Trowbridge-Reitz Sample, near normal, slope_x

Percentage Accurate: 99.0% → 99.0%
Time: 9.4s
Alternatives: 8
Speedup: 1.0×

Specification

?
\[\left(\left(cosTheta\_i > 0.9999 \land cosTheta\_i \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq u1 \land u1 \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u2 \land u2 \leq 1\right)\]
\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (cos (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * cosf((6.28318530718f * u2));
}
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(costheta_i, u1, u2)
use fmin_fmax_functions
    real(4), intent (in) :: costheta_i
    real(4), intent (in) :: u1
    real(4), intent (in) :: u2
    code = sqrt((u1 / (1.0e0 - u1))) * cos((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * cos(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * cos((single(6.28318530718) * u2));
end
\begin{array}{l}

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right)
\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 8 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 99.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (cos (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * cosf((6.28318530718f * u2));
}
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(costheta_i, u1, u2)
use fmin_fmax_functions
    real(4), intent (in) :: costheta_i
    real(4), intent (in) :: u1
    real(4), intent (in) :: u2
    code = sqrt((u1 / (1.0e0 - u1))) * cos((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * cos(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * cos((single(6.28318530718) * u2));
end
\begin{array}{l}

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right)
\end{array}

Alternative 1: 99.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (cos (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * cosf((6.28318530718f * u2));
}
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(costheta_i, u1, u2)
use fmin_fmax_functions
    real(4), intent (in) :: costheta_i
    real(4), intent (in) :: u1
    real(4), intent (in) :: u2
    code = sqrt((u1 / (1.0e0 - u1))) * cos((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * cos(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * cos((single(6.28318530718) * u2));
end
\begin{array}{l}

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right)
\end{array}
Derivation
  1. Initial program 99.1%

    \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
  2. Add Preprocessing
  3. Add Preprocessing

Alternative 2: 96.2% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.014999999664723873:\\ \;\;\;\;\frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + 1\right)}{\sqrt{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot u1 + u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (if (<= u2 0.014999999664723873)
   (/
    (*
     (sqrt u1)
     (+
      (*
       (*
        (-
         (* (* (fma (* u2 u2) -85.45681720672748 64.93939402268539) u2) u2)
         19.739208802181317)
        u2)
       u2)
      1.0))
    (sqrt (- 1.0 u1)))
   (* (sqrt (+ (* u1 u1) u1)) (cos (* 6.28318530718 u2)))))
float code(float cosTheta_i, float u1, float u2) {
	float tmp;
	if (u2 <= 0.014999999664723873f) {
		tmp = (sqrtf(u1) * ((((((fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f) * u2) * u2) - 19.739208802181317f) * u2) * u2) + 1.0f)) / sqrtf((1.0f - u1));
	} else {
		tmp = sqrtf(((u1 * u1) + u1)) * cosf((6.28318530718f * u2));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	tmp = Float32(0.0)
	if (u2 <= Float32(0.014999999664723873))
		tmp = Float32(Float32(sqrt(u1) * Float32(Float32(Float32(Float32(Float32(Float32(fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)) * u2) * u2) - Float32(19.739208802181317)) * u2) * u2) + Float32(1.0))) / sqrt(Float32(Float32(1.0) - u1)));
	else
		tmp = Float32(sqrt(Float32(Float32(u1 * u1) + u1)) * cos(Float32(Float32(6.28318530718) * u2)));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;u2 \leq 0.014999999664723873:\\
\;\;\;\;\frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + 1\right)}{\sqrt{1 - u1}}\\

\mathbf{else}:\\
\;\;\;\;\sqrt{u1 \cdot u1 + u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u2 < 0.0149999997

    1. Initial program 99.3%

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-*.f32N/A

        \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
      2. lift-sqrt.f32N/A

        \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. lift-/.f32N/A

        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. sqrt-divN/A

        \[\leadsto \color{blue}{\frac{\sqrt{u1}}{\sqrt{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. associate-*l/N/A

