GTR1 distribution

Percentage Accurate: 98.5% → 98.7%
Time: 16.9s
Alternatives: 5
Speedup: N/A×

Specification

?
\[\left(0 \leq cosTheta \land cosTheta \leq 1\right) \land \left(0.0001 \leq \alpha \land \alpha \leq 1\right)\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \alpha \cdot \alpha - 1\\ \frac{t\_0}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(t\_0 \cdot cosTheta\right) \cdot cosTheta\right)} \end{array} \end{array} \]
(FPCore (cosTheta alpha)
 :precision binary32
 (let* ((t_0 (- (* alpha alpha) 1.0)))
   (/
    t_0
    (* (* PI (log (* alpha alpha))) (+ 1.0 (* (* t_0 cosTheta) cosTheta))))))
float code(float cosTheta, float alpha) {
	float t_0 = (alpha * alpha) - 1.0f;
	return t_0 / ((((float) M_PI) * logf((alpha * alpha))) * (1.0f + ((t_0 * cosTheta) * cosTheta)));
}
function code(cosTheta, alpha)
	t_0 = Float32(Float32(alpha * alpha) - Float32(1.0))
	return Float32(t_0 / Float32(Float32(Float32(pi) * log(Float32(alpha * alpha))) * Float32(Float32(1.0) + Float32(Float32(t_0 * cosTheta) * cosTheta))))
end
function tmp = code(cosTheta, alpha)
	t_0 = (alpha * alpha) - single(1.0);
	tmp = t_0 / ((single(pi) * log((alpha * alpha))) * (single(1.0) + ((t_0 * cosTheta) * cosTheta)));
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \alpha \cdot \alpha - 1\\
\frac{t\_0}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(t\_0 \cdot cosTheta\right) \cdot cosTheta\right)}
\end{array}
\end{array}

Sampling outcomes in binary32 precision:

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 5 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 98.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \alpha \cdot \alpha - 1\\ \frac{t\_0}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(t\_0 \cdot cosTheta\right) \cdot cosTheta\right)} \end{array} \end{array} \]
(FPCore (cosTheta alpha)
 :precision binary32
 (let* ((t_0 (- (* alpha alpha) 1.0)))
   (/
    t_0
    (* (* PI (log (* alpha alpha))) (+ 1.0 (* (* t_0 cosTheta) cosTheta))))))
float code(float cosTheta, float alpha) {
	float t_0 = (alpha * alpha) - 1.0f;
	return t_0 / ((((float) M_PI) * logf((alpha * alpha))) * (1.0f + ((t_0 * cosTheta) * cosTheta)));
}
function code(cosTheta, alpha)
	t_0 = Float32(Float32(alpha * alpha) - Float32(1.0))
	return Float32(t_0 / Float32(Float32(Float32(pi) * log(Float32(alpha * alpha))) * Float32(Float32(1.0) + Float32(Float32(t_0 * cosTheta) * cosTheta))))
end
function tmp = code(cosTheta, alpha)
	t_0 = (alpha * alpha) - single(1.0);
	tmp = t_0 / ((single(pi) * log((alpha * alpha))) * (single(1.0) + ((t_0 * cosTheta) * cosTheta)));
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \alpha \cdot \alpha - 1\\
\frac{t\_0}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(t\_0 \cdot cosTheta\right) \cdot cosTheta\right)}
\end{array}
\end{array}

