From 58d83f704fa1f1a3e841dae264b0c9eb6c5a50b9 Mon Sep 17 00:00:00 2001
From: Frank Dellaert <dellaert@gmail.com>
Date: Sat, 29 Oct 2011 04:00:14 +0000
Subject: [PATCH] Documentation and headers

---
 gtsam/linear/JacobianFactor.cpp | 20 ++++++++++++--------
 gtsam/linear/JacobianFactor.h   |  2 +-
 2 files changed, 13 insertions(+), 9 deletions(-)

diff --git a/gtsam/linear/JacobianFactor.cpp b/gtsam/linear/JacobianFactor.cpp
index 50d6474ee..c20dab3c1 100644
--- a/gtsam/linear/JacobianFactor.cpp
+++ b/gtsam/linear/JacobianFactor.cpp
@@ -15,17 +15,17 @@
  * @date    Dec 8, 2010
  */
 
+#include <gtsam/linear/GaussianConditional.h>
+#include <gtsam/linear/JacobianFactor.h>
+#include <gtsam/linear/HessianFactor.h>
+#include <gtsam/linear/GaussianFactorGraph.h>
+#include <gtsam/inference/VariableSlots.h>
+#include <gtsam/inference/FactorGraph-inl.h>
 #include <gtsam/base/debug.h>
 #include <gtsam/base/timing.h>
 #include <gtsam/base/Matrix.h>
 #include <gtsam/base/FastMap.h>
 #include <gtsam/base/cholesky.h>
-#include <gtsam/inference/VariableSlots.h>
-#include <gtsam/inference/FactorGraph-inl.h>
-#include <gtsam/linear/GaussianConditional.h>
-#include <gtsam/linear/JacobianFactor.h>
-#include <gtsam/linear/HessianFactor.h>
-#include <gtsam/linear/GaussianFactorGraph.h>
 
 #include <boost/foreach.hpp>
 #include <boost/format.hpp>
@@ -33,6 +33,7 @@
 #include <boost/lambda/bind.hpp>
 #include <boost/lambda/lambda.hpp>
 
+#include <cmath>
 #include <sstream>
 #include <stdexcept>
 
@@ -337,8 +338,11 @@ namespace gtsam {
       // find first column index for this key
       size_t column_start = columnIndices[*var];
       for (size_t i = 0; i < (size_t) whitenedA.rows(); i++)
-        for (size_t j = 0; j < (size_t) whitenedA.cols(); j++)
-          entries.push_back(boost::make_tuple(i, column_start+j, whitenedA(i,j)));
+        for (size_t j = 0; j < (size_t) whitenedA.cols(); j++) {
+        	double s = whitenedA(i,j);
+          if (std::abs(s) > 1e-12) entries.push_back(
+							boost::make_tuple(i, column_start + j, s));
+        }
     }
 
     Vector whitenedb(model_->whiten(getb()));
diff --git a/gtsam/linear/JacobianFactor.h b/gtsam/linear/JacobianFactor.h
index aba1cfdf1..07876caf8 100644
--- a/gtsam/linear/JacobianFactor.h
+++ b/gtsam/linear/JacobianFactor.h
@@ -223,7 +223,7 @@ namespace gtsam {
      * Return vector of i, j, and s to generate an m-by-n sparse matrix
      * such that S(i(k),j(k)) = s(k), which can be given to MATLAB's sparse.
      * As above, the standard deviations are baked into A and b
-     * @param first column index for each variable
+     * @param columnIndices First column index for each variable.
      */
     std::vector<boost::tuple<size_t, size_t, double> >
     sparse(const std::vector<size_t>& columnIndices) const;