I'm sorry if this question has been answered before, but I've looked around and I can't really understand the explanation as to why I'm getting this error.
From what I understand I'm asking if a statement is true and then if it is I'm asking it to return an expression. And apparently I'm not allowed to get #t/#f answers and expressions? I'm not sure. Could someone help me understand.
This is my code.
(define (piecewise x)
(define pi 3.142)
(cond
((> x (* pi 2)) (- x (* 2 pi)))
((or ( > x (* pi -1) (= x ( * -1 pi)))) (sin x))
((or ( < x (* 2 pi)) (= x (* 2 pi))) (sin x))
(else (- (- 1 x) pi))))
If I may, if we take all of the suggestions and use them to simplify the code a bit, we might get the following:
(define (piecewise x)
(let* ((pi 3.142)
(tau (* 2 pi)))
(cond
((> x tau)
(- x tau))
((or (>= x (- pi))
(<= x tau))
(sin x))
(else (+ x pi)))))
This runs without errors under both Racket and Guile. Whether it computes the function correctly, only the OP can say for certain.
I am trying to write a representation of pairs that does not use cons, car or cdr but still follows the property of pairs, i.e., (car (cons x y)) should be x and (cdr (cons x y)) should be y.
So here is one solution that I got from the SICP book:
(define (special-cons x y)
(lambda (m) (m x y)))
I was able to write another solution but it can only allow numbers:
(define (special-cons a b)
(* (expt 2 a)
(expt 3 b)))
(define (num-divs n d)
(define (iter x result)
(if (= 0 (remainder x d))
(iter (/ x d) (+ 1 result))
result))
(iter n 0))
(define (special-car x)
(num-divs x 2))
(define (special-cdr x)
(num-divs x 3))
Is there any other solution that allows for pairs for any object x and object y?
What about structs (Racket) or record-types (R6RS)?
In Racket:
#lang racket
(struct cell (x y))
(define (ccons x y) (cell x y))
(define (ccar cl) (cell-x cl))
(define (ccdr cl) (cell-y cl))
(define (cpair? cl) (cell? cl))
(define x (ccons 1 2))
(cpair? x)
=> #t
(ccar (ccons 1 2))
=> 1
(ccdr (ccons 3 4))
=> 4
This is a good way of doing it.
#lang racket
(define (my-cons x y)
(lambda (p)
(if (= p 1) x y)))
(define (my-car pair)
(pair 1))
(define (my-cdr pair)
(pair 2))
Here is the test
> (my-car (my-cons 1 '(2 3 4)))
1
> (my-cdr (my-cons 1 '(2 3 4)))
'(2 3 4)
The classic Ableson and Sussman procedural implementation from Structure and Interpretation of Computer Programs (section 2.1.3):
(define (cons x y)
(define (dispatch m)
(cond ((= m 0) x)
((= m 1) y)
(else (error "Argument not 0 or 1 -- CONS" m))))
dispatch)
(define (car z)
(z 0))
(define (cdr z)
(z 1))
Rptx's solution is roughly equivalent, and this is presented for reference.
I am trying to determine the number of marbles that fall within a given circle (radius 1) given that they have random x and y coordinates.
My overall goal is to find an approximate value for pi by using monte carlo sampling by multiplying by 4 the (number of marbles within the circle)/(total number of marbles).
I intended for my function to count the number of marbles within the circle, but I am having trouble following why it does not work. Any help on following the function here would be appreciated.
Please comment if my above request for help is unclear.