Alternative 1: 98.7% accurate, N/A× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \alpha \cdot \alpha - 1\\ t_1 := {\left(\alpha \cdot \alpha\right)}^{\pi}\\ \frac{t\_0}{\log \left({t\_1}^{\left(\left(cosTheta \cdot cosTheta\right) \cdot t\_0\right)} \cdot {t\_1}^{1}\right)} \end{array} \end{array} \]
(FPCore (cosTheta alpha)
 :precision binary32
 (let* ((t_0 (- (* alpha alpha) 1.0)) (t_1 (pow (* alpha alpha) PI)))
   (/ t_0 (log (* (pow t_1 (* (* cosTheta cosTheta) t_0)) (pow t_1 1.0))))))
float code(float cosTheta, float alpha) {
	float t_0 = (alpha * alpha) - 1.0f;
	float t_1 = powf((alpha * alpha), ((float) M_PI));
	return t_0 / logf((powf(t_1, ((cosTheta * cosTheta) * t_0)) * powf(t_1, 1.0f)));
}
function code(cosTheta, alpha)
	t_0 = Float32(Float32(alpha * alpha) - Float32(1.0))
	t_1 = Float32(alpha * alpha) ^ Float32(pi)
	return Float32(t_0 / log(Float32((t_1 ^ Float32(Float32(cosTheta * cosTheta) * t_0)) * (t_1 ^ Float32(1.0)))))
end
function tmp = code(cosTheta, alpha)
	t_0 = (alpha * alpha) - single(1.0);
	t_1 = (alpha * alpha) ^ single(pi);
	tmp = t_0 / log(((t_1 ^ ((cosTheta * cosTheta) * t_0)) * (t_1 ^ single(1.0))));
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \alpha \cdot \alpha - 1\\
t_1 := {\left(\alpha \cdot \alpha\right)}^{\pi}\\
\frac{t\_0}{\log \left({t\_1}^{\left(\left(cosTheta \cdot cosTheta\right) \cdot t\_0\right)} \cdot {t\_1}^{1}\right)}
\end{array}
\end{array}
Derivation
  1. Initial program 98.6%

    \[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\color{blue}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)}} \]
    2. lift-PI.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\color{blue}{\mathsf{PI}\left(\right)} \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right)} \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    4. lift-log.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \color{blue}{\log \left(\alpha \cdot \alpha\right)}\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    5. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \color{blue}{\left(\alpha \cdot \alpha\right)}\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    6. lift-+.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \color{blue}{\left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)}} \]
    7. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \color{blue}{\left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta}\right)} \]
    8. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \color{blue}{\left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right)} \cdot cosTheta\right)} \]
    9. lift--.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\color{blue}{\left(\alpha \cdot \alpha - 1\right)} \cdot cosTheta\right) \cdot cosTheta\right)} \]
    10. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\color{blue}{\alpha \cdot \alpha} - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    11. *-commutativeN/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\color{blue}{\left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right)}} \]
    12. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \log \color{blue}{\left(\alpha \cdot \alpha\right)}\right)} \]
    13. log-pow-revN/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right) \cdot \color{blue}{\log \left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}} \]
  4. Applied rewrites98.7%

    \[\leadsto \color{blue}{\frac{\alpha \cdot \alpha - 1}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)}} \]
  5. Step-by-step derivation
    1. lift-pow.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \color{blue}{\left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)}} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \left({\left({\color{blue}{\left(\alpha \cdot \alpha\right)}}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    3. lift-PI.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\color{blue}{\mathsf{PI}\left(\right)}}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    4. lift-pow.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \left({\color{blue}{\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    5. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}^{\left(\mathsf{fma}\left(\color{blue}{cosTheta \cdot cosTheta}, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    6. lift-fma.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}^{\color{blue}{\left(\left(cosTheta \cdot cosTheta\right) \cdot \left(\alpha \cdot \alpha - 1\right) + 1\right)}}\right)} \]
    7. lift--.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}^{\left(\left(cosTheta \cdot cosTheta\right) \cdot \color{blue}{\left(\alpha \cdot \alpha - 1\right)} + 1\right)}\right)} \]
    8. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}^{\left(\left(cosTheta \cdot cosTheta\right) \cdot \left(\color{blue}{\alpha \cdot \alpha} - 1\right) + 1\right)}\right)} \]
    9. unpow-prod-upN/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \color{blue}{\left({\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}^{\left(\left(cosTheta \cdot cosTheta\right) \cdot \left(\alpha \cdot \alpha - 1\right)\right)} \cdot {\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}^{1}\right)}} \]
    10. lower-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\log \color{blue}{\left({\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}^{\left(\left(cosTheta \cdot cosTheta\right) \cdot \left(\alpha \cdot \alpha - 1\right)\right)} \cdot {\left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}^{1}\right)}} \]
  6. Applied rewrites98.7%

