This library provides aggregating operators over the solutions of a predicate. The operations are a generalisation of the bagof/3, setof/3 and findall/3 built-in predicates. Aggregations that can be computed incrementally avoid findall/3 and run in constant memory. The defined aggregation operations are counting, computing the sum, minimum, maximum, a bag of solutions and a set of solutions. We first give a simple example, computing the country with the smallest area:
smallest_country(Name, Area) :- aggregate(min(A, N), country(N, A), min(Area, Name)).
- aggregate vs. aggregate_all
The aggregate predicates use setof/3 (aggregate/4) or bagof/3
(aggregate/3), dealing with existential qualified variables
Var^Goal) and providing multiple solutions for the remaining free variables in Goal. The aggregate_all/3 predicate uses findall/3, implicitly qualifying all free variables and providing exactly one solution, while aggregate_all/4 uses sort/2 over solutions that Discriminator (see below) generated using findall/3.
- The Discriminator argument
The versions with 4 arguments deduplicate redundant solutions of
Goal. Solutions for which both the template variables and
Discriminator are identical will be treated as one solution. For
example, if we wish to compute the total population of all
countries, and for some reason
country(belgium, 11000000)may succeed twice, we can use the following to avoid counting the population of Belgium twice:
aggregate(sum(P), Name, country(Name, P), Total)
All aggregation predicates support the following operators below in
Template. In addition, they allow for an arbitrary named compound term,
where each of the arguments is a term from the list below. For example,
r(min(X), max(X)) computes both the minimum and maximum binding
- Count number of solutions. Same as
- Sum of Expr for all solutions.
- Minimum of Expr for all solutions.
- min(Expr, Witness)
- A term
min(Min, Witness), where Min is the minimal version of Expr over all solutions, and Witness is any other template applied to solutions that produced Min. If multiple solutions provide the same minimum, Witness corresponds to the first solution.
- Maximum of Expr for all solutions.
- max(Expr, Witness)
min(Expr, Witness), but producing the maximum result.
- An ordered set with all solutions for X.
- A list of all solutions for X.
The development of this library was sponsored by SecuritEase, http://www.securitease.com
- aggregate(+Template, :Goal, -Result) is nondet
- Aggregate bindings in Goal according to Template. The aggregate/3 version performs bagof/3 on Goal.
- aggregate(+Template, +Discriminator, :Goal, -Result) is nondet
- Aggregate bindings in Goal according to Template. The aggregate/4 version performs setof/3 on Goal.
- aggregate_all(+Template, :Goal, -Result) is semidet
- Aggregate bindings in Goal according to Template. The
aggregate_all/3 version performs findall/3 on Goal. Note that this
predicate fails if Template contains one or more of
max(X,Witness)and Goal has no solutions, i.e., the minimum and maximum of an empty set is undefined.
The Template values
min(X,W)are processed incrementally rather than using findall/3 and run in constant memory.
- aggregate_all(+Template, +Discriminator, :Goal, -Result) is semidet
- Aggregate bindings in Goal according to Template. The aggregate_all/4 version performs findall/3 followed by sort/2 on Goal. See aggregate_all/3 to understand why this predicate can fail.
- foreach(:Generator, :Goal)
- True when the conjunction of instances of Goal created from
solutions for Generator is true. Except for term copying, this could
be implemented as below.
foreach(Generator, Goal) :- findall(Goal, Generator, Goals), maplist(call, Goals).
The actual implementation uses findall/3 on a template created from the variables shared between Generator and Goal. Subsequently, it uses every instance of this template to instantiate Goal, call Goal and undo only the instantiation of the template and not other instantiations created by running Goal. Here is an example:
?- foreach(between(1,4,X), dif(X,Y)), Y = 5. Y = 5. ?- foreach(between(1,4,X), dif(X,Y)), Y = 3. false.
The predicate foreach/2 is mostly used if Goal performs backtrackable destructive assignment on terms. Attributed variables (underlying constraints) are an example. Another example of a backtrackable data structure is in library(hashtable). If we care only about the side effects (I/O, dynamic database, etc.) or the truth value of Goal, forall/2 is a faster and simpler alternative. If Goal instantiates its arguments it is will often fail as the argument cannot be instantiated to multiple values. It is possible to incrementally grow an argument:
?- foreach(between(1,4,X), member(X, L)). L = [1,2,3,4|_].
Note that SWI-Prolog up to version 8.3.4 created copies of Goal using copy_term/2 for each iteration, this makes the current implementation unable to properly handle compound terms (in Goal’s arguments) that share variables with the Generator. As a workaround you can define a goal that does not use compound terms, like in this example:
mem(E,L) :- % mem/2 hides the compound argument from foreach/2 member(r(E),L). ?- foreach( between(1,5,N), mem(N,L)).
- free_variables(:Generator, +Template, +VarList0, -VarList) is det
- Find free variables in bagof/setof template. In order to handle
variables properly, we have to find all the universally
quantified variables in the Generator. All variables as yet
unbound are universally quantified, unless
free_variables(Generator, Template, OldList, NewList)finds this set using OldList as an accumulator.
- sandbox:safe_meta(+Goal, -Called) is semidet[multifile]
- Declare the aggregate meta-calls safe. This cannot be proven due to the manipulations of the argument Goal.