Simplify tridiagonal solver constructor #152
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #152 +/- ##
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+ Coverage 88.67% 88.86% +0.18%
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Files 87 87
Lines 4982 4931 -51
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- Hits 4418 4382 -36
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EmilyBourne
reviewed
Jan 15, 2026
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| /* ---------------------------------------------------------- */ | ||
| /* Based on Cholesky Decomposition: A = L * D * L^T | ||
| * | ||
| * This function performs Cholesky decomposition on a | ||
| * symmetric tridiagonal matrix, factorizing it into | ||
| * a lower triangular matrix (L) and a diagonal matrix (D). | ||
| * | ||
| * By storing the decomposition, this approach enhances | ||
| * efficiency for repeated solutions, as matrix factorizations | ||
| * need not be recalculated each time. | ||
| * ---------------------------------------------------------- */ | ||
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Removing all the documentation seems like a bad idea
EmilyBourne
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Jan 15, 2026
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| /* | ||
| * This algorithm implements the Tridiagonal Matrix Algorithm (TDMA) for solving | ||
| * symmetric tridiagonal systems of equations, specifically designed to handle | ||
| * cyclic boundary conditions. The implementation is based on principles outlined | ||
| * in the following resource: | ||
| * https://en.wikipedia.org/wiki/Tridiagonal_matrix_algorithm. | ||
| */ | ||
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| template <typename T> | ||
| void SymmetricTridiagonalSolver<T>::solveSymmetricCyclicTridiagonal(T* x, T* u, T* scratch) | ||
| { | ||
| /* ---------------------------------------------------------- */ | ||
| /* Cholesky Decomposition: A = L * D * L^T | ||
| * This step factorizes the tridiagonal matrix into lower | ||
| * triangular (L) and diagonal (D) matrices. While this | ||
| * approach may be slightly less stable, it can offer improved | ||
| * performance for repeated solves due to the factorization | ||
| * being stored internally. | ||
| * ---------------------------------------------------------- */ | ||
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EmilyBourne
reviewed
Jan 15, 2026
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