UniformSampleCone, x

Percentage Accurate: 57.2% → 99.1%
Time: 9.0s
Alternatives: 16
Speedup: 3.3×

Specification

?
\[\left(\left(2.328306437 \cdot 10^{-10} \leq ux \land ux \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq uy \land uy \leq 1\right)\right) \land \left(0 \leq maxCos \land maxCos \leq 1\right)\]
\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
   (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* t_0 t_0))))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0}
\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 16 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: 57.2% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(1 - ux\right) + ux \cdot maxCos\\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0} \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (let* ((t_0 (+ (- 1.0 ux) (* ux maxCos))))
   (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* t_0 t_0))))))
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(1 - ux\right) + ux \cdot maxCos\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - t\_0 \cdot t\_0}
\end{array}
\end{array}

Alternative 1: 99.1% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (*
  (sin (fma (- uy) (* (PI) 2.0) (/ (PI) 2.0)))
  (sqrt (* (- 2.0 (fma (pow (- maxCos 1.0) 2.0) ux (* 2.0 maxCos))) ux))))
\begin{array}{l}

\\
\sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 56.3%

    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
  2. Add Preprocessing
  3. Taylor expanded in ux around 0

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
  4. Step-by-step derivation
    1. Applied rewrites99.0%

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
    2. Step-by-step derivation
      1. lift-cos.f32N/A

        \[\leadsto \color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      2. cos-neg-revN/A

        \[\leadsto \color{blue}{\cos \left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      3. sin-+PI/2-revN/A

        \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      4. lower-sin.f32N/A

        \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      5. lift-*.f32N/A

        \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)}\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      6. lift-*.f32N/A

        \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{\left(uy \cdot 2\right)} \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      7. associate-*l*N/A

        \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{uy \cdot \left(2 \cdot \mathsf{PI}\left(\right)\right)}\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      8. distribute-lft-neg-inN/A

        \[\leadsto \sin \left(\color{blue}{\left(\mathsf{neg}\left(uy\right)\right) \cdot \left(2 \cdot \mathsf{PI}\left(\right)\right)} + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      9. lower-fma.f32N/A

        \[\leadsto \sin \color{blue}{\left(\mathsf{fma}\left(\mathsf{neg}\left(uy\right), 2 \cdot \mathsf{PI}\left(\right), \frac{\mathsf{PI}\left(\right)}{2}\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      10. lower-neg.f32N/A

        \[\leadsto \sin \left(\mathsf{fma}\left(\color{blue}{-uy}, 2 \cdot \mathsf{PI}\left(\right), \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      11. *-commutativeN/A

        \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \color{blue}{\mathsf{PI}\left(\right) \cdot 2}, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      12. lower-*.f32N/A

        \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \color{blue}{\mathsf{PI}\left(\right) \cdot 2}, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      13. lift-PI.f32N/A

        \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \frac{\color{blue}{\mathsf{PI}\left(\right)}}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      14. lower-/.f3299.2

        \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
    3. Applied rewrites99.2%

      \[\leadsto \color{blue}{\sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
    4. Final simplification99.2%

      \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
    5. Add Preprocessing

    Alternative 2: 99.0% accurate, 0.6× speedup?

    \[\begin{array}{l} \\ \sin \left(\mathsf{fma}\left(0.5, \mathsf{PI}\left(\right), \left(\mathsf{PI}\left(\right) \cdot uy\right) \cdot -2\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \end{array} \]
    (FPCore (ux uy maxCos)
     :precision binary32
     (*
      (sin (fma 0.5 (PI) (* (* (PI) uy) -2.0)))
      (sqrt (* (- 2.0 (fma (pow (- maxCos 1.0) 2.0) ux (* 2.0 maxCos))) ux))))
    \begin{array}{l}
    
    \\
    \sin \left(\mathsf{fma}\left(0.5, \mathsf{PI}\left(\right), \left(\mathsf{PI}\left(\right) \cdot uy\right) \cdot -2\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}
    \end{array}
    
    Derivation
    1. Initial program 56.3%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    2. Add Preprocessing
    3. Taylor expanded in ux around 0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
    4. Step-by-step derivation
      1. Applied rewrites99.0%

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
      2. Step-by-step derivation
        1. lift-cos.f32N/A

          \[\leadsto \color{blue}{\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        2. cos-neg-revN/A

          \[\leadsto \color{blue}{\cos \left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        3. sin-+PI/2-revN/A

          \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        4. lower-sin.f32N/A

          \[\leadsto \color{blue}{\sin \left(\left(\mathsf{neg}\left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        5. lift-*.f32N/A

          \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)}\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        6. lift-*.f32N/A

          \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{\left(uy \cdot 2\right)} \cdot \mathsf{PI}\left(\right)\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        7. associate-*l*N/A

          \[\leadsto \sin \left(\left(\mathsf{neg}\left(\color{blue}{uy \cdot \left(2 \cdot \mathsf{PI}\left(\right)\right)}\right)\right) + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        8. distribute-lft-neg-inN/A

          \[\leadsto \sin \left(\color{blue}{\left(\mathsf{neg}\left(uy\right)\right) \cdot \left(2 \cdot \mathsf{PI}\left(\right)\right)} + \frac{\mathsf{PI}\left(\right)}{2}\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        9. lower-fma.f32N/A

          \[\leadsto \sin \color{blue}{\left(\mathsf{fma}\left(\mathsf{neg}\left(uy\right), 2 \cdot \mathsf{PI}\left(\right), \frac{\mathsf{PI}\left(\right)}{2}\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        10. lower-neg.f32N/A

          \[\leadsto \sin \left(\mathsf{fma}\left(\color{blue}{-uy}, 2 \cdot \mathsf{PI}\left(\right), \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        11. *-commutativeN/A

          \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \color{blue}{\mathsf{PI}\left(\right) \cdot 2}, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        12. lower-*.f32N/A

