Sample trimmed logistic on [-pi, pi]

Percentage Accurate: 99.0% → 99.0%
Time: 19.4s
Alternatives: 7
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 7 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, 1.0× speedup?

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

\\
\begin{array}{l}
t_0 := \frac{-1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\\
\log \left(-1 - \frac{-1}{\left(t\_0 - \frac{-1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u - t\_0}\right) \cdot \left(-s\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. Final simplification99.0%

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

Alternative 2: 28.6% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{\mathsf{PI}\left(\right)}{s}\\ t_1 := \frac{-1}{e^{t\_0} + 1}\\ \mathbf{if}\;\log \left(-1 - \frac{-1}{\left(t\_1 - \frac{-1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u - t\_1}\right) \cdot \left(-s\right) \leq -2.999999970665357 \cdot 10^{-10}:\\ \;\;\;\;\log \left(\left(\frac{t\_0 + 1}{u} - 2 \cdot t\_0\right) \cdot u\right) \cdot \left(-s\right)\\ \mathbf{else}:\\ \;\;\;\;\log \left(\mathsf{fma}\left(\mathsf{fma}\left({\left({\mathsf{PI}\left(\right)}^{3}\right)}^{0.3333333333333333} \cdot u, -0.5, 0.25 \cdot \mathsf{PI}\left(\right)\right), \frac{4}{s}, 1\right)\right) \cdot \left(-s\right)\\ \end{array} \end{array} \]
(FPCore (u s)
 :precision binary32
 (let* ((t_0 (/ (PI) s)) (t_1 (/ -1.0 (+ (exp t_0) 1.0))))
   (if (<=
        (*
         (log
          (-
           -1.0
           (/
            -1.0
            (- (* (- t_1 (/ -1.0 (+ (exp (/ (- (PI)) s)) 1.0))) u) t_1))))
         (- s))
        -2.999999970665357e-10)
     (* (log (* (- (/ (+ t_0 1.0) u) (* 2.0 t_0)) u)) (- s))
     (*
      (log
       (fma
        (fma (* (pow (pow (PI) 3.0) 0.3333333333333333) u) -0.5 (* 0.25 (PI)))
        (/ 4.0 s)
        1.0))
      (- s)))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \frac{\mathsf{PI}\left(\right)}{s}\\
t_1 := \frac{-1}{e^{t\_0} + 1}\\
\mathbf{if}\;\log \left(-1 - \frac{-1}{\left(t\_1 - \frac{-1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u - t\_1}\right) \cdot \left(-s\right) \leq -2.999999970665357 \cdot 10^{-10}:\\
\;\;\;\;\log \left(\left(\frac{t\_0 + 1}{u} - 2 \cdot t\_0\right) \cdot u\right) \cdot \left(-s\right)\\

\mathbf{else}:\\
\;\;\;\;\log \left(\mathsf{fma}\left(\mathsf{fma}\left({\left({\mathsf{PI}\left(\right)}^{3}\right)}^{0.3333333333333333} \cdot u, -0.5, 0.25 \cdot \mathsf{PI}\left(\right)\right), \frac{4}{s}, 1\right)\right) \cdot \left(-s\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f32 (neg.f32 s) (log.f32 (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 (*.f32 u (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (neg.f32 (PI.f32)) s)))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) #s(literal 1 binary32)))) < -2.99999997e-10

    1. Initial program 99.3%

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

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

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

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

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

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

        \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(u \cdot \left(\frac{-1}{4} \cdot \mathsf{PI}\left(\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right), \frac{4}{s}, 1\right)\right)} \]
    5. Applied rewrites6.9%

      \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), -0.5, 0.25 \cdot \mathsf{PI}\left(\right)\right), \frac{4}{s}, 1\right)\right)} \]
    6. Taylor expanded in u around -inf

      \[\leadsto \left(-s\right) \cdot \log \left(-1 \cdot \color{blue}{\left(u \cdot \left(-1 \cdot \frac{1 + \frac{\mathsf{PI}\left(\right)}{s}}{u} + 2 \cdot \frac{\mathsf{PI}\left(\right)}{s}\right)\right)}\right) \]
    7. Step-by-step derivation
      1. Applied rewrites30.5%

        \[\leadsto \left(-s\right) \cdot \log \left(\left(2 \cdot \frac{\mathsf{PI}\left(\right)}{s} - \frac{\frac{\mathsf{PI}\left(\right)}{s} + 1}{u}\right) \cdot \color{blue}{\left(-u\right)}\right) \]

      if -2.99999997e-10 < (*.f32 (neg.f32 s) (log.f32 (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 (*.f32 u (-.f32 (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (neg.f32 (PI.f32)) s)))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) (/.f32 #s(literal 1 binary32) (+.f32 #s(literal 1 binary32) (exp.f32 (/.f32 (PI.f32) s)))))) #s(literal 1 binary32))))

