Beckmann Distribution sample, tan2theta, alphax != alphay, u1 <= 0.5

Average Accuracy: 60.5% → 98.4%

Time: 20.3s

Precision: binary32

Cost: 3744

\[\left(\left(\left(\left(0.0001 \leq alphax \land alphax \leq 1\right) \land \left(0.0001 \leq alphay \land alphay \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u0 \land u0 \leq 1\right)\right) \land \left(0 \leq cos2phi \land cos2phi \leq 1\right)\right) \land 0 \leq sin2phi\]

Math

\[\frac{-\log \left(1 - u0\right)}{\frac{cos2phi}{alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}} \]

↓

\[\frac{-\mathsf{log1p}\left(-u0\right)}{\frac{1}{alphax \cdot alphax} \cdot cos2phi + \frac{sin2phi}{alphay \cdot alphay}} \]

FPCore

(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
 (/
  (- (log1p (- u0)))
  (+ (* (/ 1.0 (* alphax alphax)) cos2phi) (/ sin2phi (* alphay alphay)))))

C

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 -log1pf(-u0) / (((1.0f / (alphax * alphax)) * cos2phi) + (sin2phi / (alphay * alphay)));
}

Julia

function code(alphax, alphay, u0, cos2phi, sin2phi)
	return Float32(Float32(-log(Float32(Float32(1.0) - u0))) / Float32(Float32(cos2phi / Float32(alphax * alphax)) + Float32(sin2phi / Float32(alphay * alphay))))
end

↓

function code(alphax, alphay, u0, cos2phi, sin2phi)
	return Float32(Float32(-log1p(Float32(-u0))) / Float32(Float32(Float32(Float32(1.0) / Float32(alphax * alphax)) * cos2phi) + Float32(sin2phi / Float32(alphay * alphay))))
end

Derivation

1. Initial program 60.5%

   \[\frac{-\log \left(1 - u0\right)}{\frac{cos2phi}{alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}} \]

2. Simplified 98.5%

   \[\leadsto \color{blue}{\frac{-\mathsf{log1p}\left(-u0\right)}{\frac{cos2phi}{alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}}} \]
   Proof

   [Start] 60.5	\[ \frac{-\log \left(1 - u0\right)}{\frac{cos2phi}{alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}} \]
   sub-neg [=>] 60.5	\[ \frac{-\log \color{blue}{\left(1 + \left(-u0\right)\right)}}{\frac{cos2phi}{alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}} \]
   log1p-def [=>] 98.5	\[ \frac{-\color{blue}{\mathsf{log1p}\left(-u0\right)}}{\frac{cos2phi}{alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}} \]

3. Applied egg-rr 98.4%

   \[\leadsto \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{1}{alphax \cdot \left(-alphax\right)} \cdot \left(-cos2phi\right)} + \frac{sin2phi}{alphay \cdot alphay}} \]
   Proof

   [Start] 98.5	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{cos2phi}{alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}} \]
   frac-2neg [=>] 98.5	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{-cos2phi}{-alphax \cdot alphax}} + \frac{sin2phi}{alphay \cdot alphay}} \]
   clear-num [=>] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{1}{\frac{-alphax \cdot alphax}{-cos2phi}}} + \frac{sin2phi}{alphay \cdot alphay}} \]
   associate-/r/ [=>] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{1}{-alphax \cdot alphax} \cdot \left(-cos2phi\right)} + \frac{sin2phi}{alphay \cdot alphay}} \]
   distribute-rgt-neg-in [=>] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{1}{\color{blue}{alphax \cdot \left(-alphax\right)}} \cdot \left(-cos2phi\right) + \frac{sin2phi}{alphay \cdot alphay}} \]

4. Taylor expanded in alphax around 0 98.4%

   \[\leadsto \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{-1}{{alphax}^{2}}} \cdot \left(-cos2phi\right) + \frac{sin2phi}{alphay \cdot alphay}} \]

5. Simplified 98.4%

   \[\leadsto \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{-1}{alphax \cdot alphax}} \cdot \left(-cos2phi\right) + \frac{sin2phi}{alphay \cdot alphay}} \]
   Proof

   [Start] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{-1}{{alphax}^{2}} \cdot \left(-cos2phi\right) + \frac{sin2phi}{alphay \cdot alphay}} \]
   unpow2 [=>] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{-1}{\color{blue}{alphax \cdot alphax}} \cdot \left(-cos2phi\right) + \frac{sin2phi}{alphay \cdot alphay}} \]

6. Applied egg-rr 98.4%

   \[\leadsto \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{1}{\frac{alphax \cdot alphax}{cos2phi}}} + \frac{sin2phi}{alphay \cdot alphay}} \]
   Proof

