(FPCore (N) :precision binary64 (- (atan (+ N 1.0)) (atan N)))
(FPCore (N) :precision binary64 (log1p (expm1 (atan2 1.0 (+ 1.0 (fma N N N))))))
double code(double N) {
return atan((N + 1.0)) - atan(N);
}
double code(double N) {
return log1p(expm1(atan2(1.0, (1.0 + fma(N, N, N)))));
}
function code(N) return Float64(atan(Float64(N + 1.0)) - atan(N)) end
function code(N) return log1p(expm1(atan(1.0, Float64(1.0 + fma(N, N, N))))) end
code[N_] := N[(N[ArcTan[N[(N + 1.0), $MachinePrecision]], $MachinePrecision] - N[ArcTan[N], $MachinePrecision]), $MachinePrecision]
code[N_] := N[Log[1 + N[(Exp[N[ArcTan[1.0 / N[(1.0 + N[(N * N + N), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision]], $MachinePrecision]
\tan^{-1} \left(N + 1\right) - \tan^{-1} N
\mathsf{log1p}\left(\mathsf{expm1}\left(\tan^{-1}_* \frac{1}{1 + \mathsf{fma}\left(N, N, N\right)}\right)\right)




Bits error versus N
| Original | 14.7 |
|---|---|
| Target | 0.3 |
| Herbie | 0.3 |
Initial program 14.7
Applied egg-rr0.3
Applied egg-rr0.6
Applied egg-rr0.3
Final simplification0.3
herbie shell --seed 2022150
(FPCore (N)
:name "2atan (example 3.5)"
:precision binary64
:herbie-target
(atan (/ 1.0 (+ 1.0 (* N (+ N 1.0)))))
(- (atan (+ N 1.0)) (atan N)))