        \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}}} \]
      6. lower-/.f32N/A

        \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}}} \]
      7. lower-*.f32N/A

        \[\leadsto \frac{\color{blue}{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}}{\sqrt{1 - u1}} \]
      8. lower-sqrt.f32N/A

        \[\leadsto \frac{\color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}} \]
      9. lift-cos.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}}{\sqrt{1 - u1}} \]
      10. cos-neg-revN/A

        \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)}}{\sqrt{1 - u1}} \]
      11. lower-cos.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)}}{\sqrt{1 - u1}} \]
      12. lift-*.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(\mathsf{neg}\left(\color{blue}{\frac{314159265359}{50000000000} \cdot u2}\right)\right)}{\sqrt{1 - u1}} \]
      13. distribute-lft-neg-inN/A

        \[\leadsto \frac{\sqrt{u1} \cdot \cos \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000}\right)\right) \cdot u2\right)}}{\sqrt{1 - u1}} \]
      14. lower-*.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \cos \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000}\right)\right) \cdot u2\right)}}{\sqrt{1 - u1}} \]
      15. metadata-evalN/A

        \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(\color{blue}{\frac{-314159265359}{50000000000}} \cdot u2\right)}{\sqrt{1 - u1}} \]
      16. lower-sqrt.f3298.8

        \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(-6.28318530718 \cdot u2\right)}{\color{blue}{\sqrt{1 - u1}}} \]
    4. Applied rewrites98.8%

      \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(-6.28318530718 \cdot u2\right)}{\sqrt{1 - u1}}} \]
    5. Taylor expanded in u2 around 0

      \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)}}{\sqrt{1 - u1}} \]
    6. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)}}{\sqrt{1 - u1}} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\sqrt{u1} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot {u2}^{2}} + 1\right)}{\sqrt{1 - u1}} \]
      3. lower-fma.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}}{\sqrt{1 - u1}} \]
      4. lower--.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      5. *-commutativeN/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      6. unpow2N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot \color{blue}{\left(u2 \cdot u2\right)} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      7. associate-*r*N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right) \cdot u2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      8. lower-*.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right) \cdot u2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      9. lower-*.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      10. +-commutativeN/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      11. lower-fma.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\color{blue}{\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      12. unpow2N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      13. lower-*.f32N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
      14. unpow2N/A

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right)}{\sqrt{1 - u1}} \]
      15. lower-*.f3292.5

        \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right)}{\sqrt{1 - u1}} \]
    7. Applied rewrites92.5%

      \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)}}{\sqrt{1 - u1}} \]
    8. Step-by-step derivation
      1. Applied rewrites98.8%

        \[\leadsto \frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + \color{blue}{1}\right)}{\sqrt{1 - u1}} \]

      if 0.0149999997 < u2

      1. Initial program 98.0%

        \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      2. Add Preprocessing
      3. Taylor expanded in u1 around 0

        \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      4. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 + 1\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        2. distribute-lft-inN/A

          \[\leadsto \sqrt{\color{blue}{u1 \cdot u1 + u1 \cdot 1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        3. *-rgt-identityN/A

          \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        4. lower-fma.f3211.0

          \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      5. Applied rewrites10.9%

        \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      6. Step-by-step derivation
        1. Applied rewrites85.6%

          \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
      7. Recombined 2 regimes into one program.
      8. Add Preprocessing

