So, I have three procedures.
(define (addition a)
(+ a 1))
(define (subtraction b)
(- b 1))
(define (recursion a b)
(define a 10)
(define b 0)
(if (a > 0)
(sub1 a)
(add1 b))
(if (b > 0)
(sub1 b)
(add1 a))
0)
The first one takes an integer and adds 1 to it. The second one takes an integer and subtracts 1 from it. The third one is supposed to use these two methods and a recursive way, so if I give (recursion 3 0) as input, it should subtract 1 from 3 until it's 0, and add 1 to 0 until it's 3. As you can see, this code isn't running...
I think the base case would be when a reaches 0 or in the other case b reaches 0. Right?
You first two functions have no issues. They're the classic inc and dec functions. Inc for increment and dec for decrement.
Your "recursion" function should not take a and b as arguments and then set their values with define. Generally, you should not set values with define inside a function in scheme (there are lets to do this, and, in this case, it's not necessary). So drop the (define a something) (define b something).
The main problem with the function "recursion" is that it's not recursive.
A recursive function calls itself. For instance, lets say I recreate your first two functions.
(define (inc a) (+ a 1))
(define (dec a) (+ a 1))
Then I create another function called recursion, but I'll just use one variable for this demo. Let's say that "recursion" will take the number "a".
If a = 5, we just return a . <=== base case
If a < 5, we increment a AND call ourself on the new a . <= recursive case
If a > 5, we decrement a AND call ourself on the new a . <= recursive case
(define (recursion a)
(if (= a 5)
a
(if (< a 5)
(recursion (inc a))
(recursion (dec a)))))
To be really fair, moving toward a central base case is generally not what you want to do. You should be thinking about 'consuming' your input. 0, the empty list, or nil, or good base cases. Anything can be a base case, but these values tend to guild your thinking toward a clear algorithm.
Does that help?
Related
I'm trying to get the hang of recursion in scheme. I put together a Fibinachi function and it keeps returning unspecified instead of a number. How do I make this function return a number and to unspecified?
(define (F n)
(if (= n 0)
0)
(if (= n 1)
1)
(if (< n 2)
(+
(F (- n 1))
(F (- n 2)))))
(display (F 5))
(newline)
The function returns
#<unspecified>
I'm using guile (GNU Guile) 2.0.13.
The issue here is that your code is:
(begin
(if a 1)
(if b 2)
(if c 3))
What is wrong with this? The value of that will be unspecified except if c is true.
Why? The value of each if is unspecified when the condition is false. The begin returns the value of the last expression.
Where did the begin come from you might ask as it didn't appear in my code? To make it easier every lambda and define contains an implicit begin which is why your code was even accepted for execution.
You should use either nested ifs or a cond form:
(if a 1
(if b 2
(if c 3)))
(cond (a 1)
(b 2)
(c 3))
This is not a homework assignment. In the following code:
(defparameter nums '())
(defun fib (number)
(if (< number 2)
number
(push (+ (fib (- number 1)) (fib (- number 2))) nums))
return nums)
(format t "~a " (fib 100))
Since I am quite inexperienced with Common Lisp, I am at a loss as to why the function does not return an value. I am a trying to print first 'n' values, e.g., 100, of the Fibonacci Sequence.
Thank you.
An obvious approach to computing fibonacci numbers is this:
(defun fib (n)
(if (< n 2)
n
(+ (fib (- n 1)) (fib (- n 2)))))
(defun fibs (n)
(loop for i from 1 below n
collect (fib i)))
A little thought should tell you why no approach like this is going to help you compute the first 100 Fibonacci numbers: the time taken to compute (fib n) is equal to or a little more than the time taken to compute (fib (- n 1)) plus the time taken to compute (fib (- n 2)): this is exponential (see this stack overflow answer).
A good solution to this is memoization: the calculation of (fib n) repeats subcalculations a huge number of times, and if we can just remember the answer we computed last time we can avoid doing so again.
(An earlier version of this answer has an overcomplex macro here: something like that may be useful in general but is not needed here.)
Here is how you can memoize fib:
(defun fib (n)
(check-type n (integer 0) "natural number")
(let ((so-far '((2 . 1) (1 . 1) (0 . 0))))
(labels ((fibber (m)
(when (> m (car (first so-far)))
(push (cons m (+ (fibber (- m 1))
(fibber (- m 2))))
so-far))
(cdr (assoc m so-far))))
(fibber n))))
This keeps a table – an alist – of the results it has computed so far, and uses this to avoid recomputation.
