\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)}
\begin{array}{l}
t_0 := \alpha \cdot \alpha - 1\\
\frac{t_0}{\sqrt[3]{\left({\left(\sqrt[3]{\pi}\right)}^{2} \cdot \left(\sqrt[3]{\pi} \cdot {\pi}^{2}\right)\right) \cdot {\log \left(\alpha \cdot \alpha\right)}^{3}} \cdot \left(1 + cosTheta \cdot \left(t_0 \cdot cosTheta\right)\right)}
\end{array}
(FPCore (cosTheta alpha) :precision binary32 (/ (- (* alpha alpha) 1.0) (* (* PI (log (* alpha alpha))) (+ 1.0 (* (* (- (* alpha alpha) 1.0) cosTheta) cosTheta)))))
(FPCore (cosTheta alpha)
:precision binary32
(let* ((t_0 (- (* alpha alpha) 1.0)))
(/
t_0
(*
(cbrt
(*
(* (pow (cbrt PI) 2.0) (* (cbrt PI) (pow PI 2.0)))
(pow (log (* alpha alpha)) 3.0)))
(+ 1.0 (* cosTheta (* t_0 cosTheta)))))))float code(float cosTheta, float alpha) {
return ((alpha * alpha) - 1.0f) / ((((float) M_PI) * logf((alpha * alpha))) * (1.0f + ((((alpha * alpha) - 1.0f) * cosTheta) * cosTheta)));
}
float code(float cosTheta, float alpha) {
float t_0 = (alpha * alpha) - 1.0f;
return t_0 / (cbrtf(((powf(cbrtf(((float) M_PI)), 2.0f) * (cbrtf(((float) M_PI)) * powf(((float) M_PI), 2.0f))) * powf(logf((alpha * alpha)), 3.0f))) * (1.0f + (cosTheta * (t_0 * cosTheta))));
}



Bits error versus cosTheta



Bits error versus alpha
Results
Initial program 0.5
Applied egg-rr0.5
Applied egg-rr0.4
Final simplification0.4
herbie shell --seed 2022127
(FPCore (cosTheta alpha)
:name "GTR1 distribution"
:precision binary32
:pre (and (and (<= 0.0 cosTheta) (<= cosTheta 1.0)) (and (<= 0.0001 alpha) (<= alpha 1.0)))
(/ (- (* alpha alpha) 1.0) (* (* PI (log (* alpha alpha))) (+ 1.0 (* (* (- (* alpha alpha) 1.0) cosTheta) cosTheta)))))