Sample trimmed logistic on [-pi, pi]

Percentage Accurate: 98.9% → 98.9%
Time: 13.7s
Alternatives: 13
Speedup: 1.0×

Specification

?
\[\left(2.328306437 \cdot 10^{-10} \leq u \land u \leq 1\right) \land \left(0 \leq s \land s \leq 1.0651631\right)\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{1 + e^{\frac{\pi}{s}}}\\ \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - t\_0\right) + t\_0} - 1\right) \end{array} \end{array} \]
(FPCore (u s)
 :precision binary32
 (let* ((t_0 (/ 1.0 (+ 1.0 (exp (/ PI s))))))
   (*
    (- s)
    (log
     (-
      (/ 1.0 (+ (* u (- (/ 1.0 (+ 1.0 (exp (/ (- PI) s)))) t_0)) t_0))
      1.0)))))
float code(float u, float s) {
	float t_0 = 1.0f / (1.0f + expf((((float) M_PI) / s)));
	return -s * logf(((1.0f / ((u * ((1.0f / (1.0f + expf((-((float) M_PI) / s)))) - t_0)) + t_0)) - 1.0f));
}
function code(u, s)
	t_0 = Float32(Float32(1.0) / Float32(Float32(1.0) + exp(Float32(Float32(pi) / s))))
	return Float32(Float32(-s) * log(Float32(Float32(Float32(1.0) / Float32(Float32(u * Float32(Float32(Float32(1.0) / Float32(Float32(1.0) + exp(Float32(Float32(-Float32(pi)) / s)))) - t_0)) + t_0)) - Float32(1.0))))
end
function tmp = code(u, s)
	t_0 = single(1.0) / (single(1.0) + exp((single(pi) / s)));
	tmp = -s * log(((single(1.0) / ((u * ((single(1.0) / (single(1.0) + exp((-single(pi) / s)))) - t_0)) + t_0)) - single(1.0)));
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \frac{1}{1 + e^{\frac{\pi}{s}}}\\
\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - t\_0\right) + t\_0} - 1\right)
\end{array}
\end{array}

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 13 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: 98.9% accurate, 1.0× speedup?

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

\\
\begin{array}{l}
t_0 := \frac{1}{1 + e^{\frac{\pi}{s}}}\\
\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - t\_0\right) + t\_0} - 1\right)
\end{array}
\end{array}

Alternative 1: 98.9% accurate, 1.0× speedup?

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

\\
\begin{array}{l}
t_0 := \frac{1}{1 + e^{\frac{\pi}{s}}}\\
\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - t\_0\right) + t\_0} - 1\right)
\end{array}
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  2. Add Preprocessing

Alternative 2: 97.5% accurate, 1.3× speedup?

\[\begin{array}{l} \\ \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right)} - 1\right) \cdot \left(-s\right) \end{array} \]
(FPCore (u s)
 :precision binary32
 (*
  (log
   (-
    (/
     1.0
     (*
      u
      (-
       (/ 1.0 (+ 1.0 (exp (* -1.0 (/ PI s)))))
       (/ 1.0 (+ 1.0 (exp (/ PI s)))))))
    1.0))
  (- s)))
float code(float u, float s) {
	return logf(((1.0f / (u * ((1.0f / (1.0f + expf((-1.0f * (((float) M_PI) / s))))) - (1.0f / (1.0f + expf((((float) M_PI) / s))))))) - 1.0f)) * -s;
}
function code(u, s)
	return Float32(log(Float32(Float32(Float32(1.0) / Float32(u * Float32(Float32(Float32(1.0) / Float32(Float32(1.0) + exp(Float32(Float32(-1.0) * Float32(Float32(pi) / s))))) - Float32(Float32(1.0) / Float32(Float32(1.0) + exp(Float32(Float32(pi) / s))))))) - Float32(1.0))) * Float32(-s))
end
function tmp = code(u, s)
	tmp = log(((single(1.0) / (u * ((single(1.0) / (single(1.0) + exp((single(-1.0) * (single(pi) / s))))) - (single(1.0) / (single(1.0) + exp((single(pi) / s))))))) - single(1.0))) * -s;
end
\begin{array}{l}

\\
\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right)} - 1\right) \cdot \left(-s\right)
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  2. Taylor expanded in s around inf

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  3. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
    2. lower-/.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
    3. lower-PI.f3294.8

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  4. Applied rewrites94.8%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  5. Taylor expanded in s around inf

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right) \]
  6. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right) \]
    2. lower-/.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}} - 1\right) \]
    3. lower-PI.f3285.4

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \]
  7. Applied rewrites85.4%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}} - 1\right) \]
  8. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \color{blue}{\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right)} \]
    2. *-commutativeN/A

      \[\leadsto \color{blue}{\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \cdot \left(-s\right)} \]
    3. lower-*.f3285.4

      \[\leadsto \color{blue}{\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \cdot \left(-s\right)} \]
  9. Applied rewrites85.4%

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

    \[\leadsto \log \left(\frac{1}{\color{blue}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)}} - 1\right) \cdot \left(-s\right) \]
  11. Step-by-step derivation
    1. lower-*.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \color{blue}{\left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)}} - 1\right) \cdot \left(-s\right) \]
    2. lower--.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \color{blue}{\frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}}\right)} - 1\right) \cdot \left(-s\right) \]
    3. lower-/.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{\color{blue}{1}}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)} - 1\right) \cdot \left(-s\right) \]
    4. lower-+.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)} - 1\right) \cdot \left(-s\right) \]
    5. lower-exp.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)} - 1\right) \cdot \left(-s\right) \]
    6. lower-*.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)} - 1\right) \cdot \left(-s\right) \]
    7. lower-/.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)} - 1\right) \cdot \left(-s\right) \]
    8. lower-PI.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\pi}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)} - 1\right) \cdot \left(-s\right) \]
    9. lower-/.f32N/A

      \[\leadsto \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\pi}{s}}} - \frac{1}{\color{blue}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}}\right)} - 1\right) \cdot \left(-s\right) \]
  12. Applied rewrites97.5%

    \[\leadsto \log \left(\frac{1}{\color{blue}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right)}} - 1\right) \cdot \left(-s\right) \]
  13. Add Preprocessing

Alternative 3: 85.4% accurate, 1.3× speedup?

