I have a list comprehension in Haskell that I want to translate to Prolog.
The point of the list comprehension is rotating a 4 by 4 grid:
rotate :: [Int] -> [Int]
rotate grid = [ grid !! (a + 4 * b) | a <- [0..3], b <- [0..3] ]
Now in Prolog, I translated it like this:
rotateGrid([T0,T1,T2,T3,T4,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15],
[T0,T4,T8,T12,T1,T5,T9,T13,T2,T6,T10,T14,T3,T7,T11,T15]).
Can we do better?
We can use findall/3 for list comprehensions (Cf. the SWI-Prolog Documentation). E.g.,
?- findall(X, between(1,10,X), Xs).
Xs = [1,2,3,4,5,6,7,8,9,10]
Xs is a list holding all values that can unify with X when X is a number between 1 and 10. This is roughly equivalent to the Haskell expression let Xs = [x | x <- [1..10]](1). You can read a findall/3 statement thus: "find all values of [First Argument] such that [Conditions in Second Argument] hold, and put those values in the list, [Third Argument]".
I've used findall/3 to write a predicate rotate_grid(+Grid, ?RotatedGrid). Here is a list of the approximate Haskell-Prolog equivalences I used in the predicate; each line shows the relation between the value that the Haskell expression will evaluate to and the Prolog variable with the same value:
a <- [0..3] = A in between(0, 3, A)
b <- [0..3] = B in between(0, 3, B)
(a + 4 * d) = X in X is A + 4 * D
<Grid> !! <Index> = Element in nth0(Index, Grid, Element)
Then we simply need to find all the values of Element:
rotate_grid(Grid, RotatedGrid) :-
findall( Element,
( between(0,3,A),
between(0,3,B),
Index is A + 4 * B,
nth0(Index, Grid, Element) ),
RotatedGrid
).
To verify that this produces the right transformation, I down-cased the Prolog code from the question and posed the following query:
?- rotate_grid([t0,t1,t2,t3,t4,t5,t6,t7,t8,t9,t10,t11,t12,t13,t14,t15],
[t0,t4,t8,t12,t1,t5,t9,t13,t2,t6,t10,t14,t3,t7,t11,t15]).
| true.
Footnotes:
(1): between/3 isn't actually the analogue of [m..n], since the latter returns a list of values from m to n where between(M,N,X) will instantiate X with each value between M and N (inclusive) on backtracking. To get a list of numbers in SWI-Prolog, we can use numlist(M,N,Ns). So a stricter analogue for x <- [1.10] would be the conjunction member(X, Ns), numlist(1, 10, Ns).
You want a permutation of a list. The concrete elements are not considered. Therefore, you can generalize your Haskell signature to
rotate :: [x] -> [x]
This is already a very valuable hint for Prolog: the list's elements will not be considered - elements will not even be compared. So a Prolog solution should be able to handle variables directly, like so:
?- rotateGrid(L,R).
L = [_A,_B,_C,_D,_E,_F,_G,_H,_I,_J,_K,_L,_M,_N,_O,_P],
R = [_A,_E,_I,_M,_B,_F,_J,_N,_C,_G,_K,_O,_D,_H,_L,_P].
And your original definition handles this perfectly.
Your version using list comprehensions suggests itself to be realized via backtracking, certain precautions have to be taken. Using findall/3, as suggested by #aBathologist will rename variables:
?- length(L,16),rotate_grid(L,R).
L = [_A,_B,_C,_D,_E,_F,_G,_H,_I,_J,_K,_L,_M,_N,_O,_P],
R = [_Q,_R,_S,_T,_U,_V,_W,_X,_Y,_Z,_A1,_B1,_C1,_D1,_E1,_F1].
The built-in predicate bagof/3 addresses this problem. Note that we have to declare all local, existential variables explicitly:
rotate_grid2(Grid, RotatedGrid) :-
bagof(
Element,
A^B^Index^ % declaration of existential variables
( between(0,3,A),
between(0,3,B),
Index is A + 4 * B,
nth0(Index, Grid, Element)
),
RotatedGrid).
