UniformSampleCone, x

Percentage Accurate: 57.3% → 99.1%
Time: 7.8s
Alternatives: 22
Speedup: 1.1×

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 22 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: 57.3% 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, 0.9× speedup?

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

\\
\sin \left(\mathsf{fma}\left(-\mathsf{PI}\left(\right), uy \cdot 2, \frac{\mathsf{PI}\left(\right)}{2}\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)}
\end{array}
Derivation
  1. Initial program 59.3%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  5. Applied rewrites99.0%

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1 \cdot \left(maxCos \cdot {ux}^{2}\right) + ux \cdot \left(2 \cdot ux - 2\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    3. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(-1 \cdot maxCos\right) \cdot {ux}^{2} + ux \cdot \left(2 \cdot ux - 2\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    4. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, {ux}^{2}, ux \cdot \left(2 \cdot ux - 2\right)\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    7. unpow2N/A

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

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

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

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

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \left(2 + -1 \cdot ux\right) \cdot ux\right)} \]
  8. Applied rewrites99.0%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Alternative 2: 99.0% accurate, 0.9× speedup?

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

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \mathsf{fma}\left(ux, 2, \left(-ux\right) \cdot ux\right)\right)}
\end{array}
Derivation
  1. Initial program 59.3%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  5. Applied rewrites99.0%

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1 \cdot \left(maxCos \cdot {ux}^{2}\right) + ux \cdot \left(2 \cdot ux - 2\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    3. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(-1 \cdot maxCos\right) \cdot {ux}^{2} + ux \cdot \left(2 \cdot ux - 2\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    4. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, {ux}^{2}, ux \cdot \left(2 \cdot ux - 2\right)\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    7. unpow2N/A

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

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

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

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

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \left(2 + -1 \cdot ux\right) \cdot ux\right)} \]
  8. Applied rewrites99.0%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    5. distribute-rgt-inN/A

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \mathsf{fma}\left(ux, 2, \left(-1 \cdot ux\right) \cdot ux\right)\right)} \]
    9. mul-1-negN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \mathsf{fma}\left(ux, 2, \left(\mathsf{neg}\left(ux\right)\right) \cdot ux\right)\right)} \]
    10. lift-neg.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \mathsf{fma}\left(ux, 2, \left(-ux\right) \cdot ux\right)\right)} \]
  10. Applied rewrites99.0%

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

Alternative 3: 98.9% accurate, 1.0× speedup?

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

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(\mathsf{fma}\left(-1, maxCos, 2\right) \cdot ux - 2\right) \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)}
\end{array}
Derivation
  1. Initial program 59.3%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  5. Applied rewrites99.0%

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1 \cdot \left(maxCos \cdot {ux}^{2}\right) + ux \cdot \left(2 \cdot ux - 2\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    3. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(-1 \cdot maxCos\right) \cdot {ux}^{2} + ux \cdot \left(2 \cdot ux - 2\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    4. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, {ux}^{2}, ux \cdot \left(2 \cdot ux - 2\right)\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    7. unpow2N/A

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

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

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

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

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \left(2 + -1 \cdot ux\right) \cdot ux\right)} \]
  8. Applied rewrites99.0%

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(ux \cdot \left(2 + -1 \cdot maxCos\right) - 2\right) \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)} \]
    2. distribute-rgt-inN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(\left(2 \cdot ux + \left(-1 \cdot maxCos\right) \cdot ux\right) - 2\right) \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)} \]
    3. associate-*r*N/A

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

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

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

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

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(\left(2 + -1 \cdot maxCos\right) \cdot ux - 2\right) \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)} \]
    12. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(\left(-1 \cdot maxCos + 2\right) \cdot ux - 2\right) \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)} \]
    15. lower-fma.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(\mathsf{fma}\left(-1, maxCos, 2\right) \cdot ux - 2\right) \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)} \]
  11. Applied rewrites99.0%

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

Alternative 4: 98.9% accurate, 1.0× speedup?