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

\\
\begin{array}{l}
t_0 := \frac{1}{\frac{\pi}{s} - -2}\\
\log \left(\frac{1}{\mathsf{fma}\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - t\_0, u, t\_0\right)} - 1\right) \cdot \left(-s\right)
\end{array}
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  2. Taylor expanded in s around inf

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  3. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
    2. lower-/.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
    3. lower-PI.f3294.8

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  4. Applied rewrites94.8%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  5. Taylor expanded in s around inf

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right) \]
  6. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right) \]
    2. lower-/.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}} - 1\right) \]
    3. lower-PI.f3285.4

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \]
  7. Applied rewrites85.4%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}} - 1\right) \]
  8. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \color{blue}{\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right)} \]
    2. *-commutativeN/A

      \[\leadsto \color{blue}{\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \cdot \left(-s\right)} \]
    3. lower-*.f3285.4

      \[\leadsto \color{blue}{\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \cdot \left(-s\right)} \]
  9. Applied rewrites85.4%

    \[\leadsto \color{blue}{\log \left(\frac{1}{\mathsf{fma}\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}, u, \frac{1}{\frac{\pi}{s} - -2}\right)} - 1\right) \cdot \left(-s\right)} \]
  10. Add Preprocessing

Alternative 4: 84.9% accurate, 1.4× speedup?

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

\\
\begin{array}{l}
t_0 := 2 + \frac{\pi}{s}\\
\left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{t\_0}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{t\_0}} - 1\right)\right) \cdot s
\end{array}
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  2. Applied rewrites3.9%

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

    \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{e^{\frac{\pi}{s}} - -1}} - 1\right)\right) \cdot s \]
  4. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{e^{\frac{\pi}{s}} - -1}} - 1\right)\right) \cdot s \]
    2. lower-/.f32N/A

      \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{e^{\frac{\pi}{s}} - -1}} - 1\right)\right) \cdot s \]
    3. lower-PI.f325.9

      \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{2 + \frac{\pi}{s}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{e^{\frac{\pi}{s}} - -1}} - 1\right)\right) \cdot s \]
  5. Applied rewrites5.9%

    \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{\color{blue}{2 + \frac{\pi}{s}}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{e^{\frac{\pi}{s}} - -1}} - 1\right)\right) \cdot s \]
  6. Taylor expanded in s around inf

    \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{2 + \frac{\pi}{s}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right)\right) \cdot s \]
  7. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{2 + \frac{\pi}{s}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right)\right) \cdot s \]
    2. lower-/.f32N/A

      \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{2 + \frac{\pi}{s}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}} - 1\right)\right) \cdot s \]
    3. lower-PI.f3284.9

      \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{2 + \frac{\pi}{s}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{2 + \frac{\pi}{s}}} - 1\right)\right) \cdot s \]
  8. Applied rewrites84.9%

    \[\leadsto \left(-\log \left(\frac{1}{\frac{\mathsf{fma}\left(u, \frac{2 + \frac{\pi}{s}}{e^{\frac{-\pi}{s}} - -1} - 1, 1\right)}{\color{blue}{2 + \frac{\pi}{s}}}} - 1\right)\right) \cdot s \]
  9. Add Preprocessing

Alternative 5: 84.9% accurate, 1.7× speedup?

\[\begin{array}{l} \\ \log \left(\frac{1}{\left(1 + 2 \cdot \frac{u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right)}{s}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \end{array} \]
(FPCore (u s)
 :precision binary32
 (*
  (log
   (-
    (/
     1.0
     (*
      (+ 1.0 (* 2.0 (/ (* u (- (* 0.25 PI) (* -0.25 PI))) s)))
      (/ 1.0 (- (/ PI s) -2.0))))
    1.0))
  (- s)))
float code(float u, float s) {
	return logf(((1.0f / ((1.0f + (2.0f * ((u * ((0.25f * ((float) M_PI)) - (-0.25f * ((float) M_PI)))) / s))) * (1.0f / ((((float) M_PI) / s) - -2.0f)))) - 1.0f)) * -s;
}
function code(u, s)
	return Float32(log(Float32(Float32(Float32(1.0) / Float32(Float32(Float32(1.0) + Float32(Float32(2.0) * Float32(Float32(u * Float32(Float32(Float32(0.25) * Float32(pi)) - Float32(Float32(-0.25) * Float32(pi)))) / s))) * Float32(Float32(1.0) / Float32(Float32(Float32(pi) / s) - Float32(-2.0))))) - Float32(1.0))) * Float32(-s))
end
function tmp = code(u, s)
	tmp = log(((single(1.0) / ((single(1.0) + (single(2.0) * ((u * ((single(0.25) * single(pi)) - (single(-0.25) * single(pi)))) / s))) * (single(1.0) / ((single(pi) / s) - single(-2.0))))) - single(1.0))) * -s;
end
\begin{array}{l}

\\
\log \left(\frac{1}{\left(1 + 2 \cdot \frac{u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right)}{s}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right)
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  2. Taylor expanded in s around inf

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  3. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
    2. lower-/.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
    3. lower-PI.f3294.8

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  4. Applied rewrites94.8%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  5. Taylor expanded in s around inf

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right) \]
  6. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right) \]
    2. lower-/.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}} - 1\right) \]
    3. lower-PI.f3285.4

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \]
  7. Applied rewrites85.4%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}} - 1\right) \]
  8. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \color{blue}{\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right)} \]
    2. *-commutativeN/A

      \[\leadsto \color{blue}{\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \cdot \left(-s\right)} \]
    3. lower-*.f3285.4

      \[\leadsto \color{blue}{\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \cdot \left(-s\right)} \]
  9. Applied rewrites85.4%

    \[\leadsto \color{blue}{\log \left(\frac{1}{\mathsf{fma}\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}, u, \frac{1}{\frac{\pi}{s} - -2}\right)} - 1\right) \cdot \left(-s\right)} \]
  10. Step-by-step derivation
    1. lift-fma.f32N/A

      \[\leadsto \log \left(\frac{1}{\color{blue}{\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}\right) \cdot u + \frac{1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
    2. lift-/.f32N/A

      \[\leadsto \log \left(\frac{1}{\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}\right) \cdot u + \color{blue}{\frac{1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
    3. add-to-fractionN/A

      \[\leadsto \log \left(\frac{1}{\color{blue}{\frac{\left(\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}\right) \cdot u\right) \cdot \left(\frac{\pi}{s} - -2\right) + 1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
    4. mult-flipN/A

      \[\leadsto \log \left(\frac{1}{\color{blue}{\left(\left(\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}\right) \cdot u\right) \cdot \left(\frac{\pi}{s} - -2\right) + 1\right) \cdot \frac{1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
  11. Applied rewrites84.9%

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

    \[\leadsto \log \left(\frac{1}{\color{blue}{\left(1 + 2 \cdot \frac{u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)}{s}\right)} \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
  13. Step-by-step derivation
    1. lower-+.f32N/A

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

      \[\leadsto \log \left(\frac{1}{\left(1 + 2 \cdot \color{blue}{\frac{u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)}{s}}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
    3. lower-/.f32N/A

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

      \[\leadsto \log \left(\frac{1}{\left(1 + 2 \cdot \frac{u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)}{s}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
    5. lower--.f32N/A

      \[\leadsto \log \left(\frac{1}{\left(1 + 2 \cdot \frac{u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)}{s}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
    6. lower-*.f32N/A

      \[\leadsto \log \left(\frac{1}{\left(1 + 2 \cdot \frac{u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)}{s}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
    7. lower-PI.f32N/A

      \[\leadsto \log \left(\frac{1}{\left(1 + 2 \cdot \frac{u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)}{s}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
    8. lower-*.f32N/A

      \[\leadsto \log \left(\frac{1}{\left(1 + 2 \cdot \frac{u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)}{s}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
    9. lower-PI.f3284.9

      \[\leadsto \log \left(\frac{1}{\left(1 + 2 \cdot \frac{u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right)}{s}\right) \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
  14. Applied rewrites84.9%

    \[\leadsto \log \left(\frac{1}{\color{blue}{\left(1 + 2 \cdot \frac{u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right)}{s}\right)} \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
  15. Add Preprocessing

Alternative 6: 25.2% accurate, 2.9× speedup?

