Sample trimmed logistic on [-pi, pi]

Percentage Accurate: 99.0% → 99.0%
Time: 17.9s
Alternatives: 15
Speedup: 1.0×

Specification

?
\[\left(2.328306437 \cdot 10^{-10} \leq u \land u \leq 1\right) \land \left(0 \leq s \land s \leq 1.0651631\right)\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\\ \left(-s\right) \cdot \log \left(\frac{1}{u \cdot \left(\frac{1}{1 + e^{\frac{-\mathsf{PI}\left(\right)}{s}}} - t\_0\right) + t\_0} - 1\right) \end{array} \end{array} \]
(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)))))
\begin{array}{l}

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

Sampling outcomes in binary32 precision:

Local Percentage Accuracy vs ?

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

Accuracy vs Speed?

Herbie found 15 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: 99.0% accurate, 1.0× speedup?

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

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

Alternative 1: 99.0% accurate, 0.2× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\\ t_1 := \mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - t\_0, u, t\_0\right)\\ \left(-s\right) \cdot \log \left(\frac{{t\_1}^{-3} - 1}{\frac{1}{t\_1} + \left({t\_1}^{-2} + 1\right)}\right) \end{array} \end{array} \]
(FPCore (u s)
 :precision binary32
 (let* ((t_0 (exp (- (log1p (exp (/ (PI) s))))))
        (t_1 (fma (- (exp (- (log1p (exp (/ (- (PI)) s))))) t_0) u t_0)))
   (*
    (- s)
    (log (/ (- (pow t_1 -3.0) 1.0) (+ (/ 1.0 t_1) (+ (pow t_1 -2.0) 1.0)))))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\\
t_1 := \mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - t\_0, u, t\_0\right)\\
\left(-s\right) \cdot \log \left(\frac{{t\_1}^{-3} - 1}{\frac{1}{t\_1} + \left({t\_1}^{-2} + 1\right)}\right)
\end{array}
\end{array}
Derivation
  1. Initial program 99.0%

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

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

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

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

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

    \[\leadsto \color{blue}{\left(-s\right) \cdot \log \left(\mathsf{expm1}\left(-\log \left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)\right)\right)} \]
  5. Applied rewrites99.1%

    \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\frac{{\left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)}^{-3} - 1}{\frac{1}{\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)} + \left({\left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)}^{-2} + 1\right)}\right)} \]
  6. Add Preprocessing

Alternative 2: 99.0% accurate, 0.2× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\\ t_1 := \mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - t\_0, u, t\_0\right)\\ \left(-s\right) \cdot \log \left(\frac{{t\_1}^{-2} - 1}{\frac{1}{t\_1} + 1}\right) \end{array} \end{array} \]
(FPCore (u s)
 :precision binary32
 (let* ((t_0 (exp (- (log1p (exp (/ (PI) s))))))
        (t_1 (fma (- (exp (- (log1p (exp (/ (- (PI)) s))))) t_0) u t_0)))
   (* (- s) (log (/ (- (pow t_1 -2.0) 1.0) (+ (/ 1.0 t_1) 1.0))))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\\
t_1 := \mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - t\_0, u, t\_0\right)\\
\left(-s\right) \cdot \log \left(\frac{{t\_1}^{-2} - 1}{\frac{1}{t\_1} + 1}\right)
\end{array}
\end{array}
Derivation
  1. Initial program 99.0%

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

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

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

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

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

    \[\leadsto \color{blue}{\left(-s\right) \cdot \log \left(\mathsf{expm1}\left(-\log \left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)\right)\right)} \]
  5. Step-by-step derivation
    1. lift-expm1.f32N/A

      \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(e^{-\log \left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)} - 1\right)} \]
    2. flip--N/A

      \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\frac{e^{-\log \left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)} \cdot e^{-\log \left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)} - 1 \cdot 1}{e^{-\log \left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)} + 1}\right)} \]
  6. Applied rewrites99.0%

    \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\frac{{\left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)}^{-2} - 1}{\frac{1}{\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)} + 1}\right)} \]
  7. Add Preprocessing

