheme base))
(import (scheme list))
(import (scheme comparator))
(import (scheme hash-table))
(import (scheme process-context))
(import (scheme write))
(begin
(define (combination k lst)
(cond
((= k 0) '(()))
((null? lst) '())
(else
(let ((head (car lst))
(tail (cdr lst)))
(append (map (lambda (y) (cons head y)) (combination (- k 1) tail))
(combination k tail))))))
(define (factorial n)
(let loop ((n n)
(out 1))
(if (= n 0)
out
(loop (- n 1) (* n out)))))
(define (%binomial-coefficient n k)
;; https://en.wikipedia.org/wiki/Binomial_coefficient#Multiplicative_formula
(let loop ((i 1)
(out 1))
(if (= i (+ k 1))
out
(loop (+ i 1) (* out (/ (- (+ n 1) i) i))))))
(define (memo proc)
(let ((m (make-hash-table (make-equal-comparator))))
(lambda args
(if (hash-table-contains? m args)
(hash-table-ref m args)
(let ((v (apply proc args)))
(hash-table-set! m args v)
v)))))
(define binomial-coefficient
(memo
(lambda (n k)
(cond
((= n k) 1)
((= k 0) 1)
(else (%binomial-coefficient n k))))))
;; k-combination ranking and unranking procedures according to
;; https://en.wikipedia.org/wiki/Combinatorial_number_system
(define (ranking lst)
(let loop ((lst (sort < lst)) ;; increasing sequence
(k 1)
(out 0))
(if (null? lst)
out
(loop (cdr lst) (+ k 1) (+ out (binomial-coefficient (car lst) k))))))
(define (%unranking k N)
(let loop ((n (- k 1)))
(if (< N (binomial-coefficient (+ n 1) k))
n
(loop (+ n 1)))))
(define (unranking k N)
(let loop ((k k)
(N N)
(out '()))
(if (= k 0)
out
(let ((m (%unranking k N)))
(loop (- k 1) (- N (binomial-coefficient m k)) (cons m out))))))
(define fresh-random
(let ((memo (make-hash-table (make-eqv-comparator))))
(lambda (n)
(when (= (hash-table-size memo) n)
(error 'oops "no more fresh number" n
))
(let loop ()
(let ((r (random n)))
(if (hash-table-contains? memo r)
(loop)
(begin (hash-table-set! memo r #t) r)))))))
(define (random-k-combination k n)
(unranking k (fresh-random (binomial-coefficient n k))))
(define (combinations lst)
(if (null? lst) '(())
(let* ((head (car lst))
(tail (cdr lst))
(s (combinations tail))
(v (map (lambda (x) (cons head x)) s)))
(append s v))))
;; (define (combinations lst)
;; (append-map (lambda (k) (combination k lst)) (iota (length lst))))
(define (permutations s)
;; http://rosettacode.org/wiki/Permutations#Scheme
(cond
((null? s) '(()))
((null? (cdr s)) (list s))
(else ;; extract each item in list in turn and permutations the rest
(let splice ((l '()) (m (car s)) (r (cdr s)))
(append
(map (lambda (x) (cons m x)) (permutations (append l r)))
(if (null? r) '()
(splice (cons m l) (car r) (cdr r))))))))
(define (shift lst index)
(append (drop lst index) (take lst index)))
(define (rotations lst)
(reverse! (map (lambda (index) (shift lst index)) (iota (length lst)))))
(define (prefix? lst other)
"Return #t if LST is prefix of OTHER"
(let prefix ((lst lst)
(other other))
(if (null? lst)
#t
(if (= (car lst) (car other))
(prefix (cdr lst) (cdr other))
#f))))
(define (indices lst)
(let ((candidates (permutations lst)))
(let loop ((out (rotations lst)) ;; all rotations are solutions
(combinations (combinations lst)))
(if (null? combinations)
(reverse! out)
(let ((permutations (permutations (car combinations))))
(if (any (lambda (s) (any (lambda (p) (prefix? p s)) permutations)) out)
;; there is an existing "solution" for the
;; permutations of COMBINATION move to the next
;; combination
(loop out (cdr combinations))
(loop (cons (find (lambda (c) (if (member c out)
#f
(any (lambda (p) (prefix? p c)) permutations)))
candidates)
out)
(cdr combinations))))))))
(define (permutation-prefix? c o)
(any (lambda (p) (prefix? p o)) (permutations c)))
(define (ok? combinations candidate)
(every (lambda (c) (any (lambda (p) (permutation-prefix? c p)) candidate)) combinations))
(define (run)
(let* ((n (string->number (cadr (command-line))))
(N (iota n))
(solution (indices N))
(min (length solution))
(rotations (rotations N))
