Comments (3)
I cannot reproduce the issue. This is the result I get:
(0.673943,0.3241)
(0.673943,-0.3241)
(-0.85084,0.525425)
(-0.85084,-0.525425)
(-0.979328,0.202277)
(-0.979328,-0.202277)
(0.533286,0.845935)
(0.533286,-0.845935)
(-0.0357928,0.999359)
(-0.0357928,-0.999359)
(-0.546374,0.837541)
(-0.546374,-0.837541)
(1.20511,0.579537)
(1.20511,-0.579537)
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I did few other tests, accuracy varies greatly depending on parameters (tolerances, number of shifts, etc.). What parameters do you use? What are residuals for each root? I use defaults (Intel C++ on Windows).
I work with reciprocal polynomials with integer coefficients, most of them have ill-conditioned roots (especially cyclotomic polys).
So far I was not able to get consistent accuracy with RpolyPlusPlus (one set of parameters work for one polynomial but not for the other). I compare it with DHSEQR from MKL/LAPACK, which is very stable (but slow).
One more thing, it is more numerically robust to use std::hypot
to compute magnitude of a complex number. It takes care of the overflow/underflow and other accuracy losses.
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I used the default parameters. Did you enable any particular optimization flags when compiling using Intel C++?
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Related Issues (4)
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