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

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(\mathsf{fma}\left(-1, maxCos, 2\right) \cdot ux - 2, maxCos, -ux\right) + 2\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 59.3%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  5. Applied rewrites99.0%

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

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot ux\right) - maxCos \cdot 2\right) \cdot ux} \]
  7. Step-by-step derivation
    1. +-commutativeN/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot ux + 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. lower-fma.f3297.7

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  8. Applied rewrites97.7%

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

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + \left(-1 \cdot ux + maxCos \cdot \left(\left(-1 \cdot \left(maxCos \cdot ux\right) + 2 \cdot ux\right) - 2\right)\right)\right) \cdot ux} \]
  10. Step-by-step derivation
    1. +-commutativeN/A

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot ux + maxCos \cdot \left(\left(-1 \cdot \left(maxCos \cdot ux\right) + 2 \cdot ux\right) - 2\right)\right) + 2\right) \cdot ux} \]
  11. Applied rewrites99.0%

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

Alternative 5: 98.3% accurate, 1.0× speedup?

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

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(ux \cdot 2 - 2\right) \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)}
\end{array}
Derivation
  1. Initial program 59.3%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  5. Applied rewrites99.0%

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

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

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

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

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

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

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

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(ux \cdot 2 - 2\right) \cdot ux, maxCos, \left(-1 \cdot ux + 2\right) \cdot ux\right)} \]
    11. lower-fma.f3298.4

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(ux \cdot 2 - 2\right) \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)} \]
  8. Applied rewrites98.4%

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

Alternative 6: 98.3% accurate, 1.0× speedup?

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

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(-2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 59.3%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  5. Applied rewrites99.0%

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, -2 \cdot maxCos + 1, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    2. lower-fma.f3298.3

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, \mathsf{fma}\left(-2, maxCos, 1\right), 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  8. Applied rewrites98.3%

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

Alternative 7: 98.3% accurate, 1.0× speedup?

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

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, -ux\right) + 2\right) \cdot ux}
\end{array}
Derivation
  1. Initial program 59.3%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  5. Applied rewrites99.0%

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

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + \left(-1 \cdot ux + maxCos \cdot \left(2 \cdot ux - 2\right)\right)\right) \cdot ux} \]
  7. Step-by-step derivation
    1. +-commutativeN/A

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

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

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

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

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(ux \cdot 2 - 2, maxCos, \mathsf{neg}\left(ux\right)\right) + 2\right) \cdot ux} \]
    10. lift-neg.f3298.3

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

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

Alternative 8: 97.4% accurate, 1.1× speedup?

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

\\
\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2 \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)}
\end{array}
Derivation
  1. Initial program 59.3%

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    5. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    6. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
    9. lower-pow.f32N/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    12. lower-*.f3299.0

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
  5. Applied rewrites99.0%

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1 \cdot \left(maxCos \cdot {ux}^{2}\right) + ux \cdot \left(2 \cdot ux - 2\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    3. associate-*r*N/A

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\left(-1 \cdot maxCos\right) \cdot {ux}^{2} + ux \cdot \left(2 \cdot ux - 2\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    4. mul-1-negN/A

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, {ux}^{2}, ux \cdot \left(2 \cdot ux - 2\right)\right), maxCos, ux \cdot \left(2 + -1 \cdot ux\right)\right)} \]
    7. unpow2N/A

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

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

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

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

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

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

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

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(\mathsf{fma}\left(-maxCos, ux \cdot ux, \left(ux \cdot 2 - 2\right) \cdot ux\right), maxCos, \left(2 + -1 \cdot ux\right) \cdot ux\right)} \]
  8. Applied rewrites99.0%

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

    \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2 \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)} \]
  10. Step-by-step derivation
    1. lower-*.f3297.7

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2 \cdot ux, maxCos, \mathsf{fma}\left(-1, ux, 2\right) \cdot ux\right)} \]
  11. Applied rewrites97.7%

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

Alternative 9: 96.5% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;uy \leq 0.00015999999595806003:\\ \;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux}\\ \end{array} \end{array} \]
(FPCore (ux uy maxCos)
 :precision binary32
 (if (<= uy 0.00015999999595806003)
   (*
    1.0
    (sqrt (* (- (fma (- ux) (pow (- maxCos 1.0) 2.0) 2.0) (* maxCos 2.0)) ux)))
   (* (cos (* (* uy 2.0) (PI))) (sqrt (* (fma -1.0 ux 2.0) ux)))))
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;uy \leq 0.00015999999595806003:\\
\;\;\;\;1 \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux}\\

