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.
With my code I need to use multiple functions and combine them into one that will evaluate to the nth prime number between a and b. The functions I need to use are gen-consecutive filter value-at-position.
The problem with my code is that with the function gen-consecutive requires 3 parameters a function (f) and a and b which acts as a range, and I am not sure where to put the f argument in my nth-prime-between function.
I keep getting the error "gen-consecutive: arity mismatch" and that it expected 3 arguments (f a b) instead of just 2 arguments (a b)
Here is my code:
(define (nth-prime-between a b n)
(value-at-position filter prime? (gen-consecutive a b)) n)
Here is the other functions:
(define (gen-consecutive f a b)
(if (> a b)
'()
(cons (f a) (gen-consecutive f (+ a 1) b))))
(define (filter f lst)
(cond ((null? lst) '())
((f (car lst))
(cons (car lst) (filter f (cdr lst))))
(else
(filter f (cdr lst)))))
(define (value-at-position lst k)
(cond ((null? lst) lst)
((= k 1) (car lst))
(else (value-at-position (- k 1) (cdr lst)))))
There are 3 mistakes in your program!
I do NOT have a function prime?, therefore I used odd? instead
(define (nth-prime-between a b n)
;; missing parenthesis for the function filter
;; n is value of the function
;; (value-at-position filter odd? (gen-consecutive a b)) n)
(value-at-position (filter odd? (gen-consecutive a b)) n))
;; kill the parameter f
;;
;; (define (gen-consecutive f a b)
;; (if (> a b)
;; '()
;; (cons (f a) (gen-consecutive f (+ a 1) b))))
(define (gen-consecutive a b)
(if (> a b)
'()
(cons a (gen-consecutive (+ a 1) b))))
(define (filter f lst)
(cond ((null? lst) '())
((f (car lst))
(cons (car lst) (filter f (cdr lst))))
(else
(filter f (cdr lst)))))
(define (value-at-position lst k)
(cond ((null? lst) lst)
((= k 1) (car lst))
;; the sequence of (- k 1) and (cdr lst) is wrong
;; (else (value-at-position (- k 1) (cdr lst)))))
(else (value-at-position (cdr lst) (- k 1)))))
(define (odd? N)
(if (= (remainder N 2) 0)
#f
#t))
(nth-prime-between 1 10 3)
The deeper problem with task is:
When you call (nth-prime-between 1000 10000 2),
you must test 9000 numbers with (prime? n). Probably, it is enough to test 10 numbers.
By the way, there exists intervals of any length with no prime numbers in it.
To test a number N with with prime? you need to know the prime numbers less the (square-root N). Where will you store them?
If it is serious task, you can write a program using the sieve of Eratosthenes with a clever stopping condition.
In response to the following exercise from the SICP,
Exercise 1.3. Define a procedure that takes three numbers as arguments
and returns the sum of the squares of the two larger numbers.
I wrote the following (correct) function:
(define (square-sum-larger a b c)
(cond ((or (and (> a b) (> b c)) (and (> b a) (> a c))) (+ (* a a) (* b b)))
((or (and (> a c) (> c b)) (and (> c a) (> a b))) (+ (* a a) (* c c)))
((or (and (> b c) (> c a)) (and (> c b) (> b a))) (+ (* b b) (* c c)))))
Unfortunately, that is one of the ugliest functions I've written in my life. How do I
(a) Make it elegant, and
(b) Make it work for an arbitrary number of inputs?
I found an elegant solution (though it only works for 3 inputs):
(define (square-sum-larger a b c)
(+
(square (max a b))
(square (max (min a b) c))))
If you're willing to use your library's sort function, this becomes easy and elegant.
(define (square-sum-larger . nums)
(define sorted (sort nums >))
(let ((a (car sorted))
(b (cadr sorted)))
(+ (* a a) (* b b))))
In the above function, nums is a "rest" argument, containing a list of all arguments passed to the function. We just sort that list in descending order using >, then square the first two elements of the result.
I don't know if it's elegant enough but for a 3 argument version you can use procedure abstraction to reduce repetition:
(define (square-sum-larger a b c)
(define (square x)
(* x x))
(define (max x y)
(if (< x y) y x))
(if (< a b)
(+ (square b) (square (max a c)))
(+ (square a) (square (max b c)))))
Make it work for an arbitrary number of inputs.
