\frac{\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) + 2} + 1}{2}\begin{array}{l}
\mathbf{if}\;\alpha \le 2.2132735070342041 \cdot 10^{161}:\\
\;\;\;\;\frac{\mathsf{fma}\left(\frac{\frac{\alpha + \beta}{1}}{1}, \frac{\frac{\beta - \alpha}{\left(\alpha + \beta\right) + 2 \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) + 2}, 1\right)}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\mathsf{fma}\left(2, \frac{1}{\alpha}, 8 \cdot \frac{1}{{\alpha}^{3}} - 4 \cdot \frac{1}{{\alpha}^{2}}\right)}{2}\\
\end{array}double code(double alpha, double beta, double i) {
return ((((((alpha + beta) * (beta - alpha)) / ((alpha + beta) + (2.0 * i))) / (((alpha + beta) + (2.0 * i)) + 2.0)) + 1.0) / 2.0);
}
double code(double alpha, double beta, double i) {
double VAR;
if ((alpha <= 2.213273507034204e+161)) {
VAR = (fma((((alpha + beta) / 1.0) / 1.0), (((beta - alpha) / ((alpha + beta) + (2.0 * i))) / (((alpha + beta) + (2.0 * i)) + 2.0)), 1.0) / 2.0);
} else {
VAR = (fma(2.0, (1.0 / alpha), ((8.0 * (1.0 / pow(alpha, 3.0))) - (4.0 * (1.0 / pow(alpha, 2.0))))) / 2.0);
}
return VAR;
}



Bits error versus alpha



Bits error versus beta



Bits error versus i
Results
if alpha < 2.213273507034204e+161Initial program 15.9
rmApplied *-un-lft-identity15.9
Applied *-un-lft-identity15.9
Applied times-frac5.3
Applied times-frac5.2
Applied fma-def5.2
if 2.213273507034204e+161 < alpha Initial program 64.0
Taylor expanded around inf 39.6
Simplified39.6
Final simplification10.8
herbie shell --seed 2020079 +o rules:numerics
(FPCore (alpha beta i)
:name "Octave 3.8, jcobi/2"
:precision binary64
:pre (and (> alpha -1) (> beta -1) (> i 0.0))
(/ (+ (/ (/ (* (+ alpha beta) (- beta alpha)) (+ (+ alpha beta) (* 2 i))) (+ (+ (+ alpha beta) (* 2 i)) 2)) 1) 2))