Sample trimmed logistic on [-pi, pi]

Percentage Accurate: 98.9% → 99.0%
Time: 11.6s
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: 99.0% accurate, 0.6× speedup?

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

\\
\begin{array}{l}
t_0 := \frac{1}{e^{\frac{\pi}{s}} - -1}\\
t_1 := \mathsf{fma}\left(u, \frac{-1}{-1 - e^{\frac{-\pi}{s}}} - t\_0, t\_0\right)\\
\left(-s\right) \cdot \log \left(\frac{1 - t\_1}{t\_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. Applied rewrites98.9%

    \[\leadsto \left(-s\right) \cdot \log \left(\color{blue}{\left(\frac{\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) \cdot u}{{\left(\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) \cdot u\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - \frac{\frac{1}{e^{\frac{\pi}{s}} - -1}}{{\left(\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) \cdot u\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}}\right)} - 1\right) \]
  3. Applied rewrites98.9%

    \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\frac{\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) - \frac{1}{e^{\frac{\pi}{s}} - -1}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} \cdot \frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) - \frac{1}{e^{\frac{\pi}{s}} - -1}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - 1}{\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) - \frac{1}{e^{\frac{\pi}{s}} - -1}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} + 1}\right)} \]
  4. Applied rewrites98.9%

    \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\frac{{\left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}, u, \frac{1}{e^{\frac{\pi}{s}} - -1}\right)}\right)}^{3} - 1}{{\left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}, u, \frac{1}{e^{\frac{\pi}{s}} - -1}\right)}\right)}^{2} + \left(1 + \frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}, u, \frac{1}{e^{\frac{\pi}{s}} - -1}\right)} \cdot 1\right)}\right)} \]
  5. Applied rewrites99.0%

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

Alternative 2: 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 3: 97.7% accurate, 1.3× speedup?

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

\\
\left(-s\right) \cdot \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)
\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 inf

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right)} - \color{blue}{1}\right) \]
  4. Applied rewrites97.7%

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

Alternative 4: 86.4% accurate, 1.3× speedup?

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

\\
\begin{array}{l}
t_0 := \frac{1}{2 + \frac{\pi}{s}}\\
\left(-s\right) \cdot \log \left(\frac{1}{t\_0 + \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - t\_0\right) \cdot u} - 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. 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.f3295.0

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  4. Applied rewrites95.0%

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{\color{blue}{2 + \frac{\pi}{s}}}\right) + \frac{1}{1 + e^{\frac{\pi}{s}}}} - 1\right) \]
  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.f3286.4

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) + \frac{1}{2 + \frac{\pi}{s}}} - 1\right) \]
  7. Applied rewrites86.4%

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

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\color{blue}{\frac{1}{2 + \frac{\pi}{s}} + u \cdot \left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right)}} - 1\right) \]
    3. lower-+.f3286.4

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

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\frac{1}{2 + \frac{\pi}{s}} + \color{blue}{\left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) \cdot u}} - 1\right) \]
    6. lower-*.f3286.4

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\frac{1}{2 + \frac{\pi}{s}} + \color{blue}{\left(\frac{1}{1 + e^{\frac{-\pi}{s}}} - \frac{1}{2 + \frac{\pi}{s}}\right) \cdot u}} - 1\right) \]
  9. Applied rewrites86.4%

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

Alternative 5: 86.4% 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. Applied rewrites98.9%

    \[\leadsto \left(-s\right) \cdot \log \left(\color{blue}{\left(\frac{\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) \cdot u}{{\left(\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) \cdot u\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - \frac{\frac{1}{e^{\frac{\pi}{s}} - -1}}{{\left(\left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right) \cdot u\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}}\right)} - 1\right) \]
  3. Applied rewrites98.9%

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

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

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}\right) - \frac{1}{e^{\frac{\pi}{s}} - -1}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - 1\right) \]
    3. lower-PI.f3294.9

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right) - \frac{1}{e^{\frac{\pi}{s}} - -1}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - 1\right) \]
  6. Applied rewrites94.9%