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

\\
\log \left(\frac{1}{1 \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right)
\end{array}
Derivation
  1. Initial program 98.9%

    \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  2. Taylor expanded in s around inf

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  3. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
    2. lower-/.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
    3. lower-PI.f3294.8

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  4. Applied rewrites94.8%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  5. Taylor expanded in s around inf

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{\color{blue}{2 + \frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right) \]
  6. Step-by-step derivation
    1. lower-+.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}}} - 1\right) \]
    2. lower-/.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}} - 1\right) \]
    3. lower-PI.f3285.4

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \]
  7. Applied rewrites85.4%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}} - 1\right) \]
  8. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \color{blue}{\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right)} \]
    2. *-commutativeN/A

      \[\leadsto \color{blue}{\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \cdot \left(-s\right)} \]
    3. lower-*.f3285.4

      \[\leadsto \color{blue}{\log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \cdot \left(-s\right)} \]
  9. Applied rewrites85.4%

    \[\leadsto \color{blue}{\log \left(\frac{1}{\mathsf{fma}\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}, u, \frac{1}{\frac{\pi}{s} - -2}\right)} - 1\right) \cdot \left(-s\right)} \]
  10. Step-by-step derivation
    1. lift-fma.f32N/A

      \[\leadsto \log \left(\frac{1}{\color{blue}{\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}\right) \cdot u + \frac{1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
    2. lift-/.f32N/A

      \[\leadsto \log \left(\frac{1}{\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}\right) \cdot u + \color{blue}{\frac{1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
    3. add-to-fractionN/A

      \[\leadsto \log \left(\frac{1}{\color{blue}{\frac{\left(\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}\right) \cdot u\right) \cdot \left(\frac{\pi}{s} - -2\right) + 1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
    4. mult-flipN/A

      \[\leadsto \log \left(\frac{1}{\color{blue}{\left(\left(\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}\right) \cdot u\right) \cdot \left(\frac{\pi}{s} - -2\right) + 1\right) \cdot \frac{1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
  11. Applied rewrites84.9%

    \[\leadsto \log \left(\frac{1}{\color{blue}{\mathsf{fma}\left(\frac{-1}{-1 - e^{\frac{-\pi}{s}}} - \frac{1}{\frac{\pi}{s} - -2}, u \cdot \left(\frac{\pi}{s} - -2\right), 1\right) \cdot \frac{1}{\frac{\pi}{s} - -2}}} - 1\right) \cdot \left(-s\right) \]
  12. Taylor expanded in u around 0

    \[\leadsto \log \left(\frac{1}{\color{blue}{1} \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
  13. Step-by-step derivation
    1. Applied rewrites25.2%

      \[\leadsto \log \left(\frac{1}{\color{blue}{1} \cdot \frac{1}{\frac{\pi}{s} - -2}} - 1\right) \cdot \left(-s\right) \]
    2. Add Preprocessing

    Alternative 7: 14.3% accurate, 2.8× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(0.5 \cdot \pi\right) \cdot u\\ \mathbf{if}\;s \leq 9.999999682655225 \cdot 10^{-21}:\\ \;\;\;\;\left(-s\right) \cdot \log 1\\ \mathbf{else}:\\ \;\;\;\;4 \cdot \left(\left(1 - \frac{0.25 \cdot \pi}{t\_0}\right) \cdot t\_0\right)\\ \end{array} \end{array} \]
    (FPCore (u s)
     :precision binary32
     (let* ((t_0 (* (* 0.5 PI) u)))
       (if (<= s 9.999999682655225e-21)
         (* (- s) (log 1.0))
         (* 4.0 (* (- 1.0 (/ (* 0.25 PI) t_0)) t_0)))))
    float code(float u, float s) {
    	float t_0 = (0.5f * ((float) M_PI)) * u;
    	float tmp;
    	if (s <= 9.999999682655225e-21f) {
    		tmp = -s * logf(1.0f);
    	} else {
    		tmp = 4.0f * ((1.0f - ((0.25f * ((float) M_PI)) / t_0)) * t_0);
    	}
    	return tmp;
    }
    
    function code(u, s)
    	t_0 = Float32(Float32(Float32(0.5) * Float32(pi)) * u)
    	tmp = Float32(0.0)
    	if (s <= Float32(9.999999682655225e-21))
    		tmp = Float32(Float32(-s) * log(Float32(1.0)));
    	else
    		tmp = Float32(Float32(4.0) * Float32(Float32(Float32(1.0) - Float32(Float32(Float32(0.25) * Float32(pi)) / t_0)) * t_0));
    	end
    	return tmp
    end
    
    function tmp_2 = code(u, s)
    	t_0 = (single(0.5) * single(pi)) * u;
    	tmp = single(0.0);
    	if (s <= single(9.999999682655225e-21))
    		tmp = -s * log(single(1.0));
    	else
    		tmp = single(4.0) * ((single(1.0) - ((single(0.25) * single(pi)) / t_0)) * t_0);
    	end
    	tmp_2 = tmp;
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \left(0.5 \cdot \pi\right) \cdot u\\
    \mathbf{if}\;s \leq 9.999999682655225 \cdot 10^{-21}:\\
    \;\;\;\;\left(-s\right) \cdot \log 1\\
    
    \mathbf{else}:\\
    \;\;\;\;4 \cdot \left(\left(1 - \frac{0.25 \cdot \pi}{t\_0}\right) \cdot t\_0\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if s < 9.99999968e-21

      1. Initial program 98.9%

        \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
      2. Taylor expanded in s around inf

        \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]
      3. Step-by-step derivation
        1. Applied rewrites10.3%

          \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]

        if 9.99999968e-21 < s

        1. Initial program 98.9%

          \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
        2. Taylor expanded in s around inf

          \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
        3. Step-by-step derivation
          1. lower-*.f32N/A

            \[\leadsto 4 \cdot \color{blue}{\left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
          2. lower--.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \color{blue}{\frac{1}{4} \cdot \mathsf{PI}\left(\right)}\right) \]
          3. lower-*.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \color{blue}{\frac{1}{4}} \cdot \mathsf{PI}\left(\right)\right) \]
          4. lower--.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
          5. lower-*.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
          6. lower-PI.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
          7. lower-*.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
          8. lower-PI.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
          9. lower-*.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \frac{1}{4} \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \]
          10. lower-PI.f3211.7

            \[\leadsto 4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right) \]
        4. Applied rewrites11.7%

