I have defined the predicate that finds the minimum value in list e.g
greater(X,Y):- X > Y.
isLower(X,Y):- X < Y.
findmin( [X] , X ).
findmin( [H|T] , P ):- findmin(T,P1) , isLower(H,P1), P is H.
findmin( [H|T] , P) :- findmin(T,P1) , greater(H , P1), P is P1.
However i have hard time modifying this code to find second minimum value including nested lists.
How could i assure that the second minimum value will be returned?
I mean this mostly as a joke, but here it is:
find_second_min(L, Min2) :- sort(L, [_, Min2|_]).
So, sorting will definitely put all your items in order. You could get the minimum by just looking at the top one. If you want want the two smallest, you can look at the first two elements:
find_mins(L, Min1, Min2) :- sort(L, [Min1, Min2|_]).
As you know, sorting is O(N log N) while you can find just the minimum in O(N). So to find just one value this is probably too much work. But it's cute.
You could simply make P a list containing the two smallest numbers. Then you would need to check for each element if it is smaller than the larger one in P, and if so, replace it. Then in the end, the larger of the two is the second largest element.
By the way, you really don't need to define your own greater/isLower – why not just use the operators that are built in, >/< in their place?
This would also make it a bit easier to spot the bug you have in your code if H is exactly as large as P1.
So, here's how I would do it:
find2nd([H1, H2 | T], M) :- H1 < H2, !, find2nd_i(T, M, [H1, H2]).
find2nd([H1, H2 | T], M) :- H1 >= H2, find2nd_i(T, M, [H2, H1]).
find2nd_i([], M2, [_, M2]).
find2nd_i([H | T], M, [M1, M2]) :- H >= M2, !, find2nd_i(T, M, [M1, M2]).
find2nd_i([H | T], M, [M1, M2]) :- H < M2, H >= M1, !, find2nd_i(T, M, [M1, H]).
find2nd_i([H | T], M, [M1, M2]) :- H < M2, H < M1, find2nd_i(T, M, [H, M1]).
First of all, your implementation of findmin/2 is not very efficient:
findmin([H|T],P):- findmin(T,P1) , isLower(H,P1), P is H.
Since it does not use tail recursion. You better transform this into a clause with tail recursion and an accumulator.
You can - as is suggested by #DanielLyons sort the list and then retrieve the second element, but this requires O(n log n) time complexity for the sorting step. The sorting is however done in low level C on most Prolog systems; but eventually, if the list is very large, a linear apporach will outperform it.
You can also use #FelixDombek's approach by storing the two values into a list. One can slightly improve the efficiency of this approach by:
not using a list, but simply two parameters since it will save on pattern matching and tuple construction; and
use an if-then-else approach to save on comparisons.
This results in transforming the program into:
find2nd([H1,H2|T],Min2) :-
H1 =< H2 ->
find2nd(T,H1,H2,Min2)
;find2nd(T,H2,H1,Min2).
find2nd([],_,Min2,Min2).
find2nd([H|T],H1,H2,Min2) :-
H >= H2 ->
find2nd(T,H1,H2,Min2)
;( H >= H1 ->
find2nd(T,H1,H,Min2)
;find2nd(T,H,H1,Min2)
).
Related
I am new to prolog, I am just learning about lists and I came across this question. The answer works perfect for a list of integers.
minimo([X], X) :- !.
minimo([X,Y|Tail], N):-
( X > Y ->
minimo([Y|Tail], N)
;
minimo([X|Tail], N)
).
How can I change this code to get the smallest int from a mixed list?
This
sint([a,b,3,2,1],S)
should give an answer:
S=1
you could just ignore the problem, changing the comparison operator (>)/2 (a binary builtin predicate, actually) to the more general (#>)/2:
minimo([X], X) :- !.
minimo([X,Y|Tail], N):-
( X #> Y ->
minimo([Y|Tail], N)
;
minimo([X|Tail], N)
).
?- minimo([a,b,3,2,1],S).
S = 1.
First of all, I don't think the proposed implementation is very elegant: here they pass the minimum found element thus far by constructing a new list each time. Using an additional parameter (we call an accumulator) is usually the way to go (and is probably more efficient as well).
In order to solve the problem, we first have to find an integer. We can do this like:
sint([H|T],R) :-
integer(H),
!,
sint(T,H,R).
sint([_|T],R) :-
sint(T,R).
So here we check if the head H is an integer/1. If that is the case, we call a predicate sint/3 (not to be confused with sint/2). Otherwise we call recursively sint/2 with the tail T of the list.
