\frac{2}{1 + e^{-2 \cdot x}} - 1\begin{array}{l}
\mathbf{if}\;-2 \cdot x \le -712581.02015306731 \lor \neg \left(-2 \cdot x \le 5.1608777157782467 \cdot 10^{-4}\right):\\
\;\;\;\;\left(\sqrt[3]{\mathsf{fma}\left(\frac{1}{\sqrt{1 + e^{-2 \cdot x}}}, \frac{2}{\sqrt{1 + e^{-2 \cdot x}}}, -1\right)} \cdot \sqrt[3]{\mathsf{fma}\left(\frac{1}{\sqrt{1 + e^{-2 \cdot x}}}, \frac{2}{\sqrt{1 + e^{-2 \cdot x}}}, -1\right)}\right) \cdot \sqrt[3]{\mathsf{fma}\left(\frac{1}{\sqrt{1 + e^{-2 \cdot x}}}, \frac{2}{\sqrt{1 + e^{-2 \cdot x}}}, -1\right)}\\
\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(1, x, -\mathsf{fma}\left(5.55112 \cdot 10^{-17}, {x}^{4}, 0.33333333333333337 \cdot {x}^{3}\right)\right)\\
\end{array}double code(double x, double y) {
return ((2.0 / (1.0 + exp((-2.0 * x)))) - 1.0);
}
double code(double x, double y) {
double temp;
if ((((-2.0 * x) <= -712581.0201530673) || !((-2.0 * x) <= 0.0005160877715778247))) {
temp = ((cbrt(fma((1.0 / sqrt((1.0 + exp((-2.0 * x))))), (2.0 / sqrt((1.0 + exp((-2.0 * x))))), -1.0)) * cbrt(fma((1.0 / sqrt((1.0 + exp((-2.0 * x))))), (2.0 / sqrt((1.0 + exp((-2.0 * x))))), -1.0))) * cbrt(fma((1.0 / sqrt((1.0 + exp((-2.0 * x))))), (2.0 / sqrt((1.0 + exp((-2.0 * x))))), -1.0)));
} else {
temp = fma(1.0, x, -fma(5.551115123125783e-17, pow(x, 4.0), (0.33333333333333337 * pow(x, 3.0))));
}
return temp;
}



Bits error versus x



Bits error versus y
Results
if (* -2.0 x) < -712581.0201530673 or 0.0005160877715778247 < (* -2.0 x) Initial program 0.0
rmApplied add-sqr-sqrt0.0
Applied *-un-lft-identity0.0
Applied times-frac0.0
Applied fma-neg0.0
rmApplied add-cube-cbrt0.0
if -712581.0201530673 < (* -2.0 x) < 0.0005160877715778247Initial program 58.2
Taylor expanded around 0 0.6
Simplified0.6
Final simplification0.3
herbie shell --seed 2020053 +o rules:numerics
(FPCore (x y)
:name "Logistic function from Lakshay Garg"
:precision binary64
(- (/ 2 (+ 1 (exp (* -2 x)))) 1))