问题
Trying to solve the isomorphic graphs problem here.
Assignment info:
- Determine whether 2 undirected graphs are isomorphic.
- No isolated vertices.
- Number of vertices is less than 30
Edges of graphs are given as predicates, i.e.
e(1, 2). f(1, 2).
I'm trying to use the following approach:
- For every pair of edges (i.e. for every edge from graph 1 and 2)
- Try to bind the vertices of 2 edges
- If binding of vertices is impossible (i.e. another binding with one of the vertex already exists), then backtrack and try another pair of edges.
- Otherwise add binding and continue with the rest of graphs (i.e. one edge from each graph is removed and procedure is applied again).
Procedure recurs unless both graphs are empty (meaning that all vertices were bound from one graph to the other one) meaning a success. Otherwise procedure should always fail (i.e. no other binding combinations available, etc.)
My code seems to be working but for small graphs only (guess because it tries all the pairs :) ).
So if anyone knows how it's possible to optimize the code (I believe that several cuts can be inserted and that try_bind can be written in better way) or can tell a better approach thanks in advance.
P.s. for checking non-isomorphism I know that we can check invariants and etc. It doesn't really matter for now.
Code:
%define graph, i.e. graph is a list of edges
graph1(RES):-findall(edge(X,Y), e(X, Y), RES).
graph2(RES):-findall(edge(X,Y), f(X, Y), RES).
%define required predicate
iso:-graph1(G1), graph2(G2), iso_acc(G1, G2, [], _).
%same as above but outputs result
iso_w:-graph1(G1), graph2(G2), iso_acc(G1, G2, [], RES_MAP), write(RES_MAP).
iso_acc([], [], MAP, RES):-append(MAP, [], RES), !.
iso_acc([X|X_Rest], Y_LS, MAP, RES_MAP):-
select(Y, Y_LS, Y_Rest),
bind(X, Y, MAP, UPD_MAP),
iso_acc(X_Rest, Y_Rest, UPD_MAP, RES_MAP).
% if edges bind is successful then in RES or UPD_MAP updated binding map is returned (may return the same map
% if bindings are already defined), otherwise fails
bind([], [], MAP, RES):-append(MAP, [], RES), !.
bind(edge(X1, Y1), edge(X2, Y2), MAP, UPD_MAP):-
try_bind(b(X1, X2), MAP, RES),
try_bind(b(Y1, Y2), RES, UPD_MAP).
bind(edge(X1, Y1), edge(X2, Y2), MAP, UPD_MAP):-
try_bind(b(X1, Y2), MAP, RES),
try_bind(b(Y1, X2), RES, UPD_MAP).
%if an absolute member, we're OK (absolute member means b(X,Y) is already defined
try_bind(b(X, Y), MAP, UPD_MAP):-
member(b(X, Y), MAP),
append(MAP, [], UPD_MAP), !.
%otherwise check that we don't have other binding to X or to Y
try_bind(b(X, Y), MAP, UPD_MAP):-
member(b(X, Z), MAP),
%check if Z != Y
Z=Y,
append(MAP, [], UPD_MAP).
try_bind(b(X, Y), MAP, UPD_MAP):-
member(b(W, Y), MAP),
%check if W == X
W=X,
append(MAP, [], UPD_MAP).
%finally if we not an absolute member and if no other bindings to X and Y we add new binding
try_bind(b(X, Y), MAP, UPD_MAP):-
not(member(b(X, Z), MAP)),
not(member(b(W, Y), MAP)),
append([b(X, Y)], MAP, UPD_MAP).
回答1:
First, my congratulation for a good presentation of the problem and an elaborate solution proposal.
In the next paragraph I will talk about implementation details of your solution.
Unfortunately, I must say that I do not see this approach to the solution scalable to bigger sizes. Assume graphs of 10 edges. iso_acc/4 tries to assign first edge to any of one of the edges in second one (10 possibilities), second edge is also bind to any one (10 possibilities for each previous: 10*10), ... . If not a few of luck, that goes to 10^10 possibilities, 10! ones taken into account most of them are pruned faster.
Minor comments are:
You can skip usage of append(X,[],Y), so
bind([],[],MAP,RES) :- append(MAP,[],RES), !.
can be:
bind([],[],MAP,MAP).
Second and third rules in try_bind/3 seems unnecessary, in previous one you have already verified no b(X,Y) belongs to MAP. In other words, member(b(X,Y),MAP) is equivalent to member(b(X,Z),MAP), Z=Y.
Addendum
Let's try the following method. Let the example graph e be:
+----3----+
1 ---2--+ | +---5
+----4----+
and graph f be:
+----3----+
2 ---5--+ | +---1
+----4----+
The basic algorithm could be:
memb( X-A, [X-B|_] ) :- permutation(A,B).
memb( X, [_|Q] ) :- memb(X, Q).
match( [], _ ).
match( [H|Q], G2 ) :-
memb(H,G2),
match(Q,G2).
graph_equal(G1,G2,MAP) :-
bagof( X, graph_to_list(G1,X), L1 ),
length(MAP,40),
bagof( X, graph_to_list_vars(G2,MAP,X), L2 ), !,
length( L1, S ),
length( L2, S ),
match( L1, L2 ).