Alternative 3: 99.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\\ \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - t\_0, u, t\_0\right)} - 1\right) \end{array} \end{array} \]
(FPCore (u s)
 :precision binary32
 (let* ((t_0 (/ 1.0 (+ (exp (/ (PI) s)) 1.0))))
   (*
    (- s)
    (log
     (-
      (/ 1.0 (fma (- (/ 1.0 (+ (exp (/ (- (PI)) s)) 1.0)) t_0) u t_0))
      1.0)))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\\
\left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - t\_0, u, t\_0\right)} - 1\right)
\end{array}
\end{array}
Derivation
  1. Initial program 99.0%

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

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

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

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

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

Alternative 4: 97.5% accurate, 1.3× speedup?

\[\begin{array}{l} \\ \left(-s\right) \cdot \log \left(\frac{1}{\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u} - 1\right) \end{array} \]
(FPCore (u s)
 :precision binary32
 (*
  (- s)
  (log
   (-
    (/
     1.0
     (*
      (- (/ 1.0 (+ (exp (/ (- (PI)) s)) 1.0)) (/ 1.0 (+ (exp (/ (PI) s)) 1.0)))
      u))
    1.0))))
\begin{array}{l}

\\
\left(-s\right) \cdot \log \left(\frac{1}{\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u} - 1\right)
\end{array}
Derivation
  1. Initial program 99.0%

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

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

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\color{blue}{\left(\frac{1}{1 + e^{-1 \cdot \frac{\mathsf{PI}\left(\right)}{s}}} - \frac{1}{1 + e^{\frac{\mathsf{PI}\left(\right)}{s}}}\right) \cdot u}} - 1\right) \]
  5. Applied rewrites98.0%

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

Alternative 5: 92.0% accurate, 1.5× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := -\mathsf{PI}\left(\right)\\ \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{t\_0}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, t\_0\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \end{array} \end{array} \]
(FPCore (u s)
 :precision binary32
 (let* ((t_0 (- (PI))))
   (*
    (- s)
    (log
     (-
      (/
       1.0
       (fma
        (- (/ 1.0 (+ (exp (/ t_0 s)) 1.0)) (/ 1.0 (+ (+ (/ (PI) s) 1.0) 1.0)))
        u
        (/
         1.0
         (+ (fma (/ (fma (/ (* (PI) (PI)) s) -0.5 t_0) s) -1.0 1.0) 1.0))))
      1.0)))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := -\mathsf{PI}\left(\right)\\
\left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{t\_0}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, t\_0\right)}{s}, -1, 1\right) + 1}\right)} - 1\right)
\end{array}
\end{array}
Derivation
  1. Initial program 99.0%

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

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

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

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

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

    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(1 + \frac{\mathsf{PI}\left(\right)}{s}\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
  7. Step-by-step derivation
    1. Applied rewrites94.4%

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

      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\left(1 + -1 \cdot \frac{-1 \cdot \mathsf{PI}\left(\right) + \frac{-1}{2} \cdot \frac{{\mathsf{PI}\left(\right)}^{2}}{s}}{s}\right) + 1}\right)} - 1\right) \]
    3. Step-by-step derivation
      1. Applied rewrites92.0%

        \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \]
      2. Add Preprocessing

      Alternative 6: 92.0% accurate, 1.5× speedup?

      \[\begin{array}{l} \\ \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{\mathsf{fma}\left(\mathsf{PI}\left(\right) + s, s, \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot 0.5\right)}{s \cdot s} + 1}\right)} - 1\right) \end{array} \]
      (FPCore (u s)
       :precision binary32
       (*
        (- s)
        (log
         (-
          (/
           1.0
           (fma
            (-
             (/ 1.0 (+ (exp (/ (- (PI)) s)) 1.0))
             (/ 1.0 (+ (+ (/ (PI) s) 1.0) 1.0)))
            u
            (/ 1.0 (+ (/ (fma (+ (PI) s) s (* (* (PI) (PI)) 0.5)) (* s s)) 1.0))))
          1.0))))
      \begin{array}{l}
      
      \\
      \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{\mathsf{fma}\left(\mathsf{PI}\left(\right) + s, s, \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot 0.5\right)}{s \cdot s} + 1}\right)} - 1\right)
      \end{array}
      
      Derivation
      1. Initial program 99.0%

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

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

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

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

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

        \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(1 + \frac{\mathsf{PI}\left(\right)}{s}\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
      7. Step-by-step derivation
        1. Applied rewrites94.4%

