\frac{e^{\frac{-\left|x\right|}{s}}}{\left(s \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)\right) \cdot \left(1 + e^{\frac{-\left|x\right|}{s}}\right)}
\begin{array}{l}
t_0 := e^{-\frac{\left|x\right|}{s}}\\
\frac{t_0}{s \cdot \left(1 + \left(t_0 \cdot 2 + {t_0}^{2}\right)\right)}
\end{array}
(FPCore (x s) :precision binary32 (/ (exp (/ (- (fabs x)) s)) (* (* s (+ 1.0 (exp (/ (- (fabs x)) s)))) (+ 1.0 (exp (/ (- (fabs x)) s))))))
(FPCore (x s) :precision binary32 (let* ((t_0 (exp (- (/ (fabs x) s))))) (/ t_0 (* s (+ 1.0 (+ (* t_0 2.0) (pow t_0 2.0)))))))
float code(float x, float s) {
return expf(-fabsf(x) / s) / ((s * (1.0f + expf(-fabsf(x) / s))) * (1.0f + expf(-fabsf(x) / s)));
}
float code(float x, float s) {
float t_0 = expf(-(fabsf(x) / s));
return t_0 / (s * (1.0f + ((t_0 * 2.0f) + powf(t_0, 2.0f))));
}



Bits error versus x



Bits error versus s
Results
Initial program 0.2
Taylor expanded in s around 0 0.1
Final simplification0.1
herbie shell --seed 2022024
(FPCore (x s)
:name "Logistic distribution"
:precision binary32
:pre (and (<= 0.0 s) (<= s 1.0651631))
(/ (exp (/ (- (fabs x)) s)) (* (* s (+ 1.0 (exp (/ (- (fabs x)) s)))) (+ 1.0 (exp (/ (- (fabs x)) s))))))