Now we still need to define sint/3. In case we have reached the end of the list [], we simply return the minum found thus far:
sint([],R,R).
Otherwise there are two cases:
the head H is an integer and smaller than the element found thus far, in that case we perform recursion with the head as new current minimum:
sint([H|T],M,R):
integer(H),
H < M,
!,
sint(T,H,R).
otherwise, we simply ignore the head, and perform recursion with the tail T.
sint([_|T],M,R) :-
sint(T,M,R).
We can put the recursive clauses in an if-then-else structure. Together with the earlier defined predicate, the full program then is:
sint([H|T],R) :-
integer(H),
!,
sint(T,H,R).
sint([_|T],R) :-
sint(T,R).
sint([],R,R).
sint([H|T],M,R):
(
(integer(H),H < M)
-> sint(T,H,R)
; sint(T,M,R)
).
The advantage of this approach is that filtering and comparing (to obtain the minimum) is done at the same time, so we only iterate once over the list. This will usually result in a performance boost since the "control structures" are only executed once: more is done in an iteration, but we only iterate once.
We can generalize the approach by making the filter generic:
filter_minimum(Filter,[H|T],R) :-
Goal =.. [Filter,H],
call(Goal),
!,
filter_minimum(Filter,T,H,R).
filter_minimum(Filter,[_|T],R) :-
filter_minimum(Filter,T,R).
filter_minimum(_,[],R,R).
filter_minimum(Filter,[H|T],M,R) :-
Goal =.. [Filter,H],
(
(call(Goal),H < M)
-> filter_minimum(Filter,T,H,R)
; filter_minimum(Filter,T,M,R)
).
You can then call it with:
filter_minimum(integer,[a,b,3,2,1],R).
to filter with integer/1 and calculate the minimum.
You could just write a predicate that returns a list with the numbers and the use the above minimo/2 predicate:
only_numbers([],[]).
only_numbers([H|T],[H|T1]):-integer(H),only_numbers(T,T1).
only_numbers([H|T],L):- \+integer(H),only_numbers(T,L).
sint(L,S):-only_numbers(L,L1),minimo(L1,S).
Working on a predicate, rotate(L,M,N), where L is a new list formed by rotating M to the right N times.
My approach was to just append the tail of M to its head N times.
rotate(L, M, N) :-
( N > 0,
rotate2(L, M, N)
; L = M
).
rotate2(L, [H|T], Ct) :-
append(T, [H], L),
Ct2 is Ct - 1,
rotate2(L, T, Ct2).
Currently, my code returns L equal to the original M, no matter what N is set to.
Seems like when I'm recursing, the tail isn't properly moved to the head.
You can use append to split lists, and length to create lists:
% rotate(+List, +N, -RotatedList)
% True when RotatedList is List rotated N positions to the right
rotate(List, N, RotatedList) :-
length(Back, N), % create a list of variables of length N
append(Front, Back, List), % split L
append(Back, Front, RotatedList).
Note: this only works for N <= length(L). You can use arithmetic to fix that.
Edit for clarity
This predicate is defined for List and N arguments that are not variables when the predicate is called. I inadvertently reordered the arguments from your original question, because in Prolog, the convention is that strictly input arguments should come before output arguments. So, List and N and input arguments, RotatedList is an output argument. So these are correct queries:
?- rotate([a,b,c], 2, R).
?- rotate([a,b,c], 1, [c,a,b]).
but this:
?- rotate(L, 2, [a,b,c]).
will go into infinite recursion after finding one answer.
When reading the SWI-Prolog documentation, look out for predicate arguments marked with a "?", as in length. They can be used as shown in this example.
We want to build a predicate that gets a list L and a number N and is true if N is the length of the longest sequence of list L.
For example:
?- ls([1,2,2,4,4,4,2,3,2],3).
true.
?- ls([1,2,3,2,3,2,1,7,8],3).
false.
For this I built -
head([X|S],X). % head of the list
ls([H|T],N) :- head(T,X),H=X, NN is N-1 , ls(T,NN) . % if the head equal to his following
ls(_,0) :- !. % get seq in length N
ls([H|T],N) :- head(T,X) , not(H=X) ,ls(T,N). % if the head doesn't equal to his following
The concept is simply - check if the head equal to his following , if so , continue with the tail and decrement the N .
I checked my code and it works well (ignore cases which N = 1) -
ls([1,2,2,4,4,4,2,3,2],3).
true ;
false .