\mathbf{else}:\\
\;\;\;\;\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if uy < 1.59999996e-4

    1. Initial program 58.4%

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

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

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      5. associate-*r*N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      6. mul-1-negN/A

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      9. lower-pow.f32N/A

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lower-*.f3299.4

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    5. Applied rewrites99.4%

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

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

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

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

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

        \[\leadsto \mathsf{fma}\left({\left(uy \cdot \mathsf{PI}\left(\right)\right)}^{2}, -2, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      5. lower-pow.f32N/A

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

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

        \[\leadsto \mathsf{fma}\left({\left(\mathsf{PI}\left(\right) \cdot uy\right)}^{2}, -2, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      8. lift-PI.f3299.4

        \[\leadsto \mathsf{fma}\left({\left(\mathsf{PI}\left(\right) \cdot uy\right)}^{2}, -2, 1\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    8. Applied rewrites99.4%

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

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

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

      if 1.59999996e-4 < uy

      1. Initial program 60.6%

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

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

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

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

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
        5. associate-*r*N/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
        6. mul-1-negN/A

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

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

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
        9. lower-pow.f32N/A

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

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

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        12. lower-*.f3298.4

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      5. Applied rewrites98.4%

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + -1 \cdot ux\right) \cdot ux} \]
      7. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-1 \cdot ux + 2\right) \cdot ux} \]
        2. lower-fma.f3292.1

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux} \]
      8. Applied rewrites92.1%

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux} \]
    11. Recombined 2 regimes into one program.
    12. Add Preprocessing

    Alternative 10: 95.5% accurate, 1.1× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\\ \mathbf{if}\;maxCos \leq 1.7999999499807018 \cdot 10^{-6}:\\ \;\;\;\;t\_0 \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux}\\ \mathbf{else}:\\ \;\;\;\;t\_0 \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\ \end{array} \end{array} \]
    (FPCore (ux uy maxCos)
     :precision binary32
     (let* ((t_0 (cos (* (* uy 2.0) (PI)))))
       (if (<= maxCos 1.7999999499807018e-6)
         (* t_0 (sqrt (* (fma -1.0 ux 2.0) ux)))
         (* t_0 (sqrt (* (fma -2.0 maxCos 2.0) ux))))))
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right)\\
    \mathbf{if}\;maxCos \leq 1.7999999499807018 \cdot 10^{-6}:\\
    \;\;\;\;t\_0 \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux}\\
    
    \mathbf{else}:\\
    \;\;\;\;t\_0 \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if maxCos < 1.79999995e-6

      1. Initial program 61.4%

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

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

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

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

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
        5. associate-*r*N/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
        6. mul-1-negN/A

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

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

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
        9. lower-pow.f32N/A

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

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

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
        12. lower-*.f3299.0

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      5. Applied rewrites99.0%

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + -1 \cdot ux\right) \cdot ux} \]
      7. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-1 \cdot ux + 2\right) \cdot ux} \]
        2. lower-fma.f3298.8

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux} \]
      8. Applied rewrites98.8%

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux} \]

      if 1.79999995e-6 < maxCos

      1. Initial program 49.2%

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{ux \cdot \left(2 - 2 \cdot maxCos\right)}} \]
      4. Step-by-step derivation
        1. metadata-evalN/A

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

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

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

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

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-2 \cdot maxCos + 2\right) \cdot ux} \]
        6. lower-fma.f3281.9

          \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux} \]
      5. Applied rewrites81.9%

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\color{blue}{\mathsf{fma}\left(-2, maxCos, 2\right) \cdot ux}} \]
    3. Recombined 2 regimes into one program.
    4. Add Preprocessing

    Alternative 11: 97.5% accurate, 1.1× speedup?

    \[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - \left(maxCos + maxCos\right)\right) \cdot ux} \end{array} \]
    (FPCore (ux uy maxCos)
     :precision binary32
     (*
      (cos (* (* uy 2.0) (PI)))
      (sqrt (* (- (fma -1.0 ux 2.0) (+ maxCos maxCos)) ux))))
    \begin{array}{l}
    