      1. Initial program 98.9%

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

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

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

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

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

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

          \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(u \cdot \left(\frac{-1}{4} \cdot \mathsf{PI}\left(\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right), \frac{4}{s}, 1\right)\right)} \]
      5. Applied rewrites11.5%

        \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), -0.5, 0.25 \cdot \mathsf{PI}\left(\right)\right), \frac{4}{s}, 1\right)\right)} \]
      6. Step-by-step derivation
        1. Applied rewrites28.0%

          \[\leadsto \left(-s\right) \cdot \log \left(\mathsf{fma}\left(\mathsf{fma}\left(u \cdot {\left({\mathsf{PI}\left(\right)}^{3}\right)}^{0.3333333333333333}, -0.5, 0.25 \cdot \mathsf{PI}\left(\right)\right), \frac{4}{s}, 1\right)\right) \]
      7. Recombined 2 regimes into one program.
      8. Final simplification28.7%

        \[\leadsto \begin{array}{l} \mathbf{if}\;\log \left(-1 - \frac{-1}{\left(\frac{-1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1} - \frac{-1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u - \frac{-1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}}\right) \cdot \left(-s\right) \leq -2.999999970665357 \cdot 10^{-10}:\\ \;\;\;\;\log \left(\left(\frac{\frac{\mathsf{PI}\left(\right)}{s} + 1}{u} - 2 \cdot \frac{\mathsf{PI}\left(\right)}{s}\right) \cdot u\right) \cdot \left(-s\right)\\ \mathbf{else}:\\ \;\;\;\;\log \left(\mathsf{fma}\left(\mathsf{fma}\left({\left({\mathsf{PI}\left(\right)}^{3}\right)}^{0.3333333333333333} \cdot u, -0.5, 0.25 \cdot \mathsf{PI}\left(\right)\right), \frac{4}{s}, 1\right)\right) \cdot \left(-s\right)\\ \end{array} \]
      9. Add Preprocessing

      Alternative 3: 97.5% accurate, 1.3× speedup?

      \[\begin{array}{l} \\ \log \left(\frac{1}{\left(\frac{-1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1} - \frac{-1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u} - 1\right) \cdot \left(-s\right) \end{array} \]
      (FPCore (u s)
       :precision binary32
       (*
        (log
         (-
          (/
           1.0
           (*
            (-
             (/ -1.0 (+ (exp (/ (PI) s)) 1.0))
             (/ -1.0 (+ (exp (/ (- (PI)) s)) 1.0)))
            u))
          1.0))
        (- s)))
      \begin{array}{l}
      
      \\
      \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) \cdot \left(-s\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 rewrites98.7%

        \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\color{blue}{\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u}} - 1\right) \]
      6. Final simplification98.7%

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

      Alternative 4: 25.1% accurate, 4.2× speedup?

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

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

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

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

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

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

          \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(u \cdot \left(\frac{-1}{4} \cdot \mathsf{PI}\left(\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right), \frac{4}{s}, 1\right)\right)} \]
      5. Applied rewrites10.4%

        \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), -0.5, 0.25 \cdot \mathsf{PI}\left(\right)\right), \frac{4}{s}, 1\right)\right)} \]
      6. Taylor expanded in u around 0

        \[\leadsto \left(-s\right) \cdot \log \left(1 + \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}}\right) \]
      7. Step-by-step derivation
        1. Applied rewrites25.0%

          \[\leadsto \left(-s\right) \cdot \log \left(\frac{\mathsf{PI}\left(\right)}{s} + \color{blue}{1}\right) \]
        2. Final simplification25.0%

          \[\leadsto \log \left(\frac{\mathsf{PI}\left(\right)}{s} + 1\right) \cdot \left(-s\right) \]
        3. Add Preprocessing

        Alternative 5: 13.9% accurate, 14.6× speedup?

        \[\begin{array}{l} \\ \frac{\mathsf{PI}\left(\right)}{s} \cdot \frac{\left(-s\right) \cdot s}{s} \end{array} \]
        (FPCore (u s) :precision binary32 (* (/ (PI) s) (/ (* (- s) s) s)))
        \begin{array}{l}
        
        \\
        \frac{\mathsf{PI}\left(\right)}{s} \cdot \frac{\left(-s\right) \cdot s}{s}
        \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