From this starting point, optimizations can be done.
This algorithm needs some initial data converters, to convert each graph to a list of items in the form node-[peer1,peer2,...]. The rules for this conversion are:
bidir(G,X,Y) :- ( call(G,X,Y); call(G,Y,X) ).
bidir_vars(G,MAP,VX,VY) :-
bidir(G,X,Y), nth0(X,MAP,VX), nth0(Y,MAP,VY).
graph_to_list( G, N-XL ) :-
setof( X, bidir(G,N,X), XL).
graph_to_list_vars( G, MAP, N-XL ) :-
setof( X, bidir_vars(G,MAP,N,X), XL).
Addendum 2
Initial data for this example is:
e(1,2).
e(2,3).
e(2,4).
e(3,4).
e(3,5).
e(4,5).
f(2,5).
f(3,5).
f(4,5).
f(3,4).
f(1,4).
f(1,3).
Addendum 3
When the full algorithm is now queried with the sample graphs e and f, the result is:
[debug] ?- graph_equal(e,f,MAP).
MAP = [_G2295, 5, 1, 3, 4, 2, _G2313, _G2316, _G2319|...] ;
MAP = [_G2295, 5, 1, 4, 3, 2, _G2313, _G2316, _G2319|...] ;
That means these graphs are isomorphic, with the possible node mappings e:[5,1,3,4,2] => f:[1,2,3,4,5] and e:[5,1,4,3,2] => f:[1,2,3,4,5].
Addendum 4
Basic benchmark. Single solution:
?- time( graph_equal(e,f,_) ).
% 443 inferences, 0.000 CPU in 0.000 seconds (99% CPU, 1718453 Lips)
all solutions:
?- time( (graph_equal(e,f,_),fail) ).
% 567 inferences, 0.000 CPU in 0.000 seconds (99% CPU, 2027266 Lips)
回答2:
Solved using another approach. Code is attached (algorithm is in the code).
Some predicates from prev. case remained though (like try_bind).
Code:
% Author: Denis Korekov
% Description of algorithm:
% G1 is graph 1, G2 is graph 2
% E1 is edge of G1, E2 is edge of G2
% V1 is vertex of G1, V2 is vertex of G2
% 0) Check that graphs can be isomorphic (refer to "initial_verify" predicate)
% 1) Pick V1 and some V2 and remove them from vertices lists
% 2) Ensure that none of chosen vertices are in relative closed lists (otherwise continue but remove them)
% 3) Bind (map) V1 to V2
% 4) Expand V1 and V2
% 5) Ensure that degrees of expansions are the same
% 6) Append expansion results to the end of vertices lists and repeat
% define graph predicates here
% graph predicates end
% as we have undirected edges
way_g1(X, Y):- e(X, Y).
way_g1(X, Y):- e(Y, X).
way_g2(X, Y):- f(X, Y).
way_g2(X, Y):- f(Y, X).
% returns all vertices of graphs (non-repeating)
graph1_v(RES):-findall(X, way_g1(X, _), LS), nodes(LS, [], RES).
graph2_v(RES):-findall(X, way_g2(X, _), LS), nodes(LS, [], RES).
% returns all edges of graphs in form "e(X, Y)"
graph1_e(RES):-findall(edge(X, Y), e(X, Y), RES).
graph2_e(RES):-findall(edge(X, Y), f(X, Y), RES).
% returns a list of vertices (removes repeating vertices in a list)
% 1 - list of vertices
% 2 - closed list (discovered vertices)
% 3 - resulting list
nodes([], CL_LS, RES):-append(CL_LS, [], RES).
nodes([X|Rest], CL_LS, RES):- not(member(X, CL_LS)), nodes(Rest, .(X, CL_LS), RES).
nodes([X|Rest], CL_LS, RES):-member(X, CL_LS), nodes(Rest, CL_LS, RES).
% required predicate
iso:-graph1_v(V1), graph2_v(V2), graph1_e(E1), graph2_e(E2), initial_verify(V1, V2, E1, E2), iso_acc(V1, V2, [], [], [], _).
% same as above but outputs result (outputs resulting binding map)
iso_w:-graph1_v(V1), graph2_v(V2), graph1_e(E1), graph2_e(E2), initial_verify(V1, V2, E1, E2), iso_acc(V1, V2, [], [], [], RES_MAP), write(RES_MAP).
% initial verification that graphs at least CAN BE isomorphic
% checks the number of vertices and edges as well as degrees
% 1 - vertices of G1
% 2 - vertices of G2
% 3 - edges of G1
% 4 - edges of G2
initial_verify(X_V, Y_V, X_E, Y_E):-
length(X_V, X_VL),
length(Y_V, Y_VL),
X_VL=Y_VL,
length(X_E, X_EL),
length(Y_E, Y_EL),
X_EL=Y_EL,
get_degree_sequence_g1(X_V, [], X_S),
get_degree_sequence_g2(Y_V, [], Y_S),
%compare degree sequences
compare_lists(X_S, Y_S).