With this memoized version of the function:
> (time (fib 1000))
Timing the evaluation of (fib 1000)
User time = 0.000
System time = 0.000
Elapsed time = 0.000
Allocation = 101944 bytes
0 Page faults
43466557686937456435688527675040625802564660517371780402481729089536555417949051890403879840079255169295922593080322634775209689623239873322471161642996440906533187938298969649928516003704476137795166849228875
The above definition uses a fresh cache for each call to fib: this is fine, because the local function, fibber does reuse the cache. But you can do better than this by putting the cache outside the function altogether:
(defmacro define-function (name expression)
;; Install EXPRESSION as the function value of NAME, returning NAME
;; This is just to avoid having to say `(setf ...)`: it should
;; probably do something at compile-time too so the compiler knows
;; the function will be defined.
`(progn
(setf (fdefinition ',name) ,expression)
',name))
(define-function fib
(let ((so-far '((2 . 1) (1 . 1) (0 . 0))))
(lambda (n)
(block fib
(check-type n (integer 0) "natural number")
(labels ((fibber (m)
(when (> m (car (first so-far)))
(push (cons m (+ (fibber (- m 1))
(fibber (- m 2))))
so-far))
(cdr (assoc m so-far))))
(fibber n))))))
This version of fib will share its cache between calls, which means it is a little faster, allocates a little less memory but may be less thread-safe:
> (time (fib 1000))
[...]
Allocation = 96072 bytes
[...]
> (time (fib 1000))
[...]
Allocation = 0 bytes
[...]
Interestingly memoization was invented (or at least named) by Donald Michie, who worked on breaking Tunny (and hence with Colossus), and who I also knew slightly: the history of computing is still pretty short!
Note that memoization is one of the times where you can end up fighting a battle with the compiler. In particular for a function like this:
(defun f (...)
...
;; no function bindings or notinline declarations of F here
...
(f ...)
...)
Then the compiler is allowed (but not required) to assume that the apparently recursive call to f is a recursive call into the function it is compiling, and thus to avoid a lot of the overhead of a full function call. In particular it is not required to retrieve the current function value of the symbol f: it can just call directly into the function itself.
What this means is that an attempt to write a function, memoize which can be used to mamoize an existing recursive function, as (setf (fdefinition 'f) (memoize #'f)) may not work: the function f still call directly into the unmemoized version of itself and won't notice that the function value of f has been changed.
This is in fact true even if the recursion is indirect in many cases: the compiler is allowed to assume that calls to a function g for which there is a definition in the same file are calls to the version defined in the file, and again avoid the overhead of a full call.
The way to deal with this is to add suitable notinline declarations: if a call is covered by a notinline declaration (which must be known to the compiler) then it must be made as a full call. From the spec:
A compiler is not free to ignore this declaration; calls to the specified functions must be implemented as out-of-line subroutine calls.
What this means is that, in order to memoize functions you have to add suitable notinline declarations for recursive calls, and this means that memoizing either needs to be done by a macro, or must rely on the user adding suitable declarations to the functions to be memoized.
This is only a problem because the CL compiler is allowed to be smart: almost always that's a good thing!
Your function unconditionally returns nums (but only if a variable called return exists). To see why, we can format it like this:
(defun fib (number)
(if (< number 2)
number
(push (+ (fib (- number 1)) (fib (- number 2))) nums))
return
nums)
If the number is less than 2, then it evaluates the expression number, uselessly, and throws away the result. Otherwise, it pushes the result of the (+ ....) expression onto the nums list. Then it uselessly evaluates return, throwing away the result. If a variable called return doesn't exist, that's an error situation. Otherwise, it evaluates nums and that is the return value.
In Common Lisp, there is a return operator for terminating and returning out of anonymous named blocks (blocks whose name is the symbol nil). If you define a named function with defun, then an invisible block exists which is not anonymous: it has the same name as that function. In that case, return-from can be used:
(defun function ()
(return-from function 42) ;; function terminates, returns 42
(print 'notreached)) ;; this never executes
Certain standard control flow and looping constructs establish a hidden anonymous block, so return can be used:
(dolist (x '(1 2 3))
(return 42)) ;; loop terminates, yields 42 as its result
If we use (return ...) but there is no enclosing anonymous block, that is an error.