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

          \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\left(1 + -1 \cdot \frac{-1 \cdot \mathsf{PI}\left(\right) + \frac{-1}{2} \cdot \frac{{\mathsf{PI}\left(\right)}^{2}}{s}}{s}\right) + 1}\right)} - 1\right) \]
        3. Step-by-step derivation
          1. Applied rewrites92.0%

            \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \]
          2. Taylor expanded in s around 0

            \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{\frac{1}{2} \cdot {\mathsf{PI}\left(\right)}^{2} + s \cdot \left(s + \mathsf{PI}\left(\right)\right)}{{s}^{2}} + 1}\right)} - 1\right) \]
          3. Step-by-step derivation
            1. Applied rewrites92.0%

              \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{\mathsf{fma}\left(\mathsf{PI}\left(\right) + s, s, \left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot 0.5\right)}{s \cdot s} + 1}\right)} - 1\right) \]
            2. Add Preprocessing

            Alternative 7: 92.0% accurate, 1.5× speedup?

            \[\begin{array}{l} \\ \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{\mathsf{fma}\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 0.5, \mathsf{PI}\left(\right) \cdot s\right)}{s \cdot s} + 1}\right)} - 1\right) \end{array} \]
            (FPCore (u s)
             :precision binary32
             (*
              (- s)
              (log
               (-
                (/
                 1.0
                 (fma
                  (-
                   (/ 1.0 (+ (exp (/ (- (PI)) s)) 1.0))
                   (/ 1.0 (+ (+ (/ (PI) s) 1.0) 1.0)))
                  u
                  (/ 1.0 (+ (/ (fma (* (PI) (PI)) 0.5 (* (PI) s)) (* s s)) 1.0))))
                1.0))))
            \begin{array}{l}
            
            \\
            \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{\mathsf{fma}\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 0.5, \mathsf{PI}\left(\right) \cdot s\right)}{s \cdot s} + 1}\right)} - 1\right)
            \end{array}
            
            Derivation
            1. Initial program 99.0%

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

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

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

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

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

              \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(1 + \frac{\mathsf{PI}\left(\right)}{s}\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
            7. Step-by-step derivation
              1. Applied rewrites94.4%

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

                \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\left(1 + -1 \cdot \frac{-1 \cdot \mathsf{PI}\left(\right) + \frac{-1}{2} \cdot \frac{{\mathsf{PI}\left(\right)}^{2}}{s}}{s}\right) + 1}\right)} - 1\right) \]
              3. Step-by-step derivation
                1. Applied rewrites92.0%

                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \]
                2. Taylor expanded in s around 0

                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{\frac{1}{2} \cdot {\mathsf{PI}\left(\right)}^{2} + s \cdot \mathsf{PI}\left(\right)}{{s}^{2}} + 1}\right)} - 1\right) \]
                3. Step-by-step derivation
                  1. Applied rewrites92.0%

                    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{\mathsf{fma}\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right), 0.5, \mathsf{PI}\left(\right) \cdot s\right)}{s \cdot s} + 1}\right)} - 1\right) \]
                  2. Add Preprocessing

                  Alternative 8: 92.0% accurate, 1.5× speedup?

                  \[\begin{array}{l} \\ \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{0.5}{s} \cdot \frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s} + 1}\right)} - 1\right) \end{array} \]
                  (FPCore (u s)
                   :precision binary32
                   (*
                    (- s)
                    (log
                     (-
                      (/
                       1.0
                       (fma
                        (-
                         (/ 1.0 (+ (exp (/ (- (PI)) s)) 1.0))
                         (/ 1.0 (+ (+ (/ (PI) s) 1.0) 1.0)))
                        u
                        (/ 1.0 (+ (* (/ 0.5 s) (/ (* (PI) (PI)) s)) 1.0))))
                      1.0))))
                  \begin{array}{l}
                  
                  \\
                  \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{0.5}{s} \cdot \frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s} + 1}\right)} - 1\right)
                  \end{array}
                  
                  Derivation
                  1. Initial program 99.0%

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

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

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

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

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

                    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(1 + \frac{\mathsf{PI}\left(\right)}{s}\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
                  7. Step-by-step derivation
                    1. Applied rewrites94.4%

