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#ifndef math_Transformation_H__
#define math_Transformation_H__
#include "Matrix.h"
#include "../Self.h"
#include <cstdlib>
namespace meow {
/*!
* @brief A base class for implementing kinds of transformations.
*
* We define that the input and output form of our transformations all be
* \b matrix . Some advance methods such as calculating jacobian matrix
* will order that the input form must be a vector.
* @author cat_leopard
*/
template<class Scalar>
class Transformation {
private:
struct Myself {
size_t inputRows_;
size_t inputCols_;
size_t outputRows_;
size_t outputCols_;
size_t psize_;
Myself& copyFrom(Myself const& b) {
inputRows_ = b. inputRows_;
inputCols_ = b. inputCols_;
outputRows_ = b.outputRows_;
outputCols_ = b.outputCols_;
psize_ = b.psize_;
return *this;
}
};
Self<Myself> const self;
protected:
/*!
* Construct and setup
* @param [in] inputRows number of rows of the input matrix.
* @param [in] inputCols number of columns of the input matrix.
* @param [in] outputRows number of rows of the output matrix.
* @param [in] outputCols number of columns of the output matrix.
* @param [in] psize number of parameters
*/
Transformation(size_t inputRows, size_t inputCols,
size_t outputRows, size_t outputCols,
size_t psize): self(true) {
self()-> inputRows_ = inputRows;
self()-> inputCols_ = inputCols;
self()->outputRows_ = outputRows;
self()->outputCols_ = outputCols;
self()->psize_ = psize;
}
/*!
* Construct and copy setings from another transformation class.
* @param [in] b Specify where to copy the informations.
*/
Transformation(Transformation const& b): self(false) {
copyFrom(b);
}
/*!
* @brief Copy from the specified one
*
* @param [in] b The specified one
* @return \c *this
*/
Transformation& copyFrom(Transformation const& b) {
self().copyFrom(b.self);
return *this;
}
/*!
* @brief Ceference from the specified one
*
* @param [in] b The specified one
* @return \c *this
*/
Transformation& referenceFrom(Transformation const& b) {
self().referenceFrom(b.self);
return *this;
}
public:
/*!
* Destructor
*/
virtual ~Transformation() {
}
/*!
* @brief Return the number of rows of the input matrix.
*
* @return Number of rows.
*/
size_t inputRows() const {
return self->inputRows_;
}
/*!
* @brief Return the number of columns of the input matrix.
*
* @return Number of columns.
*/
size_t inputCols() const {
return self->inputCols_;
}
/*!
* @brief Return the number of rows of the output matrix.
*
* @return Number of rows.
*/
size_t outputRows() const {
return self->outputRows_;
}
/*!
* @brief Return the number of columns of the output matrix.
*
* @return Number of columns.
*/
size_t outputCols() const {
return self->outputCols_;
}
/*!
* @brief Return the number of parameters.
*
* @return Number of parameters.
*/
size_t parameterSize() const {
return self->psize_;
}
/*!
* @brief Get the \a i -th parameter.
*
* @param [in] i The index of the specified parameter.
* @note It's a pure virtual method.
*/
virtual Scalar parameter(size_t i) const = 0;
/*!
* @brief Setup the \a i -th parameter.
*
* @param [in] i The index of the specified parameter.
* @param [in] s The new value to the specified parameter.
* @note It's a pure virtual method.
*/
virtual Scalar parameter(size_t i, Scalar const& s) = 0;
/*!
* @brief Do transformate.
*
* @param [in] x The input matrix.
* @note It's a pure virtual method.
*/
virtual Matrix<Scalar> transformate(Matrix<Scalar> const& x) const = 0;
/*!
* @brief Calculate the jacobian matrix (derivate by the input matrix)
* of the transformation.
*
* Consider the case of a non-differentiable
* transformation might be implemented, we return an empty matrix
* now instead of making it be a pure virtual method.
* @param [in] x The input matrix.
* @return An empty matrix.
*/
virtual Matrix<Scalar> jacobian(Matrix<Scalar> const& x) const {
return Matrix<Scalar>();
}
/*!
* @brief Calculate the jacobian matrix (derivate by the \a i -th parameter)
* of the transformation.
*
* Consider the case of a non-differentiable transformation might be
* implemented, we return an empty matrix now instead of making it be
* a pure virtual method.
* @param [in] x The input matrix.
* @param [in] i The index of the specified parameter.
* @return An empty matrix.
*/
virtual Matrix<Scalar> jacobian(Matrix<Scalar> const& x, size_t i) const {
return Matrix<Scalar>();
}
/*!
* @brief Return whether this transformation is inversable or not
*
* @return \c false
*/
virtual bool inversable() const { return false; }
/*!
* @brief Do the inverse transformation
*
* @param [in] x The input matirx
* @return An empty matrix
*/
virtual Matrix<Scalar> transformateInv(Matrix<Scalar> const& x) const {
return Matrix<Scalar>();
}
/*!
* @brief Return the jacobian matrix of the inverse transformation
*
* @param [in] x The input matirx
* @return An empty matrix
*/
virtual Matrix<Scalar> jacobianInv(Matrix<Scalar> const& x) const {
return Matrix<Scalar>();
}
/*!
* @brief Return the jacobian matrix of the inverse transformation
*
* @param [in] x The input matirx
* @param [in] i The index of the specified parameter.
* @return An empty matrix
*/
virtual Matrix<Scalar> jacobianInv(Matrix<Scalar> const& x, size_t i) const {
return Matrix<Scalar>();
}
};
}
#endif // math_Transformation_H__
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