But the true answer isn't finite and there is more answer after that , how could I make it to return finite answer ?
Prolog-wise, you have a few problems. One is that your predicate only works when both arguments are instantiated, which is disappointing to Prolog. Another is your style—head/2 doesn't really add anything over [H|T]. I also think this algorithm is fundamentally flawed. I don't think you can be sure that no sequence of longer length exists in the tail of the list without retaining an unchanged copy of the guessed length. In other words, the second thing #Zakum points out, I don't think there will be a simple solution for it.
This is how I would have approached the problem. First a helper predicate for getting the maximum of two values:
max(X, Y, X) :- X >= Y.
max(X, Y, Y) :- Y > X.
Now most of the work sequence_length/2 does is delegated to a loop, except for the base case of the empty list:
sequence_length([], 0).
sequence_length([X|Xs], Length) :-
once(sequence_length_loop(X, Xs, 1, Length)).
The call to once/1 ensures we only get one answer. This will prevent the predicate from usefully generating lists with sequences while also making the predicate deterministic, which is something you desired. (It has the same effect as a nicely placed cut).
Loop's base case: copy the accumulator to the output parameter:
sequence_length_loop(_, [], Length, Length).
Inductive case #1: we have another copy of the same value. Increment the accumulator and recur.
sequence_length_loop(X, [X|Xs], Acc, Length) :-
succ(Acc, Acc1),
sequence_length_loop(X, Xs, Acc1, Length).
Inductive case #2: we have a different value. Calculate the sequence length of the remainder of the list; if it is larger than our accumulator, use that; otherwise, use the accumulator.
sequence_length_loop(X, [Y|Xs], Acc, Length) :-
X \= Y,
sequence_length([Y|Xs], LengthRemaining),
max(Acc, LengthRemaining, Length).
This is how I would approach this problem. I don't know if it will be useful for you or not, but I hope you can glean something from it.
How about adding a break to the last rule?
head([X|S],X). % head of the list
ls([H|T],N) :- head(T,X),H=X, NN is N-1 , ls(T,NN) . % if the head equal to his following
ls(_,0) :- !. % get seq in length N
ls([H|T],N) :- head(T,X) , not(H=X) ,ls(T,N),!. % if the head doesn't equal to his following
Works for me, though I'm no Prolog expert.
//EDIT: btw. try
14 ?- ls([1,2,2,4,4,4,2,3,2],2).
true ;
false.
Looks false to me, there is no check whether N is the longest sequence. Or did I get the requirements wrong?
Your code is checking if there is in list at least a sequence of elements of specified length. You need more arguments to keep the state of the search while visiting the list:
ls([E|Es], L) :- ls(E, 1, Es, L).
ls(X, N, [Y|Ys], L) :-
( X = Y
-> M is N+1,
ls(X, M, Ys, L)
; ls(Y, 1, Ys, M),
( M > N -> L = M ; L = N )
).
ls(_, N, [], N).
I have the following task:
Write a method that will add two polynoms. I.e 0+2*x^3 and 0+1*x^3+2*x^4 will give 0+3*x^3+2*x^4.
I also wrote the following code:
add_poly(+A1*x^B1+P1,+A2*x^B2+P2,+A3*x^B3+P3):-
(
B1=B2,
B3 = B2,
A3 is A1+A2,
add_poly(P1,P2,P3)
;
B1<B2,
B3=B1,
A3=A1,
add_poly(P1,+A2*x^B2+P2,P3)
;
B1>B2,
B3=B2,
A3=A2,
add_poly(+A1*x^B1+P1,P2,P3)
).
add_poly(X+P1,Y+P2,Z+P3):-
Z is X+Y,
add_poly(P1,P2,P3).
My problem is that I don't know how to stop. I would like to stop when one the arguments is null and than to append the second argument to the third one. But how can I check that they are null?
Thanks.
Several remarks:
Try to avoid disjunctions (;)/2 in the beginning. They need special indentation to be readable. And they make reading a single rule more complex — think of all the extra (=)/2 goals you have to write and keep track of.
Then, I am not sure what you can assume about your polynomials. Can you assume they are written in canonical form?
And for your program: Consider the head of your first rule:
add_poly(+A1*x^B1+P1,+A2*x^B2+P2,+A3*x^B3+P3):-
I will generalize away some of the arguments:
add_poly(+A1*x^B1+P1,_,_):-
and some of the subterms:
add_poly(+_+_,_,_):-
This corresponds to:
add_poly(+(+(_),_),_,_) :-
Not sure you like this.