(define (square-sum-larger a b . rest)
(let loop ((a (if (> a b) a b)) ;; a becomes largest of a and b
(b (if (> a b) b a)) ;; b becomes smallest of a and b
(rest rest))
(cond ((null? rest) (+ (* a a) (* b b)))
((> (car rest) a) (loop (car rest) a (cdr rest)))
((> (car rest) b) (loop a (car rest) (cdr rest)))
(else (loop a b (cdr rest))))))
A R6RS-version using sort and take:
#!r6rs
(import (rnrs)
(only (srfi :1) take))
(define (square-sum-larger . rest)
(apply +
(map (lambda (x) (* x x))
(take (list-sort > rest) 2))))
You don't need to bother sorting you just need the find the greatest two.
(define (max-fold L)
(if (null? L)
#f
(reduce (lambda (x y)
(if (> x y) x y))
(car L)
L)))
(define (remove-num-once x L)
(cond ((null? L) #f)
((= x (car L)) (cdr L))
(else (cons (car L) (remove-once x (cdr L))))))
(define (square-sum-larger . nums)
(let ((max (max-fold nums)))
(+ (square max)
(square (max-fold (remove-num-once max nums))))))
(square-sum-larger 1 8 7 4 5 6 9 2)
;Value: 145
I hacked together several code snippets from various sources and created a crude implementation of a Wolfram Blog article at http://bit.ly/HWdUqK - for those that are mathematically inclined, it is very interesting!
Not surprisingly, given that I'm still a novice at Racket, the code takes too much time to calculate the results (>90 min versus 49 seconds for the author) and eats up a lot of memory. I suspect it is all about the definition (expListY) which needs to be reworked.
Although I have it working in DrRacket, I am also having problems byte-compiling the source, and still working on it
(Error message: +: expects type <number> as 1st argument, given: #f; other arguments were: 1 -1)
Anybody want to take a stab at improving the performance and efficiency? I apologize for the unintelligible code and lack of better code comments.
PS: Should I be cutting and pasting the code directly here?
Probably similar to soegaard's solution, except this one rolls its own "parser", so it's self contained. It produces the complete 100-year listing in a bit under 6 seconds on my machine. There's a bunch of tricks that this code uses, but it's not really something that would be called "optimized" in any serious way: I'm sure that it can be made much faster with some memoization, care for maximizing tree sharing etc etc. But for such a small domain it's not worth the effort... (Same goes for the quality of this code...)
BTW#1, more than parsing, the original solution(s) use eval which does not make things faster... For things like this it's usually better to write the "evaluator" manually. BTW#2, this doesn't mean that Racket is faster than Mathematica -- I'm sure that the solution in that post makes it grind redundant cpu cycles too, and a similar solution would be faster.
#lang racket
(define (tuples list n)
(let loop ([n n])
(if (zero? n)
'(())
(for*/list ([y (in-list (loop (sub1 n)))] [x (in-list list)])
(cons x y)))))
(define precedence
(let ([t (make-hasheq)])
(for ([ops '((#f) (+ -) (* /) (||))] [n (in-naturals)])
(for ([op ops]) (hash-set! t op n)))
t))
(define (do op x y)
(case op
[(+) (+ x y)] [(-) (- x y)] [(*) (* x y)] [(/) (/ x y)]
[(||) (+ (* 10 x) y)]))
(define (run ops nums)
(unless (= (add1 (length ops)) (length nums)) (error "poof"))
(let loop ([nums (cddr nums)]
[ops (cdr ops)]
[numstack (list (cadr nums) (car nums))]
[opstack (list (car ops))])
(if (and (null? ops) (null? opstack))
(car numstack)
(let ([op (and (pair? ops) (car ops))]
[topop (and (pair? opstack) (car opstack))])
(if (> (hash-ref precedence op)
(hash-ref precedence topop))
(loop (cdr nums)
(cdr ops)
(cons (car nums) numstack)
(cons op opstack))
(loop nums
ops