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

                      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\left(1 + -1 \cdot \frac{-1 \cdot \mathsf{PI}\left(\right) + \frac{-1}{2} \cdot \frac{{\mathsf{PI}\left(\right)}^{2}}{s}}{s}\right) + 1}\right)} - 1\right) \]
                    3. Step-by-step derivation
                      1. Applied rewrites92.0%

                        \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \]
                      2. Taylor expanded in s around 0

                        \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{1}{2} \cdot \frac{{\mathsf{PI}\left(\right)}^{2}}{{s}^{2}} + 1}\right)} - 1\right) \]
                      3. Step-by-step derivation
                        1. Applied rewrites91.9%

                          \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\frac{0.5}{s} \cdot \frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s} + 1}\right)} - 1\right) \]
                        2. Add Preprocessing

                        Alternative 9: 85.7% accurate, 1.6× speedup?

                        \[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}\\ \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - t\_0, u, t\_0\right)} - 1\right) \end{array} \end{array} \]
                        (FPCore (u s)
                         :precision binary32
                         (let* ((t_0 (/ 1.0 (+ (+ (/ (PI) s) 1.0) 1.0))))
                           (*
                            (- s)
                            (log
                             (-
                              (/ 1.0 (fma (- (/ 1.0 (+ (exp (/ (- (PI)) s)) 1.0)) t_0) u t_0))
                              1.0)))))
                        \begin{array}{l}
                        
                        \\
                        \begin{array}{l}
                        t_0 := \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}\\
                        \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - t\_0, u, t\_0\right)} - 1\right)
                        \end{array}
                        \end{array}
                        
                        Derivation
                        1. Initial program 99.0%

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

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

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

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

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

                          \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(1 + \frac{\mathsf{PI}\left(\right)}{s}\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
                        7. Step-by-step derivation
                          1. Applied rewrites94.4%

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

                            \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\left(1 + \frac{\mathsf{PI}\left(\right)}{s}\right) + 1}\right)} - 1\right) \]
                          3. Step-by-step derivation
                            1. Applied rewrites86.2%

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

                            Alternative 10: 37.7% accurate, 1.8× speedup?

                            \[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{\mathsf{PI}\left(\right)}{s}\\ \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(0.5 - \frac{1}{\left(t\_0 + 1\right) + 1}, u, \frac{1}{e^{t\_0} + 1}\right)} - 1\right) \end{array} \end{array} \]
                            (FPCore (u s)
                             :precision binary32
                             (let* ((t_0 (/ (PI) s)))
                               (*
                                (- s)
                                (log
                                 (-
                                  (/
                                   1.0
                                   (fma (- 0.5 (/ 1.0 (+ (+ t_0 1.0) 1.0))) u (/ 1.0 (+ (exp t_0) 1.0))))
                                  1.0)))))
                            \begin{array}{l}
                            
                            \\
                            \begin{array}{l}
                            t_0 := \frac{\mathsf{PI}\left(\right)}{s}\\
                            \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(0.5 - \frac{1}{\left(t\_0 + 1\right) + 1}, u, \frac{1}{e^{t\_0} + 1}\right)} - 1\right)
                            \end{array}
                            \end{array}
                            
                            Derivation
                            1. Initial program 99.0%

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

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

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

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

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

                              \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(1 + \frac{\mathsf{PI}\left(\right)}{s}\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
                            7. Step-by-step derivation
                              1. Applied rewrites94.4%

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

                                \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{2} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
                              3. Step-by-step derivation
                                1. Applied rewrites37.5%

                                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(0.5 - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
                                2. Add Preprocessing

                                Alternative 11: 36.8% accurate, 2.4× speedup?

                                \[\begin{array}{l} \\ \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(0.5 - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \end{array} \]
                                (FPCore (u s)
                                 :precision binary32
                                 (*
                                  (- s)
                                  (log
                                   (-
                                    (/
                                     1.0
                                     (fma
                                      (- 0.5 (/ 1.0 (+ (+ (/ (PI) s) 1.0) 1.0)))
                                      u
                                      (/
                                       1.0
                                       (+ (fma (/ (fma (/ (* (PI) (PI)) s) -0.5 (- (PI))) s) -1.0 1.0) 1.0))))
                                    1.0))))
                                \begin{array}{l}
                                
                                \\
                                \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(0.5 - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right)
                                \end{array}
                                