So this rule applies only to terms starting with a prefix + followed by an infix +. At least your sample data did not contain a prefix +.
Also, please remark that the +-operator is left associative. That means that 1+2+3+4 associates to the left:
?- write_canonical(1+2+3+4).
+(+(+(1,2),3),4)
So if you have a term 0+3*x^3+2*x^4 the first thing you "see" is _+2*x^4. The terms on the left are nested deeper.
For your actual question (how to stop) - you will have to test explicitly that the leftmost subterm is an integer, use integer/1 - or maybe a term (*)/2 (that depends on your assumptions).
I assume that polynomials you are speaking of are in 1 variable and with integer exponents.
Here a procedure working on normal polynomial form: a polynomial can be represented as a list (a sum) of factors, where the (integer) exponent is implicitly represented by the position.
:- [library(clpfd)].
add_poly(P1, P2, Sum) :-
normalize(P1, N1),
normalize(P2, N2),
append(N1, N2, Nt),
aggregate_all(max(L), (member(M, Nt), length(M, L)), LMax),
maplist(rpad(LMax), Nt, Nn),
clpfd:transpose(Nn, Tn),
maplist(sumlist, Tn, NSum),
denormalize(NSum, Sum).
rpad(LMax, List, ListN) :-
length(List, L),
D is LMax - L,
zeros(D, Z),
append(List, Z, ListN).
% the hardest part is of course normalization: here a draft
normalize(Ts + T, [N|Ns]) :-
normalize_fact(T, N),
normalize(Ts, Ns).
normalize(T, [N]) :-
normalize_fact(T, N).
% build a list with 0s left before position E
normalize_fact(T, Normal) :-
fact_exp(T, F, E),
zeros(E, Zeros),
nth0(E, Normal, F, Zeros).
zeros(E, Zeros) :-
length(Zeros, E),
maplist(copy_term(0), Zeros).
fact_exp(F * x ^ E, F, E).
fact_exp(x ^ E, 1, E).
fact_exp(F * x, F, 1).
fact_exp(F, F, 0).
% TBD...
denormalize(NSum, NSum).
test:
?- add_poly(0+2*x^3, 0+1*x^3+2*x^4, P).
P = [0, 0, 0, 3, 2]
the answer is still in normal form, denormalize/2 should be written...
So here it is : I'm trying to calculate the sum of all primes below two millions (for this problem), but my program is very slow. I do know that the algorithm in itself is terribly bad and a brute force one, but it seems way slower than it should to me.
Here I limit the search to 20,000 so that the result isn't waited too long.
I don't think that this predicate is difficult to understand but I'll explain it anyway : I calculate the list of all the primes below 20,000 and then sum them. The sum part is fine, the primes part is really slow.
problem_010(R) :-
p010(3, [], Primes),
sumlist([2|Primes], R).
p010(20001, Primes, Primes) :- !.
p010(Current, Primes, Result) :-
(
prime(Current, Primes)
-> append([Primes, [Current]], NewPrimes)
; NewPrimes = Primes
),
NewCurrent is Current + 2,
p010(NewCurrent, NewPrimes, Result).
prime(_, []) :- !.
prime(N, [Prime|_Primes]) :- 0 is N mod Prime, !, fail.
prime(ToTest, [_|Primes]) :- prime(ToTest, Primes).
I'd like some insight about why it is so slow. Is it a good implementation of the stupid brute force algorithm, or is there some reason that makes Prolog fall?
EDIT : I already found something, by appending new primes instead of letting them in the head of the list, I have primes that occur more often at start so it's ~3 times faster. Still need some insight though :)
First, Prolog does not fail here.
There are very smart ways how to generate prime numbers. But as a cheap start simply accumulate the primes in reversed order! (7.9s -> 2.6s) In this manner the smaller ones are tested sooner. Then, consider to test only against primes up to 141. Larger primes cannot be a factor.
Then, instead of stepping only through numbers not divisible by 2, you might add 3, 5, 7.
There are people writing papers on this "problem". See, for example this paper, although it's a bit of a sophistic discussion what the "genuine" algorithm actually was, 22 centuries ago when the latest release of the abacus was celebrated as Salamis tablets.
Consider using for example a sieve method ("Sieve of Eratosthenes"): First create a list [2,3,4,5,6,....N], using for example numlist/3. The first number in the list is a prime, keep it. Eliminate its multiples from the rest of the list. The next number in the remaining list is again a prime. Again eliminate its multiples. And so on. The list will shrink quite rapidly, and you end up with only primes remaining.