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

Alternative 2: 98.3% accurate, N/A× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\\ t_1 := {t\_0}^{2}\\ \frac{\left(\alpha \cdot \alpha\right) \cdot t\_0}{t\_1} - \frac{t\_0}{t\_1} \end{array} \end{array} \]
(FPCore (cosTheta alpha)
 :precision binary32
 (let* ((t_0
         (*
          (fma (* cosTheta cosTheta) (- (* alpha alpha) 1.0) 1.0)
          (log (pow (* alpha alpha) PI))))
        (t_1 (pow t_0 2.0)))
   (- (/ (* (* alpha alpha) t_0) t_1) (/ t_0 t_1))))
float code(float cosTheta, float alpha) {
	float t_0 = fmaf((cosTheta * cosTheta), ((alpha * alpha) - 1.0f), 1.0f) * logf(powf((alpha * alpha), ((float) M_PI)));
	float t_1 = powf(t_0, 2.0f);
	return (((alpha * alpha) * t_0) / t_1) - (t_0 / t_1);
}
function code(cosTheta, alpha)
	t_0 = Float32(fma(Float32(cosTheta * cosTheta), Float32(Float32(alpha * alpha) - Float32(1.0)), Float32(1.0)) * log((Float32(alpha * alpha) ^ Float32(pi))))
	t_1 = t_0 ^ Float32(2.0)
	return Float32(Float32(Float32(Float32(alpha * alpha) * t_0) / t_1) - Float32(t_0 / t_1))
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\\
t_1 := {t\_0}^{2}\\
\frac{\left(\alpha \cdot \alpha\right) \cdot t\_0}{t\_1} - \frac{t\_0}{t\_1}
\end{array}
\end{array}
Derivation
  1. Initial program 98.6%

    \[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
  2. Add Preprocessing
  3. Applied rewrites98.6%

    \[\leadsto \color{blue}{\frac{\left(\alpha \cdot \alpha\right) \cdot \log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right) - \log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right) \cdot 1}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right) \cdot \log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)}} \]
  4. Applied rewrites98.4%

    \[\leadsto \color{blue}{\frac{\left(\alpha \cdot \alpha\right) \cdot \left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\right)}{{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\right)}^{2}} - \frac{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\right) \cdot 1}{{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\right)}^{2}}} \]
  5. Final simplification98.4%

    \[\leadsto \frac{\left(\alpha \cdot \alpha\right) \cdot \left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\right)}{{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\right)}^{2}} - \frac{\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}{{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right) \cdot \log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)\right)}^{2}} \]
  6. Add Preprocessing

Alternative 3: 98.2% accurate, N/A× speedup?

\[\begin{array}{l} \\ \frac{\alpha + 1}{\log \left({\left({\alpha}^{\pi}\right)}^{2}\right)} \cdot \frac{\alpha - 1}{\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)} \end{array} \]
(FPCore (cosTheta alpha)
 :precision binary32
 (*
  (/ (+ alpha 1.0) (log (pow (pow alpha PI) 2.0)))
  (/ (- alpha 1.0) (fma (* cosTheta cosTheta) (- (* alpha alpha) 1.0) 1.0))))
float code(float cosTheta, float alpha) {
	return ((alpha + 1.0f) / logf(powf(powf(alpha, ((float) M_PI)), 2.0f))) * ((alpha - 1.0f) / fmaf((cosTheta * cosTheta), ((alpha * alpha) - 1.0f), 1.0f));
}
function code(cosTheta, alpha)
	return Float32(Float32(Float32(alpha + Float32(1.0)) / log(((alpha ^ Float32(pi)) ^ Float32(2.0)))) * Float32(Float32(alpha - Float32(1.0)) / fma(Float32(cosTheta * cosTheta), Float32(Float32(alpha * alpha) - Float32(1.0)), Float32(1.0))))
end
\begin{array}{l}