For lists that are shorter than 16 elements, the Haskell version produces a clean error, but here we get pretty random results:
?- L=[1,2,3,4],rotate_grid(L,R).
L = [1,2,3,4], R = [1,2,3,4].
?- L=[1,2,3,4,5],rotate_grid(L,R).
L = [1,2,3,4,5], R = [1,5,2,3,4].
This is due to the unclear separation between the part that enumerates and "generates" a concrete element. The cleanest way is to add length(Grid, 16) prior to the goal bagof/3.
List comprehensions in Prolog
Currently, only B-Prolog offers a form of list comprehensions:
R#=[E: A in 0..3,B in 0..3,[E,I],(I is A+4*B,nth0(I,L,E))].
However, it does not address the second problem:
| ?- L = [1,2,3], R#=[E: A in 0..3,B in 0..3,[E,I],(I is A+4*B,nth0(I,L,E))].
L = [1,2,3]
R = [1,2,3]
yes
Use a loop predicate foreach/4
If the comprehension should retain variables, which is for example important in constraint programming, a Prolog system could offer a predicate foreach/4. This predicate is the DCG buddy of foreach/2.
Here is how variables are not retained via findall/3, the
result R contains fresh variables according to the ISO
core semantics of findall/3:
Welcome to SWI-Prolog (threaded, 64 bits, version 7.7.1)
SWI-Prolog comes with ABSOLUTELY NO WARRANTY. This is free software.
?- functor(L,foo,5), findall(X,
(between(1,5,N), M is 6-N, arg(M,L,X)), R).
L = foo(_5140, _5142, _5144, _5146, _5148),
R = [_5210, _5204, _5198, _5192, _5186].
And here is how variables can be retained via foreach/4,
the resulting list has the same variables as the compound
we started with:
Jekejeke Prolog 3, Runtime Library 1.3.0
(c) 1985-2018, XLOG Technologies GmbH, Switzerland
?- [user].
helper(N,L) --> [X], {M is 6-N, arg(M,L,X)}.
Yes
?- functor(L,foo,5), foreach(between(1,5,N),helper(N,L),R,[]).
L = foo(_A,_G,_M,_S,_Y),
R = [_Y,_S,_M,_G,_A]
Using foreach/4 instead of bagof/3 might seem a little bit over the top. foreach/4 will probably only show its full potential when implementing Picat loops, since it can build up constraints, what bagof/3 cannot do.
foreach/4 is an implementation without the full materialization of all solution that are then backtracked. It shares with bagof/3 the reconstruct of variables, but still allows backtracking in the conjunction of the closures.
Related
I am looking to implement a "general" ordinal type that supports multiple "infinities" (e.g. [1,2,..., W, W+1, W+2, .. , 2 W, .., WW, etc]). I was thinking of implementing as a composite number (e.g. [5:4:2578] < [1:5:4:2578] < [1:5:4:2579] < [1:5:5:2]) with Ints, where comparison starts from the end of the list.
Currently i have implemented it as:
newtype Ordinal = Order [Int]
deriving (Eq)
instance Ord Ordinal where
(<=) x#(Order xl) y#(Order yl)
| null xl && null yl = x == y
| null xl = (Order [0]) <= y
| null yl = x <= (Order [0])
| last xl /= last yl = last xl <= last yl
| otherwise = (init xl) <= (init yl)
I feel like my code is not clean / elegant enough. Is there a standardized library / datatype that already does this? Can i refactor my code more?
Fundamentally, you have a logical error as pointed out by #4castle. In short, you should only be comparing most significant digits if they are of the same significance. For instance, [1,2] is clearly greater than [3] even though the last element of [3] is greater than the last element of [1,2] because the 2 is of greater significance than the 3. You may find that length is useful here.