(define(monte-carlo-sampling n)
(let ((x (- (* 2 (random)) 1))
(y (- (* 2 (random)) 1)))
(cond((= 0 n)
* 4 (/ monte-carlo-sampling(+ n 1) n)
((> 1 n)
(cond((< 1 (sqrt(+ (square x) (square y))) (+ 1 (monte-carlo-sampling(- n 1)))))
((> 1 (sqrt(+ (square x) (square y))) (monte-carlo-sampling(- n 1))))
)))))
Your parentheses are all messed up, and your argument order for < is wrong. Here's how the code should look like after it's corrected:
(define (monte-carlo-sampling n)
(let ((x (- (* 2 (random)) 1))
(y (- (* 2 (random)) 1)))
(cond ((= n 0)
0)
(else
(cond ((< (sqrt (+ (square x) (square y))) 1)
(+ 1 (monte-carlo-sampling (- n 1))))
(else
(monte-carlo-sampling (- n 1))))))))
This returns the number of hits. You'd have to convert the number of hits into a pi estimate using an outer function, such as:
(define (estimate-pi n)
(* 4 (/ (monte-carlo-sampling n) n)))
Here's how I'd write the whole thing, if it were up to me:
(define (estimate-pi n)
(let loop ((i 0)
(hits 0))
(cond ((>= i n)
(* 4 (/ hits n)))
((<= (hypot (sub1 (* 2 (random)))
(sub1 (* 2 (random)))) 1)
(loop (add1 i) (add1 hits)))
(else
(loop (add1 i) hits)))))
(Tested on Racket, using the definition of hypot I gave in my last answer. If you're not using Racket, you have to change add1 and sub1 to something appropriate.)
I wrote a solution to this problem at my blog; the inner function is called sand because I was throwing grains of sand instead of marbles:
(define (pi n)
(define (sand?) (< (+ (square (rand)) (square (rand))) 1))
(do ((i 0 (+ i 1)) (p 0 (+ p (if (sand?) 1 0))))
((= i n) (exact->inexact (* 4 p (/ n))))))
This converges very slowly; after a hundred thousand iterations I had 3.14188. The blog entry also discusses a method for estimating pi developed by Archimedes over two hundred years before Christ that converges very quickly, with 27 iterations taking us to the bound of double-precision arithmetic.
Here's a general method of doing monte-carlo it accepts as arguments the number of iterations, and a thunk (procedure with no arguments) that should return #t or #f which is the experiment to be run each iteration
(define (monte-carlo trials experiment)
(define (iter trials-remaining trials-passed)
(cond ((= trials-remaining 0)
(/ trials-passed trials))
((experiment)
(iter (- trials-remaining 1) (+ trials-passed 1)))
(else
(iter (- trials-remaining 1) trials-passed))))
(iter trials 0))
Now it's just a mater of writing the specific experiment
You could write in your experiment where experiment is invoked in monte-carlo, but abstracting here gives you a much more flexible and comprehensible function. If you make a function do too many things at once it becomes hard to reason about and debug.
(define (marble-experiment)
(let ((x ...) ;;assuming you can come up with
(y ...)) ;;a way to get a random x between 0 and 1
;;with sufficient granularity for your estimate)
(< (sqrt (+ (* x x) (* y y))) 1)))
(define pi-estimate
(* 4 (monte-carlo 1000 marble-experiment)))
I am currently trying to learn Scheme to run FDTD simulations and I am having trouble building a Gaussian function in 2 dimensions.
In a forum I found this possibility for 1D:
(define ( (gaussx sigma) x)
(exp (- (/ (vector3-dot x x) (* 2 sigma sigma)))))
which if I understood currying correctly is equivalent to:
(define (gauss sigma)
(lambda(x)
(exp (- (/ (vector3-dot x x) (* 2 sigma sigma))))))
Now I would like the function to be gaussian along both x and y directions but I don't understand why this doesn't work:
(define (gauss sigma)
(lambda(x)
(lambda(y)
(exp (- (/ (+ (vector3-dot y y) (vector3-dot x x)) (* 2 sigma sigma))))
When I call
(gauss 1)
I get the following message:
ERROR: Wrong type (expecting real number): # <procedure> #f (y)
Does someone see what I am doing wrong? I also tried other solutions but I don't seem to get the logics here...
Thanks a lot for your help!
