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The sum accuracy test currently uses the default test precision for the given scalar type. However, scalars are generated via a normal distribution, and given a large enough count and strong enough random generator, the expected sum is zero. This causes the test to periodically fail. Here we estimate an upper-bound for the error as `sqrt(N) * prec` for summing N values, with each having an approximate epsilon of `prec`. Also fixed a few warnings generated by MSVC when compiling the reduction test.
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Eigen is a C++ template library for linear algebra: matrices, vectors, numerical solvers, and related algorithms.
For more information go to http://eigen.tuxfamily.org/.
For pull request, bug reports, and feature requests, go to https://gitlab.com/libeigen/eigen.
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