First of all, appending at the end of a list using append/3 is quite slow. If you must, then use difference lists instead. (Personally, I try to avoid append/3 as much as possible)
Secondly, your prime/2 always iterates over the whole list when checking a prime. This is unnecessarily slow. You can instead just check id you can find an integral factor up to the square root of the number you want to check.
problem_010(R) :-
p010(3, 2, R).
p010(2000001, Primes, Primes) :- !.
p010(Current, In, Result) :-
( prime(Current) -> Out is In+Current ; Out=In ),
NewCurrent is Current + 2,
p010(NewCurrent, Out, Result).
prime(2).
prime(3).
prime(X) :-
integer(X),
X > 3,
X mod 2 =\= 0,
\+is_composite(X, 3). % was: has_factor(X, 3)
is_composite(X, F) :- % was: has_factor(X, F)
X mod F =:= 0, !.
is_composite(X, F) :-
F * F < X,
F2 is F + 2,
is_composite(X, F2).
Disclaimer: I found this implementation of prime/1 and has_factor/2 by googling.
This code gives:
?- problem_010(R).
R = 142913828922
Yes (12.87s cpu)
Here is even faster code:
problem_010(R) :-
Max = 2000001,
functor(Bools, [], Max),
Sqrt is integer(floor(sqrt(Max))),
remove_multiples(2, Sqrt, Max, Bools),
compute_sum(2, Max, 0, R, Bools).
% up to square root of Max, remove multiples by setting bool to 0
remove_multiples(I, Sqrt, _, _) :- I > Sqrt, !.
remove_multiples(I, Sqrt, Max, Bools) :-
arg(I, Bools, B),
(
B == 0
->
true % already removed: do nothing
;
J is 2*I, % start at next multiple of I
remove(J, I, Max, Bools)
),
I1 is I+1,
remove_multiples(I1, Sqrt, Max, Bools).
remove(I, _, Max, _) :- I > Max, !.
remove(I, Add, Max, Bools) :-
arg(I, Bools, 0), % remove multiple by setting bool to 0
J is I+Add,
remove(J, Add, Max, Bools).
% sum up places that are not zero
compute_sum(Max, Max, R, R, _) :- !.
compute_sum(I, Max, RI, R, Bools) :-
arg(I, Bools, B),
(B == 0 -> RO = RI ; RO is RI + I ),
I1 is I+1,
compute_sum(I1, Max, RO, R, Bools).
This runs an order of magnitude faster than the code I gave above:
?- problem_010(R).
R = 142913828922
Yes (0.82s cpu)
OK, before the edit the problem was just the algorithm (imho).
As you noticed, it's more efficient to check if the number is divided by the smaller primes first; in a finite set, there are more numbers divisible by 3 than by 32147.
Another algorithm improvement is to stop checking when the primes are greater than the square root of the number.
Now, after your change there are indeed some prolog issues:
you use append/3. append/3 is quite slow since you have to traverse the whole list to place the element at the end.
Instead, you should use difference lists, which makes placing the element at the tail really fast.
Now, what is a difference list? Instead of creating a normal list [1,2,3] you create this one [1,2,3|T]. Notice that we leave the tail uninstantiated. Then, if we want to add one element (or more) at the end of the list we can simply say T=[4|NT]. awesome?
The following solution (accumulate primes in reverse order, stop when prime>sqrt(N), difference lists to append) takes 0.063 for 20k primes and 17sec for 2m primes while your original code took 3.7sec for 20k and the append/3 version 1.3sec.
problem_010(R) :-
p010(3, Primes, Primes),
sumlist([2|Primes], R).
p010(2000001, _Primes,[]) :- !. %checking for primes till 2mil
p010(Current, Primes,PrimesTail) :-
R is sqrt(Current),
(
prime(R,Current, Primes)
-> PrimesTail = [Current|NewPrimesTail]
; NewPrimesTail = PrimesTail
),
NewCurrent is Current + 2,
p010(NewCurrent, Primes,NewPrimesTail).
prime(_,_, Tail) :- var(Tail),!.
prime(R,_N, [Prime|_Primes]):-
Prime>R.
prime(_R,N, [Prime|_Primes]) :-0 is N mod Prime, !, fail.
prime(R,ToTest, [_|Primes]) :- prime(R,ToTest, Primes).
also, considering adding the numbers while you generate them to avoid the extra o(n) because of sumlist/2
in the end, you can always implement the AKS algorithm that runs in polynomial time (XD)