          \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right)} \]
        5. Step-by-step derivation
          1. lift--.f32N/A

            \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \color{blue}{\frac{1}{4} \cdot \pi}\right) \]
          2. sub-to-multN/A

            \[\leadsto 4 \cdot \left(\left(1 - \frac{\frac{1}{4} \cdot \pi}{u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right)}\right) \cdot \color{blue}{\left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right)\right)}\right) \]
          3. lower-unsound-*.f32N/A

            \[\leadsto 4 \cdot \left(\left(1 - \frac{\frac{1}{4} \cdot \pi}{u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right)}\right) \cdot \color{blue}{\left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right)\right)}\right) \]
        6. Applied rewrites11.7%

          \[\leadsto 4 \cdot \left(\left(1 - \frac{0.25 \cdot \pi}{\left(0.5 \cdot \pi\right) \cdot u}\right) \cdot \color{blue}{\left(\left(0.5 \cdot \pi\right) \cdot u\right)}\right) \]
      4. Recombined 2 regimes into one program.
      5. Add Preprocessing

      Alternative 8: 14.3% accurate, 3.1× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;s \leq 9.999999682655225 \cdot 10^{-21}:\\ \;\;\;\;\left(-s\right) \cdot \log 1\\ \mathbf{else}:\\ \;\;\;\;4 \cdot \left(u \cdot \left(\mathsf{fma}\left(-0.25, \frac{\pi}{u}, 0.25 \cdot \pi\right) - -0.25 \cdot \pi\right)\right)\\ \end{array} \end{array} \]
      (FPCore (u s)
       :precision binary32
       (if (<= s 9.999999682655225e-21)
         (* (- s) (log 1.0))
         (* 4.0 (* u (- (fma -0.25 (/ PI u) (* 0.25 PI)) (* -0.25 PI))))))
      float code(float u, float s) {
      	float tmp;
      	if (s <= 9.999999682655225e-21f) {
      		tmp = -s * logf(1.0f);
      	} else {
      		tmp = 4.0f * (u * (fmaf(-0.25f, (((float) M_PI) / u), (0.25f * ((float) M_PI))) - (-0.25f * ((float) M_PI))));
      	}
      	return tmp;
      }
      
      function code(u, s)
      	tmp = Float32(0.0)
      	if (s <= Float32(9.999999682655225e-21))
      		tmp = Float32(Float32(-s) * log(Float32(1.0)));
      	else
      		tmp = Float32(Float32(4.0) * Float32(u * Float32(fma(Float32(-0.25), Float32(Float32(pi) / u), Float32(Float32(0.25) * Float32(pi))) - Float32(Float32(-0.25) * Float32(pi)))));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;s \leq 9.999999682655225 \cdot 10^{-21}:\\
      \;\;\;\;\left(-s\right) \cdot \log 1\\
      
      \mathbf{else}:\\
      \;\;\;\;4 \cdot \left(u \cdot \left(\mathsf{fma}\left(-0.25, \frac{\pi}{u}, 0.25 \cdot \pi\right) - -0.25 \cdot \pi\right)\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if s < 9.99999968e-21

        1. Initial program 98.9%

          \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
        2. Taylor expanded in s around inf

          \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]
        3. Step-by-step derivation
          1. Applied rewrites10.3%

            \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]

          if 9.99999968e-21 < s

          1. Initial program 98.9%

            \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
          2. Taylor expanded in s around inf

            \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
          3. Step-by-step derivation
            1. lower-*.f32N/A

              \[\leadsto 4 \cdot \color{blue}{\left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
            2. lower--.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \color{blue}{\frac{1}{4} \cdot \mathsf{PI}\left(\right)}\right) \]
            3. lower-*.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \color{blue}{\frac{1}{4}} \cdot \mathsf{PI}\left(\right)\right) \]
            4. lower--.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
            5. lower-*.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
            6. lower-PI.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
            7. lower-*.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
            8. lower-PI.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
            9. lower-*.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \frac{1}{4} \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \]
            10. lower-PI.f3211.7

              \[\leadsto 4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right) \]
          4. Applied rewrites11.7%

            \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right)} \]
          5. Taylor expanded in u around inf

            \[\leadsto 4 \cdot \left(u \cdot \color{blue}{\left(\left(\frac{-1}{4} \cdot \frac{\mathsf{PI}\left(\right)}{u} + \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)}\right) \]
          6. Step-by-step derivation
            1. lower-*.f32N/A

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

              \[\leadsto 4 \cdot \left(u \cdot \left(\left(\frac{-1}{4} \cdot \frac{\mathsf{PI}\left(\right)}{u} + \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)\right) \]
            3. lower-fma.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\mathsf{fma}\left(\frac{-1}{4}, \frac{\mathsf{PI}\left(\right)}{u}, \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)\right) \]
            4. lower-/.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\mathsf{fma}\left(\frac{-1}{4}, \frac{\mathsf{PI}\left(\right)}{u}, \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)\right) \]
            5. lower-PI.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\mathsf{fma}\left(\frac{-1}{4}, \frac{\pi}{u}, \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)\right) \]
            6. lower-*.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\mathsf{fma}\left(\frac{-1}{4}, \frac{\pi}{u}, \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)\right) \]
            7. lower-PI.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\mathsf{fma}\left(\frac{-1}{4}, \frac{\pi}{u}, \frac{1}{4} \cdot \pi\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)\right) \]
            8. lower-*.f32N/A

              \[\leadsto 4 \cdot \left(u \cdot \left(\mathsf{fma}\left(\frac{-1}{4}, \frac{\pi}{u}, \frac{1}{4} \cdot \pi\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)\right) \]
            9. lower-PI.f3211.7

              \[\leadsto 4 \cdot \left(u \cdot \left(\mathsf{fma}\left(-0.25, \frac{\pi}{u}, 0.25 \cdot \pi\right) - -0.25 \cdot \pi\right)\right) \]
          7. Applied rewrites11.7%

            \[\leadsto 4 \cdot \left(u \cdot \color{blue}{\left(\mathsf{fma}\left(-0.25, \frac{\pi}{u}, 0.25 \cdot \pi\right) - -0.25 \cdot \pi\right)}\right) \]
        4. Recombined 2 regimes into one program.
        5. Add Preprocessing