          \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \color{blue}{\mathsf{PI}\left(\right) \cdot 2}, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        13. lift-PI.f32N/A

          \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \frac{\color{blue}{\mathsf{PI}\left(\right)}}{2}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        14. lower-/.f3299.2

          \[\leadsto \sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \color{blue}{\frac{\mathsf{PI}\left(\right)}{2}}\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      3. Applied rewrites99.2%

        \[\leadsto \color{blue}{\sin \left(\mathsf{fma}\left(-uy, \mathsf{PI}\left(\right) \cdot 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      4. Taylor expanded in uy around 0

        \[\leadsto \sin \color{blue}{\left(-2 \cdot \left(uy \cdot \mathsf{PI}\left(\right)\right) + \frac{1}{2} \cdot \mathsf{PI}\left(\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
      5. Step-by-step derivation
        1. Applied rewrites99.0%

          \[\leadsto \sin \color{blue}{\left(\mathsf{fma}\left(0.5, \mathsf{PI}\left(\right), \left(\mathsf{PI}\left(\right) \cdot uy\right) \cdot -2\right)\right)} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        2. Final simplification99.0%

          \[\leadsto \sin \left(\mathsf{fma}\left(0.5, \mathsf{PI}\left(\right), \left(\mathsf{PI}\left(\right) \cdot uy\right) \cdot -2\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
        3. Add Preprocessing

        Alternative 3: 99.0% accurate, 0.6× speedup?

        \[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \end{array} \]
        (FPCore (ux uy maxCos)
         :precision binary32
         (*
          (cos (* (* uy 2.0) (PI)))
          (sqrt (* (- 2.0 (fma (pow (- maxCos 1.0) 2.0) ux (* 2.0 maxCos))) ux))))
        \begin{array}{l}
        
        \\
        \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}
        \end{array}
        
        Derivation
        1. Initial program 56.3%

          \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        2. Add Preprocessing
        3. Taylor expanded in ux around 0

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
        4. Step-by-step derivation
          1. Applied rewrites99.0%

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
          2. Final simplification99.0%

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
          3. Add Preprocessing

          Alternative 4: 99.0% accurate, 1.0× speedup?

          \[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(ux, -2 + maxCos, 2\right), maxCos, ux\right)\right) \cdot ux} \end{array} \]
          (FPCore (ux uy maxCos)
           :precision binary32
           (*
            (cos (* (* uy 2.0) (PI)))
            (sqrt (* (- 2.0 (fma (fma ux (+ -2.0 maxCos) 2.0) maxCos ux)) ux))))
          \begin{array}{l}
          
          \\
          \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(ux, -2 + maxCos, 2\right), maxCos, ux\right)\right) \cdot ux}
          \end{array}
          
          Derivation
          1. Initial program 56.3%

            \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
          2. Add Preprocessing
          3. Taylor expanded in ux around 0

            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
          4. Step-by-step derivation
            1. Applied rewrites99.0%

              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
            2. Taylor expanded in maxCos around 0

              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \left(ux + maxCos \cdot \left(2 + \left(-2 \cdot ux + maxCos \cdot ux\right)\right)\right)\right) \cdot ux} \]
            3. Step-by-step derivation
              1. Applied rewrites98.9%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(ux, -2 + maxCos, 2\right), maxCos, ux\right)\right) \cdot ux} \]
              2. Final simplification98.9%

                \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(ux, -2 + maxCos, 2\right), maxCos, ux\right)\right) \cdot ux} \]
              3. Add Preprocessing

              Alternative 5: 96.4% accurate, 1.1× speedup?

              \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;uy \leq 8.499999967170879 \cdot 10^{-5}:\\ \;\;\;\;1 \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux}\\ \end{array} \end{array} \]
              (FPCore (ux uy maxCos)
               :precision binary32
               (if (<= uy 8.499999967170879e-5)
                 (*
                  1.0
                  (sqrt (* (- 2.0 (fma (pow (- maxCos 1.0) 2.0) ux (* 2.0 maxCos))) ux)))
                 (* (cos (* (* uy 2.0) (PI))) (sqrt (* (- 2.0 ux) ux)))))
              \begin{array}{l}
              
              \\
              \begin{array}{l}
              \mathbf{if}\;uy \leq 8.499999967170879 \cdot 10^{-5}:\\
              \;\;\;\;1 \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}\\
              
              \mathbf{else}:\\
              \;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux}\\
              
              
              \end{array}
              \end{array}
              
              Derivation
              1. Split input into 2 regimes
              2. if uy < 8.49999997e-5

                1. Initial program 55.8%

                  \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                2. Add Preprocessing
                3. Taylor expanded in ux around 0

                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
                4. Step-by-step derivation
                  1. Applied rewrites99.5%

                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
                  2. Taylor expanded in uy around 0

                    \[\leadsto \color{blue}{1} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]
                  3. Step-by-step derivation
                    1. Applied rewrites99.6%

                      \[\leadsto \color{blue}{1} \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux} \]

                    if 8.49999997e-5 < uy

                    1. Initial program 57.0%

                      \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    2. Add Preprocessing
                    3. Taylor expanded in ux around 0

                      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
                    4. Step-by-step derivation
                      1. Applied rewrites98.1%

                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
                      2. Taylor expanded in maxCos around 0

                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
                      3. Step-by-step derivation
                        1. Applied rewrites93.2%

                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
                      4. Recombined 2 regimes into one program.
                      5. Final simplification97.1%

                        \[\leadsto \begin{array}{l} \mathbf{if}\;uy \leq 8.499999967170879 \cdot 10^{-5}:\\ \;\;\;\;1 \cdot \sqrt{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux}\\ \end{array} \]
                      6. Add Preprocessing

                      Alternative 6: 98.3% accurate, 1.1× speedup?

