loopsprologpicat

Partition function P in Picat


I got the following realization of the Partition function P
in Prolog, took it from rosetta here:

/* SWI-Prolog 8.3.21 */
:- table p/2.
p(0, 1) :- !.
p(N, X) :-
    aggregate_all(sum(Z), (between(1,inf,K), M is K*(3*K-1)//2,
           (M>N, !, fail; L is N-M, p(L,Y), Z is (-1)^K*Y)), A),
    aggregate_all(sum(Z), (between(1,inf,K), M is K*(3*K+1)//2,
           (M>N, !, fail; L is N-M, p(L,Y), Z is (-1)^K*Y)), B),
    X is -A-B.
 
?- time(p(6666,X)).
% 13,962,294 inferences, 2.610 CPU in 2.743 seconds (95% CPU, 5350059 Lips)
X = 1936553061617076610800050733944860919984809503384
05932486880600467114423441282418165863.

How would one go about an implementation of the same in Picat? Is it
true that aggregate_all+sum can be replaced by foreach+:= ?
What about bignums in Picat?


Solution

  • Bignums is no problem in Picat. Here's my Picat version (inspired by the Maple approach):

    table
    partition1(0) = 1.
    partition1(N) = P =>
      S = 0,
      K = 1,
      M = (K*(3*K-1)) // 2,  
      while (M <= N)
         M := (K*(3*K-1)) // 2,  
         S := S - ((-1)**K)*partition1(N-M),
         K := K + 1
      end,
      K := 1,
      M := (K*(3*K+1)) // 2,
      while (M <= N)
         M := (K*(3*K+1)) // 2,  
         S := S - ((-1)**K)*partition1(N-M),
         K := K + 1
      end,
      P = S.
    

    Your (neat) SWI-Prolog version takes about 1,9s for p(6666) on my machine.

    ?- time(p(6666,X)), write(X), nl.
    % 13,959,720 inferences, 1.916 CPU in 1.916 seconds (100% CPU, 7285567 Lips)
    193655306161707661080005073394486091998480950338405932486880600467114423441282418165863
    X = 193655306161707661080005073394486091998480950338405932486880600467114423441282418165863.
    

    My Picat version takes about 0.2s

    Picat> time(println('p(6666)'=partition1(6666))) 
    p(6666) = 193655306161707661080005073394486091998480950338405932486880600467114423441282418165863
    
    CPU time 0.206 seconds.
    

    Update Here's a version using findall in Picat instead, sort of mimicking your approach:

    table
    p(0, 1) :- !.
    p(N, X) :-
        A = sum(findall(Z, (between(1,N,K), M is K*(3*K-1)//2,
               (M>N, !, fail; p(N-M,Y), Z is (-1)**K*Y)))),
        B = sum(findall(Z, (between(1,N,K), M is K*(3*K+1)//2,
               (M>N, !, fail; p(N-M,Y), Z is (-1)**K*Y)))),
        X is -A-B.
    

    But it's much slower (2.6s vs 0.2s):

    p(6666) = 193655306161707661080005073394486091998480950338405932486880600467114423441282418165863
    
    CPU time 2.619 seconds. Backtracks: 0
    

    I also tested to implement the same approach, i.e. using findall/3 in SWI-Prolog:

    :- table p2/2.
    p2(0, 1) :- !.
    p2(N, X) :-
            findall(Z, (between(1,N,K), M is K*(3*K-1)//2,
                        (M>N, !, fail; L is N-M, p2(L,Y), Z is (-1)**K*Y)), AA),
            sum(AA,A),
            findall(Z, (between(1,N,K), M is K*(3*K+1)//2,
                        (M>N, !, fail; L is N-M, p2(L,Y), Z is (-1)**K*Y)), BB),
            sum(BB,B),
            X is - A - B.
    
    sum(L,Sum) :-
            sum(L,0,Sum).
    sum([],Sum,Sum).
    sum([H|T],Sum0,Sum) :-
            Sum1 is Sum0 + H,
            sum(T,Sum1,Sum).
    

    It's faster than Picat's findall approach, and about the same time as your version (slightly faster but with more inferences).

    ?- time(p2(6666,X)).
    % 14,636,851 inferences, 1.814 CPU in 1.814 seconds (100% CPU, 8070412 Lips)
    X = 193655306161707661080005073394486091998480950338405932486880600467114423441282418165863.