One elegant strategy is to do a preliminary check for whether one of your Ordinals is clearly bigger than the other (that is, has digits with higher significance, or is "structurally bigger"), and only continue with the recursive underlying numerical check if not. As such, consider defining the recursive part as a helper function; and since it's a helper function anyway, you can call it with the reverse of the ordinal lists, allowing you to do simple pattern matching on the lists, comparing the most significant digit first, without needing "ugly" functions like last and init.
For who cares, i settled on the following implementation (helped by the Haskell reddit, in particular the user xplaticus):
compare x#(Order xl) y#(Order yl) = compare (length xl',xl') (length yl',yl')
where
xl' = dropWhile (0==) xl
yl' = dropWhile (0==) yl
His explanation was similar to DDub's thus i gave DDub the solved check here.
I'm studying project euler solutions and this is the solution of problem 4, which asks to
Find the largest palindrome made from the product of two 3-digit
numbers
problem_4 =
maximum [x | y<-[100..999], z<-[y..999], let x=y*z, let s=show x, s==reverse s]
I understand that this code creates a list such that x is a product of all possible z and y.
However I'm having a problem understanding what does s do here. Looks like everything after | is going to be executed everytime a new element from this list is needed, right?
I don't think I understand what's happening here. Shouldn't everything to the right of | be constraints?
A list comprehension is a rather thin wrapper around a do expression:
problem_4 = maximum $ do
y <- [100..999]
z <- [y..999]
let x = y*z
let s = show x
guard $ s == reverse s
return x
Most pieces translate directly; pieces that aren't iterators (<-) or let expressions are treated as arguments to the guard function found in Control.Monad. The effect of guard is to short-circuit the evaluation; for the list monad, this means not executing return x for the particular value of x that led to the false argument.
I don't think I understand what's happening here. Shouldn't everything to the right of | be constraints?
No, at the right part you see an expression that is a comma-separated (,) list of "parts", and every part is one of the following tree:
an "generator" of the form somevar <- somelist;
a let statement which is an expression that can be used to for instance introduce a variable that stores a subresult; and
expressions of the type boolean that act like a filter.
So it is not some sort of "constraint programming" where one simply can list some constraints and hope that Haskell figures it out (in fact personally that is the difference between a "programming language" and a "specification language": in a programming language you have "control" how the data flows, in a specification language, that is handled by a system that reads your specifications)
Basically an iterator can be compared to a "foreach" loop in many imperative programming languages. A "let" statement can be seen as introducing a temprary variable (but note that in Haskell you do not assign variable, you declare them, so you can not reassign values). The filter can be seen as an if statement.
So the list comprehension would be equivalent to something in Python like:
for y in range(100, 1000):
for z in range(y, 1000):
x = y * z
s = str(x)
if x == x[::-1]:
yield x
We thus first iterate over two ranges in a nested way, then we declare x to be the multiplication of y and z, with let s = show x, we basically convert a number (for example 15129) to its string counterpart (for example "15129"). Finally we use s == reverse s to reverse the string and check if it is equal to the original string.
Note that there are more efficient ways to test Palindromes, especially for multiplications of two numbers.
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I am learning a haskell for a few days and the laziness is something like buzzword. Because of the fact I am not familiar with laziness ( I have been working mainly with non-functional languages ) it is not easy concept for me.
So, I am asking for any excerise / example which show me what laziness is in the fact.
Thanks in advance ;)
In Haskell you can create an infinite list. For instance, all natural numbers:
[1,2..]
If Haskell loaded all the items in memory at once that wouldn't be possible. To do so you would need infinite memory.
Laziness allows you to get the numbers as you need them.
