Did you know ... Search Documentation: Pack cplint_r -- prolog/cplint_r.pl
build_xy_list(+X:list, +Y:list, -Out:list) is det
Given to lists X and Y build an output list Out in the form [X1-Y1,X2-Y2,...,XN-YN].
r_row(+X:atom, +Y:atom, -Out:atom) is det
Given two atoms X and Y, build the term `r(X,Y)` in Out.
get_set_from_xy_list(+L:list, -R:list) is det
Given an input list L in the form [X1-Y1,X2-Y2,...,XN-YN], transform it in an output list R in the form [`r(X1,Y1)`,`r(X2,Y2)`,...,`r(XN,YN)`]. This means that R will contain an X-Y relationship which can be then passed to an R data frame.
prob_bar_r(:Query:atom) is nondet
The predicate computes and plots the probability of Query as a bar chart with a bar for the probability of Query true and a bar for the probability of Query false. If Query is not ground, it returns in backtracking all ground instantiations of Query together with their probabilities
prob_bar_r(:Query:atom, :Evidence:atom) is nondet
The predicate computes the probability of the Query given Evidence as a bar chart with a bar for the probability of Query true and a bar for the probability of Query false given Evidence. If Query /Evidence are not ground, it returns in backtracking all ground instantiations of Query/Evidence together with their probabilities
mc_prob_bar_r(:Query:atom) is det
See prob_bar.
mc_sample_bar_r(:Query:atom, +Samples:int) is det
The predicate samples Query a number of Samples times and plots a bar chart with a bar for the number of successes and a bar for the number of failures. If Query is not ground, it considers it as an existential query.
mc_sample_arg_bar_r(:Query:atom, +Samples:int, ?Arg:var) is det
The predicate samples Query Samples times. Arg should be a variable in Query. The predicate plots a bar chart with a bar for each possible value of L, the list of values of Arg for which Query succeeds in a world sampled at random. The size of the bar is the number of samples returning that list of values.
mc_sample_arg_first_bar_r(:Query:atom, +Samples:int, ?Arg:var) is det
The predicate samples Query Samples times. Arg should be a variable in Query. The predicate plots a bar chart with a bar for each value of Arg returned as a first answer by Query in a world sampled at random. The size of the bar is the number of samples that returned that value. The value is failure if the query fails.
mc_rejection_sample_arg_bar_r(:Query:atom, :Evidence:atom, +Samples:int, ?Arg:var) is det
The predicate calls mc_rejection_sample_arg/5 and builds an R graph of the results. It plots a bar chart with a bar for each possible value of L, the list of values of Arg for which Query succeeds given that Evidence is true The size of the bar is the number of samples returning that list of values.
mc_mh_sample_arg_bar_r(:Query:atom, :Evidence:atom, +Samples:int, +Mix:int, +Lag:int, ?Arg:var) is det
The predicate calls mc_mh_sample_arg/7 and builds an R graph of the results. The predicate plots a bar chart with a bar for each possible value of L, the list of values of Arg for which Query succeeds in a world sampled at random. The size of the bar is the number of samples returning that list of values.
mc_mh_sample_arg_bar_r(:Query:atom, :Evidence:atom, +Samples:int, +Lag:int, ?Arg:var) is det
The predicate call mc_mh_sample_arg/6 and builds a R graph of the results. The predicate plots a bar chart with a bar for each possible value of L, the list of values of Arg for which Query succeeds in a world sampled at random. The size of the bar is the number of samples returning that list of values.
histogram_r(+List:list, +NBins:int) is det
Draws a histogram of the samples in List dividing the domain in NBins bins. List must be a list of couples of the form [V]-W or V-W where V is a sampled value and W is its weight.
density_r(+List:list) is det
Display a smooth density estimate of a sets of samples. The samples are in List as couples V-W where V is a value and W its weigth.
densities_r(+PriorList:list, +PostList:list) is det
Display a smooth density estimate of two sets of samples, usually prior and post observations. The samples from the prior are in PriorList while the samples from the posterior are in PostList as couples V-W where V is a value and W its weigth.
compute_areas_diagrams_r(+LG:list, -AUCROC:float, -AUCPR:float) is det
The predicate takes as input a list LG of pairs probability-literal in asceding order on probability where the literal can be an Atom (incading a positive example) or \+ Atom, indicating a negative example while the probability is the probability of Atom of being true. The predicate returns AUCROC: the size of the area under the ROC curve AUCPR: the size of the area under the PR curve PR and ROC diagrams are plotted. See http://cplint.lamping.unife.it/example/exauc.pl for an example
test_r(+P:probabilistic_program, +TestFolds:list_of_atoms, -LL:float, -AUCROC:float, -AUCPR:float) is det
The predicate takes as input in P a probabilistic program, tests P on the folds indicated in TestFolds and returns the log likelihood of the test examples in LL, the area under the Receiver Operating Characteristic curve in AUCROC, the area under the Precision Recall curve in AUCPR and draws R diagrams of the curves.