                      \[\begin{array}{l} \\ \cos \left(\left(uy + uy\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \end{array} \]
                      (FPCore (ux uy maxCos)
                       :precision binary32
                       (*
                        (cos (* (+ uy uy) (PI)))
                        (sqrt (* (- 2.0 (fma (fma -2.0 ux 2.0) maxCos ux)) ux))))
                      \begin{array}{l}
                      
                      \\
                      \cos \left(\left(uy + uy\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux}
                      \end{array}
                      
                      Derivation
                      1. Initial program 56.3%

                        \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                      2. Add Preprocessing
                      3. Taylor expanded in ux around 0

                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
                      4. Step-by-step derivation
                        1. Applied rewrites99.0%

                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
                        2. Taylor expanded in maxCos around 0

                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \left(ux + maxCos \cdot \left(2 + -2 \cdot ux\right)\right)\right) \cdot ux} \]
                        3. Step-by-step derivation
                          1. Applied rewrites98.3%

                            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \]
                          2. Step-by-step derivation
                            1. lift-*.f32N/A

                              \[\leadsto \cos \left(\color{blue}{\left(uy \cdot 2\right)} \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \]
                            2. *-commutativeN/A

                              \[\leadsto \cos \left(\color{blue}{\left(2 \cdot uy\right)} \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \]
                            3. count-2-revN/A

                              \[\leadsto \cos \left(\color{blue}{\left(uy + uy\right)} \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \]
                            4. lower-+.f3298.3

                              \[\leadsto \cos \left(\color{blue}{\left(uy + uy\right)} \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \]
                          3. Applied rewrites98.3%

                            \[\leadsto \cos \left(\color{blue}{\left(uy + uy\right)} \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \]
                          4. Final simplification98.3%

                            \[\leadsto \cos \left(\left(uy + uy\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \]
                          5. Add Preprocessing

                          Alternative 7: 96.4% accurate, 1.1× speedup?

                          \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;uy \leq 8.499999967170879 \cdot 10^{-5}:\\ \;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 1\right) \cdot \left(-1 + maxCos\right), 2\right) - 2 \cdot maxCos\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux}\\ \end{array} \end{array} \]
                          (FPCore (ux uy maxCos)
                           :precision binary32
                           (if (<= uy 8.499999967170879e-5)
                             (*
                              1.0
                              (sqrt
                               (*
                                (- (fma (- ux) (* (- maxCos 1.0) (+ -1.0 maxCos)) 2.0) (* 2.0 maxCos))
                                ux)))
                             (* (cos (* (* uy 2.0) (PI))) (sqrt (* (- 2.0 ux) ux)))))
                          \begin{array}{l}
                          
                          \\
                          \begin{array}{l}
                          \mathbf{if}\;uy \leq 8.499999967170879 \cdot 10^{-5}:\\
                          \;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 1\right) \cdot \left(-1 + maxCos\right), 2\right) - 2 \cdot maxCos\right) \cdot ux}\\
                          
                          \mathbf{else}:\\
                          \;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux}\\
                          
                          
                          \end{array}
                          \end{array}
                          
                          Derivation
                          1. Split input into 2 regimes
                          2. if uy < 8.49999997e-5

                            1. Initial program 55.8%

                              \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                            2. Add Preprocessing
                            3. Taylor expanded in uy around 0

                              \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                            4. Step-by-step derivation
                              1. Applied rewrites55.7%

                                \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                              2. Step-by-step derivation
                                1. lift--.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                2. lift-*.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                3. lift-+.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                4. distribute-rgt-inN/A

                                  \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right) + \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)}} \]
                                5. associate--r+N/A

                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                6. lower--.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                7. lower--.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)} - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                8. *-commutativeN/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)}\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                9. lower-*.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)}\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                10. lift-+.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                11. lift-*.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \left(\left(1 - ux\right) + \color{blue}{ux \cdot maxCos}\right) \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                12. *-commutativeN/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \left(\left(1 - ux\right) + \color{blue}{maxCos \cdot ux}\right) \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                13. +-commutativeN/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(maxCos \cdot ux + \left(1 - ux\right)\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                14. lift-fma.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                15. *-commutativeN/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(ux \cdot maxCos\right)}} \]
                                16. lift-*.f32N/A

                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(ux \cdot maxCos\right)}} \]
                              3. Applied rewrites54.3%

                                \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot maxCos\right) \cdot ux}} \]
                              4. Taylor expanded in ux around 0

                                \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot \left(-1 \cdot \left(maxCos - 1\right) + maxCos \cdot \left(maxCos - 1\right)\right)\right)\right) - 2 \cdot maxCos\right)}} \]
                              5. Step-by-step derivation
                                1. Applied rewrites99.5%

                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, \left(maxCos - 1\right) \cdot \left(-1 + maxCos\right), 2\right) - 2 \cdot maxCos\right) \cdot ux}} \]

                                if 8.49999997e-5 < uy

                                1. Initial program 57.0%

                                  \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                2. Add Preprocessing
                                3. Taylor expanded in ux around 0

                                  \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
                                4. Step-by-step derivation
                                  1. Applied rewrites98.1%

                                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
                                  2. Taylor expanded in maxCos around 0

                                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
                                  3. Step-by-step derivation
                                    1. Applied rewrites93.2%

                                      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux} \]
                                  4. Recombined 2 regimes into one program.
                                  5. Final simplification97.0%

                                    \[\leadsto \begin{array}{l} \mathbf{if}\;uy \leq 8.499999967170879 \cdot 10^{-5}:\\ \;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 1\right) \cdot \left(-1 + maxCos\right), 2\right) - 2 \cdot maxCos\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - ux\right) \cdot ux}\\ \end{array} \]
                                  6. Add Preprocessing

                                  Alternative 8: 97.4% accurate, 1.1× speedup?