    \\
    \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - \left(maxCos + maxCos\right)\right) \cdot ux}
    \end{array}
    
    Derivation
    1. Initial program 59.3%

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

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

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      5. associate-*r*N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      6. mul-1-negN/A

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      9. lower-pow.f32N/A

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lower-*.f3299.0

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    5. Applied rewrites99.0%

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(2 + -1 \cdot ux\right) - maxCos \cdot 2\right) \cdot ux} \]
    7. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot ux + 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      2. lower-fma.f3297.7

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    8. Applied rewrites97.7%

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

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - \left(maxCos + maxCos\right)\right) \cdot ux} \]
      4. lower-+.f3297.7

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-1, ux, 2\right) - \left(maxCos + maxCos\right)\right) \cdot ux} \]
    10. Applied rewrites97.7%

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

    Alternative 12: 92.8% accurate, 1.1× speedup?

    \[\begin{array}{l} \\ \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux} \end{array} \]
    (FPCore (ux uy maxCos)
     :precision binary32
     (* (cos (* (* uy 2.0) (PI))) (sqrt (* (fma -1.0 ux 2.0) ux))))
    \begin{array}{l}
    
    \\
    \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux}
    \end{array}
    
    Derivation
    1. Initial program 59.3%

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

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

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(-1 \cdot \left(ux \cdot {\left(maxCos - 1\right)}^{2}\right) + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      5. associate-*r*N/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\left(\left(-1 \cdot ux\right) \cdot {\left(maxCos - 1\right)}^{2} + 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      6. mul-1-negN/A

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - 2 \cdot maxCos\right) \cdot ux} \]
      9. lower-pow.f32N/A

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

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

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
      12. lower-*.f3299.0

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(\mathsf{fma}\left(-ux, {\left(maxCos - 1\right)}^{2}, 2\right) - maxCos \cdot 2\right) \cdot ux} \]
    5. Applied rewrites99.0%

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

      \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(2 + -1 \cdot ux\right) \cdot ux} \]
    7. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\left(-1 \cdot ux + 2\right) \cdot ux} \]
      2. lower-fma.f3291.9

        \[\leadsto \cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{\mathsf{fma}\left(-1, ux, 2\right) \cdot ux} \]
    8. Applied rewrites91.9%

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

    Alternative 13: 49.8% accurate, 2.2× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(maxCos, ux, 1\right) - ux\\ 1 \cdot \sqrt{1 - \mathsf{fma}\left(t\_0, \left(-1 - \frac{-1}{ux}\right) \cdot ux, t\_0 \cdot \left(maxCos \cdot ux\right)\right)} \end{array} \end{array} \]
    (FPCore (ux uy maxCos)
     :precision binary32
     (let* ((t_0 (- (fma maxCos ux 1.0) ux)))
       (*
        1.0
        (sqrt
         (- 1.0 (fma t_0 (* (- -1.0 (/ -1.0 ux)) ux) (* t_0 (* maxCos ux))))))))
    float code(float ux, float uy, float maxCos) {
    	float t_0 = fmaf(maxCos, ux, 1.0f) - ux;
    	return 1.0f * sqrtf((1.0f - fmaf(t_0, ((-1.0f - (-1.0f / ux)) * ux), (t_0 * (maxCos * ux)))));
    }
    
    function code(ux, uy, maxCos)
    	t_0 = Float32(fma(maxCos, ux, Float32(1.0)) - ux)
    	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - fma(t_0, Float32(Float32(Float32(-1.0) - Float32(Float32(-1.0) / ux)) * ux), Float32(t_0 * Float32(maxCos * ux))))))
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \mathsf{fma}\left(maxCos, ux, 1\right) - ux\\
    1 \cdot \sqrt{1 - \mathsf{fma}\left(t\_0, \left(-1 - \frac{-1}{ux}\right) \cdot ux, t\_0 \cdot \left(maxCos \cdot ux\right)\right)}
    \end{array}
    \end{array}
    
    Derivation
    1. Initial program 59.3%

      \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
    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 rewrites50.1%

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

        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{-1 \cdot \left(ux \cdot \left(1 - \frac{1}{ux}\right)\right)} + ux \cdot maxCos\right)} \]
      3. Step-by-step derivation
        1. associate-*r*N/A

