Merge pull request #1139 from borglab/fix/doc

doc/Code/LocalizationExample2.cpp

@@ -1,7 +1,7 @@
 // add unary measurement factors, like GPS, on all three poses
-noiseModel::Diagonal::shared_ptr unaryNoise =
+auto unaryNoise =
  noiseModel::Diagonal::Sigmas(Vector2(0.1, 0.1)); // 10cm std on x,y
-graph.add(boost::make_shared<UnaryFactor>(1, 0.0, 0.0, unaryNoise));
-graph.add(boost::make_shared<UnaryFactor>(2, 2.0, 0.0, unaryNoise));
-graph.add(boost::make_shared<UnaryFactor>(3, 4.0, 0.0, unaryNoise));
+graph.emplace_shared<UnaryFactor>(1, 0.0, 0.0, unaryNoise);
+graph.emplace_shared<UnaryFactor>(2, 2.0, 0.0, unaryNoise);
+graph.emplace_shared<UnaryFactor>(3, 4.0, 0.0, unaryNoise);
 

doc/Code/LocalizationFactor.cpp

@@ -1,13 +1,12 @@
 class UnaryFactor: public NoiseModelFactor1<Pose2> {
   double mx_, my_; ///< X and Y measurements
-
+  
 public:
   UnaryFactor(Key j, double x, double y, const SharedNoiseModel& model):
     NoiseModelFactor1<Pose2>(model, j), mx_(x), my_(y) {}
 
-  Vector evaluateError(const Pose2& q,
-                       boost::optional<Matrix&> H = boost::none) const
-  {
+  Vector evaluateError(const Pose2& q, 
+      boost::optional<Matrix&> H = boost::none) const override {
     const Rot2& R = q.rotation();
     if (H) (*H) = (gtsam::Matrix(2, 3) <<
             R.c(), -R.s(), 0.0,

doc/Code/OdometryExample.cpp

@@ -3,13 +3,11 @@ NonlinearFactorGraph graph;
 
 // Add a Gaussian prior on pose x_1
 Pose2 priorMean(0.0, 0.0, 0.0);
-noiseModel::Diagonal::shared_ptr priorNoise =
-  noiseModel::Diagonal::Sigmas(Vector3(0.3, 0.3, 0.1));
-graph.addPrior(1, priorMean, priorNoise);
+auto priorNoise = noiseModel::Diagonal::Sigmas(Vector3(0.3, 0.3, 0.1));
+graph.add(PriorFactor<Pose2>(1, priorMean, priorNoise));
 
 // Add two odometry factors
 Pose2 odometry(2.0, 0.0, 0.0);
-noiseModel::Diagonal::shared_ptr odometryNoise =
-  noiseModel::Diagonal::Sigmas(Vector3(0.2, 0.2, 0.1));
+auto odometryNoise = noiseModel::Diagonal::Sigmas(Vector3(0.2, 0.2, 0.1));
 graph.add(BetweenFactor<Pose2>(1, 2, odometry, odometryNoise));
 graph.add(BetweenFactor<Pose2>(2, 3, odometry, odometryNoise));

doc/Code/OdometryOutput1.txt

@@ -1,11 +1,14 @@
 Factor Graph:
 size: 3
-factor 0: PriorFactor on 1
-  prior mean: (0, 0, 0)
+
+Factor 0: PriorFactor on 1
+  prior mean:  (0, 0, 0)
   noise model: diagonal sigmas [0.3; 0.3; 0.1];
-factor 1: BetweenFactor(1,2)
-  measured: (2, 0, 0)
-  noise model: diagonal sigmas [0.2; 0.2; 0.1];
-factor 2: BetweenFactor(2,3)
-  measured: (2, 0, 0)
+
+Factor 1: BetweenFactor(1,2)
+  measured:  (2, 0, 0)
   noise model: diagonal sigmas [0.2; 0.2; 0.1];
+
+Factor 2: BetweenFactor(2,3)
+  measured:  (2, 0, 0)
+  noise model: diagonal sigmas [0.2; 0.2; 0.1];

doc/Code/OdometryOutput2.txt

@@ -1,11 +1,23 @@
 Initial Estimate:
+
 Values with 3 values:
-Value 1: (0.5, 0, 0.2)
-Value 2: (2.3, 0.1, -0.2)
-Value 3: (4.1, 0.1, 0.1)
+Value 1: (gtsam::Pose2)
+(0.5, 0, 0.2)
+
+Value 2: (gtsam::Pose2)
+(2.3, 0.1, -0.2)
+
+Value 3: (gtsam::Pose2)
+(4.1, 0.1, 0.1)
 
 Final Result:
+
 Values with 3 values:
-Value 1: (-1.8e-16, 8.7e-18, -9.1e-19)
-Value 2: (2, 7.4e-18, -2.5e-18)
-Value 3: (4, -1.8e-18, -3.1e-18)
+Value 1: (gtsam::Pose2)
+(7.5-16, -5.3-16, -1.8-16)
+
+Value 2: (gtsam::Pose2)
+(2, -1.1-15, -2.5-16)
+
+Value 3: (gtsam::Pose2)
+(4, -1.7-15, -2.5-16)

doc/Code/OdometryOutput3.txt

@@ -1,12 +1,12 @@
 x1 covariance:
-       0.09     1.1e-47     5.7e-33
-    1.1e-47        0.09     1.9e-17
-    5.7e-33     1.9e-17        0.01
+   0.09 1.7e-33 2.8e-33
+1.7e-33    0.09 2.6e-17
+2.8e-33 2.6e-17    0.01
 x2 covariance:
-       0.13     4.7e-18     2.4e-18
-    4.7e-18        0.17        0.02
-    2.4e-18        0.02        0.02
+   0.13 1.2e-18 6.1e-19
+1.2e-18    0.17    0.02
+6.1e-19    0.02    0.02
 x3 covariance:
-       0.17     2.7e-17     8.4e-18
-    2.7e-17        0.37        0.06
-    8.4e-18        0.06        0.03
+   0.17 8.6e-18 2.7e-18
+8.6e-18    0.37    0.06
+2.7e-18    0.06    0.03