        Alternative 9: 14.3% accurate, 3.3× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;s \leq 9.999999682655225 \cdot 10^{-21}:\\ \;\;\;\;\left(-s\right) \cdot \log 1\\ \mathbf{else}:\\ \;\;\;\;\left(-s\right) \cdot \left(u \cdot \mathsf{fma}\left(-2, \frac{\pi}{s}, \frac{\pi}{s \cdot u}\right)\right)\\ \end{array} \end{array} \]
        (FPCore (u s)
         :precision binary32
         (if (<= s 9.999999682655225e-21)
           (* (- s) (log 1.0))
           (* (- s) (* u (fma -2.0 (/ PI s) (/ PI (* s u)))))))
        float code(float u, float s) {
        	float tmp;
        	if (s <= 9.999999682655225e-21f) {
        		tmp = -s * logf(1.0f);
        	} else {
        		tmp = -s * (u * fmaf(-2.0f, (((float) M_PI) / s), (((float) M_PI) / (s * u))));
        	}
        	return tmp;
        }
        
        function code(u, s)
        	tmp = Float32(0.0)
        	if (s <= Float32(9.999999682655225e-21))
        		tmp = Float32(Float32(-s) * log(Float32(1.0)));
        	else
        		tmp = Float32(Float32(-s) * Float32(u * fma(Float32(-2.0), Float32(Float32(pi) / s), Float32(Float32(pi) / Float32(s * u)))));
        	end
        	return tmp
        end
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        \mathbf{if}\;s \leq 9.999999682655225 \cdot 10^{-21}:\\
        \;\;\;\;\left(-s\right) \cdot \log 1\\
        
        \mathbf{else}:\\
        \;\;\;\;\left(-s\right) \cdot \left(u \cdot \mathsf{fma}\left(-2, \frac{\pi}{s}, \frac{\pi}{s \cdot u}\right)\right)\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if s < 9.99999968e-21

          1. Initial program 98.9%

            \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
          2. Taylor expanded in s around inf

            \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]
          3. Step-by-step derivation
            1. Applied rewrites10.3%

              \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]

            if 9.99999968e-21 < s

            1. Initial program 98.9%

              \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
            2. Taylor expanded in s around -inf

              \[\leadsto \left(-s\right) \cdot \color{blue}{\left(4 \cdot \frac{u \cdot \left(\frac{-1}{4} \cdot \mathsf{PI}\left(\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)}{s}\right)} \]
            3. Step-by-step derivation
              1. lower-*.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \color{blue}{\frac{u \cdot \left(\frac{-1}{4} \cdot \mathsf{PI}\left(\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)}{s}}\right) \]
              2. lower-/.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \frac{u \cdot \left(\frac{-1}{4} \cdot \mathsf{PI}\left(\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)}{\color{blue}{s}}\right) \]
            4. Applied rewrites11.7%

              \[\leadsto \left(-s\right) \cdot \color{blue}{\left(4 \cdot \frac{u \cdot \left(-0.25 \cdot \pi - 0.25 \cdot \pi\right) - -0.25 \cdot \pi}{s}\right)} \]
            5. Step-by-step derivation
              1. lift-/.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \frac{u \cdot \left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right) - \frac{-1}{4} \cdot \pi}{\color{blue}{s}}\right) \]
              2. lift--.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \frac{u \cdot \left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right) - \frac{-1}{4} \cdot \pi}{s}\right) \]
              3. div-subN/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{u \cdot \left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right)}{s} - \color{blue}{\frac{\frac{-1}{4} \cdot \pi}{s}}\right)\right) \]
              4. lower--.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{u \cdot \left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right)}{s} - \color{blue}{\frac{\frac{-1}{4} \cdot \pi}{s}}\right)\right) \]
              5. lower-/.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{u \cdot \left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right)}{s} - \frac{\color{blue}{\frac{-1}{4} \cdot \pi}}{s}\right)\right) \]
              6. lift-*.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{u \cdot \left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right)}{s} - \frac{\color{blue}{\frac{-1}{4}} \cdot \pi}{s}\right)\right) \]
              7. *-commutativeN/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right) \cdot u}{s} - \frac{\color{blue}{\frac{-1}{4}} \cdot \pi}{s}\right)\right) \]
              8. lower-*.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right) \cdot u}{s} - \frac{\color{blue}{\frac{-1}{4}} \cdot \pi}{s}\right)\right) \]
              9. lift--.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right) \cdot u}{s} - \frac{\frac{-1}{4} \cdot \pi}{s}\right)\right) \]
              10. lift-*.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right) \cdot u}{s} - \frac{\frac{-1}{4} \cdot \pi}{s}\right)\right) \]
              11. lift-*.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\frac{-1}{4} \cdot \pi - \frac{1}{4} \cdot \pi\right) \cdot u}{s} - \frac{\frac{-1}{4} \cdot \pi}{s}\right)\right) \]
              12. distribute-rgt-out--N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\pi \cdot \left(\frac{-1}{4} - \frac{1}{4}\right)\right) \cdot u}{s} - \frac{\frac{-1}{4} \cdot \pi}{s}\right)\right) \]
              13. *-commutativeN/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\left(\frac{-1}{4} - \frac{1}{4}\right) \cdot \pi\right) \cdot u}{s} - \frac{\frac{-1}{4} \cdot \pi}{s}\right)\right) \]
              14. lower-*.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\left(\frac{-1}{4} - \frac{1}{4}\right) \cdot \pi\right) \cdot u}{s} - \frac{\frac{-1}{4} \cdot \pi}{s}\right)\right) \]
              15. metadata-evalN/A

                \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(\frac{-1}{2} \cdot \pi\right) \cdot u}{s} - \frac{\frac{-1}{4} \cdot \pi}{s}\right)\right) \]
            6. Applied rewrites11.7%

              \[\leadsto \left(-s\right) \cdot \left(4 \cdot \left(\frac{\left(-0.5 \cdot \pi\right) \cdot u}{s} - \color{blue}{-0.25 \cdot \frac{\pi}{s}}\right)\right) \]
            7. Taylor expanded in u around inf

              \[\leadsto \left(-s\right) \cdot \left(u \cdot \color{blue}{\left(-2 \cdot \frac{\mathsf{PI}\left(\right)}{s} + \frac{\mathsf{PI}\left(\right)}{s \cdot u}\right)}\right) \]
            8. Step-by-step derivation
              1. lower-*.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(u \cdot \left(-2 \cdot \frac{\mathsf{PI}\left(\right)}{s} + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s \cdot u}}\right)\right) \]
              2. lower-fma.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(u \cdot \mathsf{fma}\left(-2, \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}, \frac{\mathsf{PI}\left(\right)}{s \cdot u}\right)\right) \]
              3. lower-/.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(u \cdot \mathsf{fma}\left(-2, \frac{\mathsf{PI}\left(\right)}{s}, \frac{\mathsf{PI}\left(\right)}{s \cdot u}\right)\right) \]
              4. lower-PI.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(u \cdot \mathsf{fma}\left(-2, \frac{\pi}{s}, \frac{\mathsf{PI}\left(\right)}{s \cdot u}\right)\right) \]
              5. lower-/.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(u \cdot \mathsf{fma}\left(-2, \frac{\pi}{s}, \frac{\mathsf{PI}\left(\right)}{s \cdot u}\right)\right) \]
              6. lower-PI.f32N/A

                \[\leadsto \left(-s\right) \cdot \left(u \cdot \mathsf{fma}\left(-2, \frac{\pi}{s}, \frac{\pi}{s \cdot u}\right)\right) \]
              7. lower-*.f3211.3

                \[\leadsto \left(-s\right) \cdot \left(u \cdot \mathsf{fma}\left(-2, \frac{\pi}{s}, \frac{\pi}{s \cdot u}\right)\right) \]
            9. Applied rewrites11.3%

              \[\leadsto \left(-s\right) \cdot \left(u \cdot \color{blue}{\mathsf{fma}\left(-2, \frac{\pi}{s}, \frac{\pi}{s \cdot u}\right)}\right) \]
          4. Recombined 2 regimes into one program.
          5. Add Preprocessing