\\
\frac{\alpha + 1}{\log \left({\left({\alpha}^{\pi}\right)}^{2}\right)} \cdot \frac{\alpha - 1}{\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)}
\end{array}
Derivation
  1. Initial program 98.6%

    \[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
  2. Add Preprocessing
  3. Applied rewrites98.3%

    \[\leadsto \color{blue}{\frac{\alpha + 1}{\log \left({\left({\alpha}^{\pi}\right)}^{2}\right)} \cdot \frac{\alpha - 1}{\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)}} \]
  4. Add Preprocessing

Alternative 4: 98.3% accurate, N/A× speedup?

\[\begin{array}{l} \\ \frac{{\alpha}^{4} - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right) \cdot \left(\left(1 + \alpha \cdot \alpha\right) \cdot \left(\left(1 + {\left(\alpha \cdot cosTheta\right)}^{2}\right) - cosTheta \cdot cosTheta\right)\right)} \end{array} \]
(FPCore (cosTheta alpha)
 :precision binary32
 (/
  (- (pow alpha 4.0) 1.0)
  (*
   (log (pow (* alpha alpha) PI))
   (*
    (+ 1.0 (* alpha alpha))
    (- (+ 1.0 (pow (* alpha cosTheta) 2.0)) (* cosTheta cosTheta))))))
float code(float cosTheta, float alpha) {
	return (powf(alpha, 4.0f) - 1.0f) / (logf(powf((alpha * alpha), ((float) M_PI))) * ((1.0f + (alpha * alpha)) * ((1.0f + powf((alpha * cosTheta), 2.0f)) - (cosTheta * cosTheta))));
}
function code(cosTheta, alpha)
	return Float32(Float32((alpha ^ Float32(4.0)) - Float32(1.0)) / Float32(log((Float32(alpha * alpha) ^ Float32(pi))) * Float32(Float32(Float32(1.0) + Float32(alpha * alpha)) * Float32(Float32(Float32(1.0) + (Float32(alpha * cosTheta) ^ Float32(2.0))) - Float32(cosTheta * cosTheta)))))
end
function tmp = code(cosTheta, alpha)
	tmp = ((alpha ^ single(4.0)) - single(1.0)) / (log(((alpha * alpha) ^ single(pi))) * ((single(1.0) + (alpha * alpha)) * ((single(1.0) + ((alpha * cosTheta) ^ single(2.0))) - (cosTheta * cosTheta))));
end
\begin{array}{l}

\\
\frac{{\alpha}^{4} - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right) \cdot \left(\left(1 + \alpha \cdot \alpha\right) \cdot \left(\left(1 + {\left(\alpha \cdot cosTheta\right)}^{2}\right) - cosTheta \cdot cosTheta\right)\right)}
\end{array}
Derivation
  1. Initial program 98.6%

    \[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
  2. Add Preprocessing
  3. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\color{blue}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)}} \]
    2. lift-PI.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\color{blue}{\mathsf{PI}\left(\right)} \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right)} \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    4. lift-log.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \color{blue}{\log \left(\alpha \cdot \alpha\right)}\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    5. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \color{blue}{\left(\alpha \cdot \alpha\right)}\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    6. lift-+.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \color{blue}{\left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)}} \]
    7. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \color{blue}{\left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta}\right)} \]
    8. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \color{blue}{\left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right)} \cdot cosTheta\right)} \]
    9. lift--.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\color{blue}{\left(\alpha \cdot \alpha - 1\right)} \cdot cosTheta\right) \cdot cosTheta\right)} \]
    10. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\color{blue}{\alpha \cdot \alpha} - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
    11. *-commutativeN/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\color{blue}{\left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \log \left(\alpha \cdot \alpha\right)\right)}} \]
    12. lift-*.f32N/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \log \color{blue}{\left(\alpha \cdot \alpha\right)}\right)} \]
    13. log-pow-revN/A

      \[\leadsto \frac{\alpha \cdot \alpha - 1}{\left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right) \cdot \color{blue}{\log \left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right)}} \]
  4. Applied rewrites98.7%