(cons (do topop (cadr numstack) (car numstack))
(cddr numstack))
(cdr opstack)))))))
(define (expr ops* nums*)
(define ops (map symbol->string ops*))
(define nums (map number->string nums*))
(string-append* (cons (car nums) (append-map list ops (cdr nums)))))
(define nums (for/list ([i (in-range 10 0 -1)]) i))
(define year1 2012)
(define nyears 100)
(define year2 (+ year1 nyears))
(define years (make-vector nyears '()))
(for ([ops (in-list (tuples '(+ - * / ||) 9))])
(define r (run ops nums))
(when (and (integer? r) (<= year1 r) (< r year2))
(vector-set! years (- r year1)
(cons ops (vector-ref years (- r year1))))))
(for ([solutions (in-vector years)] [year (in-range year1 year2)])
(if (pair? solutions)
(printf "~a = ~a~a\n"
year (expr (car solutions) nums)
(if (null? (cdr solutions))
""
(format " (~a more)" (length (cdr solutions)))))
(printf "~a: no combination!\n" year)))
Below is my implementation. I tweaked and optimized a thing or two in your code, in my laptop it takes around 35 minutes to finish (certainly an improvement!) I found that the evaluation of expressions is the real performance killer - if it weren't for the calls to the procedure to-expression, the program would finish in under a minute.
I guess that in programming languages that natively use infix notation the evaluation would be much faster, but in Scheme the cost for parsing and then evaluating a string with an infix expression is just too much.
Maybe someone can point out a suitable replacement for the soegaard/infix package? or alternatively, a way to directly evaluate an infix expression list that takes into account operator precedence, say '(1 + 3 - 4 & 7) - where & stands for number concatenation and has the highest precedence (for example: 4 & 7 = 47), and the other arithmetic operators (+, -, *, /) follow the usual precedence rules.
#lang at-exp racket
(require (planet soegaard/infix)
(planet soegaard/infix/parser))
(define (product lst1 lst2)
(for*/list ([x (in-list lst1)]
[y (in-list lst2)])
(cons x y)))
(define (tuples lst n)
(if (zero? n)
'(())
(product lst (tuples lst (sub1 n)))))
(define (riffle numbers ops)
(if (null? ops)
(list (car numbers))
(cons (car numbers)
(cons (car ops)
(riffle (cdr numbers)
(cdr ops))))))
(define (expression-string numbers optuple)
(apply string-append
(riffle numbers optuple)))
(define (to-expression exp-str)
(eval
(parse-expression
#'here (open-input-string exp-str))))
(define (make-all-combinations numbers ops)
(let loop ((opts (tuples ops (sub1 (length numbers))))
(acc '()))
(if (null? opts)
acc
(let ((exp-str (expression-string numbers (car opts))))
(loop (cdr opts)
(cons (cons exp-str (to-expression exp-str)) acc))))))
(define (show-n-expressions all-combinations years)
(for-each (lambda (year)
(for-each (lambda (comb)
(when (= (cdr comb) year)
(printf "~s ~a~n" year (car comb))))
all-combinations)
(printf "~n"))
years))
Use it like this for replicating the results in the original blog post:
(define numbers '("10" "9" "8" "7" "6" "5" "4" "3" "2" "1"))
(define ops '("" "+" "-" "*" "/"))
; beware: this takes around 35 minutes to finish in my laptop
(define all-combinations (make-all-combinations numbers ops))
(show-n-expressions all-combinations
(build-list 5 (lambda (n) (+ n 2012))))
UPDATE :
I snarfed Eli Barzilay's expression evaluator and plugged it into my solution, now the pre-calculation of all combinations is done in around 5 seconds! The show-n-expressions procedure still needs some work to avoid iterating over the whole list of combinations each time, but that's left as an exercise for the reader. What matters is that now brute-forcing the values for all the possible expression combinations is blazing fast.
