?

Average Error: 1.47% → 1.36%
Time: 16.7s
Precision: binary32
Cost: 10272

?

\[\left(0 \leq cosTheta \land cosTheta \leq 1\right) \land \left(0.0001 \leq \alpha \land \alpha \leq 1\right)\]
\[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
↓
\[\begin{array}{l} t_0 := \alpha \cdot \alpha - 1\\ \frac{t_0}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right) \cdot \left(1 + cosTheta \cdot \left(t_0 \cdot cosTheta\right)\right)} \end{array} \]
(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
    (* (log (pow (* alpha alpha) PI)) (+ 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 / (logf(powf((alpha * alpha), ((float) M_PI))) * (1.0f + (cosTheta * (t_0 * cosTheta))));
}

function code(cosTheta, alpha)
	return Float32(Float32(Float32(alpha * alpha) - Float32(1.0)) / Float32(Float32(Float32(pi) * log(Float32(alpha * alpha))) * Float32(Float32(1.0) + Float32(Float32(Float32(Float32(alpha * alpha) - Float32(1.0)) * cosTheta) * cosTheta))))
end
↓
function code(cosTheta, alpha)
	t_0 = Float32(Float32(alpha * alpha) - Float32(1.0))
	return Float32(t_0 / Float32(log((Float32(alpha * alpha) ^ Float32(pi))) * Float32(Float32(1.0) + Float32(cosTheta * Float32(t_0 * cosTheta)))))
end

function tmp = code(cosTheta, alpha)
	tmp = ((alpha * alpha) - single(1.0)) / ((single(pi) * log((alpha * alpha))) * (single(1.0) + ((((alpha * alpha) - single(1.0)) * cosTheta) * cosTheta)));
end
↓
function tmp = code(cosTheta, alpha)
	t_0 = (alpha * alpha) - single(1.0);
	tmp = t_0 / (log(((alpha * alpha) ^ single(pi))) * (single(1.0) + (cosTheta * (t_0 * cosTheta))));
end

\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}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right) \cdot \left(1 + cosTheta \cdot \left(t_0 \cdot cosTheta\right)\right)}
\end{array}

Error?

Try it out?

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation?

  1. Initial program 1.47

    \[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]

  2. Applied egg-rr1.36

    \[\leadsto \frac{\alpha \cdot \alpha - 1}{\color{blue}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)} \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]

  3. Final simplification1.36

    \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right) \cdot \left(1 + cosTheta \cdot \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right)\right)} \]

Alternatives

Alternative 1
Error1.47%
Cost7168
\[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\alpha \cdot \left(\alpha \cdot \left(cosTheta \cdot cosTheta\right)\right) - cosTheta \cdot cosTheta\right)\right)} \]
Alternative 2
Error1.54%
Cost7136
\[\frac{\frac{\frac{\left(\alpha \cdot \alpha - 1\right) \cdot 0.5}{-\log \alpha}}{\pi}}{-1 + cosTheta \cdot \left(cosTheta - \left(\alpha \cdot \alpha\right) \cdot cosTheta\right)} \]
Alternative 3
Error1.47%
Cost7104
\[\begin{array}{l} t_0 := \alpha \cdot \alpha - 1\\ \frac{t_0}{\left(1 + cosTheta \cdot \left(t_0 \cdot cosTheta\right)\right) \cdot \left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right)} \end{array} \]
Alternative 4
Error2.64%
Cost6944
\[\frac{\frac{\frac{\left(\alpha \cdot \alpha - 1\right) \cdot 0.5}{-\log \alpha}}{\pi}}{-1 + cosTheta \cdot cosTheta} \]
Alternative 5
Error2.72%
Cost6912
\[\frac{\frac{1 - \alpha \cdot \alpha}{\pi \cdot -2}}{\log \alpha \cdot \left(1 - cosTheta \cdot cosTheta\right)} \]
Alternative 6
Error2.57%
Cost6912
\[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 - cosTheta \cdot cosTheta\right)} \]
Alternative 7
Error5.25%
Cost6784
\[0.5 \cdot \frac{\left(\alpha + 1\right) \cdot \left(\alpha - 1\right)}{\pi \cdot \log \alpha} \]
Alternative 8
Error33.15%
Cost6720
\[\frac{-0.5}{\pi \cdot \left(\log \alpha \cdot \left(1 - cosTheta \cdot cosTheta\right)\right)} \]
Alternative 9
Error33.15%
Cost6720
\[\frac{\frac{-0.5}{\log \alpha \cdot \left(1 - cosTheta \cdot cosTheta\right)}}{\pi} \]
Alternative 10
Error34.51%
Cost6592
\[\frac{0.5}{\pi \cdot \log \left(\frac{1}{\alpha}\right)} \]
Alternative 11
Error34.51%
Cost6592
\[\frac{\frac{0.5}{\log \left(\frac{1}{\alpha}\right)}}{\pi} \]
Alternative 12
Error34.51%
Cost6528
\[\frac{-0.5}{\pi \cdot \log \alpha} \]
Alternative 13
Error34.51%
Cost6528
\[\frac{\frac{-0.5}{\log \alpha}}{\pi} \]

Error

Reproduce?

herbie shell --seed 2023089 
(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)))))