So as far as I understand, the following: let, let*, letrec and letrec* are synthetics sugars used in Scheme/Racket.
Now, if I have a simple program:
(let ((x 1)
(y 2))
(+ x y))
It is translated into:
((lambda (x y) (+ x y)) 1 2)
If I have:
(let* ((x 1)
(y 2))
(+ x y))
It is translated into:
((lambda (x) ((lambda (y) (+ x y))) 2) 1)
Now, for my first question, I understand the meaning of a letrec expression, which enables one to use recursion inside a let, but I do not understand how exactly it is done. What is letrec translated to?
For example, what will
(letrec ((x 1)
(y 2))
(+ x y))
be translated into?
The second question is similar about letrec* - But for letrec* I do not understand how exactly it differs from letrec? And also, what will a letrec* expression be translated into?
See the paper "Fixing Letrec: A Faithful Yet Efficient Implementation
of Scheme’s Recursive Binding Construct" by Oscar Waddell, Dipanwita Sarkar, and,
R. Kent Dybvig.
The paper starts with a simple version and proceeds to explain a more sophisticated expansion:
https://www.cs.indiana.edu/~dyb/pubs/fixing-letrec.pdf
Since you example does not have any procedures and no real expressions I'd say you could implement it as:
(let ((x 1) (y 2))
(+ x y))
But to support the intention of the form a basic implementaiton might do something like this:
(let ((x 'undefined) (y 'undefined))
(let ((tmpx 1) (tmpy 2))
(set! x tmpx)
(set! y tmpy))
(+ x y))
Now. letrec is for lambdas to be able to call themselves by the name. So imagine this:
(let ((fib (lambda (n)
(if (< n 2) n
(+ (fib (- n 1)) (fib (- n 2)))))))
(fib 10))
It's important to understand that this does not work and why. Transforming it into a lambda call makes it so easy to see:
((lambda (fib)
(fib 10))
(lambda (n)
(if (< n 2) n
(+ (fib (- n 1)) (fib (- n 2))))))
Somehow you need to evaluate the lambda after fib is created. Lets imagine we do this:
(let ((fib 'undefined))
(set! fib (lambda (n)
(if (< n 2) n
(+ (fib (- n 1)) (fib (- n 2))))))
(fib 10))
Alternatively you can do it with a Z combinator to make it pure:
(let ((fib (Z (lambda (fib)
(lambda (n)
(if (< n 2) n
(+ (fib (- n 1)) (fib (- n 2)))))))))
(fib 10))
This requires more work by the implementation, but at least you do without mutation. To make it work with several mutual recursive bindings probably takes some more work but I'm convinced its doable.
These are the only two ways to do this properly. I know clojure has a recur which imitates recursion but in reality is a a goto.
For variables that do not make closures from the letrec bindings they work as let and later more like let* since Soegaards answer about fix is backwards compatible and some has adapted it. If you write compatible code though you should not be tempted to assume this.
Related
Here is the Y-combinator in Racket:
#lang lazy
(define Y (λ(f)((λ(x)(f (x x)))(λ(x)(f (x x))))))
(define Fact
(Y (λ(fact) (λ(n) (if (zero? n) 1 (* n (fact (- n 1))))))))
(define Fib
(Y (λ(fib) (λ(n) (if (<= n 1) n (+ (fib (- n 1)) (fib (- n 2))))))))
Here is the Y-combinator in Scheme:
(define Y
(lambda (f)
((lambda (x) (x x))
(lambda (g)
(f (lambda args (apply (g g) args)))))))
(define fac
(Y
(lambda (f)
(lambda (x)
(if (< x 2)
1
(* x (f (- x 1))))))))
(define fib
(Y
(lambda (f)
(lambda (x)
(if (< x 2)
x
(+ (f (- x 1)) (f (- x 2))))))))
(display (fac 6))
(newline)
(display (fib 6))
(newline)
My question is: Why does Scheme require the apply function but Racket does not?
Racket is very close to plain Scheme for most purposes, and for this example, they're the same. But the real difference between the two versions is the need for a delaying wrapper which is needed in a strict language (Scheme and Racket), but not in a lazy one (Lazy Racket, a different language).
