[Type] Introduce function to compute the determinant of any square matrix#5877
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fredroy merged 5 commits intosofa-framework:masterfrom Feb 9, 2026
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| for (size_t j = 0; j < N; ++j) | ||
| { | ||
| if (j == p) continue; | ||
| submat(i - 1, colIndex++) = mat(i, j); |
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Wouldn't it be more efficient to only create a vector of col and row indices that is reduced of one element for each determinant development ? So in the end your 'submatrix' is like a view on the original matrix, instead of copying the same values multiple times ?
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I did not try to reach high performances because I don't have the need. Currently, I use it only in init().
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would your changes be easily introduced @bakpaul ?
if yes, we can add it inside this PR
else, it could be done in a later one
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Yes I think so, I just need to take time to do it. Give me one week ?
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* Add a version without copy of the matrix content, also works with sparse matrix * Remove unwanted header
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@bakpaul I finally changed the algorithm for a Gaussian elimination. Neither your code or mine worked on a 12x12 matrix. It hanged infinitely. I also implemented benchmarks for this function: alxbilger/SofaBenchmark#44. Here is a possible result: For small matrices, even 3x3 we are way slower than Eigen. |
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Well it makes sense, thinking about it now, it was in n! complexity |
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