Debug printout and variable names
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976b56fd44
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2178589263
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@ -313,8 +313,9 @@ GaussianFactor::eliminate(const string& key) const
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size_t n = A.size2();
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// Do in-place QR to get R, d of the augmented system
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if (verbose) ::print(A,"A before");
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if (verbose) ::print(b,"b before");
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if (verbose) ::print(A,"A");
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if (verbose) ::print(b,"b = ");
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if (verbose) ::print(sigmas_,"sigmas = ");
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std::list<boost::tuple<Vector, double, double> > solution =
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weighted_eliminate(A, b, sigmas_);
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@ -339,30 +340,31 @@ GaussianFactor::eliminate(const string& key) const
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}
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// create base conditional Gaussian
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GaussianConditional::shared_ptr cg(new GaussianConditional(key,
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GaussianConditional::shared_ptr conditional(new GaussianConditional(key,
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sub(d, 0, n1), // form d vector
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sub(R, 0, n1, 0, n1), // form R matrix
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sub(newSigmas, 0, n1))); // get standard deviations
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// extract the block matrices for parents in both CG and LF
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GaussianFactor::shared_ptr lf(new GaussianFactor);
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GaussianFactor::shared_ptr factor(new GaussianFactor);
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size_t j = n1;
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BOOST_FOREACH(string cur_key, ordering)
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if (cur_key!=key) {
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size_t dim = getDim(cur_key);
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cg->add(cur_key, sub(R, 0, n1, j, j+dim));
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lf->insert(cur_key, sub(R, n1, maxRank, j, j+dim));
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conditional->add(cur_key, sub(R, 0, n1, j, j+dim));
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factor->insert(cur_key, sub(R, n1, maxRank, j, j+dim));
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j+=dim;
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}
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// Set sigmas
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lf->sigmas_ = sub(newSigmas,n1,maxRank);
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factor->sigmas_ = sub(newSigmas,n1,maxRank);
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// extract ds vector for the new b
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lf->set_b(sub(d, n1, maxRank));
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if (verbose) lf->print("lf");
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factor->set_b(sub(d, n1, maxRank));
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if (verbose) conditional->print("Conditional");
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if (verbose) factor->print("Factor");
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return make_pair(cg, lf);
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return make_pair(conditional, factor);
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}
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/* ************************************************************************* */
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