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

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

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right) - \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - 1\right) \]
    3. lower-PI.f3283.2

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right) - \frac{1}{2 + \frac{\pi}{s}}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{e^{\frac{\pi}{s}} - -1}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - 1\right) \]
  9. Applied rewrites83.2%

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

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

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right) - \frac{1}{2 + \frac{\pi}{s}}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - 1\right) \]
    3. lower-PI.f3283.3

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right) - \frac{1}{2 + \frac{\pi}{s}}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right)\right)}^{2} - {\left(e^{\frac{\pi}{s}} - -1\right)}^{-2}} - 1\right) \]
  12. Applied rewrites83.3%

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

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

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right) - \frac{1}{2 + \frac{\pi}{s}}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right)\right)}^{2} - {\left(2 + \frac{\mathsf{PI}\left(\right)}{\color{blue}{s}}\right)}^{-2}} - 1\right) \]
    3. lower-PI.f3286.3

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right) - \frac{1}{2 + \frac{\pi}{s}}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right)\right)}^{2} - {\left(2 + \frac{\pi}{s}\right)}^{-2}} - 1\right) \]
  15. Applied rewrites86.3%

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

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

      \[\leadsto \color{blue}{\log \left(\frac{u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right) - \frac{1}{2 + \frac{\pi}{s}}}{{\left(u \cdot \left(\frac{1}{e^{\frac{-\pi}{s}} - -1} - \frac{1}{2 + \frac{\pi}{s}}\right)\right)}^{2} - {\left(2 + \frac{\pi}{s}\right)}^{-2}} - 1\right) \cdot \left(-s\right)} \]
  17. Applied rewrites86.4%

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

Alternative 6: 24.8% accurate, 2.4× speedup?

\[\begin{array}{l} \\ \left(-s\right) \cdot \log \left(1 + 4 \cdot \frac{u \cdot \left(-0.25 \cdot \pi - 0.25 \cdot \pi\right) - -0.25 \cdot \pi}{s}\right) \end{array} \]
(FPCore (u s)
 :precision binary32
 (*
  (- s)
  (log
   (+ 1.0 (* 4.0 (/ (- (* u (- (* -0.25 PI) (* 0.25 PI))) (* -0.25 PI)) s))))))
float code(float u, float s) {
	return -s * logf((1.0f + (4.0f * (((u * ((-0.25f * ((float) M_PI)) - (0.25f * ((float) M_PI)))) - (-0.25f * ((float) M_PI))) / s))));
}
function code(u, s)
	return Float32(Float32(-s) * log(Float32(Float32(1.0) + Float32(Float32(4.0) * Float32(Float32(Float32(u * Float32(Float32(Float32(-0.25) * Float32(pi)) - Float32(Float32(0.25) * Float32(pi)))) - Float32(Float32(-0.25) * Float32(pi))) / s)))))
end
function tmp = code(u, s)
	tmp = -s * log((single(1.0) + (single(4.0) * (((u * ((single(-0.25) * single(pi)) - (single(0.25) * single(pi)))) - (single(-0.25) * single(pi))) / s))));
end
\begin{array}{l}

\\
\left(-s\right) \cdot \log \left(1 + 4 \cdot \frac{u \cdot \left(-0.25 \cdot \pi - 0.25 \cdot \pi\right) - -0.25 \cdot \pi}{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

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

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

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

      \[\leadsto \left(-s\right) \cdot \log \left(1 + 4 \cdot \frac{u \cdot \left(\frac{-1}{4} \cdot \mathsf{PI}\left(\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)}{\color{blue}{s}}\right) \]
  4. Applied rewrites24.8%

    \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(1 + 4 \cdot \frac{u \cdot \left(-0.25 \cdot \pi - 0.25 \cdot \pi\right) - -0.25 \cdot \pi}{s}\right)} \]
  5. Add Preprocessing

Alternative 7: 14.4% accurate, 4.4× speedup?