The expression (return ...) is different from just return, which evaluates a variable named by the symbol return, retrieving its contents.
It is not clear how to repair your fib function, because the requirements are unknown. The side effect of pushing values into a global list normally doesn't belong inside a mathematical function like this, which should be pure (side-effect-free).
So you might know that if you know the two previous numbers you can compute the next. What comes after 3, 5? If you guess 8 you have understood it. Now if you start with 0, 1 and roll 1, 1, 1, 2, etc you collect the first variable until you have the number of numbers you'd like:
(defun fibs (elements)
"makes a list of elements fibonacci numbers starting with the first"
(loop :for a := 0 :then b
:for b := 1 :then c
:for c := (+ a b)
:for n :below elements
:collect a))
(fibs 10)
; ==> (0 1 1 2 3 5 8 13 21 34)
Every form in Common Lisp "returns" a value. You can say it evaluates to. eg.
(if (< a b)
5
10)
This evaluates either to 5 or 10. Thus you can do this and expect that it evaluates to either 15 or 20:
(+ 10
(if (< a b)
5
10))
You basically want your functions to have one expression that calculates the result. eg.
(defun fib (n)
(if (zerop n)
n
(+ (fib (1- n)) (fib (- n 2)))))
This evaluates to the result og the if expression... loop with :collect returns the list. You also have (return expression) and (return-from name expression) but they are usually unnecessary.
Your global variable num is actually not that a bad idea.
It is about to have a central memory about which fibonacci numbers were already calculated. And not to calculate those already calculated numbers again.
This is the very idea of memoization.
But first, I do it in bad manner with a global variable.
Bad version with global variable *fibonacci*
(defparameter *fibonacci* '(1 1))
(defun fib (number)
(let ((len (length *fibonacci*)))
(if (> len number)
(elt *fibonacci* (- len number 1)) ;; already in *fibonacci*
(labels ((add-fibs (n-times)
(push (+ (car *fibonacci*)
(cadr *fibonacci*))
*fibonacci*)
(cond ((zerop n-times) (car *fibonacci*))
(t (add-fibs (1- n-times))))))
(add-fibs (- number len))))))
;;> (fib 10)
;; 89
;;> *fibonacci*
;; (89 55 34 21 13 8 5 3 2 1 1)
Good functional version (memoization)
In memoization, you hide the global *fibonacci* variable
into the environment of a lexical function (the memoized version of a function).
(defun memoize (fn)
(let ((cache (make-hash-table :test #'equal)))
#'(lambda (&rest args)
(multiple-value-bind (val win) (gethash args cache)
(if win
val
(setf (gethash args cache)
(apply fn args)))))))
(defun fib (num)
(cond ((zerop num) 1)
((= 1 num) 1)
(t (+ (fib (- num 1))
(fib (- num 2))))))
The previously global variable *fibonacci* is here actually the local variable cache of the memoize function - encapsulated/hidden from the global environment,
accessible/look-up-able only through the function fibm.
Applying memoization on fib (bad version!)
(defparameter fibm (memoize #'fib))
Since common lisp is a Lisp 2 (separated namespace between function and variable names) but we have here to assign the memoized function to a variable,
we have to use (funcall <variable-name-bearing-function> <args for memoized function>).
(funcall fibm 10) ;; 89
Or we define an additional
(defun fibm (num)
(funcall fibm num))
and can do
(fibm 10)
However, this saves/memoizes only the out calls e.g. here only the
Fibonacci value for 10. Although for that, Fibonacci numbers
for 9, 8, ..., 1 are calculated, too.
To make them saved, look the next section!
Applying memoization on fib (better version by #Sylwester - thank you!)
(setf (symbol-function 'fib) (memoize #'fib))
Now the original fib function is the memoized function,
so all fib-calls will be memoized.
In addition, you don't need funcall to call the memoized version,
but just do
(fib 10)
I am still new in racket language.
I am implementing a switch case in racket but it is not working.