                                  \[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(2, maxCos, ux\right)\right) \cdot ux} \end{array} \]
                                  (FPCore (ux uy maxCos)
                                   :precision binary32
                                   (* (cos (* (* uy 2.0) (PI))) (sqrt (* (- 2.0 (fma 2.0 maxCos ux)) ux))))
                                  \begin{array}{l}
                                  
                                  \\
                                  \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(2, maxCos, ux\right)\right) \cdot ux}
                                  \end{array}
                                  
                                  Derivation
                                  1. Initial program 56.3%

                                    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                  2. Add Preprocessing
                                  3. Taylor expanded in ux around 0

                                    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right)\right) - 2 \cdot maxCos\right)}} \]
                                  4. Step-by-step derivation
                                    1. Applied rewrites99.0%

                                      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(2 - \mathsf{fma}\left({\left(maxCos - 1\right)}^{2}, ux, 2 \cdot maxCos\right)\right) \cdot ux}} \]
                                    2. Taylor expanded in maxCos around 0

                                      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \left(ux + maxCos \cdot \left(2 + -2 \cdot ux\right)\right)\right) \cdot ux} \]
                                    3. Step-by-step derivation
                                      1. Applied rewrites98.3%

                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(\mathsf{fma}\left(-2, ux, 2\right), maxCos, ux\right)\right) \cdot ux} \]
                                      2. Taylor expanded in ux around 0

                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(2, maxCos, ux\right)\right) \cdot ux} \]
                                      3. Step-by-step derivation
                                        1. Applied rewrites97.4%

                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(2, maxCos, ux\right)\right) \cdot ux} \]
                                        2. Final simplification97.4%

                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 - \mathsf{fma}\left(2, maxCos, ux\right)\right) \cdot ux} \]
                                        3. Add Preprocessing

                                        Alternative 9: 75.2% accurate, 2.0× speedup?

                                        \[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(maxCos, ux, 1 - ux\right)\\ t_1 := \left(1 - ux\right) + ux \cdot maxCos\\ \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.9995499849319458:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), t\_0, 1\right)}\\ \mathbf{else}:\\ \;\;\;\;1 \cdot \sqrt{\left(2 - maxCos\right) \cdot ux - \left(t\_0 \cdot maxCos\right) \cdot ux}\\ \end{array} \end{array} \]
                                        (FPCore (ux uy maxCos)
                                         :precision binary32
                                         (let* ((t_0 (fma maxCos ux (- 1.0 ux))) (t_1 (+ (- 1.0 ux) (* ux maxCos))))
                                           (if (<= (* t_1 t_1) 0.9995499849319458)
                                             (sqrt (fma (- ux (fma maxCos ux 1.0)) t_0 1.0))
                                             (* 1.0 (sqrt (- (* (- 2.0 maxCos) ux) (* (* t_0 maxCos) ux)))))))
                                        float code(float ux, float uy, float maxCos) {
                                        	float t_0 = fmaf(maxCos, ux, (1.0f - ux));
                                        	float t_1 = (1.0f - ux) + (ux * maxCos);
                                        	float tmp;
                                        	if ((t_1 * t_1) <= 0.9995499849319458f) {
                                        		tmp = sqrtf(fmaf((ux - fmaf(maxCos, ux, 1.0f)), t_0, 1.0f));
                                        	} else {
                                        		tmp = 1.0f * sqrtf((((2.0f - maxCos) * ux) - ((t_0 * maxCos) * ux)));
                                        	}
                                        	return tmp;
                                        }
                                        
                                        function code(ux, uy, maxCos)
                                        	t_0 = fma(maxCos, ux, Float32(Float32(1.0) - ux))
                                        	t_1 = Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos))
                                        	tmp = Float32(0.0)
                                        	if (Float32(t_1 * t_1) <= Float32(0.9995499849319458))
                                        		tmp = sqrt(fma(Float32(ux - fma(maxCos, ux, Float32(1.0))), t_0, Float32(1.0)));
                                        	else
                                        		tmp = Float32(Float32(1.0) * sqrt(Float32(Float32(Float32(Float32(2.0) - maxCos) * ux) - Float32(Float32(t_0 * maxCos) * ux))));
                                        	end
                                        	return tmp
                                        end
                                        
                                        \begin{array}{l}
                                        
                                        \\
                                        \begin{array}{l}
                                        t_0 := \mathsf{fma}\left(maxCos, ux, 1 - ux\right)\\
                                        t_1 := \left(1 - ux\right) + ux \cdot maxCos\\
                                        \mathbf{if}\;t\_1 \cdot t\_1 \leq 0.9995499849319458:\\
                                        \;\;\;\;\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), t\_0, 1\right)}\\
                                        
                                        \mathbf{else}:\\
                                        \;\;\;\;1 \cdot \sqrt{\left(2 - maxCos\right) \cdot ux - \left(t\_0 \cdot maxCos\right) \cdot ux}\\
                                        
                                        
                                        \end{array}
                                        \end{array}
                                        
                                        Derivation
                                        1. Split input into 2 regimes
                                        2. if (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos))) < 0.999549985

                                          1. Initial program 88.2%

                                            \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                          2. Add Preprocessing
                                          3. Step-by-step derivation
                                            1. lift--.f32N/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                            2. lift-*.f32N/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                            3. fp-cancel-sub-sign-invN/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{1 + \left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                            4. +-commutativeN/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right) + 1}} \]
                                            5. *-commutativeN/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right)} + 1} \]
                                            6. lower-fma.f32N/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\left(1 - ux\right) + ux \cdot maxCos, \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)}} \]
                                            7. lift-+.f32N/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{\left(1 - ux\right) + ux \cdot maxCos}, \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                            8. +-commutativeN/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{ux \cdot maxCos + \left(1 - ux\right)}, \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                            9. lift-*.f32N/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right), \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                            10. *-commutativeN/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{maxCos \cdot ux} + \left(1 - ux\right), \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                            11. lower-fma.f32N/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)}, \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                            12. lower-neg.f3288.6