Here's something interesting: dynamic programming, the bane of every intro. algorithms student, becomes simple and natural when written in a lazy and functional language. Take the example of string edit distance. This is the problem of measuring how similar two DNA strands are or how many bytes changed between two releases of a binary executable or just how 'different' two strings are. The dynamic programming algorithm, expressed mathematically, is simple:
let:
• d_{i,j} be the edit distance of
the first string at index i, which has length m
and the second string at index j, which has length m
• let a_i be the i^th character of the first string
• let b_j be the j^th character of the second string
define:
d_{i,0} = i (0 <= i <= m)
d_{0,j} = j (0 <= j <= n)
d_{i,j} = d_{i - 1, j - 1} if a_i == b_j
d_{i,j} = min { if a_i != b_j
d_{i - 1, j} + 1 (delete)
d_{i, j - 1} + 1 (insert)
d_{i - 1, j - 1} + 1 (modify)
}
return d_{m, n}
And the algorithm, expressed in Haskell, follows the same shape of the algorithm:
distance a b = d m n
where (m, n) = (length a, length b)
a' = Array.listArray (1, m) a
b' = Array.listArray (1, n) b
d i 0 = i
d 0 j = j
d i j
| a' ! i == b' ! j = ds ! (i - 1, j - 1)
| otherwise = minimum [ ds ! (i - 1, j) + 1
, ds ! (i, j - 1) + 1
, ds ! (i - 1, j - 1) + 1
]
ds = Array.listArray bounds
[d i j | (i, j) <- Array.range bounds]
bounds = ((0, 0), (m, n))
In a strict language we wouldn't be able to define it so straightforwardly because the cells of the array would be strictly evaluated. In Haskell we're able to have the definition of each cell reference the definitions of other cells because Haskell is lazy – the definitions are only evaluated at the very end when d m n asks the array for the value of the last cell. A lazy language lets us set up a graph of standing dominoes; it's only when we ask for a value that we need to compute the value, which topples the first domino, which topples all the other dominoes. (In a strict language, we would have to set up an array of closures, doing the work that the Haskell compiler does for us automatically. It's easy to transform implementations between strict and lazy languages; it's all a matter of which language expresses which idea better.)
The blog post does a much better job of explaining all this.
So, I am asking for any excerise / example which show me what laziness is in the fact.
Click on Lazy on haskell.org to get the canonical example. There are many other examples just like it to illustrate the concept of delayed evaluation that benefits from not executing some parts of the program logic. Lazy is certainly not slow, but the opposite of eager evaluation common to most imperative programming languages.
Laziness is a consequence of non-strict function evaluation. Consider the "infinite" list of 1s:
ones = 1:ones
At the time of definition, the (:) function isn't evaluated; ones is just a promise to do so when it is necessary. Such a time would be when you pattern match:
myHead :: [a] -> a
myHead (x:rest) = x
When myHead ones is called, x and rest are needed, but the pattern match against 1:ones simply binds x to 1 and rest to ones; we don't need evaluate ones any further at this time, so we don't.
The syntax for infinite lists, using the .. "operator" for arithmetic sequences, is sugar for calls to enumFrom and enumFromThen. That is
-- An infintite list of ones
ones = [1,1..] -- enumFromThen 1 1
-- The natural numbers
nats = [1..] -- enumFrom 1
so again, laziness just comes from the non-strict evaluation of enumFrom.
Unlike with other languages, Haskell decouples the creation and definition of an object.... You can easily watch this in action using Debug.Trace.
You can define a variable like this
aValue = 100
(the value on the right hand side could include a complicated evaluation, but let's keep it simple)
To see if this code ever gets called, you can wrap the expression in Debug.Trace.trace like this
import Debug.Trace
aValue = trace "evaluating aValue" 100
Note that this doesn't change the definition of aValue, it just forces the program to output "evaluating aValue" whenever this expression is actually created at runtime.
(Also note that trace is considered unsafe for production code, and should only be used to debug).
Now, try two experiments.... Write two different mains
main = putStrLn $ "The value of aValue is " ++ show aValue
and
main = putStrLn "'sup"
When run, you will see that the first program actually creates aValue (you will see the "creating aValue" message, while the second does not.