That wrapper is put around the (x x) or (g g) -- what we know about this thing is that evaluating it will get you into an infinite loop, and we also know that it's going to be the resulting (recursive) function. Because it's a function, we can delay its evaluation with a lambda: instead of (x x) use (lambda (a) ((x x) a)). This works fine, but it has another assumption -- that the wrapped function takes a single argument. We could just as well wrap it with a function of two arguments: (lambda (a b) ((x x) a b)) but that won't work in other cases too. The solution is to use a rest argument (args) and use apply, therefore making the wrapper accept any number of arguments and pass them along to the recursive function. Strictly speaking, it's not required always, it's "only" required if you want to be able to produce recursive functions of any arity.
On the other hand, you have the Lazy Racket code, which is, as I said above, a different language -- one with call-by-need semantics. Since this language is lazy, there is no need to wrap the infinitely-looping (x x) expression, it's used as-is. And since no wrapper is required, there is no need to deal with the number of arguments, therefore no need for apply. In fact, the lazy version doesn't even need the assumption that you're generating a function value -- it can generate any value. For example, this:
(Y (lambda (ones) (cons 1 ones)))
works fine and returns an infinite list of 1s. To see this, try
(!! (take 20 (Y (lambda (ones) (cons 1 ones)))))
(Note that the !! is needed to "force" the resulting value recursively, since Lazy Racket doesn't evaluate recursively by default. Also, note the use of take -- without it, Racket will try to create that infinite list, which will not get anywhere.)
Scheme does not require apply function. you use apply to accept more than one argument.
in the factorial case, here is my implementation which does not require apply
;;2013/11/29
(define (Fact-maker f)
(lambda (n)
(cond ((= n 0) 1)
(else (* n (f (- n 1)))))))
(define (fib-maker f)
(lambda (n)
(cond ((or (= n 0) (= n 1)) 1)
(else
(+ (f (- n 1))
(f (- n 2)))))))
(define (Y F)
((lambda (procedure)
(F (lambda (x) ((procedure procedure) x))))
(lambda (procedure)
(F (lambda (x) ((procedure procedure) x))))))
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)))
this is possibly much of an elementary question, but I'm having trouble with a procedure I have to write in Scheme. The procedure should return all the prime numbers less or equal to N (N is from input).
(define (isPrimeHelper x k)
(if (= x k) #t
(if (= (remainder x k) 0) #f
(isPrimeHelper x (+ k 1)))))
(define ( isPrime x )
(cond
(( = x 1 ) #t)
(( = x 2 ) #t)
( else (isPrimeHelper x 2 ) )))
(define (printPrimesUpTo n)
(define result '())
(define (helper x)
(if (= x (+ 1 n)) result
(if (isPrime x) (cons x result) ))
( helper (+ x 1)))
( helper 1 ))
My check for prime works, however the function printPrimesUpTo seem to loop forever. Basically the idea is to check whether a number is prime and put it in a result list.
Thanks :)
You have several things wrong, and your code is very non-idiomatic. First, the number 1 is not prime; in fact, is it neither prime nor composite. Second, the result variable isn't doing what you think it is. Third, your use of if is incorrect everywhere it appears; if is an expression, not a statement as in some other programming languages. And, as a matter of style, closing parentheses are stacked at the end of the line, and don't occupy a line of their own. You need to talk with your professor or teaching assistant to clear up some basic misconceptions about Scheme.
The best algorithm to find the primes less than n is the Sieve of Eratosthenes, invented about twenty-two centuries ago by a Greek mathematician who invented the leap day and a system of latitude and longitude, accurately measured the circumference of the Earth and the distance from Earth to Sun, and was chief librarian of Ptolemy's library at Alexandria. Here is a simple version of his algorithm:
(define (primes n)
(let ((bits (make-vector (+ n 1) #t)))
(let loop ((p 2) (ps '()))
(cond ((< n p) (reverse ps))
((vector-ref bits p)
(do ((i (+ p p) (+ i p))) ((< n i))
(vector-set! bits i #f))
(loop (+ p 1) (cons p ps)))
(else (loop (+ p 1) ps))))))
Called as (primes 50), that returns the list (2 3 5 7 11 13 17 19 23 29 31 37 41 43 47). It is much faster than testing numbers for primality by trial division, as you are attempting to do. If you must, here is a proper primality checker:
(define (prime? n)
(let loop ((d 2))
(cond ((< n (* d d)) #t)
((zero? (modulo n d)) #f)
(else (loop (+ d 1))))))
Improvements are possible for both algorithms. If you are interested, I modestly recommend this essay on my blog.