    \[\leadsto \color{blue}{\frac{\alpha \cdot \alpha - 1}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)}} \]
  5. Taylor expanded in alpha around inf

    \[\leadsto \frac{\color{blue}{{\alpha}^{2} \cdot \left(1 - \frac{1}{{\alpha}^{2}}\right)}}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
  6. Step-by-step derivation
    1. pow2N/A

      \[\leadsto \frac{{\color{blue}{\alpha}}^{2} \cdot \left(1 - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    2. flip--N/A

      \[\leadsto \frac{\color{blue}{{\alpha}^{2}} \cdot \left(1 - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    3. metadata-evalN/A

      \[\leadsto \frac{{\alpha}^{2} \cdot \left(1 - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    4. metadata-evalN/A

      \[\leadsto \frac{{\alpha}^{2} \cdot \left(1 - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    5. sqr-powN/A

      \[\leadsto \frac{{\alpha}^{2} \cdot \left(1 - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    6. metadata-evalN/A

      \[\leadsto \frac{{\alpha}^{2} \cdot \left(1 - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    7. pow2N/A

      \[\leadsto \frac{{\alpha}^{2} \cdot \left(1 - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    8. lower-*.f32N/A

      \[\leadsto \frac{{\alpha}^{2} \cdot \color{blue}{\left(1 - \frac{1}{{\alpha}^{2}}\right)}}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    9. pow2N/A

      \[\leadsto \frac{\left(\alpha \cdot \alpha\right) \cdot \left(\color{blue}{1} - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    10. lift-*.f32N/A

      \[\leadsto \frac{\left(\alpha \cdot \alpha\right) \cdot \left(\color{blue}{1} - \frac{1}{{\alpha}^{2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    11. lower--.f32N/A

      \[\leadsto \frac{\left(\alpha \cdot \alpha\right) \cdot \left(1 - \color{blue}{\frac{1}{{\alpha}^{2}}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    12. pow-flipN/A

      \[\leadsto \frac{\left(\alpha \cdot \alpha\right) \cdot \left(1 - {\alpha}^{\color{blue}{\left(\mathsf{neg}\left(2\right)\right)}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    13. metadata-evalN/A

      \[\leadsto \frac{\left(\alpha \cdot \alpha\right) \cdot \left(1 - {\alpha}^{-2}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
    14. lower-pow.f3298.3

      \[\leadsto \frac{\left(\alpha \cdot \alpha\right) \cdot \left(1 - {\alpha}^{\color{blue}{-2}}\right)}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
  7. Applied rewrites98.3%

    \[\leadsto \frac{\color{blue}{\left(\alpha \cdot \alpha\right) \cdot \left(1 - {\alpha}^{-2}\right)}}{\log \left({\left({\left(\alpha \cdot \alpha\right)}^{\pi}\right)}^{\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, \alpha \cdot \alpha - 1, 1\right)\right)}\right)} \]
  8. Taylor expanded in cosTheta around inf

    \[\leadsto \color{blue}{\frac{{\alpha}^{4} - 1}{\log \left({\left({\alpha}^{2}\right)}^{\mathsf{PI}\left(\right)}\right) \cdot \left(\left(1 + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)}} \]
  9. Step-by-step derivation
    1. lower-/.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\color{blue}{\log \left({\left({\alpha}^{2}\right)}^{\mathsf{PI}\left(\right)}\right) \cdot \left(\left(1 + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)}} \]
    2. lift-pow.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\log \color{blue}{\left({\left({\alpha}^{2}\right)}^{\mathsf{PI}\left(\right)}\right)} \cdot \left(\left(1 + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)} \]
    3. lift--.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\color{blue}{\log \left({\left({\alpha}^{2}\right)}^{\mathsf{PI}\left(\right)}\right)} \cdot \left(\left(1 + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)} \]
    4. lower-*.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\log \left({\left({\alpha}^{2}\right)}^{\mathsf{PI}\left(\right)}\right) \cdot \color{blue}{\left(\left(1 + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)}} \]
    5. lower-log.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\log \left({\left({\alpha}^{2}\right)}^{\mathsf{PI}\left(\right)}\right) \cdot \left(\color{blue}{\left(1 + {\alpha}^{2}\right)} \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)} \]
    6. pow2N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right) \cdot \left(\left(1 + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)} \]
    7. lift-*.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right) \cdot \left(\left(1 + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)} \]
    8. lift-pow.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\mathsf{PI}\left(\right)}\right) \cdot \left(\left(\color{blue}{1} + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)} \]
    9. lift-PI.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right) \cdot \left(\left(1 + {\alpha}^{2}\right) \cdot \left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)\right)} \]
    10. lower-*.f32N/A