Best regards
Mei
I don't think there's need for a double currying here, try this:
(define (gauss sigma)
(lambda (x y)
(exp (- (/ (+ (vector3-dot y y) (vector3-dot x x)) (* 2 sigma sigma))))))
Call it like this:
(define gauss-1 (gauss 1))
(gauss-1 some-x some-y)
But if you definitely need the double currying, this should work:
(define (gauss sigma)
(lambda (x)
(lambda (y)
(exp (- (/ (+ (vector3-dot y y) (vector3-dot x x)) (* 2 sigma sigma)))))))
Using it like this:
(define gauss-1 (gauss 1))
((gauss-1 some-x) some-y)
I'm trying to learn scheme via SICP. Exercise 1.3 reads as follow: Define a procedure that takes three numbers as arguments and returns the sum of the squares of the two larger numbers. Please comment on how I can improve my solution.
(define (big x y)
(if (> x y) x y))
(define (p a b c)
(cond ((> a b) (+ (square a) (square (big b c))))
(else (+ (square b) (square (big a c))))))
Using only the concepts presented at that point of the book, I would do it:
(define (square x) (* x x))
(define (sum-of-squares x y) (+ (square x) (square y)))
(define (min x y) (if (< x y) x y))
(define (max x y) (if (> x y) x y))
(define (sum-squares-2-biggest x y z)
(sum-of-squares (max x y) (max z (min x y))))
big is called max. Use standard library functionality when it's there.
My approach is different. Rather than lots of tests, I simply add the squares of all three, then subtract the square of the smallest one.
(define (exercise1.3 a b c)
(let ((smallest (min a b c))
(square (lambda (x) (* x x))))
(+ (square a) (square b) (square c) (- (square smallest)))))
Whether you prefer this approach, or a bunch of if tests, is up to you, of course.
Alternative implementation using SRFI 95:
(define (exercise1.3 . args)
(let ((sorted (sort! args >))
(square (lambda (x) (* x x))))
(+ (square (car sorted)) (square (cadr sorted)))))
As above, but as a one-liner (thanks synx # freenode #scheme); also requires SRFI 1 and SRFI 26:
(define (exercise1.3 . args)
(apply + (map! (cut expt <> 2) (take! (sort! args >) 2))))
What about something like this?
(define (p a b c)
(if (> a b)
(if (> b c)
(+ (square a) (square b))
(+ (square a) (square c)))
(if (> a c)
(+ (square a) (square b))
(+ (square b) (square c)))))
I did it with the following code, which uses the built-in min, max, and square procedures. They're simple enough to implement using only what's been introduced in the text up to that point.
(define (sum-of-highest-squares x y z)
(+ (square (max x y))
(square (max (min x y) z))))
Using only the concepts introduced up to that point of the text, which I think is rather important, here is a different solution:
(define (smallest-of-three a b c)
(if (< a b)
(if (< a c) a c)
(if (< b c) b c)))
(define (square a)
(* a a))
(define (sum-of-squares-largest a b c)
(+ (square a)
(square b)
(square c)
(- (square (smallest-of-three a b c)))))
(define (sum-sqr x y)
(+ (square x) (square y)))
(define (sum-squares-2-of-3 x y z)
(cond ((and (<= x y) (<= x z)) (sum-sqr y z))
((and (<= y x) (<= y z)) (sum-sqr x z))
((and (<= z x) (<= z y)) (sum-sqr x y))))
(define (f a b c)
(if (= a (min a b c))
(+ (* b b) (* c c))
(f b c a)))
Looks ok to me, is there anything specific you want to improve on?
You could do something like:
(define (max2 . l)
(lambda ()
(let ((a (apply max l)))
(values a (apply max (remv a l))))))
(define (q a b c)
(call-with-values (max2 a b c)
(lambda (a b)
(+ (* a a) (* b b)))))
(define (skip-min . l)
(lambda ()
(apply values (remv (apply min l) l))))
(define (p a b c)
(call-with-values (skip-min a b c)
(lambda (a b)
(+ (* a a) (* b b)))))
And this (proc p) can be easily converted to handle any number of arguments.
