\frac{2}{1 + e^{-2 \cdot x}} - 1\begin{array}{l}
\mathbf{if}\;x \le -9.6621564271044073 \cdot 10^{-4}:\\
\;\;\;\;\frac{2 \cdot \frac{2}{\left(1 + {\left(e^{-2}\right)}^{x}\right) \cdot \left(1 + {\left(e^{-2}\right)}^{x}\right)} - 1 \cdot 1}{1 + \frac{2}{1 + {\left(e^{-2}\right)}^{x}}}\\
\mathbf{elif}\;x \le 9.27427744022323226 \cdot 10^{-4}:\\
\;\;\;\;x \cdot 1 - {x}^{3} \cdot \left(x \cdot 5.55112 \cdot 10^{-17} + 0.33333333333333337\right)\\
\mathbf{else}:\\
\;\;\;\;\log \left(e^{\frac{2}{1 + {\left(e^{-2}\right)}^{x}} - 1}\right)\\
\end{array}double code(double x, double y) {
return ((double) (((double) (2.0 / ((double) (1.0 + ((double) exp(((double) (-2.0 * x)))))))) - 1.0));
}
double code(double x, double y) {
double VAR;
if ((x <= -0.0009662156427104407)) {
VAR = ((double) (((double) (((double) (2.0 * ((double) (2.0 / ((double) (((double) (1.0 + ((double) pow(((double) exp(-2.0)), x)))) * ((double) (1.0 + ((double) pow(((double) exp(-2.0)), x)))))))))) - ((double) (1.0 * 1.0)))) / ((double) (1.0 + ((double) (2.0 / ((double) (1.0 + ((double) pow(((double) exp(-2.0)), x))))))))));
} else {
double VAR_1;
if ((x <= 0.0009274277440223232)) {
VAR_1 = ((double) (((double) (x * 1.0)) - ((double) (((double) pow(x, 3.0)) * ((double) (((double) (x * 5.551115123125783e-17)) + 0.33333333333333337))))));
} else {
VAR_1 = ((double) log(((double) exp(((double) (((double) (2.0 / ((double) (1.0 + ((double) pow(((double) exp(-2.0)), x)))))) - 1.0))))));
}
VAR = VAR_1;
}
return VAR;
}



Bits error versus x



Bits error versus y
Results
if x < -9.6621564271044073e-4Initial program 0.0
rmApplied flip--0.0
Simplified0.0
Simplified0.0
if -9.6621564271044073e-4 < x < 9.27427744022323226e-4Initial program 59.1
Taylor expanded around 0 0.0
Simplified0.0
if 9.27427744022323226e-4 < x Initial program 0.0
rmApplied add-log-exp0.0
Applied add-log-exp0.0
Applied diff-log0.0
Simplified0.0
Final simplification0.0
herbie shell --seed 2020179
(FPCore (x y)
:name "Logistic function from Lakshay Garg"
:precision binary64
(- (/ 2.0 (+ 1.0 (exp (* -2.0 x)))) 1.0))