          Alternative 10: 14.3% accurate, 4.7× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;s \leq 9.999999682655225 \cdot 10^{-21}:\\ \;\;\;\;\left(-s\right) \cdot \log 1\\ \mathbf{else}:\\ \;\;\;\;4 \cdot \mathsf{fma}\left(u \cdot \pi, 0.5, -0.25 \cdot \pi\right)\\ \end{array} \end{array} \]
          (FPCore (u s)
           :precision binary32
           (if (<= s 9.999999682655225e-21)
             (* (- s) (log 1.0))
             (* 4.0 (fma (* u PI) 0.5 (* -0.25 PI)))))
          float code(float u, float s) {
          	float tmp;
          	if (s <= 9.999999682655225e-21f) {
          		tmp = -s * logf(1.0f);
          	} else {
          		tmp = 4.0f * fmaf((u * ((float) M_PI)), 0.5f, (-0.25f * ((float) M_PI)));
          	}
          	return tmp;
          }
          
          function code(u, s)
          	tmp = Float32(0.0)
          	if (s <= Float32(9.999999682655225e-21))
          		tmp = Float32(Float32(-s) * log(Float32(1.0)));
          	else
          		tmp = Float32(Float32(4.0) * fma(Float32(u * Float32(pi)), Float32(0.5), Float32(Float32(-0.25) * Float32(pi))));
          	end
          	return tmp
          end
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          \mathbf{if}\;s \leq 9.999999682655225 \cdot 10^{-21}:\\
          \;\;\;\;\left(-s\right) \cdot \log 1\\
          
          \mathbf{else}:\\
          \;\;\;\;4 \cdot \mathsf{fma}\left(u \cdot \pi, 0.5, -0.25 \cdot \pi\right)\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if s < 9.99999968e-21

            1. Initial program 98.9%

              \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
            2. Taylor expanded in s around inf

              \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]
            3. Step-by-step derivation
              1. Applied rewrites10.3%

                \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]

              if 9.99999968e-21 < s

              1. Initial program 98.9%

                \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
              2. Taylor expanded in s around inf

                \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
              3. Step-by-step derivation
                1. lower-*.f32N/A

                  \[\leadsto 4 \cdot \color{blue}{\left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
                2. lower--.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \color{blue}{\frac{1}{4} \cdot \mathsf{PI}\left(\right)}\right) \]
                3. lower-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \color{blue}{\frac{1}{4}} \cdot \mathsf{PI}\left(\right)\right) \]
                4. lower--.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
                5. lower-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
                6. lower-PI.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
                7. lower-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
                8. lower-PI.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) \]
                9. lower-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \frac{1}{4} \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \]
                10. lower-PI.f3211.7

                  \[\leadsto 4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right) \]
              4. Applied rewrites11.7%

                \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right)} \]
              5. Step-by-step derivation
                1. lift--.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \color{blue}{\frac{1}{4} \cdot \pi}\right) \]
                2. lift-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) - \frac{1}{4} \cdot \color{blue}{\pi}\right) \]
                3. fp-cancel-sub-sign-invN/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{4}\right)\right) \cdot \pi}\right) \]
                4. lift-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{4}\right)\right)} \cdot \pi\right) \]
                5. metadata-evalN/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) + \frac{-1}{4} \cdot \pi\right) \]
                6. lift-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) + \frac{-1}{4} \cdot \color{blue}{\pi}\right) \]
                7. lift--.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) + \frac{-1}{4} \cdot \pi\right) \]
                8. lift-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) + \frac{-1}{4} \cdot \pi\right) \]
                9. lift-*.f32N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \pi\right) + \frac{-1}{4} \cdot \pi\right) \]
                10. distribute-rgt-out--N/A

                  \[\leadsto 4 \cdot \left(u \cdot \left(\pi \cdot \left(\frac{1}{4} - \frac{-1}{4}\right)\right) + \frac{-1}{4} \cdot \pi\right) \]
                11. associate-*r*N/A

                  \[\leadsto 4 \cdot \left(\left(u \cdot \pi\right) \cdot \left(\frac{1}{4} - \frac{-1}{4}\right) + \color{blue}{\frac{-1}{4}} \cdot \pi\right) \]
                12. lower-fma.f32N/A

                  \[\leadsto 4 \cdot \mathsf{fma}\left(u \cdot \pi, \color{blue}{\frac{1}{4} - \frac{-1}{4}}, \frac{-1}{4} \cdot \pi\right) \]
                13. lower-*.f32N/A

                  \[\leadsto 4 \cdot \mathsf{fma}\left(u \cdot \pi, \color{blue}{\frac{1}{4}} - \frac{-1}{4}, \frac{-1}{4} \cdot \pi\right) \]
                14. metadata-eval11.7

                  \[\leadsto 4 \cdot \mathsf{fma}\left(u \cdot \pi, 0.5, -0.25 \cdot \pi\right) \]
              6. Applied rewrites11.7%

                \[\leadsto 4 \cdot \mathsf{fma}\left(u \cdot \pi, \color{blue}{0.5}, -0.25 \cdot \pi\right) \]
            4. Recombined 2 regimes into one program.
            5. Add Preprocessing