                                Derivation
                                1. Initial program 99.0%

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

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

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

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

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

                                  \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(1 + \frac{\mathsf{PI}\left(\right)}{s}\right) + 1}, u, \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right)} - 1\right) \]
                                7. Step-by-step derivation
                                  1. Applied rewrites94.4%

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

                                    \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\left(1 + -1 \cdot \frac{-1 \cdot \mathsf{PI}\left(\right) + \frac{-1}{2} \cdot \frac{{\mathsf{PI}\left(\right)}^{2}}{s}}{s}\right) + 1}\right)} - 1\right) \]
                                  3. Step-by-step derivation
                                    1. Applied rewrites92.0%

                                      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \]
                                    2. Taylor expanded in s around inf

                                      \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(\frac{1}{2} - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, \frac{-1}{2}, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \]
                                    3. Step-by-step derivation
                                      1. Applied rewrites37.1%

                                        \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\mathsf{fma}\left(0.5 - \frac{1}{\left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) + 1}, u, \frac{1}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\frac{\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)}{s}, -0.5, -\mathsf{PI}\left(\right)\right)}{s}, -1, 1\right) + 1}\right)} - 1\right) \]
                                      2. Add Preprocessing

                                      Alternative 12: 24.9% accurate, 3.2× speedup?

                                      \[\begin{array}{l} \\ \left(-s\right) \cdot \log \left(\mathsf{fma}\left(\frac{\mathsf{fma}\left(0.5, \mathsf{PI}\left(\right), \frac{\left(\left(0.5 \cdot \mathsf{PI}\left(\right)\right) \cdot -1\right) \cdot u}{0.5}\right)}{s}, 2, 1\right)\right) \end{array} \]
                                      (FPCore (u s)
                                       :precision binary32
                                       (*
                                        (- s)
                                        (log
                                         (fma (/ (fma 0.5 (PI) (/ (* (* (* 0.5 (PI)) -1.0) u) 0.5)) s) 2.0 1.0))))
                                      \begin{array}{l}
                                      
                                      \\
                                      \left(-s\right) \cdot \log \left(\mathsf{fma}\left(\frac{\mathsf{fma}\left(0.5, \mathsf{PI}\left(\right), \frac{\left(\left(0.5 \cdot \mathsf{PI}\left(\right)\right) \cdot -1\right) \cdot u}{0.5}\right)}{s}, 2, 1\right)\right)
                                      \end{array}
                                      
                                      Derivation
                                      1. Initial program 99.0%

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

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

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

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

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

                                        \[\leadsto \color{blue}{\left(-s\right) \cdot \log \left(\mathsf{expm1}\left(-\log \left(\mathsf{fma}\left(e^{-\mathsf{log1p}\left(e^{\frac{-\mathsf{PI}\left(\right)}{s}}\right)} - e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}, u, e^{-\mathsf{log1p}\left(e^{\frac{\mathsf{PI}\left(\right)}{s}}\right)}\right)\right)\right)\right)} \]
                                      5. Taylor expanded in s around -inf

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

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

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

                                          \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(\frac{\frac{1}{2} \cdot \mathsf{PI}\left(\right) + \frac{u \cdot \left(\frac{-1}{2} \cdot \left(\mathsf{PI}\left(\right) \cdot e^{\mathsf{neg}\left(\log 2\right)}\right) - \frac{1}{2} \cdot \left(\mathsf{PI}\left(\right) \cdot e^{\mathsf{neg}\left(\log 2\right)}\right)\right)}{e^{\mathsf{neg}\left(\log 2\right)}}}{s}, 2, 1\right)\right)} \]
                                      7. Applied rewrites25.3%

                                        \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(\frac{\mathsf{fma}\left(0.5, \mathsf{PI}\left(\right), \frac{\left(\left(0.5 \cdot \mathsf{PI}\left(\right)\right) \cdot -1\right) \cdot u}{0.5}\right)}{s}, 2, 1\right)\right)} \]
                                      8. Add Preprocessing

                                      Alternative 13: 11.8% accurate, 23.2× speedup?