      \[\leadsto \frac{{\alpha}^{4} - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right) \cdot \left(\left(1 + {\alpha}^{2}\right) \cdot \color{blue}{\left(\left(1 + {\alpha}^{2} \cdot {cosTheta}^{2}\right) - {cosTheta}^{2}\right)}\right)} \]
  10. Applied rewrites98.3%

    \[\leadsto \color{blue}{\frac{{\alpha}^{4} - 1}{\log \left({\left(\alpha \cdot \alpha\right)}^{\pi}\right) \cdot \left(\left(1 + \alpha \cdot \alpha\right) \cdot \left(\left(1 + {\left(\alpha \cdot cosTheta\right)}^{2}\right) - cosTheta \cdot cosTheta\right)\right)}} \]
  11. Add Preprocessing

Alternative 5: 98.1% accurate, N/A× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \log \alpha \cdot \pi\\ t_1 := \mathsf{fma}\left(cosTheta \cdot cosTheta, -1, 1\right)\\ t_2 := \frac{0.5}{t\_0 \cdot t\_1}\\ t_3 := t\_2 - \frac{-0.5 \cdot \left(cosTheta \cdot cosTheta\right)}{t\_0 \cdot {t\_1}^{2}}\\ \mathsf{fma}\left(\frac{{\left(cosTheta \cdot \alpha\right)}^{2} \cdot t\_3}{t\_1}, -1, t\_3\right) \cdot \left(\alpha \cdot \alpha\right) - t\_2 \end{array} \end{array} \]
(FPCore (cosTheta alpha)
 :precision binary32
 (let* ((t_0 (* (log alpha) PI))
        (t_1 (fma (* cosTheta cosTheta) -1.0 1.0))
        (t_2 (/ 0.5 (* t_0 t_1)))
        (t_3 (- t_2 (/ (* -0.5 (* cosTheta cosTheta)) (* t_0 (pow t_1 2.0))))))
   (-
    (*
     (fma (/ (* (pow (* cosTheta alpha) 2.0) t_3) t_1) -1.0 t_3)
     (* alpha alpha))
    t_2)))
float code(float cosTheta, float alpha) {
	float t_0 = logf(alpha) * ((float) M_PI);
	float t_1 = fmaf((cosTheta * cosTheta), -1.0f, 1.0f);
	float t_2 = 0.5f / (t_0 * t_1);
	float t_3 = t_2 - ((-0.5f * (cosTheta * cosTheta)) / (t_0 * powf(t_1, 2.0f)));
	return (fmaf(((powf((cosTheta * alpha), 2.0f) * t_3) / t_1), -1.0f, t_3) * (alpha * alpha)) - t_2;
}
function code(cosTheta, alpha)
	t_0 = Float32(log(alpha) * Float32(pi))
	t_1 = fma(Float32(cosTheta * cosTheta), Float32(-1.0), Float32(1.0))
	t_2 = Float32(Float32(0.5) / Float32(t_0 * t_1))
	t_3 = Float32(t_2 - Float32(Float32(Float32(-0.5) * Float32(cosTheta * cosTheta)) / Float32(t_0 * (t_1 ^ Float32(2.0)))))
	return Float32(Float32(fma(Float32(Float32((Float32(cosTheta * alpha) ^ Float32(2.0)) * t_3) / t_1), Float32(-1.0), t_3) * Float32(alpha * alpha)) - t_2)
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \log \alpha \cdot \pi\\
t_1 := \mathsf{fma}\left(cosTheta \cdot cosTheta, -1, 1\right)\\
t_2 := \frac{0.5}{t\_0 \cdot t\_1}\\
t_3 := t\_2 - \frac{-0.5 \cdot \left(cosTheta \cdot cosTheta\right)}{t\_0 \cdot {t\_1}^{2}}\\
\mathsf{fma}\left(\frac{{\left(cosTheta \cdot \alpha\right)}^{2} \cdot t\_3}{t\_1}, -1, t\_3\right) \cdot \left(\alpha \cdot \alpha\right) - t\_2
\end{array}
\end{array}
Derivation
  1. Initial program 98.6%