   [Start] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{-1}{alphax \cdot alphax} \cdot \left(-cos2phi\right) + \frac{sin2phi}{alphay \cdot alphay}} \]
   frac-2neg [=>] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{--1}{-alphax \cdot alphax}} \cdot \left(-cos2phi\right) + \frac{sin2phi}{alphay \cdot alphay}} \]
   metadata-eval [=>] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{\color{blue}{1}}{-alphax \cdot alphax} \cdot \left(-cos2phi\right) + \frac{sin2phi}{alphay \cdot alphay}} \]
   associate-*l/ [=>] 98.5	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{1 \cdot \left(-cos2phi\right)}{-alphax \cdot alphax}} + \frac{sin2phi}{alphay \cdot alphay}} \]
   *-un-lft-identity [<=] 98.5	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{\color{blue}{-cos2phi}}{-alphax \cdot alphax} + \frac{sin2phi}{alphay \cdot alphay}} \]
   frac-2neg [<=] 98.5	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{cos2phi}{alphax \cdot alphax}} + \frac{sin2phi}{alphay \cdot alphay}} \]
   clear-num [=>] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{1}{\frac{alphax \cdot alphax}{cos2phi}}} + \frac{sin2phi}{alphay \cdot alphay}} \]

7. Simplified 98.4%

   \[\leadsto \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{1}{alphax \cdot alphax} \cdot cos2phi} + \frac{sin2phi}{alphay \cdot alphay}} \]
   Proof

   [Start] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{1}{\frac{alphax \cdot alphax}{cos2phi}} + \frac{sin2phi}{alphay \cdot alphay}} \]
   associate-/r/ [=>] 98.4	\[ \frac{-\mathsf{log1p}\left(-u0\right)}{\color{blue}{\frac{1}{alphax \cdot alphax} \cdot cos2phi} + \frac{sin2phi}{alphay \cdot alphay}} \]

8. Final simplification 98.4%

   \[\leadsto \frac{-\mathsf{log1p}\left(-u0\right)}{\frac{1}{alphax \cdot alphax} \cdot cos2phi + \frac{sin2phi}{alphay \cdot alphay}} \]

Alternatives

Alternative 1
Accuracy	92.9%
Cost	3716

\[\begin{array}{l} t_0 := \frac{sin2phi}{alphay \cdot alphay}\\ \mathbf{if}\;t_0 \leq 0.30000001192092896:\\ \;\;\;\;\frac{u0 + \left(u0 \cdot u0\right) \cdot 0.5}{t_0 + \frac{cos2phi}{alphax \cdot alphax}}\\ \mathbf{else}:\\ \;\;\;\;\left(\mathsf{log1p}\left(-u0\right) \cdot \left(alphay \cdot alphay\right)\right) \cdot \frac{-1}{sin2phi}\\ \end{array} \]

Alternative 2
Accuracy	92.9%
Cost	3684

\[\begin{array}{l} t_0 := \frac{sin2phi}{alphay \cdot alphay}\\ \mathbf{if}\;t_0 \leq 0.30000001192092896:\\ \;\;\;\;\frac{u0 + \left(u0 \cdot u0\right) \cdot 0.5}{t_0 + \frac{cos2phi}{alphax \cdot alphax}}\\ \mathbf{else}:\\ \;\;\;\;alphay \cdot \left(alphay \cdot \frac{-\mathsf{log1p}\left(-u0\right)}{sin2phi}\right)\\ \end{array} \]

Alternative 3
Accuracy	92.9%
Cost	3684

\[\begin{array}{l} t_0 := \frac{sin2phi}{alphay \cdot alphay}\\ \mathbf{if}\;t_0 \leq 0.30000001192092896:\\ \;\;\;\;\frac{u0 + \left(u0 \cdot u0\right) \cdot 0.5}{t_0 + \frac{cos2phi}{alphax \cdot alphax}}\\ \mathbf{else}:\\ \;\;\;\;\frac{alphay \cdot \left(\mathsf{log1p}\left(-u0\right) \cdot \left(-alphay\right)\right)}{sin2phi}\\ \end{array} \]

Alternative 4
Accuracy	98.5%
Cost	3680

\[\frac{-\mathsf{log1p}\left(-u0\right)}{\frac{sin2phi}{alphay \cdot alphay} + \frac{cos2phi}{alphax \cdot alphax}} \]

Alternative 5
Accuracy	98.4%
Cost	3680

\[\frac{-\mathsf{log1p}\left(-u0\right)}{\frac{sin2phi}{alphay \cdot alphay} + \frac{\frac{cos2phi}{alphax}}{alphax}} \]

Alternative 6
Accuracy	83.5%
Cost	612

\[\begin{array}{l} \mathbf{if}\;sin2phi \leq 9.999999747378752 \cdot 10^{-6}:\\ \;\;\;\;\frac{u0}{\frac{sin2phi}{alphay \cdot alphay} + \frac{\frac{cos2phi}{alphax}}{alphax}}\\ \mathbf{else}:\\ \;\;\;\;\frac{\left(alphay \cdot alphay\right) \cdot \left(u0 + \left(u0 \cdot u0\right) \cdot \left(0.5 + u0 \cdot 0.3333333333333333\right)\right)}{sin2phi}\\ \end{array} \]