      Alternative 3: 96.2% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.014999999664723873:\\ \;\;\;\;\frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + 1\right)}{\sqrt{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \left(u1 - -1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (if (<= u2 0.014999999664723873)
         (/
          (*
           (sqrt u1)
           (+
            (*
             (*
              (-
               (* (* (fma (* u2 u2) -85.45681720672748 64.93939402268539) u2) u2)
               19.739208802181317)
              u2)
             u2)
            1.0))
          (sqrt (- 1.0 u1)))
         (* (sqrt (* u1 (- u1 -1.0))) (cos (* 6.28318530718 u2)))))
      float code(float cosTheta_i, float u1, float u2) {
      	float tmp;
      	if (u2 <= 0.014999999664723873f) {
      		tmp = (sqrtf(u1) * ((((((fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f) * u2) * u2) - 19.739208802181317f) * u2) * u2) + 1.0f)) / sqrtf((1.0f - u1));
      	} else {
      		tmp = sqrtf((u1 * (u1 - -1.0f))) * cosf((6.28318530718f * u2));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.014999999664723873))
      		tmp = Float32(Float32(sqrt(u1) * Float32(Float32(Float32(Float32(Float32(Float32(fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)) * u2) * u2) - Float32(19.739208802181317)) * u2) * u2) + Float32(1.0))) / sqrt(Float32(Float32(1.0) - u1)));
      	else
      		tmp = Float32(sqrt(Float32(u1 * Float32(u1 - Float32(-1.0)))) * cos(Float32(Float32(6.28318530718) * u2)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;u2 \leq 0.014999999664723873:\\
      \;\;\;\;\frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + 1\right)}{\sqrt{1 - u1}}\\
      
      \mathbf{else}:\\
      \;\;\;\;\sqrt{u1 \cdot \left(u1 - -1\right)} \cdot \cos \left(6.28318530718 \cdot u2\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 0.0149999997

        1. Initial program 99.3%

          \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
          2. lift-sqrt.f32N/A

            \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          3. lift-/.f32N/A

            \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          4. sqrt-divN/A

            \[\leadsto \color{blue}{\frac{\sqrt{u1}}{\sqrt{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          5. associate-*l/N/A

            \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}}} \]
          6. lower-/.f32N/A

            \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}}} \]
          7. lower-*.f32N/A

            \[\leadsto \frac{\color{blue}{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}}{\sqrt{1 - u1}} \]
          8. lower-sqrt.f32N/A

            \[\leadsto \frac{\color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}} \]
          9. lift-cos.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}}{\sqrt{1 - u1}} \]
          10. cos-neg-revN/A

            \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)}}{\sqrt{1 - u1}} \]
          11. lower-cos.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)}}{\sqrt{1 - u1}} \]
          12. lift-*.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(\mathsf{neg}\left(\color{blue}{\frac{314159265359}{50000000000} \cdot u2}\right)\right)}{\sqrt{1 - u1}} \]
          13. distribute-lft-neg-inN/A

            \[\leadsto \frac{\sqrt{u1} \cdot \cos \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000}\right)\right) \cdot u2\right)}}{\sqrt{1 - u1}} \]
          14. lower-*.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \cos \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000}\right)\right) \cdot u2\right)}}{\sqrt{1 - u1}} \]
          15. metadata-evalN/A

            \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(\color{blue}{\frac{-314159265359}{50000000000}} \cdot u2\right)}{\sqrt{1 - u1}} \]
          16. lower-sqrt.f3298.8

            \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(-6.28318530718 \cdot u2\right)}{\color{blue}{\sqrt{1 - u1}}} \]
        4. Applied rewrites98.8%

          \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(-6.28318530718 \cdot u2\right)}{\sqrt{1 - u1}}} \]
        5. Taylor expanded in u2 around 0

          \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)}}{\sqrt{1 - u1}} \]
        6. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)}}{\sqrt{1 - u1}} \]
          2. *-commutativeN/A

            \[\leadsto \frac{\sqrt{u1} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot {u2}^{2}} + 1\right)}{\sqrt{1 - u1}} \]
          3. lower-fma.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}}{\sqrt{1 - u1}} \]
          4. lower--.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          5. *-commutativeN/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          6. unpow2N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot \color{blue}{\left(u2 \cdot u2\right)} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          7. associate-*r*N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right) \cdot u2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          8. lower-*.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right) \cdot u2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          9. lower-*.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          10. +-commutativeN/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          11. lower-fma.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\color{blue}{\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          12. unpow2N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          13. lower-*.f32N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
          14. unpow2N/A