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

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

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

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

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

            \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(u \cdot \left(\frac{-1}{4} \cdot \mathsf{PI}\left(\right) - \frac{1}{4} \cdot \mathsf{PI}\left(\right)\right) - \frac{-1}{4} \cdot \mathsf{PI}\left(\right), \frac{4}{s}, 1\right)\right)} \]
        5. Applied rewrites10.4%

          \[\leadsto \left(-s\right) \cdot \log \color{blue}{\left(\mathsf{fma}\left(\mathsf{fma}\left(u \cdot \mathsf{PI}\left(\right), -0.5, 0.25 \cdot \mathsf{PI}\left(\right)\right), \frac{4}{s}, 1\right)\right)} \]
        6. Taylor expanded in u around 0

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

            \[\leadsto \left(-s\right) \cdot \color{blue}{\frac{\mathsf{PI}\left(\right)}{s}} \]
          2. lower-PI.f3210.5

            \[\leadsto \left(-s\right) \cdot \frac{\color{blue}{\mathsf{PI}\left(\right)}}{s} \]
        8. Applied rewrites10.5%

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

            \[\leadsto \color{blue}{\left(\mathsf{neg}\left(s\right)\right)} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          2. neg-sub0N/A

            \[\leadsto \color{blue}{\left(0 - s\right)} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          3. flip--N/A

            \[\leadsto \color{blue}{\frac{0 \cdot 0 - s \cdot s}{0 + s}} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          4. metadata-evalN/A

            \[\leadsto \frac{\color{blue}{0} - s \cdot s}{0 + s} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          5. lift-*.f32N/A

            \[\leadsto \frac{0 - \color{blue}{s \cdot s}}{0 + s} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          6. neg-sub0N/A

            \[\leadsto \frac{\color{blue}{\mathsf{neg}\left(s \cdot s\right)}}{0 + s} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          7. lower-/.f32N/A

            \[\leadsto \color{blue}{\frac{\mathsf{neg}\left(s \cdot s\right)}{0 + s}} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          8. lift-*.f32N/A

            \[\leadsto \frac{\mathsf{neg}\left(\color{blue}{s \cdot s}\right)}{0 + s} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          9. distribute-lft-neg-inN/A

            \[\leadsto \frac{\color{blue}{\left(\mathsf{neg}\left(s\right)\right) \cdot s}}{0 + s} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          10. lift-neg.f32N/A

            \[\leadsto \frac{\color{blue}{\left(-s\right)} \cdot s}{0 + s} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          11. lower-*.f32N/A

            \[\leadsto \frac{\color{blue}{\left(-s\right) \cdot s}}{0 + s} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
          12. lower-+.f3213.1

            \[\leadsto \frac{\left(-s\right) \cdot s}{\color{blue}{0 + s}} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
        10. Applied rewrites13.1%

          \[\leadsto \color{blue}{\frac{\left(-s\right) \cdot s}{0 + s}} \cdot \frac{\mathsf{PI}\left(\right)}{s} \]
        11. Final simplification13.1%

          \[\leadsto \frac{\mathsf{PI}\left(\right)}{s} \cdot \frac{\left(-s\right) \cdot s}{s} \]
        12. Add Preprocessing

        Alternative 6: 11.6% accurate, 36.4× speedup?

        \[\begin{array}{l} \\ \left(\mathsf{PI}\left(\right) \cdot u\right) \cdot 2 - \mathsf{PI}\left(\right) \end{array} \]
        (FPCore (u s) :precision binary32 (- (* (* (PI) u) 2.0) (PI)))
        \begin{array}{l}
        
        \\
        \left(\mathsf{PI}\left(\right) \cdot u\right) \cdot 2 - \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 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 rewrites98.7%

          \[\leadsto \left(-s\right) \cdot \log \left(\frac{1}{\color{blue}{\left(\frac{1}{e^{\frac{-\mathsf{PI}\left(\right)}{s}} + 1} - \frac{1}{e^{\frac{\mathsf{PI}\left(\right)}{s}} + 1}\right) \cdot u}} - 1\right) \]
        6. 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. cancel-sign-sub-invN/A

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

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

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

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

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

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

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

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

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

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

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

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

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

            \[\leadsto \color{blue}{\left(u \cdot 2\right) \cdot \mathsf{PI}\left(\right)} + -1 \cdot \mathsf{PI}\left(\right) \]
        8. Applied rewrites10.5%

          \[\leadsto \color{blue}{\mathsf{fma}\left(u \cdot 2, \mathsf{PI}\left(\right), -\mathsf{PI}\left(\right)\right)} \]
        9. Step-by-step derivation
          1. Applied rewrites10.7%

            \[\leadsto \left(\mathsf{PI}\left(\right) \cdot u\right) \cdot 2 - \color{blue}{\mathsf{PI}\left(\right)} \]
          2. Add Preprocessing

          Alternative 7: 11.4% 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.f3210.5

              \[\leadsto -\color{blue}{\mathsf{PI}\left(\right)} \]
          5. Applied rewrites10.5%

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

          Reproduce

          ?
          herbie shell --seed 2024276 
          (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))))