CrossCorrelationCache¶
This is an introduction to the CrossCorrelationCache class. We write a small overarching summary of the class where we define the algorithm/equation/structure reasoning for having this class or where it fits with the rest of the code.
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template<int T>
class CrossCorrelationCache : public mrcpp::ObjectCache<CrossCorrelation>¶ Public Functions
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const Eigen::MatrixXd &getRMatrix(int order)¶
Fetches the cross correlation coefficients.
The cross correlation coefficients
\[ C^{(+)}_{ijp} = \int_0^1 dz \int_0^1 dx \phi_i(x) \phi_j(x - z) \phi_p(z) \]with \( i, j = 0, \ldots, k \) and \( p = 0, \ldots, 2k + 1 \). They are grouped in the so called right matrix\[\begin{split} \begin{pmatrix} C^{(+)}_{000} & C^{(+)}_{001} & \ldots & C^{(+)}_{00,2k+1} \\ C^{(+)}_{010} & C^{(+)}_{011} & \ldots & C^{(+)}_{01,2k+1} \\ \ldots & \ldots & \ldots & \ldots \\ C^{(+)}_{k, k - 1, 0} & C^{(+)}_{k, k - 1, 1} & \ldots & C^{(+)}_{k, k - 1, 2k+1} \\ C^{(+)}_{kk0} & C^{(+)}_{kk1} & \ldots & C^{(+)}_{kk,2k+1} \end{pmatrix} \end{split}\]that is returned by the method.- Parameters:
order – [in] Dimension of \( V_0 \subset L^2(\mathbb R) \) minus one, that is the maximum degree \( k \) of polynomials in \( V_0 \subset L^2(0, 1) \).
- Returns:
The right matrix of cross correlation coefficients.
Protected Attributes
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std::string libPath¶
Base path to filter library.
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const Eigen::MatrixXd &getRMatrix(int order)¶