With Scott Hoffman's and some irc help I corrected my faulty code, here it is
(define (p a b c)
(cond ((> a b)
(cond ((> b c)
(+ (square a) (square b)))
(else (+ (square a) (square c)))))
(else
(cond ((> a c)
(+ (square b) (square a))))
(+ (square b) (square c)))))
You can also sort the list and add the squares of the first and second element of the sorted list:
(require (lib "list.ss")) ;; I use PLT Scheme
(define (exercise-1-3 a b c)
(let* [(sorted-list (sort (list a b c) >))
(x (first sorted-list))
(y (second sorted-list))]
(+ (* x x) (* y y))))
Here's yet another way to do it:
#!/usr/bin/env mzscheme
#lang scheme/load
(module ex-1.3 scheme/base
(define (ex-1.3 a b c)
(let* ((square (lambda (x) (* x x)))
(p (lambda (a b c) (+ (square a) (square (if (> b c) b c))))))
(if (> a b) (p a b c) (p b a c))))
(require scheme/contract)
(provide/contract [ex-1.3 (-> number? number? number? number?)]))
;; tests
(module ex-1.3/test scheme/base
(require (planet "test.ss" ("schematics" "schemeunit.plt" 2))
(planet "text-ui.ss" ("schematics" "schemeunit.plt" 2)))
(require 'ex-1.3)
(test/text-ui
(test-suite
"ex-1.3"
(test-equal? "1 2 3" (ex-1.3 1 2 3) 13)
(test-equal? "2 1 3" (ex-1.3 2 1 3) 13)
(test-equal? "2 1. 3.5" (ex-1.3 2 1. 3.5) 16.25)
(test-equal? "-2 -10. 3.5" (ex-1.3 -2 -10. 3.5) 16.25)
(test-exn "2+1i 0 0" exn:fail:contract? (lambda () (ex-1.3 2+1i 0 0)))
(test-equal? "all equal" (ex-1.3 3 3 3) 18))))
(require 'ex-1.3/test)
Example:
$ mzscheme ex-1.3.ss
6 success(es) 0 failure(s) 0 error(s) 6 test(s) run
0
It's nice to see how other people have solved this problem. This was my solution:
(define (isGreater? x y z)
(if (and (> x z) (> y z))
(+ (square x) (square y))
0))
(define (sumLarger x y z)
(if (= (isGreater? x y z) 0)
(sumLarger y z x)
(isGreater? x y z)))
I solved it by iteration, but I like ashitaka's and the (+ (square (max x y)) (square (max (min x y) z))) solutions better, since in my version, if z is the smallest number, isGreater? is called twice, creating an unnecessarily slow and circuitous procedure.
(define (sum a b) (+ a b))
(define (square a) (* a a))
(define (greater a b )
( if (< a b) b a))
(define (smaller a b )
( if (< a b) a b))
(define (sumOfSquare a b)
(sum (square a) (square b)))
(define (sumOfSquareOfGreaterNumbers a b c)
(sumOfSquare (greater a b) (greater (smaller a b) c)))
I've had a go:
(define (procedure a b c)
(let ((y (sort (list a b c) >)) (square (lambda (x) (* x x))))
(+ (square (first y)) (square(second y)))))
;exercise 1.3
(define (sum-square-of-max a b c)
(+ (if (> a b) (* a a) (* b b))
(if (> b c) (* b b) (* c c))))
I think this is the smallest and most efficient way:
(define (square-sum-larger a b c)
(+
(square (max a b))
(square (max (min a b) c))))
Below is the solution that I came up with. I find it easier to reason about a solution when the code is decomposed into small functions.
; Exercise 1.3
(define (sum-square-largest a b c)
(+ (square (greatest a b))
(square (greatest (least a b) c))))
(define (greatest a b)
(cond (( > a b) a)
(( < a b) b)))
(define (least a b)
(cond ((> a b) b)
((< a b) a)))
(define (square a)
(* a a))