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@ -1,6 +1,8 @@ |
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//! Module containing constraint based algorithms like CTPC and Hiton.
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use itertools::Itertools; |
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use rayon::iter::{IntoParallelIterator, ParallelIterator}; |
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use rayon::prelude::ParallelExtend; |
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use std::collections::BTreeSet; |
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use std::usize; |
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@ -41,7 +43,8 @@ impl<P: ParameterLearning> StructureLearningAlgorithm for CTPC<P> { |
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net.initialize_adj_matrix(); |
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for child_node in net.get_node_indices() { |
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let mut learned_parent_sets: Vec<(usize, BTreeSet<usize>)> = vec![]; |
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learned_parent_sets.par_extend(net.get_node_indices().into_par_iter().map(|child_node| { |
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let mut cache = Cache::new(&self.parameter_learning); |
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let mut candidate_parent_set: BTreeSet<usize> = net |
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.get_node_indices() |
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@ -82,6 +85,9 @@ impl<P: ParameterLearning> StructureLearningAlgorithm for CTPC<P> { |
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candidate_parent_set = candidate_parent_set_TMP; |
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separation_set_size += 1; |
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} |
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(child_node, candidate_parent_set) |
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})); |
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for (child_node, candidate_parent_set) in learned_parent_sets { |
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for parent_node in candidate_parent_set.iter() { |
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net.add_edge(*parent_node, child_node); |
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} |
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