yap-6.3/packages/ProbLog/problog/flags.yap

%%% -*- Mode: Prolog; -*-

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%  $Date: 2011-12-08 16:20:16 +0100 (Thu, 08 Dec 2011) $
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%% @file problog/flags.yap

:-module(flags, [problog_define_flag/4,
                         problog_define_flag/5,
                         problog_define_flag/6,
                         problog_defined_flag/5,
                         problog_defined_flag_group/1,
                         set_problog_flag/2,
                         reset_problog_flags/0,
                         problog_flag/2]).

:- use_module(gflags).
:- use_module(os).
:- use_module(logger).
:- use_module(library(system), [file_exists/1, delete_file/1,file_property/2]).


/** @defgroup ProbLogMiscellaneous ProbLog Miscellaneous Predicates
@ingroup problog
@{


Both the learning and the inference module have various parameters, or flags, that can be adjusted by the user.
The following predicates are defined by ProbLog to access and set these flags.

*/

/**
 * @pred problog_flags
 *
This predicate lists all the flags name, value, domain and description.
*/


/**  @pred problog_flag(+Name, -Value)

This predicate gives the value of the flag with the specified name. The supported flags are:

+ use_db_trie

    Flag telling whether to use the builtin trie to trie transformation.
The possible values for this flag are true or false.

+ db_trie_opt_lvl

    Sets the optimization level for the trie to trie transformation
The possible values for this flag are any integer

+ compare_opt_lvl

    Flag telling whether to use comparison mode for the optimization level.
The possible values for this flag are true or false.

+ db_min_prefix

    Sets the minimum size of the prefix for dbtrie to optimize.
The possible values for this flag are any integer

+ use_naive_trie

    Flag telling whether to use the naive algorithm to generate bdd scripts.
The possible values for this flag are true or false.

+ use_old_trie

    Flag telling whether to use the old not nested trie to trie transformation.
The possible values for this flag are true or false.

+ use_dec_trie

    Flag telling whether to use the decomposition method.
The possible values for this flag are true or false.

+ subset_check

    Flag telling whether to perform subset check in nested tries.
The possible values for this flag are true or false.

+ deref_terms

    Flag telling whether to dereference BDD terms after their last use.
The possible values for this flag are true or false.

+ trie_preprocess

    Flag telling whether to perform a preprocess step to nested tries.
The possible values for this flag are true or false.

+ refine_anclst

    Flag telling whether to refine the ancestor list with their children.
The possible values for this flag are true or false.

+ anclst_represent

    Flag that sets the representation of the ancestor list.
The possible values for this flag are list or integer

+ max_depth

    Sets the maximum proof depth.
The possible values for this flag are any integer.

+ retain_tables

    Flag telling whether to retain tables after the query.
The possible values for this flag are true or false.

+ mc_batchsize

    Flag related to Monte Carlo Sampling that sets the number of samples before update.
The possible values for this flag are any integer greater than zero.

+ min_mc_samples

    Flag related to Monte Carlo Sampling that sets the minimum number of samples before convergence. The possible values for this flag are any integer greater than or equal to zero.

+ max_mc_samples

    Flag related to Monte Carlo Sampling that sets the maximum number of samples waiting to converge.
The possible values for this flag are any integer greater than or equal to zero.

+ randomizer

    Flag related to Monte Carlo Sampling telling whether the random numbers are repeatable or not.
The possible values for this flag are repeatable or nonrepeatable.

+ search_method

    Flag related to DNF Monte Carlo Sampling that sets the search method for picking the proof.
The possible values for this flag are linear or binary.

+ represent_world

    Flag related to Monte Carlo Sampling that sets the structure that represents sampled world.
The possible values for this flag are list, record, array or hash_table

+ first_threshold

    Flag related to inference that sets the starting threshold of iterative deepening.
The possible values for this flag are a number in the interval (0,1).

+ last_threshold

    Flag related to inference that sets the stopping threshold of iterative deepening.
The possible values for this flag are a number in the interval (0,1).

+ id_stepsize

    Flag related to inference that sets the threshold shrinking factor of iterative deepening.
The possible values for this flag are a number in the interval [0,1].