So, I shift into using the equal and condition. I want to know how can i call a function that takes input. for example: factorial(n) function
I want to call it in :
(if (= c 1) (factorial (n))
There are two syntax problems with this snippet:
(if (= c 1) (factorial (n)))
For starters, an if expression in Racket needs three parts:
(if <condition> <consequent> <alternative>)
The first thing to fix would be to provide an expression that will be executed when c equals 1, and another that will run if c is not equal to 1. Say, something like this:
(if (= c 1) 1 (factorial (n)))
Now the second problem: in Scheme, when you surround a symbol with parentheses it means that you're trying to execute a function. So if you write (n), the interpreter believes that n is a function with no arguments and that you're trying to call it. To fix this, simply remove the () around n:
(if (= c 1) 1 (factorial n))
Now that the syntax problems are out of the way, let's examine the logic. In Scheme, we normally use recursion to express solutions, but a recursion has to advance at some point, so it will eventually end. If you keep passing the same parameter to the recursion, without modifying it, you'll get caught in an infinite loop. Here's the proper way to write a recursive factorial procedure:
(define (factorial n)
(if (<= n 0) ; base case: if n <= 0
1 ; then return 1
(* n (factorial (- n 1))))) ; otherwise multiply and advance recursion
Notice how we decrement n at each step, to make sure that it will eventually reach zero, ending the recursion. Once you get comfortable with this solution, we can think of making it better. Read about tail recursion, see how the compiler will optimize our loops as long as we write them in such a way that the last thing done on each execution path is the recursive call, with nothing left to do after it. For instance, the previous code can be written more efficiently as follows, and see how we pass the accumulated answer in a parameter:
(define (factorial n)
(let loop ([n n] [acc 1])
(if (<= n 0)
acc
(loop (- n 1) (* n acc)))))
UPDATE
After taking a look at the comments, I see that you want to implement a switchcase procedure. Once again, there are problems with the way you're declaring functions. This is wrong:
(define fact(x)
The correct way is this:
(define (fact x)
And for actually implementing switchcase, it's possible to use nested ifs as you attempted, but that's not the best way. Learn how to use the cond expression or the case expression, either one will make your solution simpler. And anyway you have to provide an additional condition, in case c is neither 1 nor 2. Also, you're confounding the parameter name - is it c or x? With all the recommendations in place, here's how your code should look:
(define (switchcase c)
(cond ((= c 1) (fact c))
((= c 2) (triple c))
(else (error "unknown value" c))))
In racket-lang, conditionals with if has syntax:
(if <expr> <expr> <expr>)
So in your case, you have to provide another <expr>.
(define (factorial n)
(if (= n 1) 1 (* n (factorial (- n 1)))))
;^exp ^exp ^exp
(factorial 3)
The results would be 6
Update:
(define (factorial n)
(if (= n 1) 1 (* n (factorial (- n 1)))))
(define (triple x)
(* 3 x))
(define (switchcase c)
(if (= c 1)
(factorial c)
(if(= c 2)
(triple c) "c is not 1 or 2")))
(switchcase 2)
If you want something a lot closer to a switch case given you can return procedures.
(define (switch input cases)
(let ((lookup (assoc input cases)))
(if lookup
(cdr lookup)
(error "Undefined case on " input " in " cases))))
(define (this-switch c)
(let ((cases (list (cons 1 triple)
(cons 2 factorial))))
((switch c cases) c)))
I'm unsure of how to turn count-forwards into a tail-recursive program. It takes a non-negative number, n, and returns the list of integers from 0 to n (including n).
Edit: Okay, I finally got this one to work. The problem wasn't that my current program was recursive and I needed to make it tail-recursive- It was just plain wrong. The actual answer is really short and clean. So if anyone else is stuck on this and is also a total programming noob, here's a few hints that might help:
1) Your helper program is designed to keep track of the list so far.
2) Its base case is.. If x = 0.. what do you do? add 0 onto.. something.
3) Recur on x - 1, and then add x onto your list so far.
4) When you get to your actual program, count-forwards, all you need is the helper. But remember that it takes two arguments!
The only recursive function here is list-reverse. It is tail-recursive, because the call to itself is the last operation in the function body.
Your function for generating a nondecreasing sequence from zero to m, which contains the successive results of adding 1 to the previous element, would look something like:
(define (my-reverse lst)
(define (rev-do xs ys)
(if (empty? xs)
ys
(rev-do (cdr xs) (cons (car xs) ys))))
(rev-do lst empty))
(define (seq m n)
(seq-do m n (list m)))
(define (seq-do m n xs)
(if (= m n)
(my-reverse xs)
(let ((next (add1 m)))
(seq-do next n (cons next xs)))))
(define (seq-from-zero m)
(seq 0 m))
Test:
> (seq-from-zero 10)
(0 1 2 3 4 5 6 7 8 9 10)
seq-do is a general function for generating nondecreasing sequences from m to n; it is tail-recursive, because the last operation is the call to itself.