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right)}{\sqrt{1 - u1}} \]
          15. lower-*.f3292.5

            \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right)}{\sqrt{1 - u1}} \]
        7. Applied rewrites92.5%

          \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)}}{\sqrt{1 - u1}} \]
        8. Step-by-step derivation
          1. Applied rewrites98.8%

            \[\leadsto \frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + \color{blue}{1}\right)}{\sqrt{1 - u1}} \]

          if 0.0149999997 < u2

          1. Initial program 98.0%

            \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
          2. Add Preprocessing
          3. Taylor expanded in u1 around 0

            \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          4. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 + 1\right)}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
            2. distribute-lft-inN/A

              \[\leadsto \sqrt{\color{blue}{u1 \cdot u1 + u1 \cdot 1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
            3. *-rgt-identityN/A

              \[\leadsto \sqrt{u1 \cdot u1 + \color{blue}{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
            4. lower-fma.f3210.5

              \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
          5. Applied rewrites8.2%

            \[\leadsto \sqrt{\color{blue}{\mathsf{fma}\left(u1, u1, u1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
          6. Step-by-step derivation
            1. Applied rewrites85.6%

              \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(u1 - -1\right)}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
          7. Recombined 2 regimes into one program.
          8. Add Preprocessing

          Alternative 4: 94.0% accurate, 1.1× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.014999999664723873:\\ \;\;\;\;\frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + 1\right)}{\sqrt{1 - u1}}\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (if (<= u2 0.014999999664723873)
             (/
              (*
               (sqrt u1)
               (+
                (*
                 (*
                  (-
                   (* (* (fma (* u2 u2) -85.45681720672748 64.93939402268539) u2) u2)
                   19.739208802181317)
                  u2)
                 u2)
                1.0))
              (sqrt (- 1.0 u1)))
             (* (sqrt u1) (cos (* 6.28318530718 u2)))))
          float code(float cosTheta_i, float u1, float u2) {
          	float tmp;
          	if (u2 <= 0.014999999664723873f) {
          		tmp = (sqrtf(u1) * ((((((fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f) * u2) * u2) - 19.739208802181317f) * u2) * u2) + 1.0f)) / sqrtf((1.0f - u1));
          	} else {
          		tmp = sqrtf(u1) * cosf((6.28318530718f * u2));
          	}
          	return tmp;
          }
          
          function code(cosTheta_i, u1, u2)
          	tmp = Float32(0.0)
          	if (u2 <= Float32(0.014999999664723873))
          		tmp = Float32(Float32(sqrt(u1) * Float32(Float32(Float32(Float32(Float32(Float32(fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)) * u2) * u2) - Float32(19.739208802181317)) * u2) * u2) + Float32(1.0))) / sqrt(Float32(Float32(1.0) - u1)));
          	else
          		tmp = Float32(sqrt(u1) * cos(Float32(Float32(6.28318530718) * u2)));
          	end
          	return tmp
          end
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          \mathbf{if}\;u2 \leq 0.014999999664723873:\\
          \;\;\;\;\frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + 1\right)}{\sqrt{1 - u1}}\\
          
          \mathbf{else}:\\
          \;\;\;\;\sqrt{u1} \cdot \cos \left(6.28318530718 \cdot u2\right)\\
          
          
          \end{array}
          \end{array}
          
          Derivation
          1. Split input into 2 regimes
          2. if u2 < 0.0149999997

            1. Initial program 99.3%

              \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
            2. Add Preprocessing
            3. Step-by-step derivation
              1. lift-*.f32N/A

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
              2. lift-sqrt.f32N/A

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              3. lift-/.f32N/A

                \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. sqrt-divN/A

                \[\leadsto \color{blue}{\frac{\sqrt{u1}}{\sqrt{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              5. associate-*l/N/A

                \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}}} \]
              6. lower-/.f32N/A