First, it is good style to express nested structure by indentation, so it is visually apparent; and also to put each of if's clauses, the consequent and the alternative, on its own line:
(define (isPrimeHelper x k)
(if (= x k)
#t ; consequent
(if (= (remainder x k) 0) ; alternative
;; ^^ indentation
#f ; consequent
(isPrimeHelper x (+ k 1))))) ; alternative
(define (printPrimesUpTo n)
(define result '())
(define (helper x)
(if (= x (+ 1 n))
result ; consequent
(if (isPrime x) ; alternative
(cons x result) )) ; no alternative!
;; ^^ indentation
( helper (+ x 1)))
( helper 1 ))
Now it is plainly seen that the last thing that your helper function does is to call itself with an incremented x value, always. There's no stopping conditions, i.e. this is an infinite loop.
Another thing is, calling (cons x result) does not alter result's value in any way. For that, you need to set it, like so: (set! result (cons x result)). You also need to put this expression in a begin group, as it is evaluated not for its value, but for its side-effect:
(define (helper x)
(if (= x (+ 1 n))
result
(begin
(if (isPrime x)
(set! result (cons x result)) ) ; no alternative!
(helper (+ x 1)) )))
Usually, the explicit use of set! is considered bad style. One standard way to express loops is as tail-recursive code using named let, usually with the canonical name "loop" (but it can be any name whatever):
(define (primesUpTo n)
(let loop ((x n)
(result '()))
(cond
((<= x 1) result) ; return the result
((isPrime x)
(loop (- x 1) (cons x result))) ; alter the result being built
(else (loop (- x 1) result))))) ; go on with the same result
which, in presence of tail-call optimization, is actually equivalent to the previous version.
The (if) expression in your (helper) function is not the tail expression of the function, and so is not returned, but control will always continue to (helper (+ x 1)) and recurse.
The more efficient prime?(from Sedgewick's "Algorithms"):
(define (prime? n)
(define (F n i) "helper"
(cond ((< n (* i i)) #t)
((zero? (remainder n i)) #f)
(else
(F n (+ i 1)))))
"primality test"
(cond ((< n 2) #f)
(else
(F n 2))))
You can do this much more nicely. I reformated your code:
(define (prime? x)
(define (prime-helper x k)
(cond ((= x k) #t)
((= (remainder x k) 0) #f)
(else
(prime-helper x (+ k 1)))))
(cond ((= x 1) #f)
((= x 2) #t)
(else
(prime-helper x 2))))
(define (primes-up-to n)
(define (helper x)
(cond ((= x 0) '())
((prime? x)
(cons x (helper (- x 1))))
(else
(helper (- x 1)))))
(reverse
(helper n)))
scheme#(guile-user)> (primes-up-to 20)
$1 = (2 3 5 7 11 13 17 19)
Please don’t write Scheme like C or Java – and have a look at these style rules for languages of the lisp-family for the sake of readability: Do not use camel-case, do not put parentheses on own lines, mark predicates with ?, take care of correct indentation, do not put additional whitespace within parentheses.
I'm new to functional language and I'm doing SICP programming assignments using Racket.
Below is a snippet of code, and Racket informs me that define: expected only one expression for the function body, but found 5 extra parts, in line 5 ((define (y k)):
(define (simpson f a b n)
(define h (/ (- b a) n))
(define (y k)
(f (+ a (* k h))))
(define (factor k)
(cond ((or (= k 0) (= k n))
1)
((odd? k)
4)
(else
2)))
(define (term k)
(* (factor k)
(y k)))
(define (next k)
(+ k 1))
(if (not (even? n))
(error "n can't be odd")
(* (/ h 3)
(sum term (exact->inexact a) next n))))
I guess this problem is related to the language settings, but I already use "advanced" option.
Anybody know how to configure Racket properly, or internal "define" is not supported?
Indeed, it's as you say: internal defines are not supported by the Advanced language. For working with the SICP exercises, I've been told it's best to use the neil/sicp package: instructions for using this are detailed here.
However, even the standard Racket language (#lang racket) will support internal defines without problems.
I'm making a function that multiplies all numbers between an 1 input and a "x" input with dotimes loop. If you please, check my function and say what's wrong since I don't know loops very well in Scheme.
(define (product x)
(let ((result 1))
(dotimes (temp x)
(set! result (* temp (+ result 1))))
result))
Use recursion. It is the way to do things in Scheme/Racket. And try to never use set! and other functions that change variables unless there really is no other choice.
Here's a textbook example of recursion in Scheme:
(define factorial
(lambda (x)
(if (<= x 1)
1
(* x (factorial (- x 1))))))