            Alternative 11: 14.2% accurate, 0.9× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{1 + e^{\frac{\pi}{s}}}\\ \mathbf{if}\;\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - t\_0\right) + t\_0} - 1\right) \leq -1.999999936531045 \cdot 10^{-19}:\\ \;\;\;\;\left(-s\right) \cdot \frac{1}{\frac{s}{\pi}}\\ \mathbf{else}:\\ \;\;\;\;\left(-s\right) \cdot \log 1\\ \end{array} \end{array} \]
            (FPCore (u s)
             :precision binary32
             (let* ((t_0 (/ 1.0 (+ 1.0 (exp (/ PI s))))))
               (if (<=
                    (*
                     (- s)
                     (log
                      (-
                       (/ 1.0 (+ (* u (- (/ 1.0 (+ 1.0 (exp (/ (- PI) s)))) t_0)) t_0))
                       1.0)))
                    -1.999999936531045e-19)
                 (* (- s) (/ 1.0 (/ s PI)))
                 (* (- s) (log 1.0)))))
            float code(float u, float s) {
            	float t_0 = 1.0f / (1.0f + expf((((float) M_PI) / s)));
            	float tmp;
            	if ((-s * logf(((1.0f / ((u * ((1.0f / (1.0f + expf((-((float) M_PI) / s)))) - t_0)) + t_0)) - 1.0f))) <= -1.999999936531045e-19f) {
            		tmp = -s * (1.0f / (s / ((float) M_PI)));
            	} else {
            		tmp = -s * logf(1.0f);
            	}
            	return tmp;
            }
            
            function code(u, s)
            	t_0 = Float32(Float32(1.0) / Float32(Float32(1.0) + exp(Float32(Float32(pi) / s))))
            	tmp = Float32(0.0)
            	if (Float32(Float32(-s) * log(Float32(Float32(Float32(1.0) / Float32(Float32(u * Float32(Float32(Float32(1.0) / Float32(Float32(1.0) + exp(Float32(Float32(-Float32(pi)) / s)))) - t_0)) + t_0)) - Float32(1.0)))) <= Float32(-1.999999936531045e-19))
            		tmp = Float32(Float32(-s) * Float32(Float32(1.0) / Float32(s / Float32(pi))));
            	else
            		tmp = Float32(Float32(-s) * log(Float32(1.0)));
            	end
            	return tmp
            end
            
            function tmp_2 = code(u, s)
            	t_0 = single(1.0) / (single(1.0) + exp((single(pi) / s)));
            	tmp = single(0.0);
            	if ((-s * log(((single(1.0) / ((u * ((single(1.0) / (single(1.0) + exp((-single(pi) / s)))) - t_0)) + t_0)) - single(1.0)))) <= single(-1.999999936531045e-19))
            		tmp = -s * (single(1.0) / (s / single(pi)));
            	else
            		tmp = -s * log(single(1.0));
            	end
            	tmp_2 = tmp;
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            t_0 := \frac{1}{1 + e^{\frac{\pi}{s}}}\\
            \mathbf{if}\;\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - t\_0\right) + t\_0} - 1\right) \leq -1.999999936531045 \cdot 10^{-19}:\\
            \;\;\;\;\left(-s\right) \cdot \frac{1}{\frac{s}{\pi}}\\
            
            \mathbf{else}:\\
            \;\;\;\;\left(-s\right) \cdot \log 1\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if (*.f32 (neg.f32 s) (log.f32 (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 (*.f32 u (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (neg.f32 (PI.f32)) s)))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) #s(literal 1 binary32)))) < -1.99999994e-19

              1. Initial program 98.9%

                \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
              2. Step-by-step derivation
                1. lift-*.f32N/A

                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\color{blue}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right)} + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
                2. lift--.f32N/A

                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \color{blue}{\left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right)} + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
                3. sub-flipN/A

                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \color{blue}{\left(\frac{1}{1 + e^{\frac{-\pi}{s}}} + \left(\mathsf{neg}\left(\frac{1}{1 + e^{\frac{\pi}{s}}}\right)\right)\right)} + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
                4. distribute-lft-inN/A

                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\color{blue}{\left(u \cdot \frac{1}{1 + e^{\frac{-\pi}{s}}} + u \cdot \left(\mathsf{neg}\left(\frac{1}{1 + e^{\frac{\pi}{s}}}\right)\right)\right)} + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
                5. flip3-+N/A

                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\color{blue}{\frac{{\left(u \cdot \frac{1}{1 + e^{\frac{-\pi}{s}}}\right)}^{3} + {\left(u \cdot \left(\mathsf{neg}\left(\frac{1}{1 + e^{\frac{\pi}{s}}}\right)\right)\right)}^{3}}{\left(u \cdot \frac{1}{1 + e^{\frac{-\pi}{s}}}\right) \cdot \left(u \cdot \frac{1}{1 + e^{\frac{-\pi}{s}}}\right) + \left(\left(u \cdot \left(\mathsf{neg}\left(\frac{1}{1 + e^{\frac{\pi}{s}}}\right)\right)\right) \cdot \left(u \cdot \left(\mathsf{neg}\left(\frac{1}{1 + e^{\frac{\pi}{s}}}\right)\right)\right) - \left(u \cdot \frac{1}{1 + e^{\frac{-\pi}{s}}}\right) \cdot \left(u \cdot \left(\mathsf{neg}\left(\frac{1}{1 + e^{\frac{\pi}{s}}}\right)\right)\right)\right)}} + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
              3. Applied rewrites98.9%

                \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\color{blue}{\frac{{\left(\frac{u}{e^{\frac{-\pi}{s}} - -1}\right)}^{3} + {\left(\frac{u}{-1 - e^{\frac{\pi}{s}}}\right)}^{3}}{\mathsf{fma}\left(\frac{u}{e^{\frac{-\pi}{s}} - -1}, \frac{u}{e^{\frac{-\pi}{s}} - -1}, \frac{u}{-1 - e^{\frac{\pi}{s}}} \cdot \frac{u}{-1 - e^{\frac{\pi}{s}}} - \frac{u}{e^{\frac{-\pi}{s}} - -1} \cdot \frac{u}{-1 - e^{\frac{\pi}{s}}}\right)}} + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
              4. Taylor expanded in u around 0

                \[\leadsto \left(-s\right) \cdot \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}} \]
              5. Step-by-step derivation
                1. lower-/.f32N/A

                  \[\leadsto \left(-s\right) \cdot \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}} \]
                2. lower-PI.f3211.5

                  \[\leadsto \left(-s\right) \cdot \frac{\pi}{s} \]
              6. Applied rewrites11.5%

                \[\leadsto \left(-s\right) \cdot \color{blue}{\frac{\pi}{s}} \]
              7. Step-by-step derivation
                1. lift-/.f32N/A

                  \[\leadsto \left(-s\right) \cdot \frac{\pi}{\color{blue}{s}} \]
                2. div-flipN/A

                  \[\leadsto \left(-s\right) \cdot \frac{1}{\color{blue}{\frac{s}{\pi}}} \]
                3. lower-unsound-/.f32N/A

                  \[\leadsto \left(-s\right) \cdot \frac{1}{\color{blue}{\frac{s}{\pi}}} \]
                4. lower-unsound-/.f3211.5

                  \[\leadsto \left(-s\right) \cdot \frac{1}{\frac{s}{\color{blue}{\pi}}} \]
              8. Applied rewrites11.5%

                \[\leadsto \left(-s\right) \cdot \frac{1}{\color{blue}{\frac{s}{\pi}}} \]

              if -1.99999994e-19 < (*.f32 (neg.f32 s) (log.f32 (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 (*.f32 u (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (neg.f32 (PI.f32)) s)))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) #s(literal 1 binary32))))

              1. Initial program 98.9%

                \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
              2. Taylor expanded in s around inf

                \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]
              3. Step-by-step derivation
                1. Applied rewrites10.3%

