Automagic code reformat and cleanup

KinectToVR · Feb 21, 2023 · 5c7e2a3 · 5c7e2a3
1 parent 1fa150d
commit 5c7e2a3
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Showing 21 changed files with 795 additions and 789 deletions.
diff --git a/Amethyst.Support/KalmanFilter.h b/Amethyst.Support/KalmanFilter.h
@@ -4,135 +4,135 @@
 class CKalmanFilter
 {
 public:
-	/**
-	* Create a Kalman filter with the specified matrices.
-	*   A - System dynamics matrix
-	*   B - Input matrix
-	*   C - Output matrix
-	*   Q - Process noise covariance
-	*   R - Measurement noise covariance
-	*   P - Estimate error covariance
-	*/
-
-	CKalmanFilter()
-	{
-		constexpr int _n = 3; // Number of states
-		constexpr int _m = 1; // Number of measurements
-		constexpr int _c = 1; // Number of control inputs
-
-		Eigen::MatrixXf _A(_n, _n); // System dynamics matrix
-		Eigen::MatrixXf _B(_n, _c); // Input control matrix
-		Eigen::MatrixXf _C(_m, _n); // Output matrix
-		Eigen::MatrixXf _Q(_n, _n); // Process noise covariance
-		Eigen::MatrixXf _R(_m, _m); // Measurement noise covariance
-		Eigen::MatrixXf _P(_n, _n); // Estimate error covariance
-
-		double dt = 1.0 / 100;
-		// Discrete LTI projectile motion, measuring position only
-		_A << 1, dt, 0, 0, 1, dt, 0, 0, 1;
-		_B << 0, 0, 0;
-		_C << 1, 0, 0;
-
-		// Reasonable covariance matrices
-		_Q << .17, .17, .0, .17, .17, .0, .0, .0, .0;
-		_R << 5;
-		_P << .3, .3, .3, .3, 30000, 30, .3, 30, 300;
-
-		A = _A;
-		B = _B;
-		C = _C;
-		Q = _Q;
-		R = _R;
-
-		P0 = _P;
-
-		m = _C.rows();
-		n = _A.rows();
-		c = _B.cols();
-
-		I = Eigen::MatrixXf(n, n);
-		x_hat = Eigen::VectorXf(n);
-
-		initialized = false;
-		I.setIdentity();
-	}
-
-	/**
-	* Initialize the filter with initial states as zero.
-	*/
-	void init()
-	{
-		x_hat.setZero();
-		P = P0;
-		initialized = true;
-	}
-
-	/**
-	* Initialize the filter with a guess for initial states.
-	*/
-	void init(const Eigen::VectorXf& x0)
-	{
-		x_hat = x0;
-		P = P0;
-		initialized = true;
-	}
-
-	/**
-	* Update the prediction based on control input.
-	*/
-	void predict(const Eigen::VectorXf& u)
-	{
-		if (!initialized)
-			init();
-
-		x_hat = A * x_hat + B * u;
-		P = A * P * A.transpose() + Q;
-	}
-
-	/**
-	* Update the estimated state based on measured values.
-	*/
-	void update(const Eigen::VectorXf& y)
-	{
-		K = P * C.transpose() * (C * P * C.transpose() + R).inverse();
-		x_hat += K * (y - C * x_hat);
-		P = (I - K * C) * P;
-	}
-
-	/**
-	* Update the dynamics matrix.
-	*/
-	void update_dynamics(const Eigen::MatrixXf A)
-	{
-		this->A = A;
-	}
-
-	/**
-	* Update the output matrix.
-	*/
-	void update_output(const Eigen::MatrixXf C)
-	{
-		this->C = C;
-	}
-
-	/**
-	* Return the current state.
-	*/
-	Eigen::VectorXf state() { return x_hat; };
+    /**
+    * Create a Kalman filter with the specified matrices.
+    *   A - System dynamics matrix
+    *   B - Input matrix
+    *   C - Output matrix
+    *   Q - Process noise covariance
+    *   R - Measurement noise covariance
+    *   P - Estimate error covariance
+    */
+
+    CKalmanFilter()
+    {
+        constexpr int _n = 3; // Number of states
+        constexpr int _m = 1; // Number of measurements
+        constexpr int _c = 1; // Number of control inputs
+
+        Eigen::MatrixXf _A(_n, _n); // System dynamics matrix
+        Eigen::MatrixXf _B(_n, _c); // Input control matrix
+        Eigen::MatrixXf _C(_m, _n); // Output matrix
+        Eigen::MatrixXf _Q(_n, _n); // Process noise covariance
+        Eigen::MatrixXf _R(_m, _m); // Measurement noise covariance
+        Eigen::MatrixXf _P(_n, _n); // Estimate error covariance
+
+        double dt = 1.0 / 100;
+        // Discrete LTI projectile motion, measuring position only
+        _A << 1, dt, 0, 0, 1, dt, 0, 0, 1;
+        _B << 0, 0, 0;
+        _C << 1, 0, 0;
+
+        // Reasonable covariance matrices
+        _Q << .17, .17, .0, .17, .17, .0, .0, .0, .0;
+        _R << 5;
+        _P << .3, .3, .3, .3, 30000, 30, .3, 30, 300;
+
+        A = _A;
+        B = _B;
+        C = _C;
+        Q = _Q;
+        R = _R;
+
+        P0 = _P;
+
+        m = _C.rows();
+        n = _A.rows();
+        c = _B.cols();
+
+        I = Eigen::MatrixXf(n, n);
+        x_hat = Eigen::VectorXf(n);
+
+        initialized = false;
+        I.setIdentity();
+    }
+
+    /**
+    * Initialize the filter with initial states as zero.
+    */
+    void init()
+    {
+        x_hat.setZero();
+        P = P0;
+        initialized = true;
+    }
+
+    /**
+    * Initialize the filter with a guess for initial states.
+    */
+    void init(const Eigen::VectorXf& x0)
+    {
+        x_hat = x0;
+        P = P0;
+        initialized = true;
+    }
+
+    /**
+    * Update the prediction based on control input.
+    */
+    void predict(const Eigen::VectorXf& u)
+    {
+        if (!initialized)
+            init();
+
+        x_hat = A * x_hat + B * u;
+        P = A * P * A.transpose() + Q;
+    }
+
+    /**
+    * Update the estimated state based on measured values.
+    */
+    void update(const Eigen::VectorXf& y)
+    {
+        K = P * C.transpose() * (C * P * C.transpose() + R).inverse();
+        x_hat += K * (y - C * x_hat);
+        P = (I - K * C) * P;
+    }
+
+    /**
+    * Update the dynamics matrix.
+    */
+    void update_dynamics(const Eigen::MatrixXf A)
+    {
+        this->A = A;
+    }
+
+    /**
+    * Update the output matrix.
+    */
+    void update_output(const Eigen::MatrixXf C)
+    {
+        this->C = C;
+    }
+
+    /**
+    * Return the current state.
+    */
+    Eigen::VectorXf state() { return x_hat; };
 