I've also implemented reverse from scratch, so that you can use it in your homework problems.
My solution to exercise 1.11 of SICP is:
(define (f n)
(if (< n 3)
n
(+ (f (- n 1)) (* 2 (f (- n 2))) (* 3 (f (- n 3))))
))
As expected, a evaluation such as (f 100) takes a long time. I was wondering if there was a way to improve this code (without foregoing the recursion), and/or take advantage of multi-core box. I am using 'mit-scheme'.
The exercise tells you to write two functions, one that computes f "by means of a recursive process", and another that computes f "by means of an iterative process". You did the recursive one. Since this function is very similar to the fib function given in the examples of the section you linked to, you should be able to figure this out by looking at the recursive and iterative examples of the fib function:
; Recursive
(define (fib n)
(cond ((= n 0) 0)
((= n 1) 1)
(else (+ (fib (- n 1))
(fib (- n 2))))))
; Iterative
(define (fib n)
(fib-iter 1 0 n))
(define (fib-iter a b count)
(if (= count 0)
b
(fib-iter (+ a b) a (- count 1))))
In this case you would define an f-iter function which would take a, b, and c arguments as well as a count argument.
Here is the f-iter function. Notice the similarity to fib-iter:
(define (f-iter a b c count)
(if (= count 0)
c
(f-iter (+ a (* 2 b) (* 3 c)) a b (- count 1))))
And through a little trial and error, I found that a, b, and c should be initialized to 2, 1, and 0 respectively, which also follows the pattern of the fib function initializing a and b to 1 and 0. So f looks like this:
(define (f n)
(f-iter 2 1 0 n))
Note: f-iter is still a recursive function but because of the way Scheme works, it runs as an iterative process and runs in O(n) time and O(1) space, unlike your code which is not only a recursive function but a recursive process. I believe this is what the author of Exercise 1.1 was looking for.
I'm not sure how best to code it in Scheme, but a common technique to improve speed on something like this would be to use memoization. In a nutshell, the idea is to cache the result of f(p) (possibly for every p seen, or possibly the last n values) so that next time you call f(p), the saved result is returned, rather than being recalculated. In general, the cache would be a map from a tuple (representing the input arguments) to the return type.
Well, if you ask me, think like a mathematician. I can't read scheme, but if you're coding a Fibonacci function, instead of defining it recursively, solve the recurrence and define it with a closed form. For the Fibonacci sequence, the closed form can be found here for example. That'll be MUCH faster.
edit: oops, didn't see that you said forgoing getting rid of the recursion. In that case, your options are much more limited.
See this article for a good tutorial on developing a fast Fibonacci function with functional programming. It uses Common LISP, which is slightly different from Scheme in some aspects, but you should be able to get by with it. Your implementation is equivalent to the bogo-fig function near the top of the file.
To put it another way:
To get tail recursion, the recursive call has to be the very last thing the procedure does.
Your recursive calls are embedded within the * and + expressions, so they are not tail calls (since the * and + are evaluated after the recursive call.)
Jeremy Ruten's version of f-iter is tail-recursive rather than iterative (i.e. it looks like a recursive procedure but is as efficient as the iterative equivalent.)
However you can make the iteration explicit:
(define (f n)
(let iter
((a 2) (b 1) (c 0) (count n))
(if (<= count 0)
c
(iter (+ a (* 2 b) (* 3 c)) a b (- count 1)))))
or
(define (f n)
(do
((a 2 (+ a (* 2 b) (* 3 c)))
(b 1 a)
(c 0 b)
(count n (- count 1)))
((<= count 0) c)))
That particular exercise can be solved by using tail recursion - instead of waiting for each recursive call to return (as is the case in the straightforward solution you present), you can accumulate the answer in a parameter, in such a way that the recursion behaves exactly the same as an iteration in terms of the space it consumes. For instance:
(define (f n)
(define (iter a b c count)
(if (zero? count)
c
(iter (+ a (* 2 b) (* 3 c))
a
b
(- count 1))))
(if (< n 3)
n
(iter 2 1 0 n)))