# 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.

template<int T>
class CrossCorrelationCache : public mrcpp::ObjectCache<CrossCorrelation>

Public Functions

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

std::string libPath

Base path to filter library.

Private Members