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

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

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

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

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(-ux\right) \cdot \left(1 - \color{blue}{\frac{1}{ux}}\right) + ux \cdot maxCos\right)} \]
        6. lift-/.f3250.6

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(-ux\right) \cdot \left(1 - \frac{1}{\color{blue}{ux}}\right) + ux \cdot maxCos\right)} \]
      4. Applied rewrites50.6%

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

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

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

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

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

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

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

          \[\leadsto 1 \cdot \sqrt{1 - \left(\color{blue}{\mathsf{fma}\left(maxCos, ux, 1\right)} - ux\right) \cdot \left(\left(-ux\right) \cdot \left(1 - \frac{1}{ux}\right) + ux \cdot maxCos\right)} \]
        8. lift--.f3250.6

          \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\left(\mathsf{fma}\left(maxCos, ux, 1\right) - ux\right)} \cdot \left(\left(-ux\right) \cdot \left(1 - \frac{1}{ux}\right) + ux \cdot maxCos\right)} \]
      6. Applied rewrites50.6%

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

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

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

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

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

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

          \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(\left(maxCos \cdot ux + 1\right) - ux, \left(-ux\right) \cdot \left(1 - \frac{1}{ux}\right), \left(\left(maxCos \cdot ux + 1\right) - ux\right) \cdot \left(ux \cdot maxCos\right)\right)}} \]
      8. Applied rewrites50.6%

        \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1\right) - ux, \left(1 - \frac{1}{ux}\right) \cdot \left(-ux\right), \left(\mathsf{fma}\left(maxCos, ux, 1\right) - ux\right) \cdot \left(maxCos \cdot ux\right)\right)}} \]
      9. Final simplification50.6%

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

      Alternative 14: 49.8% accurate, 2.7× speedup?

      \[\begin{array}{l} \\ \sqrt{1 - \mathsf{fma}\left(maxCos, ux, \left(-1 - \frac{-1}{ux}\right) \cdot ux\right) \cdot \mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot 1 \end{array} \]
      (FPCore (ux uy maxCos)
       :precision binary32
       (*
        (sqrt
         (-
          1.0
          (*
           (fma maxCos ux (* (- -1.0 (/ -1.0 ux)) ux))
           (fma maxCos ux (- 1.0 ux)))))
        1.0))
      float code(float ux, float uy, float maxCos) {
      	return sqrtf((1.0f - (fmaf(maxCos, ux, ((-1.0f - (-1.0f / ux)) * ux)) * fmaf(maxCos, ux, (1.0f - ux))))) * 1.0f;
      }
      
      function code(ux, uy, maxCos)
      	return Float32(sqrt(Float32(Float32(1.0) - Float32(fma(maxCos, ux, Float32(Float32(Float32(-1.0) - Float32(Float32(-1.0) / ux)) * ux)) * fma(maxCos, ux, Float32(Float32(1.0) - ux))))) * Float32(1.0))
      end
      
      \begin{array}{l}
      
      \\
      \sqrt{1 - \mathsf{fma}\left(maxCos, ux, \left(-1 - \frac{-1}{ux}\right) \cdot ux\right) \cdot \mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot 1
      \end{array}
      
      Derivation
      1. Initial program 59.3%

        \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
      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 rewrites50.1%

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

          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{-1 \cdot \left(ux \cdot \left(1 - \frac{1}{ux}\right)\right)} + ux \cdot maxCos\right)} \]
        3. Step-by-step derivation
          1. associate-*r*N/A

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

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

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

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

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(-ux\right) \cdot \left(1 - \color{blue}{\frac{1}{ux}}\right) + ux \cdot maxCos\right)} \]
          6. lift-/.f3250.6

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(-ux\right) \cdot \left(1 - \frac{1}{\color{blue}{ux}}\right) + ux \cdot maxCos\right)} \]
        4. Applied rewrites50.6%

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

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

            \[\leadsto \color{blue}{\sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(-ux\right) \cdot \left(1 - \frac{1}{ux}\right) + ux \cdot maxCos\right)} \cdot 1} \]
          3. lower-*.f3250.6

            \[\leadsto \color{blue}{\sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(-ux\right) \cdot \left(1 - \frac{1}{ux}\right) + ux \cdot maxCos\right)} \cdot 1} \]
        6. Applied rewrites50.6%

          \[\leadsto \color{blue}{\sqrt{1 - \mathsf{fma}\left(maxCos, ux, \left(1 - \frac{1}{ux}\right) \cdot \left(-ux\right)\right) \cdot \mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot 1} \]
        7. Final simplification50.6%

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

        Alternative 15: 49.8% accurate, 2.7× speedup?