#lang racket
(define (tuples lst n)
(if (zero? n)
'(())
(for*/list ((y (in-list (tuples lst (sub1 n))))
(x (in-list lst)))
(cons x y))))
(define (riffle numbers ops)
(if (null? ops)
(list (car numbers))
(cons (car numbers)
(cons (car ops)
(riffle (cdr numbers)
(cdr ops))))))
(define (expression-string numbers optuple)
(string-append*
(map (lambda (x)
(cond ((eq? x '&) "")
((symbol? x) (symbol->string x))
((number? x) (number->string x))))
(riffle numbers optuple))))
(define eval-ops
(let ((precedence (make-hasheq
'((& . 3) (/ . 2) (* . 2)
(- . 1) (+ . 1) (#f . 0))))
(apply-op (lambda (op x y)
(case op
((+) (+ x y)) ((-) (- x y))
((*) (* x y)) ((/) (/ x y))
((&) (+ (* 10 x) y))))))
(lambda (nums ops)
(let loop ((nums (cddr nums))
(ops (cdr ops))
(numstack (list (cadr nums) (car nums)))
(opstack (list (car ops))))
(if (and (null? ops) (null? opstack))
(car numstack)
(let ((op (and (pair? ops) (car ops)))
(topop (and (pair? opstack) (car opstack))))
(if (> (hash-ref precedence op)
(hash-ref precedence topop))
(loop (cdr nums)
(cdr ops)
(cons (car nums) numstack)
(cons op opstack))
(loop nums
ops
(cons (apply-op topop (cadr numstack) (car numstack))
(cddr numstack))
(cdr opstack)))))))))
(define (make-all-combinations numbers ops)
(foldl (lambda (optuple tail)
(cons (cons (eval-ops numbers optuple) optuple) tail))
empty (tuples ops (sub1 (length numbers)))))
(define (show-n-expressions all-combinations numbers years)
(for-each (lambda (year)
(for-each (lambda (comb)
(when (= (car comb) year)
(printf "~s ~a~n"
year
(expression-string numbers (cdr comb)))))
all-combinations)
(printf "~n"))
years))
Use it like this:
(define numbers '(10 9 8 7 6 5 4 3 2 1))
(define ops '(& + - * /))
; this is very fast now!
(define all-combinations (make-all-combinations numbers ops))
(show-n-expressions all-combinations numbers
(build-list 5 (lambda (n) (+ n 2012))))
As Óscar points out, the problem is that soegaard/infix is slow for this type of problem.
I found a standard shunting-yard parser for infix expressions on GitHub and wrote the following program in Racket:
#lang racket
(require "infix-calc.scm")
(define operators '("*" "/" "+" "-" ""))
(time
(for*/list ([o1 (in-list operators)]
[o2 (in-list operators)]
[o3 (in-list operators)]
[o4 (in-list operators)]
[o5 (in-list operators)]
[o6 (in-list operators)]
[o7 (in-list operators)]
[o8 (in-list operators)]
[o9 (in-list operators)]
[expr (in-value
(apply string-append
(list "1" o1 "2" o2 "3" o3 "4" o4 "5" o5 "6" o6 "7" o7 "8" o8 "9" o9 "10")))]
#:when (= (first (calc expr)) 2012))
expr))
After a little less than 3 minutes the results are:
Welcome to DrRacket, version 5.2.900.2--2012-03-29(8c22c6c/a) [3m].
Language: racket; memory limit: 128 MB.
cpu time: 144768 real time: 148818 gc time: 25252
'("1*2*3+4*567*8/9-10"
"1*2+34*56+7+89+10"
"1*23+45*6*7+89+10"
"1+2+3/4*5*67*8+9-10"
"1+2+3+4*567*8/9-10"
"1+2+34*56+7+8+9*10"
"1+23+45*6*7+8+9*10"
"1-2+345*6-7*8+9-10"
"12*34*5+6+7*8-9*10"
"12*34*5+6-7-8-9-10"
"1234+5-6+789-10")
The infix parser was written by Andrew Levenson.
The parser and the above code can be found here:
https://github.com/soegaard/Scheme-Infix-Calculator
this isn't a complete answer, but i think it's an alternative to the library Óscar López is asking for. unfortunately it's in clojure, but hopefully it's clear enough...