 private:
-	// Matrices for computation
-	Eigen::MatrixXf A, B, C, Q, R, P, K, P0;
+    // Matrices for computation
+    Eigen::MatrixXf A, B, C, Q, R, P, K, P0;
 
-	// System dimensions
-	int m, n, c;
+    // System dimensions
+    int m, n, c;
 
-	// Is the filter initialized?
-	bool initialized = false;
+    // Is the filter initialized?
+    bool initialized = false;
 
-	// n-size identity
-	Eigen::MatrixXf I;
+    // n-size identity
+    Eigen::MatrixXf I;
 
-	// Estimated states
-	Eigen::VectorXf x_hat;
+    // Estimated states
+    Eigen::VectorXf x_hat;
 };
diff --git a/Amethyst.Support/PropertySheet.props b/Amethyst.Support/PropertySheet.props
@@ -1,8 +1,9 @@
 <?xml version="1.0" encoding="utf-8"?>
+
 <Project ToolsVersion="4.0" xmlns="http://schemas.microsoft.com/developer/msbuild/2003">
-  <ImportGroup Label="PropertySheets" />
-  <PropertyGroup Label="UserMacros" />
-  <!--
+    <ImportGroup Label="PropertySheets" />
+    <PropertyGroup Label="UserMacros" />
+    <!--
     To customize common C++/WinRT project properties: 
     * right-click the project node
     * expand the Common Properties item
@@ -11,6 +12,6 @@
     For more advanced scenarios, and complete documentation, please see:
     https://github.com/Microsoft/cppwinrt/tree/master/nuget 
     -->
-  <PropertyGroup />
-  <ItemDefinitionGroup />
+    <PropertyGroup />
+    <ItemDefinitionGroup />
 </Project>