This is the idea of laziness.... You can put as many definitions in a program as you want, but only those that are used will be actually created at runtime.
The real use of this can be seen with objects of infinite size. Many lists, trees, etc. have an infinite number of elements. Your program will use only some finite number of values, but you don't want to muddy the definition of the object with this messy fact. Take for instance the infinite lists given in other answers here....
[1..] -- = [1,2,3,4,....]
You can again see laziness in action here using trace, although you will have to write out a variant of [1..] in an expanded form to do this.
f::Int->[Int]
f x = trace ("creating " ++ show x) (x:f (x+1)) --remember, the trace part doesn't change the expression, it is just used for debugging
Now you will see that only the elements you use are created.
main = putStrLn $ "the list is " ++ show (take 4 $ f 1)
yields
creating 1
creating 2
creating 3
creating 4
the list is [1,2,3,4]
and
main = putStrLn "yo"
will not show any item being created.
I'm currently reading Implementing functional languages: a tutorial by SPJ and the (sub)chapter I'll be referring to in this question is 3.8.7 (page 136).
The first remark there is that a reader following the tutorial has not yet implemented C scheme compilation (that is, of expressions appearing in non-strict contexts) of ECase expressions.
The solution proposed is to transform a Core program so that ECase expressions simply never appear in non-strict contexts. Specifically, each such occurrence creates a new supercombinator with exactly one variable which body corresponds to the original ECase expression, and the occurrence itself is replaced with a call to that supercombinator.
Below I present a (slightly modified) example of such transformation from 1
t a b = Pack{2,1} ;
f x = Pack{2,2} (case t x 7 6 of
<1> -> 1;
<2> -> 2) Pack{1,0} ;
main = f 3
== transformed into ==>
t a b = Pack{2,1} ;
f x = Pack{2,2} ($Case1 (t x 7 6)) Pack{1,0} ;
$Case1 x = case x of
<1> -> 1;
<2> -> 2 ;
main = f 3
I implemented this solution and it works like charm, that is, the output is Pack{2,2} 2 Pack{1,0}.
However, what I don't understand is - why all that trouble? I hope it's not just me, but the first thought I had of solving the problem was to just implement compilation of ECase expressions in C scheme. And I did it by mimicking the rule for compilation in E scheme (page 134 in 1 but I present that rule here for completeness): so I used
E[[case e of alts]] p = E[[e]] p ++ [Casejump D[[alts]] p]
and wrote
C[[case e of alts]] p = C[[e]] p ++ [Eval] ++ [Casejump D[[alts]] p]
I added [Eval] because Casejump needs an argument on top of the stack in weak head normal form (WHNF) and C scheme doesn't guarantee that, as opposed to E scheme.
But then the output changes to enigmatic: Pack{2,2} 2 6.
The same applies when I use the same rule as for E scheme, i.e.
C[[case e of alts]] p = E[[e]] p ++ [Casejump D[[alts]] p]
So I guess that my "obvious" solution is inherently wrong - and I can see that from outputs. But I'm having trouble stating formal arguments as to why that approach was bound to fail.
Can someone provide me with such argument/proof or some intuition as to why the naive approach doesn't work?
The purpose of the C scheme is to not perform any computation, but just delay everything until an EVAL happens (which it might or might not). What are you doing in your proposed code generation for case? You're calling EVAL! And the whole purpose of C is to not call EVAL on anything, so you've now evaluated something prematurely.
The only way you could generate code directly for case in the C scheme would be to add some new instruction to perform the case analysis once it's evaluated.
But we (Thomas Johnsson and I) decided it was simpler to just lift out such expressions. The exact historical details are lost in time though. :)
I'm trying to write a function in Haskell that calculates all factors of a given number except itself.
The result should look something like this:
factorlist 15 => [1,3,5]
I'm new to Haskell and the whole recursion subject, which I'm pretty sure I'm suppoused to apply in this example but I don't know where or how.
