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Doc: add link to doc of sparse solver concept
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@@ -223,7 +223,8 @@ ALIASES = "only_for_vectors=This is only for vectors (either row-
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"note_about_using_kernel_to_study_multiple_solutions=If you need a complete analysis of the space of solutions, take the one solution obtained by this method and add to it elements of the kernel, as determined by kernel()." \
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"note_about_checking_solutions=This method just tries to find as good a solution as possible. If you want to check whether a solution exists or if it is accurate, just call this function to get a result and then compute the error of this result, or use MatrixBase::isApprox() directly, for instance like this: \code bool a_solution_exists = (A*result).isApprox(b, precision); \endcode This method avoids dividing by zero, so that the non-existence of a solution doesn't by itself mean that you'll get \c inf or \c nan values." \
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"note_try_to_help_rvo=This function returns the result by value. In order to make that efficient, it is implemented as just a return statement using a special constructor, hopefully allowing the compiler to perform a RVO (return value optimization)." \
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"nonstableyet=\warning This is not considered to be part of the stable public API yet. Changes may happen in future releases. See \ref Experimental \"Experimental parts of Eigen\""
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"nonstableyet=\warning This is not considered to be part of the stable public API yet. Changes may happen in future releases. See \ref Experimental \"Experimental parts of Eigen\"" \
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"implsparsesolverconcept=This class follows the \link TutorialSparseSolverConcept sparse solver concept \endlink."
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ALIASES += "eigenAutoToc= "
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@@ -4,7 +4,7 @@ In Eigen, there are several methods available to solve linear systems when the c
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\eigenAutoToc
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\section TutorialSparseDirectSolvers Sparse solvers
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\section TutorialSparseSolverList List of sparse solvers
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%Eigen currently provides a limited set of built-in solvers, as well as wrappers to external solver libraries.
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They are summarized in the following table:
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@@ -53,6 +53,8 @@ They are summarized in the following table:
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Here \c SPD means symmetric positive definite.
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\section TutorialSparseSolverConcept Sparse solver concept
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All these solvers follow the same general concept.
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Here is a typical and general example:
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\code
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