        \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \end{array} \]
        (FPCore (ux uy maxCos)
         :precision binary32
         (*
          1.0
          (sqrt
           (-
            1.0
            (* (+ (- 1.0 ux) (* ux maxCos)) (* (- (+ (/ 1.0 ux) maxCos) 1.0) ux))))))
        float code(float ux, float uy, float maxCos) {
        	return 1.0f * sqrtf((1.0f - (((1.0f - ux) + (ux * maxCos)) * ((((1.0f / ux) + maxCos) - 1.0f) * ux))));
        }
        
        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 - ux) + (ux * maxcos)) * ((((1.0e0 / ux) + maxcos) - 1.0e0) * ux))))
        end function
        
        function code(ux, uy, maxCos)
        	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos)) * Float32(Float32(Float32(Float32(Float32(1.0) / ux) + maxCos) - Float32(1.0)) * ux)))))
        end
        
        function tmp = code(ux, uy, maxCos)
        	tmp = single(1.0) * sqrt((single(1.0) - (((single(1.0) - ux) + (ux * maxCos)) * ((((single(1.0) / ux) + maxCos) - single(1.0)) * ux))));
        end
        
        \begin{array}{l}
        
        \\
        1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)}
        \end{array}
        
        Derivation
        1. Initial program 59.3%

          \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
        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 rewrites50.1%

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

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

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

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

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

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

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

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

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
            8. lift-/.f3250.6

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)} \]
          4. Applied rewrites50.6%

            \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(\left(\frac{1}{ux} + maxCos\right) - 1\right) \cdot ux\right)}} \]
          5. Add Preprocessing

          Alternative 16: 49.3% accurate, 2.7× speedup?

          \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \end{array} \]
          (FPCore (ux uy maxCos)
           :precision binary32
           (*
            1.0
            (sqrt
             (-
              1.0
              (*
               (+ (- 1.0 ux) (* ux maxCos))
               (* (+ ux (/ (- 1.0 ux) maxCos)) maxCos))))))
          float code(float ux, float uy, float maxCos) {
          	return 1.0f * sqrtf((1.0f - (((1.0f - ux) + (ux * maxCos)) * ((ux + ((1.0f - ux) / maxCos)) * maxCos))));
          }
          
          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 - ux) + (ux * maxcos)) * ((ux + ((1.0e0 - ux) / maxcos)) * maxcos))))
          end function
          
          function code(ux, uy, maxCos)
          	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos)) * Float32(Float32(ux + Float32(Float32(Float32(1.0) - ux) / maxCos)) * maxCos)))))
          end
          
          function tmp = code(ux, uy, maxCos)
          	tmp = single(1.0) * sqrt((single(1.0) - (((single(1.0) - ux) + (ux * maxCos)) * ((ux + ((single(1.0) - ux) / maxCos)) * maxCos))));
          end
          
          \begin{array}{l}
          
          \\
          1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}
          \end{array}
          
          Derivation
          1. Initial program 59.3%

            \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
          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 rewrites50.1%

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

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

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

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

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

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

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \left(\frac{1}{maxCos} - \frac{ux}{maxCos}\right)\right) \cdot maxCos\right)} \]
              6. div-subN/A

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

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

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
              9. lift--.f3250.3

                \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)} \]
            4. Applied rewrites50.3%

              \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \color{blue}{\left(\left(ux + \frac{1 - ux}{maxCos}\right) \cdot maxCos\right)}} \]
            5. Add Preprocessing