+ prunecheck

    Flag related to inference telling whether to stop derivations including all facts of known proofs.
The possible values for this flag are on or off.

+ maxsteps

    Flag related to inference that sets the max. number of prob. steps per derivation.
The possible values for this flag are any integer greater than zero.

+ mc_logfile

    Flag related to MCMC that sets the logfile for montecarlo.
The possible values for this flag are any valid filename.

+ bdd_time

    Flag related to BDD that sets the BDD computation timeout in seconds.
The possible values for this flag are any integer greater than zero.

+ bdd_par_file

    Flag related to BDD that sets the file for BDD variable parameters.
The possible values for this flag are any valid filename.

+ bdd_result

    Flag related to BDD that sets the file to store result calculated from BDD.
The possible values for this flag are any valid filename.

+ bdd_file

    Flag related to BDD that sets the file for the BDD script.
The possible values for this flag are any valid filename.

+ save_bdd

    Flag related to BDD telling whether to save BDD files for (last) lower bound.
The possible values for this flag are true or false.

+ dynamic_reorder

    Flag related to BDD telling whether to use dynamic re-ordering for BDD.
The possible values for this flag are true or false.

+ bdd_static_order

    Flag related to BDD telling whether to use static order.
The possible values for this flag are true or false.

+ static_order_file

    Flag related to BDD that sets the file for BDD static order.
The possible values for this flag are any valid filename.

+ verbose

    Flag telling whether to output intermediate information.
The possible values for this flag are true or false.

+ show_proofs

    Flag telling whether to output proofs.
The possible values for this flag are true or false.

+ triedump

    Flag telling whether to generate the file: trie_file containing the trie structure.
The possible values for this flag are true or false.

+ dir

    Flag telling the location of the output files directory.
The possible values for this flag are any valid directory name.

*/

/** @pred set_problog_flag(+Name, +Value)

the predicate sets the value of the given flag. The supported flags are the ones listed in above
*/

/** @pred learning_flags

the predicate sets the value of the given flag. The supported flags are the ones listed in above
*/

/** @pred learning_flag(+Name, -Value)

This predicate gives the value of the learning flag with the specified name. The supported flags are:

+ output_directory

    Flag setting the directory where to store results.
The possible values for this flag are any valid path name.

+ query_directory

    Flag setting the directory where to store BDD files.
The possible values for this flag are any valid path name.

+ verbosity_level

    Flag telling how much output shall be given.
The possible values for this flag are an integer between 0 and 5 (0=nothing, 5=all).

+ reuse_initialized_bdds

    Flag telling whether to reuse BDDs from previous runs.
The possible values for this flag are true or false.

+ rebuild_bdds

    Flag telling whether to rebuild BDDs every nth iteration.
The possible values for this flag are any integer greater or equal to zero (0=never).

+ check_duplicate_bdds

    Flag telling whether to store intermediate results in hash table.
The possible values for this flag are true or false.

+ init_method

    Flag setting the ProbLog predicate to search proofs.
The possible values for this flag are of the form: (+Query,-P,+BDDFile,+ProbFile,+Call). For example: A,B,C,D,problog_kbest_save(A,100,B,E,C,D)

+ probability_initializer

    Flag setting the ProbLog predicate to initialize probabilities.
The possible values for this flag are of the form: (+FactID,-P,+Call). For example: A,B,random_probability(A,B)

+ log_frequency

    Flag telling whether to log results every nth iteration.
The possible values for this flag are any integer greater than zero.

+ alpha

    Flag setting the weight of negative examples.
The possible values for this flag are number or "auto" (auto=n_p/n_n).

+ slope

    Flag setting the slope of the sigmoid function.
The possible values for this flag are any real number greater than zero.

+ learning_rate

    Flag setting the default Learning rate (if line_search=false)
The possible values for this flag are any number greater than zero or "examples``

+ line_search

    Flag telling whether to use line search to estimate the learning rate.
The possible values for this flag are true or false.

+ line_search_tau

    Flag setting the Tau value for line search.
The possible values for this flag are a number in the interval (0,1).

+ line_search_tolerance

    Flag setting the tolerance value for line search.
The possible values for this flag are any number greater than zero.

+ line_search_interval

    Flag setting the interval for line search.