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

\\
\left(-s\right) \cdot \frac{s}{u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\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 u around inf

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

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

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

      \[\leadsto \left(-s\right) \cdot \frac{1}{u \cdot \left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \color{blue}{\frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}}\right)} \]
  4. Applied rewrites17.3%

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

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

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

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

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

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

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

      \[\leadsto \left(-s\right) \cdot \frac{s}{u \cdot \left(\frac{1}{4} \cdot \pi - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
    7. lower-PI.f3214.4

      \[\leadsto \left(-s\right) \cdot \frac{s}{u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right)} \]
  7. Applied rewrites14.4%

    \[\leadsto \left(-s\right) \cdot \frac{s}{\color{blue}{u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right)}} \]
  8. Add Preprocessing

Alternative 8: 11.5% accurate, 4.6× speedup?

\[\begin{array}{l} \\ 4 \cdot \left(\left(1 - \frac{0.5}{u}\right) \cdot \left(\left(\pi \cdot 0.5\right) \cdot u\right)\right) \end{array} \]
(FPCore (u s)
 :precision binary32
 (* 4.0 (* (- 1.0 (/ 0.5 u)) (* (* PI 0.5) u))))
float code(float u, float s) {
	return 4.0f * ((1.0f - (0.5f / u)) * ((((float) M_PI) * 0.5f) * u));
}
function code(u, s)
	return Float32(Float32(4.0) * Float32(Float32(Float32(1.0) - Float32(Float32(0.5) / u)) * Float32(Float32(Float32(pi) * Float32(0.5)) * u)))
end
function tmp = code(u, s)
	tmp = single(4.0) * ((single(1.0) - (single(0.5) / u)) * ((single(pi) * single(0.5)) * u));
end
\begin{array}{l}

\\
4 \cdot \left(\left(1 - \frac{0.5}{u}\right) \cdot \left(\left(\pi \cdot 0.5\right) \cdot u\right)\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

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
  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.f3211.5

      \[\leadsto 4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right) \]
  4. Applied rewrites11.5%

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right)} \]
  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-*.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 rewrites11.5%

    \[\leadsto 4 \cdot \left(\left(1 - \frac{0.25 \cdot \pi}{\left(\pi \cdot 0.5\right) \cdot u}\right) \cdot \color{blue}{\left(\left(\pi \cdot 0.5\right) \cdot u\right)}\right) \]
  7. Taylor expanded in u around 0

    \[\leadsto 4 \cdot \left(\left(1 - \frac{\frac{1}{2}}{u}\right) \cdot \left(\left(\pi \cdot \color{blue}{\frac{1}{2}}\right) \cdot u\right)\right) \]
  8. Step-by-step derivation
    1. lower-/.f3211.5

      \[\leadsto 4 \cdot \left(\left(1 - \frac{0.5}{u}\right) \cdot \left(\left(\pi \cdot 0.5\right) \cdot u\right)\right) \]
  9. Applied rewrites11.5%

    \[\leadsto 4 \cdot \left(\left(1 - \frac{0.5}{u}\right) \cdot \left(\left(\pi \cdot \color{blue}{0.5}\right) \cdot u\right)\right) \]
  10. Add Preprocessing

Alternative 9: 11.5% accurate, 4.6× speedup?

\[\begin{array}{l} \\ 4 \cdot \left(\frac{u - 0.5}{u} \cdot \left(\left(\pi \cdot 0.5\right) \cdot u\right)\right) \end{array} \]
(FPCore (u s) :precision binary32 (* 4.0 (* (/ (- u 0.5) u) (* (* PI 0.5) u))))
float code(float u, float s) {
	return 4.0f * (((u - 0.5f) / u) * ((((float) M_PI) * 0.5f) * u));
}
function code(u, s)
	return Float32(Float32(4.0) * Float32(Float32(Float32(u - Float32(0.5)) / u) * Float32(Float32(Float32(pi) * Float32(0.5)) * u)))
end
function tmp = code(u, s)
	tmp = single(4.0) * (((u - single(0.5)) / u) * ((single(pi) * single(0.5)) * u));
end
\begin{array}{l}