            Alternative 17: 49.1% accurate, 2.8× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} t_0 := \mathsf{fma}\left(maxCos, ux, 1 - ux\right)\\ 1 \cdot \sqrt{1 - \mathsf{fma}\left(t\_0, 1 - ux, t\_0 \cdot \left(maxCos \cdot ux\right)\right)} \end{array} \end{array} \]
            (FPCore (ux uy maxCos)
             :precision binary32
             (let* ((t_0 (fma maxCos ux (- 1.0 ux))))
               (* 1.0 (sqrt (- 1.0 (fma t_0 (- 1.0 ux) (* t_0 (* maxCos ux))))))))
            float code(float ux, float uy, float maxCos) {
            	float t_0 = fmaf(maxCos, ux, (1.0f - ux));
            	return 1.0f * sqrtf((1.0f - fmaf(t_0, (1.0f - ux), (t_0 * (maxCos * ux)))));
            }
            
            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) - fma(t_0, Float32(Float32(1.0) - ux), Float32(t_0 * Float32(maxCos * ux))))))
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            t_0 := \mathsf{fma}\left(maxCos, ux, 1 - ux\right)\\
            1 \cdot \sqrt{1 - \mathsf{fma}\left(t\_0, 1 - ux, t\_0 \cdot \left(maxCos \cdot ux\right)\right)}
            \end{array}
            \end{array}
            
            Derivation
            1. Initial program 59.3%

              \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
            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 rewrites50.1%

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

                  \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1 - ux, \mathsf{fma}\left(maxCos, ux, \color{blue}{1 - ux}\right) \cdot \left(maxCos \cdot ux\right)\right)} \]
                21. lower-*.f3250.2

                  \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(\mathsf{fma}\left(maxCos, ux, 1 - ux\right), 1 - ux, \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \color{blue}{\left(maxCos \cdot ux\right)}\right)} \]
              3. Applied rewrites50.2%

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

              Alternative 18: 49.1% 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 59.3%

                \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
              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 rewrites50.1%

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

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

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

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

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

                    \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)} \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  7. lift--.f3250.1

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

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

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

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

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

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

                    \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \color{blue}{\mathsf{fma}\left(maxCos, ux, 1 - ux\right)}} \]
                  14. lift--.f3250.1

                    \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos, ux, 1 - ux\right) \cdot \mathsf{fma}\left(maxCos, ux, \color{blue}{1 - ux}\right)} \]
                3. Applied rewrites50.1%

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

                Alternative 19: 47.7% accurate, 4.1× speedup?

                \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)} \end{array} \]
                (FPCore (ux uy maxCos)
                 :precision binary32
                 (* 1.0 (sqrt (- 1.0 (* (+ (- 1.0 ux) (* ux maxCos)) (- 1.0 ux))))))
                float code(float ux, float uy, float maxCos) {
                	return 1.0f * sqrtf((1.0f - (((1.0f - ux) + (ux * maxCos)) * (1.0f - ux))));
                }
                
                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 - ux) + (ux * maxcos)) * (1.0e0 - ux))))
                end function
                
                function code(ux, uy, maxCos)
                	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - Float32(Float32(Float32(Float32(1.0) - ux) + Float32(ux * maxCos)) * Float32(Float32(1.0) - ux)))))
                end
                
                function tmp = code(ux, uy, maxCos)
                	tmp = single(1.0) * sqrt((single(1.0) - (((single(1.0) - ux) + (ux * maxCos)) * (single(1.0) - ux))));
                end
                
                \begin{array}{l}
                
                \\
                1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - ux\right)}
                \end{array}
                
                Derivation
                1. Initial program 59.3%

                  \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                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 rewrites50.1%

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

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

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

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\color{blue}{1} - ux\right)} \]
                    3. lift--.f3249.0

                      \[\leadsto 1 \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(1 - \color{blue}{ux}\right)} \]
                  4. Applied rewrites49.0%

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

                  Alternative 20: 40.8% accurate, 5.0× speedup?

                  \[\begin{array}{l} \\ 1 \cdot \sqrt{1 - \mathsf{fma}\left(\left(maxCos + maxCos\right) - 2, ux, 1\right)} \end{array} \]
                  (FPCore (ux uy maxCos)
                   :precision binary32
                   (* 1.0 (sqrt (- 1.0 (fma (- (+ maxCos maxCos) 2.0) ux 1.0)))))
                  float code(float ux, float uy, float maxCos) {
                  	return 1.0f * sqrtf((1.0f - fmaf(((maxCos + maxCos) - 2.0f), ux, 1.0f)));
                  }
                  
                  function code(ux, uy, maxCos)
                  	return Float32(Float32(1.0) * sqrt(Float32(Float32(1.0) - fma(Float32(Float32(maxCos + maxCos) - Float32(2.0)), ux, Float32(1.0)))))
                  end
                  
