\frac{-\log \left(1 - u0\right)}{\frac{cos2phi}{alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}}
\left(alphay \cdot alphay\right) \cdot \left(\left(alphax \cdot alphax\right) \cdot \frac{-\mathsf{log1p}\left(-u0\right)}{\mathsf{fma}\left(sin2phi, alphax \cdot alphax, cos2phi \cdot \left(alphay \cdot alphay\right)\right)}\right)
(FPCore (alphax alphay u0 cos2phi sin2phi) :precision binary32 (/ (- (log (- 1.0 u0))) (+ (/ cos2phi (* alphax alphax)) (/ sin2phi (* alphay alphay)))))
(FPCore (alphax alphay u0 cos2phi sin2phi)
:precision binary32
(*
(* alphay alphay)
(*
(* alphax alphax)
(/
(- (log1p (- u0)))
(fma sin2phi (* alphax alphax) (* cos2phi (* alphay alphay)))))))float code(float alphax, float alphay, float u0, float cos2phi, float sin2phi) {
return -logf(1.0f - u0) / ((cos2phi / (alphax * alphax)) + (sin2phi / (alphay * alphay)));
}
float code(float alphax, float alphay, float u0, float cos2phi, float sin2phi) {
return (alphay * alphay) * ((alphax * alphax) * (-log1pf(-u0) / fmaf(sin2phi, (alphax * alphax), (cos2phi * (alphay * alphay)))));
}



Bits error versus alphax



Bits error versus alphay



Bits error versus u0



Bits error versus cos2phi



Bits error versus sin2phi
Initial program 12.4
Simplified0.6
Applied frac-add_binary320.7
Applied associate-/r/_binary320.5
Simplified0.5
Applied associate-*r*_binary320.5
Simplified0.5
Final simplification0.5
herbie shell --seed 2022020
(FPCore (alphax alphay u0 cos2phi sin2phi)
:name "Beckmann Distribution sample, tan2theta, alphax != alphay, u1 <= 0.5"
:precision binary32
:pre (and (and (and (and (and (<= 0.0001 alphax) (<= alphax 1.0)) (and (<= 0.0001 alphay) (<= alphay 1.0))) (and (<= 2.328306437e-10 u0) (<= u0 1.0))) (and (<= 0.0 cos2phi) (<= cos2phi 1.0))) (<= 0.0 sin2phi))
(/ (- (log (- 1.0 u0))) (+ (/ cos2phi (* alphax alphax)) (/ sin2phi (* alphay alphay)))))