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Add considering variable-impact to counting based stable models
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@ -388,20 +388,35 @@ impl Adf {
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}
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fn two_val_model_counts(&mut self, interpr: &[Term]) -> Vec<Vec<Term>> {
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self.two_val_model_counts_logic(interpr, &vec![Term::UND; interpr.len()])
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self.two_val_model_counts_logic(interpr, &vec![Term::UND; interpr.len()], 0)
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}
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fn two_val_model_counts_logic(&mut self, interpr: &[Term], must_be: &[Term]) -> Vec<Vec<Term>> {
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log::trace!("two_val_model_counts({:?}) called ", interpr);
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fn two_val_model_counts_logic(
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&mut self,
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interpr: &[Term],
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will_be: &[Term],
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depth: usize,
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) -> Vec<Vec<Term>> {
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log::trace!("two_val_model_counts({:?}) called", interpr);
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log::debug!("two_val_model_recursion_depth: {}/{}", depth, interpr.len());
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if let Some((idx, ac)) = interpr
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.iter()
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.enumerate()
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.filter(|(idx, val)| !(val.is_truth_value() || must_be[*idx].is_truth_value()))
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.min_by(|(_idx_a, val_a), (_idx_b, val_b)| {
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self.bdd
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.filter(|(idx, val)| !(val.is_truth_value() || will_be[*idx].is_truth_value()))
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.min_by(|(idx_a, val_a), (idx_b, val_b)| {
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match self
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.bdd
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.models(**val_a, true)
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.minimum()
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.cmp(&self.bdd.models(**val_b, true).minimum())
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{
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// if the minimal counts are equal, choose the maximal var_impact
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std::cmp::Ordering::Equal => self
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.bdd
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.var_impact(Var(*idx_b), interpr)
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.cmp(&self.bdd.var_impact(Var(*idx_a), interpr)),
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value => value,
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}
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})
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{
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let mut result = Vec::new();
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@ -412,6 +427,7 @@ impl Adf {
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ac,
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check_models
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);
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let _ = self // return value can be ignored, but must be catched
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.bdd
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.interpretations(*ac, check_models, Var(idx), &[], &[])
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@ -421,7 +437,7 @@ impl Adf {
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let res = negative
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.iter()
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.try_for_each(|var| {
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if new_int[var.value()].is_true() || must_be[var.value()] == Term::TOP {
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if new_int[var.value()].is_true() || will_be[var.value()] == Term::TOP {
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return Err(());
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}
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new_int[var.value()] = Term::BOT;
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@ -430,7 +446,7 @@ impl Adf {
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.and(positive.iter().try_for_each(|var| {
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if (new_int[var.value()].is_truth_value()
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&& !new_int[var.value()].is_true())
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|| must_be[var.value()] == Term::BOT
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|| will_be[var.value()] == Term::BOT
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{
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return Err(());
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}
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@ -440,7 +456,13 @@ impl Adf {
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if res.is_ok() {
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new_int[idx] = if check_models { Term::TOP } else { Term::BOT };
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let upd_int = self.update_interpretation(&new_int);
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result.append(&mut self.two_val_model_counts_logic(&upd_int, must_be));
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if self.check_consistency(&upd_int, will_be) {
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result.append(&mut self.two_val_model_counts_logic(
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&upd_int,
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will_be,
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depth + 1,
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));
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}
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}
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res
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});
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@ -452,14 +474,17 @@ impl Adf {
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.collect::<Vec<Term>>();
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let mut upd_int = self.update_interpretation(&new_int);
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// TODO: should be "must be true/false" instead of setting it to TOP/BOT and will need sanity checks at every iteration
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log::trace!("\nnew_int {new_int:?}\nupd_int {upd_int:?}");
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if new_int[idx].no_inf_inconsistency(&upd_int[idx]) {
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upd_int[idx] = if check_models { Term::BOT } else { Term::TOP };
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if new_int[idx].no_inf_inconsistency(&upd_int[idx]) {
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let mut must_be_new = must_be.to_vec();
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let mut must_be_new = will_be.to_vec();
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must_be_new[idx] = new_int[idx];
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result.append(&mut self.two_val_model_counts_logic(&upd_int, &must_be_new));
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result.append(&mut self.two_val_model_counts_logic(
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&upd_int,
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&must_be_new,
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depth + 1,
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));
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}
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}
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result
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@ -470,15 +495,17 @@ impl Adf {
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.enumerate()
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.map(|(idx, val)| {
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if !val.is_truth_value() {
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must_be[idx]
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will_be[idx]
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} else {
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*val
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}
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})
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.collect::<Vec<Term>>();
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// TODO: Not copletely correct - should be a check if concluded is consistant with ac
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if concluded == self.update_interpretation(&concluded) {
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vec![concluded]
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let ac = self.ac.clone();
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let result = self.apply_interpretation(&ac, &concluded);
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if self.check_consistency(&result, &concluded) {
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vec![result]
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} else {
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vec![interpr.to_vec()]
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}
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@ -486,8 +513,11 @@ impl Adf {
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}
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fn update_interpretation(&mut self, interpretation: &[Term]) -> Vec<Term> {
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interpretation
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.iter()
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self.apply_interpretation(interpretation, interpretation)
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}
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fn apply_interpretation(&mut self, ac: &[Term], interpretation: &[Term]) -> Vec<Term> {
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ac.iter()
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.map(|ac| {
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interpretation
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.iter()
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@ -503,6 +533,13 @@ impl Adf {
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.collect::<Vec<Term>>()
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}
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fn check_consistency(&mut self, interpretation: &[Term], will_be: &[Term]) -> bool {
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interpretation
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.iter()
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.zip(will_be.iter())
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.all(|(int, wb)| wb.no_inf_inconsistency(int))
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}
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/// Computes the complete models
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/// Returns an Iterator which contains all complete models
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pub fn complete<'a, 'c>(&'a mut self) -> impl Iterator<Item = Vec<Term>> + 'c
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@ -405,6 +405,16 @@ impl Bdd {
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var_set
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}
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}
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pub fn var_impact(&self, var: Var, termlist: &[Term]) -> usize {
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termlist.iter().fold(0usize, |acc, val| {
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if self.var_dependencies(*val).contains(&var) {
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acc + 1
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} else {
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acc
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}
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})
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}
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}
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#[cfg(test)]
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