Alternative 7
Accuracy	87.5%
Cost	608

\[\frac{u0 + \left(u0 \cdot u0\right) \cdot 0.5}{\frac{sin2phi}{alphay \cdot alphay} + \frac{cos2phi}{alphax \cdot alphax}} \]

Alternative 8
Accuracy	81.5%
Cost	484

\[\begin{array}{l} \mathbf{if}\;sin2phi \leq 9.999999747378752 \cdot 10^{-6}:\\ \;\;\;\;\frac{u0}{\frac{sin2phi}{alphay \cdot alphay} + \frac{\frac{cos2phi}{alphax}}{alphax}}\\ \mathbf{else}:\\ \;\;\;\;alphay \cdot \left(alphay \cdot \frac{u0 + \left(u0 \cdot u0\right) \cdot 0.5}{sin2phi}\right)\\ \end{array} \]

Alternative 9
Accuracy	81.5%
Cost	484

\[\begin{array}{l} \mathbf{if}\;sin2phi \leq 9.999999747378752 \cdot 10^{-6}:\\ \;\;\;\;\frac{u0}{\frac{sin2phi}{alphay \cdot alphay} + \frac{\frac{cos2phi}{alphax}}{alphax}}\\ \mathbf{else}:\\ \;\;\;\;\frac{\left(alphay \cdot alphay\right) \cdot \left(u0 + \left(u0 \cdot u0\right) \cdot 0.5\right)}{sin2phi}\\ \end{array} \]

Alternative 10
Accuracy	65.8%
Cost	420

\[\begin{array}{l} \mathbf{if}\;\frac{sin2phi}{alphay \cdot alphay} \leq 1.9999999996399175 \cdot 10^{-23}:\\ \;\;\;\;\frac{u0}{\frac{cos2phi}{alphax \cdot alphax}}\\ \mathbf{else}:\\ \;\;\;\;u0 \cdot \frac{alphay \cdot alphay}{sin2phi}\\ \end{array} \]

Alternative 11
Accuracy	65.8%
Cost	420

\[\begin{array}{l} \mathbf{if}\;\frac{sin2phi}{alphay \cdot alphay} \leq 1.9999999996399175 \cdot 10^{-23}:\\ \;\;\;\;\frac{u0 \cdot alphax}{\frac{cos2phi}{alphax}}\\ \mathbf{else}:\\ \;\;\;\;u0 \cdot \frac{alphay \cdot alphay}{sin2phi}\\ \end{array} \]

Alternative 12
Accuracy	75.9%
Cost	416

\[\frac{u0}{\frac{sin2phi}{alphay \cdot alphay} + \frac{cos2phi}{alphax \cdot alphax}} \]

Alternative 13
Accuracy	75.9%
Cost	416

\[\frac{u0}{\frac{sin2phi}{alphay \cdot alphay} + \frac{\frac{cos2phi}{alphax}}{alphax}} \]

Alternative 14
Accuracy	67.1%
Cost	292

\[\begin{array}{l} \mathbf{if}\;sin2phi \leq 3.99999987306209 \cdot 10^{-20}:\\ \;\;\;\;u0 \cdot \left(alphax \cdot \frac{alphax}{cos2phi}\right)\\ \mathbf{else}:\\ \;\;\;\;\left(alphay \cdot alphay\right) \cdot \frac{u0}{sin2phi}\\ \end{array} \]

Alternative 15
Accuracy	67.1%
Cost	292

\[\begin{array}{l} \mathbf{if}\;sin2phi \leq 3.99999987306209 \cdot 10^{-20}:\\ \;\;\;\;u0 \cdot \left(alphax \cdot \frac{alphax}{cos2phi}\right)\\ \mathbf{else}:\\ \;\;\;\;u0 \cdot \frac{alphay \cdot alphay}{sin2phi}\\ \end{array} \]

Alternative 16
Accuracy	67.1%
Cost	292

\[\begin{array}{l} \mathbf{if}\;sin2phi \leq 3.99999987306209 \cdot 10^{-20}:\\ \;\;\;\;\frac{alphax}{\frac{\frac{cos2phi}{u0}}{alphax}}\\ \mathbf{else}:\\ \;\;\;\;u0 \cdot \frac{alphay \cdot alphay}{sin2phi}\\ \end{array} \]

Alternative 17
Accuracy	23.6%
Cost	224

\[alphax \cdot \left(u0 \cdot \frac{alphax}{cos2phi}\right) \]

Alternative 18
Accuracy	23.6%
Cost	224

\[\frac{alphax}{cos2phi} \cdot \left(u0 \cdot alphax\right) \]

Alternative 19
Accuracy	23.6%
Cost	224

\[u0 \cdot \left(alphax \cdot \frac{alphax}{cos2phi}\right) \]

Reproduce

herbie shell --seed 2023137 
(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)))))