My idea was to compare the given number with the first element of a list from 1 to n div2
with the mod function but somehow recursively and if the result is 0 then I add the number on a new list. (I hope this make sense)
I would appreciate any help on this matter
Here is my code until now: (it doesn't work.. but somehow to illustrate my idea)
factorList :: Int -> [Int]
factorList n |n `mod` head [1..n`div`2] == 0 = x:[]
There are several ways to handle this. But first of all, lets write a small little helper:
isFactorOf :: Integral a => a -> a -> Bool
isFactorOf x n = n `mod` x == 0
That way we can write 12 `isFactorOf` 24 and get either True or False. For the recursive part, lets assume that we use a function with two arguments: one being the number we want to factorize, the second the factor, which we're currently testing. We're only testing factors lesser or equal to n `div` 2, and this leads to:
createList n f | f <= n `div` 2 = if f `isFactorOf` n
then f : next
else next
| otherwise = []
where next = createList n (f + 1)
So if the second parameter is a factor of n, we add it onto the list and proceed, otherwise we just proceed. We do this only as long as f <= n `div` 2. Now in order to create factorList, we can simply use createList with a sufficient second parameter:
factorList n = createList n 1
The recursion is hidden in createList. As such, createList is a worker, and you could hide it in a where inside of factorList.
Note that one could easily define factorList with filter or list comprehensions:
factorList' n = filter (`isFactorOf` n) [1 .. n `div` 2]
factorList'' n = [ x | x <- [1 .. n`div` 2], x `isFactorOf` n]
But in this case you wouldn't have written the recursion yourself.
Further exercises:
Try to implement the filter function yourself.
Create another function, which returns only prime factors. You can either use your previous result and write a prime filter, or write a recursive function which generates them directly (latter is faster).
#Zeta's answer is interesting. But if you're new to Haskell like I am, you may want a "simple" answer to start with. (Just to get the basic recursion pattern...and to understand the indenting, and things like that.)
I'm not going to divide anything by 2 and I will include the number itself. So factorlist 15 => [1,3,5,15] in my example:
factorList :: Int -> [Int]
factorList value = factorsGreaterOrEqual 1
where
factorsGreaterOrEqual test
| (test == value) = [value]
| (value `mod` test == 0) = test : restOfFactors
| otherwise = restOfFactors
where restOfFactors = factorsGreaterOrEqual (test + 1)
The first line is the type signature, which you already knew about. The type signature doesn't have to live right next to the list of pattern definitions for a function, (though the patterns themselves need to be all together on sequential lines).
Then factorList is defined in terms of a helper function. This helper function is defined in a where clause...that means it is local and has access to the value parameter. Were we to define factorsGreaterOrEqual globally, then it would need two parameters as value would not be in scope, e.g.
factorsGreaterOrEqual 4 15 => [5,15]
You might argue that factorsGreaterOrEqual is a useful function in its own right. Maybe it is, maybe it isn't. But in this case we're going to say it isn't of general use besides to help us define factorList...so using the where clause and picking up value implicitly is cleaner.
The indentation rules of Haskell are (to my tastes) weird, but here they are summarized. I'm indenting with two spaces here because it grows too far right if you use 4.
Having a list of boolean tests with that pipe character in front are called "guards" in Haskell. I simply establish the terminal condition as being when the test hits the value; so factorsGreaterOrEqual N = [N] if we were doing a call to factorList N. Then we decide whether to concatenate the test number into the list by whether dividing the value by it has no remainder. (otherwise is a Haskell keyword, kind of like default in C-like switch statements for the fall-through case)
Showing another level of nesting and another implicit parameter demonstration, I added a where clause to locally define a function called restOfFactors. There is no need to pass test as a parameter to restOfFactors because it lives "in the scope" of factorsGreaterOrEqual...and as that lives in the scope of factorList then value is available as well.