                \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}}} \]
              7. lower-*.f32N/A

                \[\leadsto \frac{\color{blue}{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}}{\sqrt{1 - u1}} \]
              8. lower-sqrt.f32N/A

                \[\leadsto \frac{\color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}} \]
              9. lift-cos.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}}{\sqrt{1 - u1}} \]
              10. cos-neg-revN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)}}{\sqrt{1 - u1}} \]
              11. lower-cos.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)}}{\sqrt{1 - u1}} \]
              12. lift-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(\mathsf{neg}\left(\color{blue}{\frac{314159265359}{50000000000} \cdot u2}\right)\right)}{\sqrt{1 - u1}} \]
              13. distribute-lft-neg-inN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000}\right)\right) \cdot u2\right)}}{\sqrt{1 - u1}} \]
              14. lower-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000}\right)\right) \cdot u2\right)}}{\sqrt{1 - u1}} \]
              15. metadata-evalN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(\color{blue}{\frac{-314159265359}{50000000000}} \cdot u2\right)}{\sqrt{1 - u1}} \]
              16. lower-sqrt.f3298.8

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(-6.28318530718 \cdot u2\right)}{\color{blue}{\sqrt{1 - u1}}} \]
            4. Applied rewrites98.8%

              \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(-6.28318530718 \cdot u2\right)}{\sqrt{1 - u1}}} \]
            5. Taylor expanded in u2 around 0

              \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)}}{\sqrt{1 - u1}} \]
            6. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)}}{\sqrt{1 - u1}} \]
              2. *-commutativeN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot {u2}^{2}} + 1\right)}{\sqrt{1 - u1}} \]
              3. lower-fma.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}}{\sqrt{1 - u1}} \]
              4. lower--.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              5. *-commutativeN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              6. unpow2N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot \color{blue}{\left(u2 \cdot u2\right)} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              7. associate-*r*N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right) \cdot u2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              8. lower-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right) \cdot u2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              9. lower-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              10. +-commutativeN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              11. lower-fma.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\color{blue}{\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              12. unpow2N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              13. lower-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              14. unpow2N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right)}{\sqrt{1 - u1}} \]
              15. lower-*.f3292.5

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right)}{\sqrt{1 - u1}} \]
            7. Applied rewrites92.5%

              \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)}}{\sqrt{1 - u1}} \]
            8. Step-by-step derivation
              1. Applied rewrites98.8%

                \[\leadsto \frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + \color{blue}{1}\right)}{\sqrt{1 - u1}} \]

              if 0.0149999997 < u2

              1. Initial program 98.0%

                \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              2. Add Preprocessing
              3. Taylor expanded in u1 around 0

                \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. Step-by-step derivation
                1. lower-sqrt.f3272.7

                  \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              5. Applied rewrites72.7%

                \[\leadsto \color{blue}{\sqrt{u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
            9. Recombined 2 regimes into one program.
            10. Add Preprocessing

            Alternative 5: 90.5% accurate, 1.8× speedup?

            \[\begin{array}{l} \\ \frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + 1\right)}{\sqrt{1 - u1}} \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (/
              (*
               (sqrt u1)
               (+
                (*
                 (*
                  (-
                   (* (* (fma (* u2 u2) -85.45681720672748 64.93939402268539) u2) u2)
                   19.739208802181317)
                  u2)
                 u2)
                1.0))
              (sqrt (- 1.0 u1))))
            float code(float cosTheta_i, float u1, float u2) {
            	return (sqrtf(u1) * ((((((fmaf((u2 * u2), -85.45681720672748f, 64.93939402268539f) * u2) * u2) - 19.739208802181317f) * u2) * u2) + 1.0f)) / sqrtf((1.0f - u1));
            }
            
            function code(cosTheta_i, u1, u2)
            	return Float32(Float32(sqrt(u1) * Float32(Float32(Float32(Float32(Float32(Float32(fma(Float32(u2 * u2), Float32(-85.45681720672748), Float32(64.93939402268539)) * u2) * u2) - Float32(19.739208802181317)) * u2) * u2) + Float32(1.0))) / sqrt(Float32(Float32(1.0) - u1)))
            end
            
            \begin{array}{l}
            
            \\
            \frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + 1\right)}{\sqrt{1 - u1}}
            \end{array}
            