% main algorithm
% 1 - list of vertices of G1
% 2 - list of vertices of G2
% 3 - closed list of G1
% 4 - closed list of G2
% 5 - initial binding map
% 6 - resulting binding map
% if both vertices lists are empty -> isomorphic, backtrack and cut
iso_acc([], [], _, _, ISO_MAP, RES):-append(ISO_MAP, [], RES), !.
% otherwise for every node of G1, for every root of G2
iso_acc([X|X_Rest], Y_LS, CL_X, CL_Y, ISO_MAP, RES):-
select(Y, Y_LS, Y_Rest),
%if X or Y in closed -> continue (next predicate)
not(member(X, CL_X)),
not(member(Y, CL_Y)),
%map X to Y
try_bind(b(X, Y), ISO_MAP, UPD_MAP),
%expand X and Y, use CL_X and CL_Y
expand_g1(X, CL_X, CL_X_UPD, X_RES, X_L),
expand_g2(Y, CL_Y, CL_Y_UPD, Y_RES, Y_L),
%compare lengths of expansions
X_L=Y_L,
%if OK continue with iso_acc with new closed lists and new mapping
append(X_Rest, X_RES, X_NEW),
append(Y_Rest, Y_RES, Y_NEW),
iso_acc(X_NEW, Y_NEW, CL_X_UPD, CL_Y_UPD, UPD_MAP, RES).
% executed in case X and some Y are in closed list (skips such elements)
iso_acc([X|X_Rest], Y_LS, CL_X, CL_Y, ISO_MAP, RES):-
select(Y, Y_LS, Y_Rest),
member(X, CL_X),
member(Y, CL_Y),
iso_acc(X_Rest, Y_Rest, CL_X, CL_Y, ISO_MAP, RES).
% returns sorted degree sequence
% 1 - list of vertices
% 2 - current degree sequence
% 3 - resulting degree sequence
get_degree_sequence_g1([], DEG_S, RES):-
insert_sort(DEG_S, RES).
get_degree_sequence_g1([X|Rest], DEG_S, RES):-
findall(X, way_g1(X, _), LS),
length(LS, L),
append([L], DEG_S, DEG_S_UPD),
get_degree_sequence_g1(Rest, DEG_S_UPD, RES).
get_degree_sequence_g2([], DEG_S, RES):-
insert_sort(DEG_S, RES).
get_degree_sequence_g2([X|Rest], DEG_S, RES):-
findall(X, way_g2(X, _), LS),
length(LS, L),
append([L], DEG_S, DEG_S_UPD),
get_degree_sequence_g2(Rest, DEG_S_UPD, RES).
% compares two lists element by element
compare_lists([], []).
compare_lists([X|X_Rest], [Y|Y_Rest]):-
X=Y,
compare_lists(X_Rest, Y_Rest).
% checks whether binding exist, if not adds it (binding cannot be added if some other binding referring to same
% variables exists already (i.e. (1, 2) cannot be added if (2, 2) exists)
% 1 - binding to add / check in form "b(X, Y)"
% 2 - initial binding map
% 3 - resulting binding map (may remain the same)
try_bind(b(X, Y), MAP, MAP):-
member(b(X, Z), MAP),
Z=Y,
member(b(W, Y), MAP),
W=X.
try_bind(b(X, Y), MAP, UPD_MAP):-
not(member(b(X, _), MAP)),
not(member(b(_, Y), MAP)),
append([b(X, Y)], MAP, UPD_MAP).
% returns updated closed list (X goes to CL), children of X, Length of children, TODO: members of closed lists should not be repeated.
% 1 - Node to expand
% 2 - initial closed list
% 3 - updated closed list (result)
% 4 - updated binding map (result)
% 5 - quantity of children (result)
expand_g1(X, CL, CL_UPD, RES, L):-
findall(Y, (way_g1(X, Y), (not(member(Y, CL)))), LS),
%set results
append(LS, [], RES),
%update closed list
append([X], CL, CL_UPD),
%set length
length(RES, L).
expand_g2(X, CL, CL_UPD, RES, L):-
findall(Y, (way_g2(X, Y), (not(member(Y, CL)))), LS),
%set results
append(LS, [], RES),
%update closed list
append([X], CL, CL_UPD),
%set length
length(RES, L).
% sort algorithm, used in degree sequence verification (simple insertion sort)
% 1 - list to sort
% 2 - result
insert_sort(LS, RES):-insert_sort_acc(LS, [], RES).
insert_sort_acc([], RES, RES).
insert_sort_acc([X|Rest], LS, RES):-insert(X, LS, RES1), insert_sort_acc(Rest, RES1, RES).
% insert item at list
% 1 - item to insert
% 2 - list to insert to
% 3 - result
insert(X,[],[X]).
insert(X, [Y|Rest], [X, Y|Rest]):-X=<Y, !.
insert(X, [Y|Y_Rest], [Y|RES_Rest]):-insert(X, Y_Rest, RES_Rest).
来源：https://stackoverflow.com/questions/30609969/prolog-isomorphic-graphs