From 136a7cdfd02a6dc07692703744f764d8fd7830ff Mon Sep 17 00:00:00 2001
From: scottiyio <scottmb2001@yahoo.com>
Date: Thu, 24 Apr 2025 22:06:46 -0400
Subject: [PATCH] Delete examples/SE2LIEKF_NoFactors.cpp

---
 examples/SE2LIEKF_NoFactors.cpp | 124 --------------------------------
 1 file changed, 124 deletions(-)
 delete mode 100644 examples/SE2LIEKF_NoFactors.cpp

diff --git a/examples/SE2LIEKF_NoFactors.cpp b/examples/SE2LIEKF_NoFactors.cpp
deleted file mode 100644
index 51693b7ee..000000000
--- a/examples/SE2LIEKF_NoFactors.cpp
+++ /dev/null
@@ -1,124 +0,0 @@
-
-/* ----------------------------------------------------------------------------
-
- * GTSAM Copyright 2010, Georgia Tech Research Corporation,
- * Atlanta, Georgia 30332-0415
- * All Rights Reserved
- * Authors: Frank Dellaert, et al. (see THANKS for the full author list)
-
- * See LICENSE for the license information
-
- * -------------------------------------------------------------------------- */
-
-/**
- * @file SE2LIEKF_NoFactors.cpp
- *
- * A simple left invariant EKF operating in SE(2) using an odometry and GPS measurements.
- * No factors are used here.
- * This data was compared to a left invariant EKF on SE(2) using identical measurements and noise from the source of the
- * InEKF plugin https://inekf.readthedocs.io/en/latest/
- * Based on the paper "An Introduction to the Invariant Extended Kalman Filter" by
- * Easton R. Potokar, Randal W. Beard, and Joshua G. Mangelson
- * @date April 1, 2025
- * @author Scott Baker
- */
-
-
-
-#include <gtsam/geometry/Pose2.h>
-#include <gtsam/geometry/Point2.h>
-#include <Eigen/Dense>
-#include <gtsam/base/Matrix.h>
-
-using namespace std;
-using namespace gtsam;
-
-#define PI    3.14159265358
-
-// Create an adjoint class
-// Function for the prediction stage.
-// Note that U is the exponential map of some control vector (u*dt)
-  void predict(Pose2& X, Matrix& P,  Vector3& u, Matrix& Q)
-      {
-    //Pose2 U = Pose2::Expmap(u*dt);
-    Pose2 U(u(0), u(1), u(2));
-    Matrix Adj = U.inverse().AdjointMap();
-    X = X.compose(U);
-    P = Adj * P * Adj.transpose() + Q;
-    }
-
-  // Update stage that uses GPS measurements in a left invariant update way.
-  void update(Pose2& X, Matrix& P, Point2& z, Matrix& H, Matrix& R)
-        {
-    // find residual R^T * (z - zhat)
-    Point2 zhat = X.translation();
-    Point2 e_world = z-zhat;
-    Point2 residual = X.rotation().unrotate(e_world);
-    Matrix S = H*P*H.transpose() + R;
-    Matrix K = P*H.transpose()*S.inverse();
-    Vector3 delta = K*residual;
-    X = X * Pose2::Expmap(delta);
-    P = (Matrix3::Identity() - K*H) * P;
-    }
-
-
-
-int main() {
-
-  // Define movements and measurements
-  const double dt = 1.0;
-
-  Vector3 u1(1.0, 1.0, 0.5), u2(1.0,1.0,0.0); // odometry
-  Point2 z1(1.0, 0.0), z2(1.0, 1.0); // gps
-
-
-
-  // Set up noise models (uses simple GPS)
-
-  // Odometry Process
-  Vector3 pModel(0.05, 0.05, 0.001);    // covariance of the odometry process (rad)
-  Matrix Q = pModel.asDiagonal();       // Q covariance matrix
-
-  // GPS process
-  Vector2 rModel(0.01, 0.01);
-  Matrix R = rModel.asDiagonal();
-  Matrix H(2,3);
-  H << 1,0,0,
-      0,1,0;
-
-  // A matrix that transforms the P matrix into a form of [theta, x, y] for comparison to InEKF's structure.
-  Matrix3 TransformP;
-  TransformP << 0, 0, 1,
-      1,0,0,
-      0,1,0;
-
-// Initialize
-  Pose2 X(0, 0, 0);
-  Matrix P = Matrix3::Identity()*0.1;
-
-  cout << "Initial X\n" << X << endl;
-  cout << "Initial P\n" << TransformP * P * TransformP.transpose() << endl;
-
- // First Prediction
-  predict(X, P, u1, dt, Q);
-  cout << "Predicted X1\n" << X << endl;
-  cout << "Predicted P1\n" << TransformP * P * TransformP.transpose() << endl;
-
-  // First Update
-  update(X, P, z1, H, R);
-  cout << "Updated X1\n" << X << endl;
-  cout << "Updated P1\n" << TransformP * P * TransformP.transpose() << endl;
-
-  // Second Prediction
-  predict(X, P, u2, dt, Q);
-  cout << "Predicted X2\n" << X << endl;
-  cout << "Predicted P2\n" << TransformP * P * TransformP.transpose() << endl;
-
-  // Second Update
-  update(X, P, z2, H, R);
-  cout << "Updated X2\n" << X << endl;
-  cout << "Updated P2\n" << TransformP * P * TransformP.transpose() << endl;
-
-  return 0;
-  }
-