            Derivation
            1. Initial program 99.1%

              \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
            2. Add Preprocessing
            3. Step-by-step derivation
              1. lift-*.f32N/A

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
              2. lift-sqrt.f32N/A

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              3. lift-/.f32N/A

                \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              4. sqrt-divN/A

                \[\leadsto \color{blue}{\frac{\sqrt{u1}}{\sqrt{1 - u1}}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
              5. associate-*l/N/A

                \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}}} \]
              6. lower-/.f32N/A

                \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}}} \]
              7. lower-*.f32N/A

                \[\leadsto \frac{\color{blue}{\sqrt{u1} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}}{\sqrt{1 - u1}} \]
              8. lower-sqrt.f32N/A

                \[\leadsto \frac{\color{blue}{\sqrt{u1}} \cdot \cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}{\sqrt{1 - u1}} \]
              9. lift-cos.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\frac{314159265359}{50000000000} \cdot u2\right)}}{\sqrt{1 - u1}} \]
              10. cos-neg-revN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)}}{\sqrt{1 - u1}} \]
              11. lower-cos.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\cos \left(\mathsf{neg}\left(\frac{314159265359}{50000000000} \cdot u2\right)\right)}}{\sqrt{1 - u1}} \]
              12. lift-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(\mathsf{neg}\left(\color{blue}{\frac{314159265359}{50000000000} \cdot u2}\right)\right)}{\sqrt{1 - u1}} \]
              13. distribute-lft-neg-inN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000}\right)\right) \cdot u2\right)}}{\sqrt{1 - u1}} \]
              14. lower-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \color{blue}{\left(\left(\mathsf{neg}\left(\frac{314159265359}{50000000000}\right)\right) \cdot u2\right)}}{\sqrt{1 - u1}} \]
              15. metadata-evalN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(\color{blue}{\frac{-314159265359}{50000000000}} \cdot u2\right)}{\sqrt{1 - u1}} \]
              16. lower-sqrt.f3298.5

                \[\leadsto \frac{\sqrt{u1} \cdot \cos \left(-6.28318530718 \cdot u2\right)}{\color{blue}{\sqrt{1 - u1}}} \]
            4. Applied rewrites98.5%

              \[\leadsto \color{blue}{\frac{\sqrt{u1} \cdot \cos \left(-6.28318530718 \cdot u2\right)}{\sqrt{1 - u1}}} \]
            5. Taylor expanded in u2 around 0

              \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\left(1 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right)\right)}}{\sqrt{1 - u1}} \]
            6. Step-by-step derivation
              1. +-commutativeN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) + 1\right)}}{\sqrt{1 - u1}} \]
              2. *-commutativeN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \left(\color{blue}{\left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}\right) \cdot {u2}^{2}} + 1\right)}{\sqrt{1 - u1}} \]
              3. lower-fma.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left({u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}}{\sqrt{1 - u1}} \]
              4. lower--.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{{u2}^{2} \cdot \left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{98696044010906577398881}{5000000000000000000000}}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              5. *-commutativeN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2}} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              6. unpow2N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot \color{blue}{\left(u2 \cdot u2\right)} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              7. associate-*r*N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right) \cdot u2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              8. lower-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right) \cdot u2} - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              9. lower-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\color{blue}{\left(\left(\frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000} + \frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot u2\right)} \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              10. +-commutativeN/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\color{blue}{\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              11. lower-fma.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\color{blue}{\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right)} \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              12. unpow2N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              13. lower-*.f32N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, \color{blue}{u2 \cdot u2}, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, {u2}^{2}, 1\right)}{\sqrt{1 - u1}} \]
              14. unpow2N/A