                  \begin{array}{l}
                  
                  \\
                  1 \cdot \sqrt{1 - \mathsf{fma}\left(\left(maxCos + maxCos\right) - 2, ux, 1\right)}
                  \end{array}
                  
                  Derivation
                  1. Initial program 59.3%

                    \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                  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 rewrites50.1%

                      \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    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. pow2N/A

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

                        \[\leadsto 1 \cdot \sqrt{1 - \left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)} \]
                      3. +-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{1 - \left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)} \]
                      4. pow2N/A

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

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

                        \[\leadsto 1 \cdot \sqrt{1 - \left(\left(2 \cdot maxCos - 2\right) \cdot ux + 1\right)} \]
                      7. lower-fma.f32N/A

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(2 \cdot maxCos - 2, \color{blue}{ux}, 1\right)} \]
                      8. lower--.f32N/A

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

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos \cdot 2 - 2, ux, 1\right)} \]
                      10. lift-*.f3240.6

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos \cdot 2 - 2, ux, 1\right)} \]
                    4. Applied rewrites40.6%

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

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos \cdot 2 - 2, ux, 1\right)} \]
                      2. *-commutativeN/A

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(2 \cdot maxCos - 2, ux, 1\right)} \]
                      3. count-2-revN/A

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(\left(maxCos + maxCos\right) - 2, ux, 1\right)} \]
                      4. lower-+.f3240.6

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(\left(maxCos + maxCos\right) - 2, ux, 1\right)} \]
                    6. Applied rewrites40.6%

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

                    Alternative 21: 40.1% 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 59.3%

                      \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                    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 rewrites50.1%

                        \[\leadsto \color{blue}{1} \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                      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. pow2N/A

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

                          \[\leadsto 1 \cdot \sqrt{1 - \left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)} \]
                        3. +-commutativeN/A

                          \[\leadsto 1 \cdot \sqrt{1 - \left(1 + ux \cdot \left(2 \cdot maxCos - 2\right)\right)} \]
                        4. pow2N/A

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

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

                          \[\leadsto 1 \cdot \sqrt{1 - \left(\left(2 \cdot maxCos - 2\right) \cdot ux + 1\right)} \]
                        7. lower-fma.f32N/A

                          \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(2 \cdot maxCos - 2, \color{blue}{ux}, 1\right)} \]
                        8. lower--.f32N/A

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

                          \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos \cdot 2 - 2, ux, 1\right)} \]
                        10. lift-*.f3240.6

                          \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(maxCos \cdot 2 - 2, ux, 1\right)} \]
                      4. Applied rewrites40.6%

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

                        \[\leadsto 1 \cdot \sqrt{1 - \mathsf{fma}\left(-2, ux, 1\right)} \]
                      6. Step-by-step derivation
                        1. Applied rewrites39.9%

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

                        Alternative 22: 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 59.3%

                          \[\cos \left(\left(uy \cdot 2\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \sqrt{1 - \left(\left(1 - ux\right) + ux \cdot maxCos\right) \cdot \left(\left(1 - ux\right) + ux \cdot maxCos\right)} \]
                        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 rewrites50.1%

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

                            \[\leadsto 1 \cdot \sqrt{1 - \color{blue}{1}} \]
                          3. Step-by-step derivation
                            1. pow26.6

                              \[\leadsto 1 \cdot \sqrt{1 - 1} \]
                            2. *-commutative6.6

                              \[\leadsto 1 \cdot \sqrt{1 - 1} \]
                            3. +-commutative6.6

                              \[\leadsto 1 \cdot \sqrt{1 - 1} \]
                            4. pow26.6

                              \[\leadsto 1 \cdot \sqrt{1 - 1} \]
                          4. Applied rewrites6.6%

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

                          Reproduce

                          ?
                          herbie shell --seed 2025037 
                          (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)))))))