\\
4 \cdot \left(\frac{u - 0.5}{u} \cdot \left(\left(\pi \cdot 0.5\right) \cdot u\right)\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

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
  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.f3211.5

      \[\leadsto 4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right) \]
  4. Applied rewrites11.5%

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right)} \]
  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-*.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 rewrites11.5%

    \[\leadsto 4 \cdot \left(\left(1 - \frac{0.25 \cdot \pi}{\left(\pi \cdot 0.5\right) \cdot u}\right) \cdot \color{blue}{\left(\left(\pi \cdot 0.5\right) \cdot u\right)}\right) \]
  7. Taylor expanded in u around 0

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

      \[\leadsto 4 \cdot \left(\frac{u - \frac{1}{2}}{u} \cdot \left(\left(\pi \cdot \color{blue}{\frac{1}{2}}\right) \cdot u\right)\right) \]
    2. lower--.f3211.5

      \[\leadsto 4 \cdot \left(\frac{u - 0.5}{u} \cdot \left(\left(\pi \cdot 0.5\right) \cdot u\right)\right) \]
  9. Applied rewrites11.5%

    \[\leadsto 4 \cdot \left(\frac{u - 0.5}{u} \cdot \left(\color{blue}{\left(\pi \cdot 0.5\right)} \cdot u\right)\right) \]
  10. Add Preprocessing

Alternative 10: 11.5% accurate, 5.6× speedup?

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

\\
u \cdot \mathsf{fma}\left(-1, \frac{\pi}{u}, 2 \cdot \pi\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

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
  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.f3211.5

      \[\leadsto 4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right) \]
  4. Applied rewrites11.5%

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right)} \]
  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-*.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 rewrites11.5%

    \[\leadsto 4 \cdot \left(\left(1 - \frac{0.25 \cdot \pi}{\left(\pi \cdot 0.5\right) \cdot u}\right) \cdot \color{blue}{\left(\left(\pi \cdot 0.5\right) \cdot u\right)}\right) \]
  7. Taylor expanded in u around inf

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

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

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

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

      \[\leadsto u \cdot \mathsf{fma}\left(-1, \frac{\pi}{u}, 2 \cdot \mathsf{PI}\left(\right)\right) \]
    5. lower-*.f32N/A

      \[\leadsto u \cdot \mathsf{fma}\left(-1, \frac{\pi}{u}, 2 \cdot \mathsf{PI}\left(\right)\right) \]
    6. lower-PI.f3211.5

      \[\leadsto u \cdot \mathsf{fma}\left(-1, \frac{\pi}{u}, 2 \cdot \pi\right) \]
  9. Applied rewrites11.5%

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

Alternative 11: 11.5% accurate, 7.1× speedup?

\[\begin{array}{l} \\ \left(\pi \cdot \left(0.5 \cdot u - 0.25\right)\right) \cdot 4 \end{array} \]
(FPCore (u s) :precision binary32 (* (* PI (- (* 0.5 u) 0.25)) 4.0))
float code(float u, float s) {
	return (((float) M_PI) * ((0.5f * u) - 0.25f)) * 4.0f;
}
function code(u, s)
	return Float32(Float32(Float32(pi) * Float32(Float32(Float32(0.5) * u) - Float32(0.25))) * Float32(4.0))
end
function tmp = code(u, s)
	tmp = (single(pi) * ((single(0.5) * u) - single(0.25))) * single(4.0);
end
\begin{array}{l}

\\
\left(\pi \cdot \left(0.5 \cdot u - 0.25\right)\right) \cdot 4
\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

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
  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.f3211.5

      \[\leadsto 4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right) \]
  4. Applied rewrites11.5%