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), \color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, 1\right)} \]
                                            13. lift-+.f32N/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, 1\right)} \]
                                            14. +-commutativeN/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, 1\right)} \]
                                            15. lift-*.f32N/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), 1\right)} \]
                                            16. *-commutativeN/A

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\left(\color{blue}{maxCos \cdot ux} + \left(1 - ux\right)\right), 1\right)} \]
                                            17. lower-fma.f3288.6

                                              \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)}, 1\right)} \]
                                          4. Applied rewrites88.6%

                                            \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}} \]
                                          5. Taylor expanded in uy around 0

                                            \[\leadsto \color{blue}{\sqrt{1 + \left(ux - \left(1 + maxCos \cdot ux\right)\right) \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)}} \]
                                          6. Step-by-step derivation
                                            1. Applied rewrites74.0%

                                              \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}} \]

                                            if 0.999549985 < (*.f32 (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)) (+.f32 (-.f32 #s(literal 1 binary32) ux) (*.f32 ux maxCos)))

                                            1. Initial program 38.9%

                                              \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                            2. Add Preprocessing
                                            3. Taylor expanded in uy around 0

                                              \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                            4. Step-by-step derivation
                                              1. Applied rewrites33.2%

                                                \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                              2. Step-by-step derivation
                                                1. lift--.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                2. lift-*.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                3. lift-+.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                4. distribute-rgt-inN/A

                                                  \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right) + \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)}} \]
                                                5. associate--r+N/A

                                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                6. lower--.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                7. lower--.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)} - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                8. *-commutativeN/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)}\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                9. lower-*.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)}\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                10. lift-+.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                11. lift-*.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \left(\left(1 - ux\right) + \color{blue}{ux \cdot maxCos}\right) \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                12. *-commutativeN/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \left(\left(1 - ux\right) + \color{blue}{maxCos \cdot ux}\right) \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                13. +-commutativeN/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(maxCos \cdot ux + \left(1 - ux\right)\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                14. lift-fma.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                15. *-commutativeN/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(ux \cdot maxCos\right)}} \]
                                                16. lift-*.f32N/A

                                                  \[\leadsto 1 \cdot \sqrt{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(ux \cdot maxCos\right)}} \]
                                              3. Applied rewrites31.1%

                                                \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot maxCos\right) \cdot ux}} \]
                                              4. Taylor expanded in ux around 0

                                                \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(2 - maxCos\right)} - \left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot maxCos\right) \cdot ux} \]
                                              5. Step-by-step derivation
                                                1. Applied rewrites74.0%

                                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(2 - maxCos\right) \cdot ux} - \left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot maxCos\right) \cdot ux} \]
                                              6. Recombined 2 regimes into one program.
                                              7. Add Preprocessing

                                              Alternative 10: 80.0% accurate, 3.3× speedup?

                                              \[\begin{array}{l} \\ 1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 1\right) \cdot \left(-1 + maxCos\right), 2\right) - 2 \cdot maxCos\right) \cdot ux} \end{array} \]
                                              (FPCore (ux uy maxCos)
                                               :precision binary32
                                               (*
                                                1.0
                                                (sqrt
                                                 (*
                                                  (- (fma (- ux) (* (- maxCos 1.0) (+ -1.0 maxCos)) 2.0) (* 2.0 maxCos))
                                                  ux))))
                                              float code(float ux, float uy, float maxCos) {
                                              	return 1.0f * sqrtf(((fmaf(-ux, ((maxCos - 1.0f) * (-1.0f + maxCos)), 2.0f) - (2.0f * maxCos)) * ux));
                                              }
                                              
                                              function code(ux, uy, maxCos)
                                              	return Float32(Float32(1.0) * sqrt(Float32(Float32(fma(Float32(-ux), Float32(Float32(maxCos - Float32(1.0)) * Float32(Float32(-1.0) + maxCos)), Float32(2.0)) - Float32(Float32(2.0) * maxCos)) * ux)))
                                              end
                                              
                                              \begin{array}{l}
                                              
                                              \\
                                              1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \left(maxCos - 1\right) \cdot \left(-1 + maxCos\right), 2\right) - 2 \cdot maxCos\right) \cdot ux}
                                              \end{array}
                                              
                                              Derivation
                                              1. Initial program 56.3%

                                                \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                              2. Add Preprocessing
                                              3. Taylor expanded in uy around 0

                                                \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                              4. Step-by-step derivation
                                                1. Applied rewrites47.5%

                                                  \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                2. Step-by-step derivation
                                                  1. lift--.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                  2. lift-*.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                  3. lift-+.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                  4. distribute-rgt-inN/A

                                                    \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right) + \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)}} \]
                                                  5. associate--r+N/A

                                                    \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                  6. lower--.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                  7. lower--.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \left(1 - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)} - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  8. *-commutativeN/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)}\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  9. lower-*.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)}\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  10. lift-+.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  11. lift-*.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \left(\left(1 - ux\right) + \color{blue}{ux \cdot maxCos}\right) \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  12. *-commutativeN/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \left(\left(1 - ux\right) + \color{blue}{maxCos \cdot ux}\right) \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  13. +-commutativeN/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\left(maxCos \cdot ux + \left(1 - ux\right)\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  14. lift-fma.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot \left(1 - ux\right)\right) - \left(ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  15. *-commutativeN/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(ux \cdot maxCos\right)}} \]
                                                  16. lift-*.f32N/A

                                                    \[\leadsto 1 \cdot \sqrt{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(ux \cdot maxCos\right)}} \]
                                                3. Applied rewrites46.2%

