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authorredpony <redpony@ec762483-ff6d-05da-a07a-a48fb63a330f>2010-06-22 05:12:27 +0000
committerredpony <redpony@ec762483-ff6d-05da-a07a-a48fb63a330f>2010-06-22 05:12:27 +0000
commit0172721855098ca02b207231a654dffa5e4eb1c9 (patch)
tree8069c3a62e2d72bd64a2cdeee9724b2679c8a56b /vest/line_optimizer.cc
parent37728b8be4d0b3df9da81fdda2198ff55b4b2d91 (diff)
initial checkin
git-svn-id: https://ws10smt.googlecode.com/svn/trunk@2 ec762483-ff6d-05da-a07a-a48fb63a330f
Diffstat (limited to 'vest/line_optimizer.cc')
-rw-r--r--vest/line_optimizer.cc103
1 files changed, 103 insertions, 0 deletions
diff --git a/vest/line_optimizer.cc b/vest/line_optimizer.cc
new file mode 100644
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--- /dev/null
+++ b/vest/line_optimizer.cc
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+#include "line_optimizer.h"
+
+#include <limits>
+#include <algorithm>
+
+#include "sparse_vector.h"
+#include "scorer.h"
+
+using namespace std;
+
+typedef ErrorSurface::const_iterator ErrorIter;
+
+// sort by increasing x-ints
+struct IntervalComp {
+ bool operator() (const ErrorIter& a, const ErrorIter& b) const {
+ return a->x < b->x;
+ }
+};
+
+double LineOptimizer::LineOptimize(
+ const vector<ErrorSurface>& surfaces,
+ const LineOptimizer::ScoreType type,
+ float* best_score,
+ const double epsilon) {
+ // cerr << "MIN=" << MINIMIZE_SCORE << " MAX=" << MAXIMIZE_SCORE << " MINE=" << type << endl;
+ vector<ErrorIter> all_ints;
+ for (vector<ErrorSurface>::const_iterator i = surfaces.begin();
+ i != surfaces.end(); ++i) {
+ const ErrorSurface& surface = *i;
+ for (ErrorIter j = surface.begin(); j != surface.end(); ++j)
+ all_ints.push_back(j);
+ }
+ sort(all_ints.begin(), all_ints.end(), IntervalComp());
+ double last_boundary = all_ints.front()->x;
+ Score* acc = all_ints.front()->delta->GetZero();
+ float& cur_best_score = *best_score;
+ cur_best_score = (type == MAXIMIZE_SCORE ?
+ -numeric_limits<float>::max() : numeric_limits<float>::max());
+ bool left_edge = true;
+ double pos = numeric_limits<double>::quiet_NaN();
+ for (vector<ErrorIter>::iterator i = all_ints.begin();
+ i != all_ints.end(); ++i) {
+ const ErrorSegment& seg = **i;
+ assert(seg.delta);
+ if (seg.x - last_boundary > epsilon) {
+ float sco = acc->ComputeScore();
+ if ((type == MAXIMIZE_SCORE && sco > cur_best_score) ||
+ (type == MINIMIZE_SCORE && sco < cur_best_score) ) {
+ cur_best_score = sco;
+ if (left_edge) {
+ pos = seg.x - 0.1;
+ left_edge = false;
+ } else {
+ pos = last_boundary + (seg.x - last_boundary) / 2;
+ }
+ // cerr << "NEW BEST: " << pos << " (score=" << cur_best_score << ")\n";
+ }
+ // string xx; acc->ScoreDetails(&xx); cerr << "---- " << xx;
+ // cerr << "---- s=" << sco << "\n";
+ last_boundary = seg.x;
+ }
+ // cerr << "x-boundary=" << seg.x << "\n";
+ acc->PlusEquals(*seg.delta);
+ }
+ float sco = acc->ComputeScore();
+ if ((type == MAXIMIZE_SCORE && sco > cur_best_score) ||
+ (type == MINIMIZE_SCORE && sco < cur_best_score) ) {
+ cur_best_score = sco;
+ if (left_edge) {
+ pos = 0;
+ } else {
+ pos = last_boundary + 1000.0;
+ }
+ }
+ delete acc;
+ return pos;
+}
+
+void LineOptimizer::RandomUnitVector(const vector<int>& features_to_optimize,
+ SparseVector<double>* axis,
+ RandomNumberGenerator<boost::mt19937>* rng) {
+ axis->clear();
+ for (int i = 0; i < features_to_optimize.size(); ++i)
+ axis->set_value(features_to_optimize[i], rng->next() - 0.5);
+ (*axis) /= axis->l2norm();
+}
+
+void LineOptimizer::CreateOptimizationDirections(
+ const vector<int>& features_to_optimize,
+ int additional_random_directions,
+ RandomNumberGenerator<boost::mt19937>* rng,
+ vector<SparseVector<double> >* dirs) {
+ const int num_directions = features_to_optimize.size() + additional_random_directions;
+ dirs->resize(num_directions);
+ for (int i = 0; i < num_directions; ++i) {
+ SparseVector<double>& axis = (*dirs)[i];
+ if (i < features_to_optimize.size())
+ axis.set_value(features_to_optimize[i], 1.0);
+ else
+ RandomUnitVector(features_to_optimize, &axis, rng);
+ }
+ cerr << "Generated " << num_directions << " total axes to optimize along.\n";
+}