(R (length rotations))
;; other stuff
(cx (combinations N))
(px (filter (lambda (x) (not (member x rotations))) (permutations N)))
;; other other stuff
(pn (length px))
(PN (iota pn)))
(display "(length solution) => ") (display (length solution))
(display "\n")
(display "(length rotations) => ") (display R)
(display "\n")
(let try ((x (- (length solution) 1)))
(let ((count (binomial-coefficient pn (- x R))))
(let loop ((index 0)
(cxx (map (lambda (x) (list-ref px x)) (random-k-combination (- x R) pn))))
(when (= (modulo index (expt 10 5)) 0)
(display "n=") (display n) (display " x=") (display x)
(display " ")
(display index) (display "/") (display count) (display "\n"))
(let ((candidate (append rotations cxx)))
(let ((continue? (not (ok? cx candidate))))
(if continue?
(loop (+ index 1)
(map (lambda (x) (list-ref px x)) (random-k-combination (- x R) pn)))
(begin (display "new solution n=") (display n)
(display " length=") (display x)
(display " ") (display candidate)
(display "\n")
(try (- x 1)))))))))))
))
With that list of permutations I can query any pattern.
I am wondering if there is a smaller set and whether there is definitive algorithm to compute that kind of set.
Based on this answer https://math.stackexchange.com/a/3146793/23663
The following program yields a solution that is a minimal solution according to math ™:
import itertools
import math
f = math.factorial
bc = lambda n, k: f(n) // f(k) // f(n-k) if k<n else 0
def pk(*args):
print(*args)
return args[-1]
def stringify(iterable):
return ''.join(str(x) for x in iterable)
def combinations(tab):
out = []
for i in range(1, len(tab) + 1):
out.extend(stringify(x) for x in itertools.combinations(tab, i))
assert len(out) == 2**len(tab) - 1
return out
def ok(solutions, tab):
cx = combinations(tab)
px = [stringify(x) for x in itertools.permutations(tab)]
for combination in cx:
pcx = [''.join(x) for x in itertools.permutations(combination)]
# check for existing solution
for solution in solutions:
if any(solution.startswith(p) for p in pcx):
# yeah, there is an existing solution
break
else:
print('failed with combination={}'.format(combination))
break
else:
return True
return False
def run(n):
tab = list(range(n))
cx = list(itertools.combinations(tab, n//2))
for c in cx:
L = [(i, i in c) for i in tab]
A = []
B = []
while True:
for i in range(len(L) - 1):
if (not L[i][1]) and L[i + 1][1]:
A.append(L[i + 1][0])
B.append(L[i][0])
L.remove((L[i + 1][0], True))
L.remove((L[i][0], False))
break
else:
break
l = [i for (i, _) in L]
yield A + l + B
for i in range(7):
tab = stringify(range(i))
solutions = [stringify(x) for x in run(i)]
assert ok(solutions, tab)
print("n={}, size={}, solutions={}".format(i, len(solutions), solutions))
The above program output is:
n=0, size=1, solutions=['']
n=1, size=1, solutions=['0']
n=2, size=2, solutions=['01', '10']
n=3, size=3, solutions=['012', '120', '201']
n=4, size=6, solutions=['0123', '2031', '3012', '1230', '1302', '2310']
n=5, size=10, solutions=['01234', '20341', '30142', '40123', '12340', '13402', '14203', '23410', '24013', '34021']
n=6, size=20, solutions=['012345', '301452', '401253', '501234', '203451', '240513', '250314', '340521', '350124', '450132', '123450', '142503', '152304', '134502', '135024', '145032', '234510', '235104', '245130', '345210']
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've written the code for multiplicative inverse of modulo m. It works for most of the initial cases but not for some. The code is below:
(define (inverse x m)
(let loop ((x (modulo x m)) (a 1))
(cond ((zero? x) #f) ((= x 1) a)
(else (let ((q (- (quotient m x))))
(loop (+ m (* q x)) (modulo (* q a) m)))))))
For example it gives correct values for (inverse 5 11) -> 9 (inverse 9 11) -> 5 (inverse 7 11 ) - > 8 (inverse 8 12) -> #f but when i give (inverse 5 12) it produces #f while it should have been 5. Can you see where the bug is?