                                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(1 - ux\right)\right) - \left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot maxCos\right) \cdot ux}} \]
                                                4. Taylor expanded in ux around 0

                                                  \[\leadsto 1 \cdot \sqrt{\color{blue}{ux \cdot \left(\left(2 + -1 \cdot \left(ux \cdot \left(-1 \cdot \left(maxCos - 1\right) + maxCos \cdot \left(maxCos - 1\right)\right)\right)\right) - 2 \cdot maxCos\right)}} \]
                                                5. Step-by-step derivation
                                                  1. Applied rewrites79.4%

                                                    \[\leadsto 1 \cdot \sqrt{\color{blue}{\left(\mathsf{fma}\left(-ux, \left(maxCos - 1\right) \cdot \left(-1 + maxCos\right), 2\right) - 2 \cdot maxCos\right) \cdot ux}} \]
                                                  2. Add Preprocessing

                                                  Alternative 11: 49.4% accurate, 3.5× speedup?

                                                  \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - \left(\mathsf{fma}\left(maxCos, ux, 1\right) - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \end{array} \]
                                                  (FPCore (ux uy maxCos)
                                                   :precision binary32
                                                   (*
                                                    1.0
                                                    (sqrt (- 1.0 (* (- (fma maxCos ux 1.0) ux) (+ (- 1.0 ux) (* ux maxCos)))))))
                                                  float code(float ux, float uy, float maxCos) {
                                                  	return 1.0f * sqrtf((1.0f - ((fmaf(maxCos, ux, 1.0f) - ux) * ((1.0f - ux) + (ux * maxCos)))));
                                                  }
                                                  
                                                  function code(ux, uy, maxCos)
                                                  	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(Float32(fma(maxCos, ux, Float32(1.0)) - ux) * Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos))))))
                                                  end
                                                  
                                                  \begin{array}{l}
                                                  
                                                  \\
                                                  1 \cdot \sqrt{1 - \left(\mathsf{fma}\left(maxCos, ux, 1\right) - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}
                                                  \end{array}
                                                  
                                                  Derivation
                                                  1. Initial program 56.3%

                                                    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  2. Add Preprocessing
                                                  3. Taylor expanded in uy around 0

                                                    \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                  4. Step-by-step derivation
                                                    1. Applied rewrites47.5%

                                                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                    2. Step-by-step derivation
                                                      1. lift-+.f32N/A

                                                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      2. lift-*.f32N/A

                                                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + \color{blue}{ux \cdot maxCos}\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      3. *-commutativeN/A

                                                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + \color{blue}{maxCos \cdot ux}\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      4. +-commutativeN/A

                                                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(maxCos \cdot ux + \left(1 - ux\right)\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      5. lift--.f32N/A

                                                        \[\leadsto 1 \cdot \sqrt{1 - \left(maxCos \cdot ux + \color{blue}{\left(1 - ux\right)}\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      6. associate-+r-N/A

                                                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(maxCos \cdot ux + 1\right) - ux\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      7. lower--.f32N/A

                                                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\left(maxCos \cdot ux + 1\right) - ux\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      8. lower-fma.f3247.5

                                                        \[\leadsto 1 \cdot \sqrt{1 - \left(\color{blue}{\mathsf{fma}\left(maxCos, ux, 1\right)} - ux\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                    3. Applied rewrites47.5%

                                                      \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\mathsf{fma}\left(maxCos, ux, 1\right) - ux\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                    4. Add Preprocessing

                                                    Alternative 12: 49.4% accurate, 3.7× speedup?

                                                    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(maxCos, ux, 1 - ux\right)\\ 1 \cdot \sqrt{1 - t\_0 \cdot t\_0} \end{array} \end{array} \]
                                                    (FPCore (ux uy maxCos)
                                                     :precision binary32
                                                     (let* ((t_0 (fma maxCos ux (- 1.0 ux)))) (* 1.0 (sqrt (- 1.0 (* t_0 t_0))))))
                                                    float code(float ux, float uy, float maxCos) {
                                                    	float t_0 = fmaf(maxCos, ux, (1.0f - ux));
                                                    	return 1.0f * sqrtf((1.0f - (t_0 * t_0)));
                                                    }
                                                    
                                                    function code(ux, uy, maxCos)
                                                    	t_0 = fma(maxCos, ux, Float32(Float32(1.0) - ux))
                                                    	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(t_0 * t_0))))
                                                    end
                                                    
                                                    \begin{array}{l}
                                                    
                                                    \\
                                                    \begin{array}{l}
                                                    t_0 := \mathsf{fma}\left(maxCos, ux, 1 - ux\right)\\
                                                    1 \cdot \sqrt{1 - t\_0 \cdot t\_0}
                                                    \end{array}
                                                    \end{array}
                                                    
                                                    Derivation
                                                    1. Initial program 56.3%

                                                      \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                    2. Add Preprocessing
                                                    3. Step-by-step derivation
                                                      1. lift-+.f32N/A

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      2. +-commutativeN/A

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      3. lift-*.f32N/A

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      4. *-commutativeN/A

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\color{blue}{maxCos \cdot ux} + \left(1 - ux\right)\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      5. lower-fma.f3256.3

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      6. lift-+.f32N/A

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                      7. +-commutativeN/A

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}} \]
                                                      8. lift-*.f32N/A

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right)} \]
                                                      9. *-commutativeN/A

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \left(\color{blue}{maxCos \cdot ux} + \left(1 - ux\right)\right)} \]
                                                      10. lower-fma.f3256.3

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)}} \]
                                                    4. Applied rewrites56.3%

                                                      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \mathsf{fma}\left(maxCos, ux, 1 - ux\right)}} \]
                                                    5. Taylor expanded in uy around 0

                                                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \]
                                                    6. Step-by-step derivation
                                                      1. Applied rewrites47.5%

                                                        \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \]
                                                      2. Add Preprocessing

                                                      Alternative 13: 49.4% accurate, 4.5× speedup?