(def default-priorities
{'+ 1, '- 1, '* 2, '/ 2, '& 3})
(defn- extend-tree [tree priorities operator value]
(if (seq? tree)
(let [[op left right] tree
[old new] (map priorities [op operator])]
(if (> new old)
(list op left (extend-tree right priorities operator value))
(list operator tree value)))
(list operator tree value)))
(defn priority-tree
([operators values] (priority-tree operators values default-priorities))
([operators values priorities] (priority-tree operators values priorities nil))
([operators values priorities tree]
(if-let [operators (seq operators)]
(if tree
(recur
(rest operators) (rest values) priorities
(extend-tree tree priorities (first operators) (first values)))
(let [[v1 v2 & values] values]
(recur (rest operators) values priorities (list (first operators) v1 v2))))
tree)))
; [] [+ & *] [1 2 3 4] 1+23*4
; [+ 1 2] [& *] [3 4] - initial tree
; [+ 1 [& 2 3]] [*] [4] - binds more strongly than + so replace right-most node
; [+ 1 [* [& 2 3] 4]] [] [] - descend until do not bind more tightly, and extend
(println (priority-tree ['+ '& '*] [1 2 3 4])) ; 1+23*4
(println (priority-tree ['& '- '* '+ '&] [1 2 3 4 5 6])) ; 12 - 3*4 + 56
the output is:
(+ 1 (* (& 2 3) 4))
(+ (- (& 1 2) (* 3 4)) (& 5 6))
[update] adding the following
(defn & [a b] (+ b (* 10 a)))
(defn all-combinations [tokens length]
(if (> length 0)
(for [token tokens
smaller (all-combinations tokens (dec length))]
(cons token smaller))
[[]]))
(defn all-expressions [operators digits]
(map #(priority-tree % digits)
(all-combinations operators (dec (count digits)))))
(defn all-solutions [target operators digits]
(doseq [expression
(filter #(= (eval %) target)
(all-expressions operators digits))]
(println expression)))
(all-solutions 2012 ['+ '- '* '/ '&] (range 10 0 -1))
solves the problem, but it's slow - 28 minutes to complete. this is on a nice, fairly recent laptop (i7-2640M).
(+ (- (+ 10 (* 9 (& 8 7))) (& 6 5)) (* 4 (& (& 3 2) 1)))
(+ (- (+ (+ (* (* 10 9) 8) 7) 6) 5) (* 4 (& (& 3 2) 1)))
(- (- (+ (- (& 10 9) (* 8 7)) (* (& (& 6 5) 4) 3)) 2) 1)
(i only printed 2012 - see code above - but it would have evaluated the entire sequence).
so, unfortunately, this doesn't really answer the question, since it's no faster than Óscar López's code. i guess the next step would be to put some smarts into the evaluation and so save some time. but what?
[update 2] after reading the other posts here i replaced eval with
(defn my-eval [expr]
(if (seq? expr)
(let [[op left right] expr]
(case op
+ (+ (my-eval left) (my-eval right))
- (- (my-eval left) (my-eval right))
* (* (my-eval left) (my-eval right))
/ (/ (my-eval left) (my-eval right))
& (& (my-eval left) (my-eval right))))
expr))
and the running time drops to 45 secs. still not great, but it's a very inefficient parse/evaluation.
[update 3] for completeness, the following is an implementation of the shunting-yard algorithm (a simple one that is always left-associative) and the associated eval, butit only reduces the time to 35s.