Thanks for any help.
The algorithm you quoted is Algorithm 9.4.4 from the book Prime Numbers by Richard Crandall and Carl Pomerance. In the text of the book they state that the algorithm works for both prime and composite moduli, but in the errata to their book they correctly state that the algorithm works always for prime moduli and mostly, but not always, for composite moduli. Hence the failure that you found.
Like you, I used Algorithm 9.4.4 and was mystified at some of my results until I discovered the problem.
Here's the modular inverse function that I use now, which works with both prime and composite moduli, as long as its two arguments are coprime to one another. It is essentially the extended Euclidean algorithm that #OscarLopez uses, but with some redundant calculations stripped out. If you like, you can change the function to return #f instead of throwing an error.
(define (inverse x m)
(let loop ((x x) (b m) (a 0) (u 1))
(if (zero? x)
(if (= b 1) (modulo a m)
(error 'inverse "must be coprime"))
(let* ((q (quotient b x)))
(loop (modulo b x) x u (- a (* u q)))))))
Does it have to be precisely that algorithm? if not, try this one, taken from wikibooks:
(define (egcd a b)
(if (zero? a)
(values b 0 1)
(let-values (((g y x) (egcd (modulo b a) a)))
(values g (- x (* (quotient b a) y)) y))))
(define (modinv a m)
(let-values (((g x y) (egcd a m)))
(if (not (= g 1))
#f
(modulo x m))))
It works as expected:
(modinv 5 11) ; 9
(modinv 9 11) ; 5
(modinv 7 11) ; 8
(modinv 8 12) ; #f
(modinv 5 12) ; 5
I think this is the Haskell code on that page translated directly into Scheme:
(define (inverse p q)
(cond ((= p 0) #f)
((= p 1) 1)
(else
(let ((recurse (inverse (mod q p) p)))
(and recurse
(let ((n (- p recurse)))
(div (+ (* n q) 1) p)))))))
It looks like you're trying to convert it from recursive to tail-recursive, which is why things don't match up so well.
These two functions below can help you as well.
Theory
Here’s how we find the multiplicative inverse d. We want e*d = 1(mod n), which means that ed + nk = 1 for some integer k. So we’ll write a procedure that solves the general equation ax + by = 1, where a and b are given, x and y are variables, and all of these values are integers. We’ll use this procedure to solve ed + nk = 1 for d and k. Then we can throw away k and simply return d.
>
(define (ax+by=1 a b)
(if (= b 0)
(cons 1 0)
(let* ((q (quotient a b))
(r (remainder a b))
(e (ax+by=1 b r))
(s (car e))
(t (cdr e)))
(cons t (- s (* q t))))))
This function is a general solution to an equation in form of ax+by=1 where a and b is given.The inverse-mod function simply uses this solution and returns the inverse.
(define inverse-mod (lambda (a m)
(if (not (= 1 (gcd a m)))
(display "**Error** No inverse exists.")
(if (> 0(car (ax+by=1 a m)))
(+ (car (ax+by=1 a m)) m)
(car (ax+by=1 a m))))))
Some test cases are :
(inverse-mod 5 11) ; -> 9 5*9 = 45 = 1 (mod 11)
(inverse-mod 9 11) ; -> 5
(inverse-mod 7 11) ; -> 8 7*8 = 56 = 1 (mod 11)
(inverse-mod 5 12) ; -> 5 5*5 = 25 = 1 (mod 12)
(inverse-mod 8 12) ; -> error no inverse exists