    \[\frac{\alpha \cdot \alpha - 1}{\left(\pi \cdot \log \left(\alpha \cdot \alpha\right)\right) \cdot \left(1 + \left(\left(\alpha \cdot \alpha - 1\right) \cdot cosTheta\right) \cdot cosTheta\right)} \]
  2. Add Preprocessing
  3. Taylor expanded in alpha around 0

    \[\leadsto \color{blue}{{\alpha}^{2} \cdot \left(\left(-1 \cdot \frac{{\alpha}^{2} \cdot \left({cosTheta}^{2} \cdot \left(\frac{1}{2} \cdot \frac{1}{\mathsf{PI}\left(\right) \cdot \left(\log \alpha \cdot \left(1 + -1 \cdot {cosTheta}^{2}\right)\right)} - \frac{-1}{2} \cdot \frac{{cosTheta}^{2}}{\mathsf{PI}\left(\right) \cdot \left(\log \alpha \cdot {\left(1 + -1 \cdot {cosTheta}^{2}\right)}^{2}\right)}\right)\right)}{1 + -1 \cdot {cosTheta}^{2}} + \frac{1}{2} \cdot \frac{1}{\mathsf{PI}\left(\right) \cdot \left(\log \alpha \cdot \left(1 + -1 \cdot {cosTheta}^{2}\right)\right)}\right) - \frac{-1}{2} \cdot \frac{{cosTheta}^{2}}{\mathsf{PI}\left(\right) \cdot \left(\log \alpha \cdot {\left(1 + -1 \cdot {cosTheta}^{2}\right)}^{2}\right)}\right) - \frac{1}{2} \cdot \frac{1}{\mathsf{PI}\left(\right) \cdot \left(\log \alpha \cdot \left(1 + -1 \cdot {cosTheta}^{2}\right)\right)}} \]
  4. Applied rewrites97.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{{\left(cosTheta \cdot \alpha\right)}^{2} \cdot \left(\frac{0.5}{\left(\log \alpha \cdot \pi\right) \cdot \mathsf{fma}\left(cosTheta \cdot cosTheta, -1, 1\right)} - \frac{-0.5 \cdot \left(cosTheta \cdot cosTheta\right)}{\left(\log \alpha \cdot \pi\right) \cdot {\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, -1, 1\right)\right)}^{2}}\right)}{\mathsf{fma}\left(cosTheta \cdot cosTheta, -1, 1\right)}, -1, \frac{0.5}{\left(\log \alpha \cdot \pi\right) \cdot \mathsf{fma}\left(cosTheta \cdot cosTheta, -1, 1\right)} - \frac{-0.5 \cdot \left(cosTheta \cdot cosTheta\right)}{\left(\log \alpha \cdot \pi\right) \cdot {\left(\mathsf{fma}\left(cosTheta \cdot cosTheta, -1, 1\right)\right)}^{2}}\right) \cdot \left(\alpha \cdot \alpha\right) - \frac{0.5}{\left(\log \alpha \cdot \pi\right) \cdot \mathsf{fma}\left(cosTheta \cdot cosTheta, -1, 1\right)}} \]
  5. Add Preprocessing

Reproduce

?
herbie shell --seed 2025057 
(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)))))