                                                      \[\begin{array}{l} \\ \sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)} \end{array} \]
                                                      (FPCore (ux uy maxCos)
                                                       :precision binary32
                                                       (sqrt (fma (- ux (fma maxCos ux 1.0)) (fma maxCos ux (- 1.0 ux)) 1.0)))
                                                      float code(float ux, float uy, float maxCos) {
                                                      	return sqrtf(fmaf((ux - fmaf(maxCos, ux, 1.0f)), fmaf(maxCos, ux, (1.0f - ux)), 1.0f));
                                                      }
                                                      
                                                      function code(ux, uy, maxCos)
                                                      	return sqrt(fma(Float32(ux - fma(maxCos, ux, Float32(1.0))), fma(maxCos, ux, Float32(Float32(1.0) - ux)), Float32(1.0)))
                                                      end
                                                      
                                                      \begin{array}{l}
                                                      
                                                      \\
                                                      \sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}
                                                      \end{array}
                                                      
                                                      Derivation
                                                      1. Initial program 56.3%

                                                        \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                      2. Add Preprocessing
                                                      3. Step-by-step derivation
                                                        1. lift--.f32N/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                        2. lift-*.f32N/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                        3. fp-cancel-sub-sign-invN/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{1 + \left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)}} \]
                                                        4. +-commutativeN/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right) + 1}} \]
                                                        5. *-commutativeN/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right)\right)} + 1} \]
                                                        6. lower-fma.f32N/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\left(1 - ux\right) + ux \cdot maxCos, \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)}} \]
                                                        7. lift-+.f32N/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{\left(1 - ux\right) + ux \cdot maxCos}, \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                                        8. +-commutativeN/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{ux \cdot maxCos + \left(1 - ux\right)}, \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                                        9. lift-*.f32N/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right), \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                                        10. *-commutativeN/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{maxCos \cdot ux} + \left(1 - ux\right), \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                                        11. lower-fma.f32N/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)}, \mathsf{neg}\left(\left(\left(1 - ux\right) + ux \cdot maxCos\right)\right), 1\right)} \]
                                                        12. lower-neg.f3256.4

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), \color{blue}{-\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, 1\right)} \]
                                                        13. lift-+.f32N/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\color{blue}{\left(\left(1 - ux\right) + ux \cdot maxCos\right)}, 1\right)} \]
                                                        14. +-commutativeN/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\color{blue}{\left(ux \cdot maxCos + \left(1 - ux\right)\right)}, 1\right)} \]
                                                        15. lift-*.f32N/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\left(\color{blue}{ux \cdot maxCos} + \left(1 - ux\right)\right), 1\right)} \]
                                                        16. *-commutativeN/A

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\left(\color{blue}{maxCos \cdot ux} + \left(1 - ux\right)\right), 1\right)} \]
                                                        17. lower-fma.f3256.4

                                                          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)}, 1\right)} \]
                                                      4. Applied rewrites56.4%

                                                        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), -\mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}} \]
                                                      5. Taylor expanded in uy around 0

                                                        \[\leadsto \color{blue}{\sqrt{1 + \left(ux - \left(1 + maxCos \cdot ux\right)\right) \cdot \left(\left(1 + maxCos \cdot ux\right) - ux\right)}} \]
                                                      6. Step-by-step derivation
                                                        1. Applied rewrites47.5%

                                                          \[\leadsto \color{blue}{\sqrt{\mathsf{fma}\left(ux - \mathsf{fma}\left(maxCos, ux, 1\right), \mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1\right)}} \]
                                                        2. Add Preprocessing

                                                        Alternative 14: 40.4% accurate, 5.0× speedup?

                                                        \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - \mathsf{fma}\left(\mathsf{fma}\left(2, maxCos, -2\right), ux, 1\right)} \end{array} \]
                                                        (FPCore (ux uy maxCos)
                                                         :precision binary32
                                                         (* 1.0 (sqrt (- 1.0 (fma (fma 2.0 maxCos -2.0) ux 1.0)))))
                                                        float code(float ux, float uy, float maxCos) {
                                                        	return 1.0f * sqrtf((1.0f - fmaf(fmaf(2.0f, maxCos, -2.0f), ux, 1.0f)));
                                                        }
                                                        
                                                        function code(ux, uy, maxCos)
                                                        	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - fma(fma(Float32(2.0), maxCos, Float32(-2.0)), ux, Float32(1.0)))))
                                                        end
                                                        
                                                        \begin{array}{l}
                                                        
                                                        \\
                                                        1 \cdot \sqrt{1 - \mathsf{fma}\left(\mathsf{fma}\left(2, maxCos, -2\right), ux, 1\right)}
                                                        \end{array}
                                                        
                                                        Derivation
                                                        1. Initial program 56.3%

                                                          \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                        2. Add Preprocessing
                                                        3. Taylor expanded in uy around 0

                                                          \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                        4. Step-by-step derivation
                                                          1. Applied rewrites47.5%

                                                            \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                          2. Taylor expanded in ux around 0

                                                            \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)}} \]
                                                          3. Step-by-step derivation
                                                            1. Applied rewrites39.6%

                                                              \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(2, maxCos, -2\right), ux, 1\right)}} \]
                                                            2. Add Preprocessing

                                                            Alternative 15: 39.7% accurate, 6.2× speedup?