*/

problog_define_flag(Flag, Type, Description, DefaultValue):-
  flag_define(Flag, Type, DefaultValue, Description).

problog_define_flag(Flag, Type, Description, DefaultValue, FlagGroup):-
  flag_define(Flag, FlagGroup, Type, DefaultValue, Description).

problog_define_flag(Flag, Type, Description, DefaultValue, FlagGroup, Handler):-
  flag_define(Flag, FlagGroup, Type, DefaultValue, Handler, Description).

problog_defined_flag(Flag, Group, DefaultValue, Domain, Message):-
  flag_defined(Flag, Group, DefaultValue, Domain, Message).

problog_defined_flag_group(Group):-
  flag_group_defined(Group).

set_problog_flag(Flag, Value):-
  flag_set(Flag, Value).

problog_flag(Flag, Value):-
  flag_get(Flag, Value).

reset_problog_flags:- flags_reset.

:- initialization((
  flag_add_validation_syntactic_sugar(problog_flag_validate_dummy, flag_validate_dummy),
  flag_add_validation_syntactic_sugar(problog_flag_validate_atom, flag_validate_atom),
  flag_add_validation_syntactic_sugar(problog_flag_validate_atomic, flag_validate_atomic),
  flag_add_validation_syntactic_sugar(problog_flag_validate_number, flag_validate_number),
  flag_add_validation_syntactic_sugar(problog_flag_validate_integer, flag_validate_integer),
  flag_add_validation_syntactic_sugar(problog_flag_validate_directory, flag_validate_directory),
  flag_add_validation_syntactic_sugar(problog_flag_validate_file, flag_validate_file),
  flag_add_validation_syntactic_sugar(problog_flag_validate_in_list(L), flag_validate_in_list(L)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_in_interval(I, Type), flag_validate_in_interval(I, Type)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_in_interval_closed([L, U]), flag_validate_in_interval([L, U], number)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_in_interval_open([L, U]), flag_validate_in_interval((L, U), number)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_in_interval_left_open([L, U]), flag_validate_in_interval((L, [U]), number)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_in_interval_right_open([L, U]), flag_validate_in_interval(([L], U), number)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_integer_in_interval_closed([L, U]), flag_validate_in_interval([L, U], integer)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_integer_in_interval_open([L, U]), flag_validate_in_interval((L, U), integer)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_integer_in_interval_left_open([L, U]), flag_validate_in_interval((L, [U]), integer)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_integer_in_interval_right_open([L, U]), flag_validate_in_interval(([L], U), integer)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_float_in_interval_closed([L, U]), flag_validate_in_interval([L, U], float)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_float_in_interval_open([L, U]), flag_validate_in_interval((L, U), float)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_float_in_interval_left_open([L, U]), flag_validate_in_interval((L, [U]), float)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_float_in_interval_right_open([L, U]), flag_validate_in_interval(([L], U), float)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_posnumber, flag_validate_in_interval((0, [+inf]), number)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_posint, flag_validate_in_interval((0, +inf), integer)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_nonegint, flag_validate_in_interval(([0], +inf), integer)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_boolean, flag_validate_in_list([true, false])),
  flag_add_validation_syntactic_sugar(problog_flag_validate_switch, flag_validate_in_list([on, off])),
  flag_add_validation_syntactic_sugar(problog_flag_validate_method, flag_validate_in_list([max, delta, exact, montecarlo, low, kbest])),
  flag_add_validation_syntactic_sugar(problog_flag_validate_aggregate, flag_validate_in_list([sum, prod, soft_prod])),
  flag_add_validation_syntactic_sugar(problog_flag_validate_indomain_0_1_open, flag_validate_in_interval((0, 1), number)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_indomain_0_1_close, flag_validate_in_interval([0, 1], number)),
  flag_add_validation_syntactic_sugar(problog_flag_validate_0to5, flag_validate_in_interval([0, 5], integer))
)).

last_threshold_handler(message, '').
last_threshold_handler(validating, _Value).
last_threshold_handler(validated, _Value).
last_threshold_handler(stored, Value):-
  ValueLog is log(Value),
  flag_store(last_threshold_log, ValueLog).