                                      \[\begin{array}{l} \\ \mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), 0.5, -0.25 \cdot \mathsf{PI}\left(\right)\right) \cdot 4 \end{array} \]
                                      (FPCore (u s) :precision binary32 (* (fma (* u (PI)) 0.5 (* -0.25 (PI))) 4.0))
                                      \begin{array}{l}
                                      
                                      \\
                                      \mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), 0.5, -0.25 \cdot \mathsf{PI}\left(\right)\right) \cdot 4
                                      \end{array}
                                      
                                      Derivation
                                      1. Initial program 99.0%

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

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

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

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

                                          \[\leadsto \color{blue}{\left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) + \left(\mathsf{neg}\left(\frac{1}{4}\right)\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot 4 \]
                                        4. distribute-rgt-out--N/A

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

                                          \[\leadsto \left(u \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{\frac{1}{2}}\right) + \left(\mathsf{neg}\left(\frac{1}{4}\right)\right) \cdot \mathsf{PI}\left(\right)\right) \cdot 4 \]
                                        6. associate-*r*N/A

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

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

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

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

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

                                          \[\leadsto \mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), \frac{1}{2}, \color{blue}{\frac{-1}{4} \cdot \mathsf{PI}\left(\right)}\right) \cdot 4 \]
                                        12. lower-PI.f3211.2

                                          \[\leadsto \mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), 0.5, -0.25 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot 4 \]
                                      5. Applied rewrites11.2%

                                        \[\leadsto \color{blue}{\mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), 0.5, -0.25 \cdot \mathsf{PI}\left(\right)\right) \cdot 4} \]
                                      6. Add Preprocessing

                                      Alternative 14: 11.8% accurate, 23.2× speedup?

                                      \[\begin{array}{l} \\ \mathsf{fma}\left(0.5 \cdot \mathsf{PI}\left(\right), u, -0.25 \cdot \mathsf{PI}\left(\right)\right) \cdot 4 \end{array} \]
                                      (FPCore (u s) :precision binary32 (* (fma (* 0.5 (PI)) u (* -0.25 (PI))) 4.0))
                                      \begin{array}{l}
                                      
                                      \\
                                      \mathsf{fma}\left(0.5 \cdot \mathsf{PI}\left(\right), u, -0.25 \cdot \mathsf{PI}\left(\right)\right) \cdot 4
                                      \end{array}
                                      
                                      Derivation
                                      1. Initial program 99.0%

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

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

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

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

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

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

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

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

                                          \[\leadsto \color{blue}{\left(u \cdot \left(\frac{1}{4} \cdot \mathsf{PI}\left(\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right)\right) + \left(\mathsf{neg}\left(\frac{1}{4}\right)\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot 4 \]
                                        4. distribute-rgt-out--N/A

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

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

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

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

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

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

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

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

                                          \[\leadsto \mathsf{fma}\left(\frac{1}{2} \cdot \mathsf{PI}\left(\right), u, \color{blue}{\frac{-1}{4} \cdot \mathsf{PI}\left(\right)}\right) \cdot 4 \]
                                        13. lower-PI.f3211.2

                                          \[\leadsto \mathsf{fma}\left(0.5 \cdot \mathsf{PI}\left(\right), u, -0.25 \cdot \color{blue}{\mathsf{PI}\left(\right)}\right) \cdot 4 \]
                                      8. Applied rewrites11.2%

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

                                      Alternative 15: 11.5% accurate, 170.0× speedup?

                                      \[\begin{array}{l} \\ -\mathsf{PI}\left(\right) \end{array} \]
                                      (FPCore (u s) :precision binary32 (- (PI)))
                                      \begin{array}{l}
                                      
                                      \\
                                      -\mathsf{PI}\left(\right)
                                      \end{array}
                                      
                                      Derivation
                                      1. Initial program 99.0%

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

                                        \[\leadsto \color{blue}{-1 \cdot \mathsf{PI}\left(\right)} \]
                                      4. Step-by-step derivation
                                        1. mul-1-negN/A

                                          \[\leadsto \color{blue}{\mathsf{neg}\left(\mathsf{PI}\left(\right)\right)} \]
                                        2. lower-neg.f32N/A

                                          \[\leadsto \color{blue}{-\mathsf{PI}\left(\right)} \]
                                        3. lower-PI.f3211.0

                                          \[\leadsto -\color{blue}{\mathsf{PI}\left(\right)} \]
                                      5. Applied rewrites11.0%

                                        \[\leadsto \color{blue}{-\mathsf{PI}\left(\right)} \]
                                      6. Add Preprocessing

                                      Reproduce

                                      ?
                                      herbie shell --seed 2024359 
                                      (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))))