                  \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]
              4. Recombined 2 regimes into one program.
              5. Add Preprocessing

              Alternative 12: 14.2% accurate, 0.9× speedup?

              \[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{1 + e^{\frac{\pi}{s}}}\\ \mathbf{if}\;\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - t\_0\right) + t\_0} - 1\right) \leq -1.999999936531045 \cdot 10^{-19}:\\ \;\;\;\;\left(-s\right) \cdot \frac{\pi}{s}\\ \mathbf{else}:\\ \;\;\;\;\left(-s\right) \cdot \log 1\\ \end{array} \end{array} \]
              (FPCore (u s)
               :precision binary32
               (let* ((t_0 (/ 1.0 (+ 1.0 (exp (/ PI s))))))
                 (if (<=
                      (*
                       (- s)
                       (log
                        (-
                         (/ 1.0 (+ (* u (- (/ 1.0 (+ 1.0 (exp (/ (- PI) s)))) t_0)) t_0))
                         1.0)))
                      -1.999999936531045e-19)
                   (* (- s) (/ PI s))
                   (* (- s) (log 1.0)))))
              float code(float u, float s) {
              	float t_0 = 1.0f / (1.0f + expf((((float) M_PI) / s)));
              	float tmp;
              	if ((-s * logf(((1.0f / ((u * ((1.0f / (1.0f + expf((-((float) M_PI) / s)))) - t_0)) + t_0)) - 1.0f))) <= -1.999999936531045e-19f) {
              		tmp = -s * (((float) M_PI) / s);
              	} else {
              		tmp = -s * logf(1.0f);
              	}
              	return tmp;
              }
              
              function code(u, s)
              	t_0 = Float32(Float32(1.0) / Float32(Float32(1.0) + exp(Float32(Float32(pi) / s))))
              	tmp = Float32(0.0)
              	if (Float32(Float32(-s) * log(Float32(Float32(Float32(1.0) / Float32(Float32(u * Float32(Float32(Float32(1.0) / Float32(Float32(1.0) + exp(Float32(Float32(-Float32(pi)) / s)))) - t_0)) + t_0)) - Float32(1.0)))) <= Float32(-1.999999936531045e-19))
              		tmp = Float32(Float32(-s) * Float32(Float32(pi) / s));
              	else
              		tmp = Float32(Float32(-s) * log(Float32(1.0)));
              	end
              	return tmp
              end
              
              function tmp_2 = code(u, s)
              	t_0 = single(1.0) / (single(1.0) + exp((single(pi) / s)));
              	tmp = single(0.0);
              	if ((-s * log(((single(1.0) / ((u * ((single(1.0) / (single(1.0) + exp((-single(pi) / s)))) - t_0)) + t_0)) - single(1.0)))) <= single(-1.999999936531045e-19))
              		tmp = -s * (single(pi) / s);
              	else
              		tmp = -s * log(single(1.0));
              	end
              	tmp_2 = tmp;
              end
              
              \begin{array}{l}
              
              \\
              \begin{array}{l}
              t_0 := \frac{1}{1 + e^{\frac{\pi}{s}}}\\
              \mathbf{if}\;\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - t\_0\right) + t\_0} - 1\right) \leq -1.999999936531045 \cdot 10^{-19}:\\
              \;\;\;\;\left(-s\right) \cdot \frac{\pi}{s}\\
              
              \mathbf{else}:\\
              \;\;\;\;\left(-s\right) \cdot \log 1\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if (*.f32 (neg.f32 s) (log.f32 (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 (*.f32 u (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (neg.f32 (PI.f32)) s)))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) #s(literal 1 binary32)))) < -1.99999994e-19

                1. Initial program 98.9%

                  \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
                2. Taylor expanded in u around 0

                  \[\leadsto \left(-s\right) \cdot \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}} \]
                3. Step-by-step derivation
                  1. lower-/.f32N/A

                    \[\leadsto \left(-s\right) \cdot \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}} \]
                  2. lower-PI.f3211.5

                    \[\leadsto \left(-s\right) \cdot \frac{\pi}{s} \]
                4. Applied rewrites11.5%

                  \[\leadsto \left(-s\right) \cdot \color{blue}{\frac{\pi}{s}} \]

                if -1.99999994e-19 < (*.f32 (neg.f32 s) (log.f32 (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 (*.f32 u (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (neg.f32 (PI.f32)) s)))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) #s(literal 1 binary32))))

                1. Initial program 98.9%

                  \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
                2. Taylor expanded in s around inf

                  \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]
                3. Step-by-step derivation
                  1. Applied rewrites10.3%

                    \[\leadsto \left(-s\right) \cdot \log \color{blue}{1} \]
                4. Recombined 2 regimes into one program.
                5. Add Preprocessing

                Alternative 13: 11.5% accurate, 46.3× speedup?

                \[\begin{array}{l} \\ -\pi \end{array} \]
                (FPCore (u s) :precision binary32 (- PI))
                float code(float u, float s) {
                	return -((float) M_PI);
                }
                
                function code(u, s)
                	return Float32(-Float32(pi))
                end
                
                function tmp = code(u, s)
                	tmp = -single(pi);
                end
                
                \begin{array}{l}
                
                \\
                -\pi
                \end{array}
                
                Derivation
                1. Initial program 98.9%

                  \[\left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{1 + e^{\frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
                2. Taylor expanded in u around 0

                  \[\leadsto \color{blue}{-1 \cdot \mathsf{PI}\left(\right)} \]
                3. Step-by-step derivation
                  1. lower-*.f32N/A

                    \[\leadsto -1 \cdot \color{blue}{\mathsf{PI}\left(\right)} \]
                  2. lower-PI.f3211.5

                    \[\leadsto -1 \cdot \pi \]
                4. Applied rewrites11.5%

                  \[\leadsto \color{blue}{-1 \cdot \pi} \]
                5. Step-by-step derivation
                  1. lift-*.f32N/A

                    \[\leadsto -1 \cdot \color{blue}{\pi} \]
                  2. mul-1-negN/A

                    \[\leadsto \mathsf{neg}\left(\pi\right) \]
                  3. lift-neg.f3211.5

                    \[\leadsto -\pi \]
                6. Applied rewrites11.5%

                  \[\leadsto \color{blue}{-\pi} \]
                7. Add Preprocessing

                Reproduce

                ?
                herbie shell --seed 2025157 
                (FPCore (u s)
                  :name "Sample trimmed logistic on [-pi, pi]"
                  :precision binary32
                  :pre (and (and (<= 2.328306437e-10 u) (<= u 1.0)) (and (<= 0.0 s) (<= s 1.0651631)))
                  (* (- s) (log (- (/ 1.0 (+ (* u (- (/ 1.0 (+ 1.0 (exp (/ (- PI) s)))) (/ 1.0 (+ 1.0 (exp (/ PI s)))))) (/ 1.0 (+ 1.0 (exp (/ PI s)))))) 1.0))))