                                                            \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)} \end{array} \]
                                                            (FPCore (ux uy maxCos)
                                                             :precision binary32
                                                             (* 1.0 (sqrt (- 1.0 (fma -2.0 ux 1.0)))))
                                                            float code(float ux, float uy, float maxCos) {
                                                            	return 1.0f * sqrtf((1.0f - fmaf(-2.0f, ux, 1.0f)));
                                                            }
                                                            
                                                            function code(ux, uy, maxCos)
                                                            	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - fma(Float32(-2.0), ux, Float32(1.0)))))
                                                            end
                                                            
                                                            \begin{array}{l}
                                                            
                                                            \\
                                                            1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)}
                                                            \end{array}
                                                            
                                                            Derivation
                                                            1. Initial program 56.3%

                                                              \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                            2. Add Preprocessing
                                                            3. Taylor expanded in uy around 0

                                                              \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                            4. Step-by-step derivation
                                                              1. Applied rewrites47.5%

                                                                \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                              2. Taylor expanded in ux around 0

                                                                \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)}} \]
                                                              3. Step-by-step derivation
                                                                1. Applied rewrites39.6%

                                                                  \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(2, maxCos, -2\right), ux, 1\right)}} \]
                                                                2. Taylor expanded in maxCos around 0

                                                                  \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)} \]
                                                                3. Step-by-step derivation
                                                                  1. Applied rewrites39.0%

                                                                    \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)} \]
                                                                  2. Add Preprocessing

                                                                  Alternative 16: 6.6% accurate, 8.2× speedup?

                                                                  \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - 1} \end{array} \]
                                                                  (FPCore (ux uy maxCos) :precision binary32 (* 1.0 (sqrt (- 1.0 1.0))))
                                                                  float code(float ux, float uy, float maxCos) {
                                                                  	return 1.0f * sqrtf((1.0f - 1.0f));
                                                                  }
                                                                  
                                                                  module fmin_fmax_functions
                                                                      implicit none
                                                                      private
                                                                      public fmax
                                                                      public fmin
                                                                  
                                                                      interface fmax
                                                                          module procedure fmax88
                                                                          module procedure fmax44
                                                                          module procedure fmax84
                                                                          module procedure fmax48
                                                                      end interface
                                                                      interface fmin
                                                                          module procedure fmin88
                                                                          module procedure fmin44
                                                                          module procedure fmin84
                                                                          module procedure fmin48
                                                                      end interface
                                                                  contains
                                                                      real(8) function fmax88(x, y) result (res)
                                                                          real(8), intent (in) :: x
                                                                          real(8), intent (in) :: y
                                                                          res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                                                                      end function
                                                                      real(4) function fmax44(x, y) result (res)
                                                                          real(4), intent (in) :: x
                                                                          real(4), intent (in) :: y
                                                                          res = merge(y, merge(x, max(x, y), y /= y), x /= x)
                                                                      end function
                                                                      real(8) function fmax84(x, y) result(res)
                                                                          real(8), intent (in) :: x
                                                                          real(4), intent (in) :: y
                                                                          res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
                                                                      end function
                                                                      real(8) function fmax48(x, y) result(res)
                                                                          real(4), intent (in) :: x
                                                                          real(8), intent (in) :: y
                                                                          res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
                                                                      end function
                                                                      real(8) function fmin88(x, y) result (res)
                                                                          real(8), intent (in) :: x
                                                                          real(8), intent (in) :: y
                                                                          res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                                                                      end function
                                                                      real(4) function fmin44(x, y) result (res)
                                                                          real(4), intent (in) :: x
                                                                          real(4), intent (in) :: y
                                                                          res = merge(y, merge(x, min(x, y), y /= y), x /= x)
                                                                      end function
                                                                      real(8) function fmin84(x, y) result(res)
                                                                          real(8), intent (in) :: x
                                                                          real(4), intent (in) :: y
                                                                          res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
                                                                      end function
                                                                      real(8) function fmin48(x, y) result(res)
                                                                          real(4), intent (in) :: x
                                                                          real(8), intent (in) :: y
                                                                          res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
                                                                      end function
                                                                  end module
                                                                  
                                                                  real(4) function code(ux, uy, maxcos)
                                                                  use fmin_fmax_functions
                                                                      real(4), intent (in) :: ux
                                                                      real(4), intent (in) :: uy
                                                                      real(4), intent (in) :: maxcos
                                                                      code = 1.0e0 * sqrt((1.0e0 - 1.0e0))
                                                                  end function
                                                                  
                                                                  function code(ux, uy, maxCos)
                                                                  	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(1.0))))
                                                                  end
                                                                  
                                                                  function tmp = code(ux, uy, maxCos)
                                                                  	tmp = single(1.0) * sqrt((single(1.0) - single(1.0)));
                                                                  end
                                                                  
                                                                  \begin{array}{l}
                                                                  
                                                                  \\
                                                                  1 \cdot \sqrt{1 - 1}
                                                                  \end{array}
                                                                  
                                                                  Derivation
                                                                  1. Initial program 56.3%

                                                                    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                                  2. Add Preprocessing
                                                                  3. Taylor expanded in uy around 0

                                                                    \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                                  4. Step-by-step derivation
                                                                    1. Applied rewrites47.5%

                                                                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                                                                    2. Taylor expanded in ux around 0

                                                                      \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{1}} \]
                                                                    3. Step-by-step derivation
                                                                      1. Applied rewrites6.6%

                                                                        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{1}} \]
                                                                      2. Add Preprocessing

                                                                      Reproduce

                                                                      ?
                                                                      herbie shell --seed 2025018 
                                                                      (FPCore (ux uy maxCos)
                                                                        :name "UniformSampleCone, x"
                                                                        :precision binary32
                                                                        :pre (and (and (and (<= 2.328306437e-10 ux) (<= ux 1.0)) (and (<= 2.328306437e-10 uy) (<= uy 1.0))) (and (<= 0.0 maxCos) (<= maxCos 1.0)))
                                                                        (* (cos (* (* uy 2.0) (PI))) (sqrt (- 1.0 (* (+ (- 1.0 ux) (* ux maxCos)) (+ (- 1.0 ux) (* ux maxCos)))))))