(defn shunting-yard
([operators values] (shunting-yard operators values default-priorities))
([operators values priorities]
(let [[value & values] values]
(shunting-yard operators values priorities nil (list value))))
([operators values priorities stack-ops stack-vals]
; (println operators values stack-ops stack-vals)
(if-let [[new & short-operators] operators]
(let [[value & short-values] values]
(if-let [[old & short-stack-ops] stack-ops]
(if (> (priorities new) (priorities old))
(recur short-operators short-values priorities (cons new stack-ops) (cons value stack-vals))
(recur operators values priorities short-stack-ops (cons old stack-vals)))
(recur short-operators short-values priorities (list new) (cons value stack-vals))))
(concat (reverse stack-vals) stack-ops))))
(defn stack-eval
([stack] (stack-eval (rest stack) (list (first stack))))
([stack values]
(if-let [[op & stack] stack]
(let [[right left & tail] values]
(case op
+ (recur stack (cons (+ left right) tail))
- (recur stack (cons (- left right) tail))
* (recur stack (cons (* left right) tail))
/ (recur stack (cons (/ left right) tail))
& (recur stack (cons (& left right) tail))
(recur stack (cons op values))))
(first values))))
Interesting! I had to try it, it's in Python, hope you don't mind. It runs in about 28 seconds, PyPy 1.8, Core 2 Duo 1.4
from __future__ import division
from math import log
from operator import add, sub, mul
div = lambda a, b: float(a) / float(b)
years = set(range(2012, 2113))
none = lambda a, b: a * 10 ** (int(log(b, 10)) + 1) + b
priority = {none: 3, mul: 2, div: 2, add: 1, sub: 1}
symbols = {none: '', mul: '*', div: '/', add: '+', sub: '-', None: ''}
def evaluate(numbers, operators):
ns, ops = [], []
for n, op in zip(numbers, operators):
while ops and (op is None or priority[ops[-1]] >= priority[op]):
last_n = ns.pop()
last_op = ops.pop()
n = last_op(last_n, n)
ns.append(n)
ops.append(op)
return n
def display(numbers, operators):
return ''.join([
i for n, op in zip(numbers, operators) for i in (str(n), symbols[op])])
def expressions(years):
numbers = 10, 9, 8, 7, 6, 5, 4, 3, 2, 1
operators = none, add, sub, mul, div
pools = [operators] * (len(numbers) - 1) + [[None]]
result = [[]]
for pool in pools:
result = [x + [y] for x in result for y in pool]
for ops in result:
expression = evaluate(numbers, ops)
if expression in years:
yield '%d = %s' % (expression, display(numbers, ops))
for year in sorted(expressions(years)):
print year
I found code for generating Sierpinski carpet at http://rosettacode.org/wiki/Sierpinski_carpet#Scheme - but it won't run in the DrRacket environment or WeScheme. Could someone provide solutions for either environments?
It looks like this code runs fine in DrRacket after prepending a
#lang racket
line indicating that the code is written in Racket. I can provide more detail if this is not sufficient.
I've translated the program to run under WeScheme. I've made a few changes: rather than use (display) and (newline), I use the image primitives that WeScheme provides to make a slightly nicer picture. You can view the running program and its source code. For convenience, I also include the source here:
;; Sierpenski carpet.
;; http://rosettacode.org/wiki/Sierpinski_carpet#Scheme
(define SQUARE (square 10 "solid" "red"))
(define SPACE (square 10 "solid" "white"))
(define (carpet n)
(local [(define (in-carpet? x y)
(cond ((or (zero? x) (zero? y))
#t)
((and (= 1 (remainder x 3)) (= 1 (remainder y 3)))
#f)
(else
(in-carpet? (quotient x 3) (quotient y 3)))))]
(letrec ([outer (lambda (i)
(cond
[(< i (expt 3 n))
(local ([define a-row
(letrec ([inner
(lambda (j)
(cond [(< j (expt 3 n))
(cons (if (in-carpet? i j)
SQUARE
SPACE)
(inner (add1 j)))]
[else
empty]))])
(inner 0))])
(cons (apply beside a-row)
(outer (add1 i))))]
[else
empty]))])
(apply above (outer 0)))))
(carpet 3)
Here is the modified code for WeScheme. WeScheme don't support do-loop syntax, so I use unfold from srfi-1 instead
(define (unfold p f g seed)
(if (p seed) '()
(cons (f seed)
(unfold p f g (g seed)))))
(define (1- n) (- n 1))
(define (carpet n)
(letrec ((in-carpet?
(lambda (x y)
(cond ((or (zero? x) (zero? y))
#t)
((and (= 1 (remainder x 3)) (= 1 (remainder y 3)))
#f)
(else
(in-carpet? (quotient x 3) (quotient y 3)))))))
(let ((result
(unfold negative?
(lambda (i)
(unfold negative?
(lambda (j) (in-carpet? i j))
1-
(1- (expt 3 n))))
1-
(1- (expt 3 n)))))
(for-each (lambda (line)
(begin
(for-each (lambda (char) (display (if char #\# #\space))) line)
(newline)))
result))))