Robert Bradshaw wrote: > From before, relative errors for the naive vs. other algorithm, > 100000 runs, uniformly chosen in unit square (though nearly all > distributions look basically the same): > > naive > better 26187 > avg 1.4940916064705992895601085724e-16 > worst 5.7659574333851360909896621025e-16 > other > better 63116 > avg 9.5414951065097745299683547276e-17 > worst 3.9584519821557590591785765975e-16 > > - Robert >
This is not my speciality, but since the problem here is with things like fp cancellation on subtraction etc., wouldn't it be better to increase the odds of wildly different values? Something like exp(uniform square)? Dag Sverre _______________________________________________ Cython-dev mailing list [email protected] http://codespeak.net/mailman/listinfo/cython-dev