id_stepsize_handler(message, '').
id_stepsize_handler(validating, _Value).
id_stepsize_handler(validated, _Value).
id_stepsize_handler(stored, Value):-
  ValueLog is log(Value),
  flag_store(id_stepsize_log, ValueLog).

bdd_file_handler(message, '').
bdd_file_handler(validating, _Value).
bdd_file_handler(validate, Value):-
  convert_filename_to_working_path(Value, Path),
  catch(file_exists(Path), _, fail), file_property(Path, type(regular)), !.
bdd_file_handler(validate, Value):-
  convert_filename_to_working_path(Value, Path),
  catch((\+ file_exists(Path), tell(Path)), _, fail),
  told, 
  catch(delete_file(Path),_, fail).
bdd_file_handler(validated, _Value).
bdd_file_handler(stored, Value):-
  atomic_concat(Value, '_probs', ParValue),
  flag_set(bdd_par_file, ParValue),
  atomic_concat(Value, '_res', ResValue),
  flag_set(bdd_result, ResValue).

working_file_handler(message, '').
working_file_handler(validating, _Value).
working_file_handler(validate, Value):-
  convert_filename_to_working_path(Value, Path),
  catch(file_exists(Path), _, fail), file_property(Path, type(regular)), !.
working_file_handler(validate, Value):-
  convert_filename_to_working_path(Value, Path),
  catch((\+ file_exists(Path), tell(Path)), _, fail),
  told, 
  catch(delete_file(Path),_, fail).
working_file_handler(validated, _Value).
working_file_handler(stored, _Value).

auto_handler(message, 'auto non-zero').
auto_handler(validating, Value) :-
	number(Value),
	Value =\= 0.
auto_handler(validate, Value):-
  Value == auto.
auto_handler(validated, _Value).
auto_handler(stored, _Value).


examples_handler(message, 'examples').
examples_handler(validating, _Value).
examples_handler(validate, Value):-
  Value == examples.
examples_handler(validated, _Value).
examples_handler(stored, _Value).


learning_init_handler(message, '(Q,P,BDDFile,ProbFile,Query)').
learning_init_handler(validating, (_,_,_,_,_)).
%learning_init_handler(validate, V_).
learning_init_handler(validated, _Value).
learning_init_handler(stored, _Value).

learning_libdd_init_handler(message, '(Q,BDD,Query)').
learning_libdd_init_handler(validating, (_,_,_)).
%learning_init_handler(validate, V_).
learning_libdd_init_handler(validated, _Value).
learning_libdd_init_handler(stored, _Value).

learning_prob_init_handler(message, '(0,1] or uniform(l,h) ').
learning_prob_init_handler(validating, uniform(Low,High)) :-
	number(Low),
	number(High),
	Low<High,
	Low>0,
	High =< 1.
learning_prob_init_handler(validating, N) :-
	number(N),
	N>0,
	N =< 1.
learning_prob_init_handler(validating, A) :-
       atom(A), !.
%learning_prob_init_handler(validate, V_).
learning_prob_init_handler(validated, _Value).
learning_prob_init_handler(stored, _Value).


linesearch_interval_handler(message,'nonempty interval(L,H)').
linesearch_interval_handler(validating,V):-
	V=(L,H),
	number(L),
	number(H),
	L<H.
%linesearch_interval_handler(validate,_).
linesearch_interval_handler(validated,_).
linesearch_interval_handler(stored,_).



learning_output_dir_handler(message, '').
learning_output_dir_handler(validating, _Value).
learning_output_dir_handler(validated, _Value).
learning_output_dir_handler(stored, Value):-
	concat_path_with_filename(Value,'out.dat',Filename),
	logger_set_filename(Filename).

/*
problog_flag_validate_learninginit
problog_flag_validate_interval


validation_type_values(problog_flag_validate_learninginit,'(QueryID,P, BDD,Probs,Call)').

validation_type_values(problog_flag_validate_learningprobinit,'(FactID,P,Call)').

validation_type_values(problog_flag_validate_interval,'any nonempty interval (a,b)').


problog_flag_validate_interval.
problog_flag_validate_interval( (V1,V2) ) :-
  number(V1),
  number(V2),
  V1<V2.

*/

%% @}