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right)} \]
  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-*.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 rewrites11.5%

    \[\leadsto 4 \cdot \left(\left(1 - \frac{0.25 \cdot \pi}{\left(\pi \cdot 0.5\right) \cdot u}\right) \cdot \color{blue}{\left(\left(\pi \cdot 0.5\right) \cdot u\right)}\right) \]
  7. Step-by-step derivation
    1. lift-*.f32N/A

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

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

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

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

      \[\leadsto \left(\left(1 - \frac{\frac{1}{4} \cdot \pi}{\left(\pi \cdot \frac{1}{2}\right) \cdot u}\right) \cdot \left(\left(\pi \cdot \frac{1}{2}\right) \cdot u\right)\right) \cdot 4 \]
    6. sub-to-mult-revN/A

      \[\leadsto \left(\left(\pi \cdot \frac{1}{2}\right) \cdot u - \frac{1}{4} \cdot \pi\right) \cdot 4 \]
    7. *-lft-identityN/A

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

      \[\leadsto \left(1 \cdot \left(\left(\pi \cdot \frac{1}{2}\right) \cdot u\right) - \frac{1}{4} \cdot \pi\right) \cdot \color{blue}{4} \]
  8. Applied rewrites11.5%

    \[\leadsto \left(\pi \cdot \left(0.5 \cdot u - 0.25\right)\right) \cdot \color{blue}{4} \]
  9. Add Preprocessing

Alternative 12: 11.5% accurate, 7.3× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(-1, \pi, 2 \cdot \left(u \cdot \pi\right)\right) \end{array} \]
(FPCore (u s) :precision binary32 (fma -1.0 PI (* 2.0 (* u PI))))
float code(float u, float s) {
	return fmaf(-1.0f, ((float) M_PI), (2.0f * (u * ((float) M_PI))));
}
function code(u, s)
	return fma(Float32(-1.0), Float32(pi), Float32(Float32(2.0) * Float32(u * Float32(pi))))
end
\begin{array}{l}

\\
\mathsf{fma}\left(-1, \pi, 2 \cdot \left(u \cdot \pi\right)\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

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right)} \]
  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.f3211.5

      \[\leadsto 4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right) \]
  4. Applied rewrites11.5%

    \[\leadsto \color{blue}{4 \cdot \left(u \cdot \left(0.25 \cdot \pi - -0.25 \cdot \pi\right) - 0.25 \cdot \pi\right)} \]
  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-*.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 rewrites11.5%

    \[\leadsto 4 \cdot \left(\left(1 - \frac{0.25 \cdot \pi}{\left(\pi \cdot 0.5\right) \cdot u}\right) \cdot \color{blue}{\left(\left(\pi \cdot 0.5\right) \cdot u\right)}\right) \]
  7. Taylor expanded in u around 0

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

      \[\leadsto \mathsf{fma}\left(-1, \mathsf{PI}\left(\right), 2 \cdot \left(u \cdot \mathsf{PI}\left(\right)\right)\right) \]
    2. lower-PI.f32N/A

      \[\leadsto \mathsf{fma}\left(-1, \pi, 2 \cdot \left(u \cdot \mathsf{PI}\left(\right)\right)\right) \]
    3. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(-1, \pi, 2 \cdot \left(u \cdot \mathsf{PI}\left(\right)\right)\right) \]
    4. lower-*.f32N/A

      \[\leadsto \mathsf{fma}\left(-1, \pi, 2 \cdot \left(u \cdot \mathsf{PI}\left(\right)\right)\right) \]
    5. lower-PI.f3211.5

      \[\leadsto \mathsf{fma}\left(-1, \pi, 2 \cdot \left(u \cdot \pi\right)\right) \]
  9. Applied rewrites11.5%

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

Alternative 13: 11.3% 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.f3211.3

      \[\leadsto -1 \cdot \pi \]
  4. Applied rewrites11.3%

    \[\leadsto \color{blue}{-1 \cdot \pi} \]
  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.f3211.3

      \[\leadsto -\pi \]
  6. Applied rewrites11.3%

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

Reproduce

?
herbie shell --seed 2025156 
(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))))