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(\frac{-961389193575684075633145058384385882649239799132134631991269883031841}{11250000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{9740909103402808085817682884085781839780052161}{150000000000000000000000000000000000000000000}\right) \cdot u2\right) \cdot u2 - \frac{98696044010906577398881}{5000000000000000000000}, \color{blue}{u2 \cdot u2}, 1\right)}{\sqrt{1 - u1}} \]
              15. lower-*.f3279.4

                \[\leadsto \frac{\sqrt{u1} \cdot \mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, \color{blue}{u2 \cdot u2}, 1\right)}{\sqrt{1 - u1}} \]
            7. Applied rewrites79.4%

              \[\leadsto \frac{\sqrt{u1} \cdot \color{blue}{\mathsf{fma}\left(\left(\mathsf{fma}\left(-85.45681720672748, u2 \cdot u2, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317, u2 \cdot u2, 1\right)}}{\sqrt{1 - u1}} \]
            8. Step-by-step derivation
              1. Applied rewrites89.3%

                \[\leadsto \frac{\sqrt{u1} \cdot \left(\left(\left(\left(\mathsf{fma}\left(u2 \cdot u2, -85.45681720672748, 64.93939402268539\right) \cdot u2\right) \cdot u2 - 19.739208802181317\right) \cdot u2\right) \cdot u2 + \color{blue}{1}\right)}{\sqrt{1 - u1}} \]
              2. Add Preprocessing

              Alternative 6: 79.3% accurate, 5.4× speedup?

              \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \end{array} \]
              (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt (/ u1 (- 1.0 u1))))
              float code(float cosTheta_i, float u1, float u2) {
              	return sqrtf((u1 / (1.0f - u1)));
              }
              
              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(costheta_i, u1, u2)
              use fmin_fmax_functions
                  real(4), intent (in) :: costheta_i
                  real(4), intent (in) :: u1
                  real(4), intent (in) :: u2
                  code = sqrt((u1 / (1.0e0 - u1)))
              end function
              
              function code(cosTheta_i, u1, u2)
              	return sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
              end
              
              function tmp = code(cosTheta_i, u1, u2)
              	tmp = sqrt((u1 / (single(1.0) - u1)));
              end
              
              \begin{array}{l}
              
              \\
              \sqrt{\frac{u1}{1 - u1}}
              \end{array}
              
              Derivation
              1. Initial program 99.1%

                \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              2. Add Preprocessing
              3. Taylor expanded in u2 around 0

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
              4. Step-by-step derivation
                1. lower-sqrt.f32N/A

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                2. lower-/.f32N/A

                  \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
                3. lower--.f3279.8

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \]
              5. Applied rewrites79.8%

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
              6. Add Preprocessing

              Alternative 7: 62.5% accurate, 12.3× speedup?

              \[\begin{array}{l} \\ \sqrt{u1} \end{array} \]
              (FPCore (cosTheta_i u1 u2) :precision binary32 (sqrt u1))
              float code(float cosTheta_i, float u1, float u2) {
              	return sqrtf(u1);
              }
              
              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(costheta_i, u1, u2)
              use fmin_fmax_functions
                  real(4), intent (in) :: costheta_i
                  real(4), intent (in) :: u1
                  real(4), intent (in) :: u2
                  code = sqrt(u1)
              end function
              
              function code(cosTheta_i, u1, u2)
              	return sqrt(u1)
              end
              
              function tmp = code(cosTheta_i, u1, u2)
              	tmp = sqrt(u1);
              end
              
              \begin{array}{l}
              
              \\
              \sqrt{u1}
              \end{array}
              
              Derivation
              1. Initial program 99.1%

                \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
              2. Add Preprocessing
              3. Taylor expanded in u2 around 0

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
              4. Step-by-step derivation
                1. lower-sqrt.f32N/A

                  \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                2. lower-/.f32N/A

                  \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
                3. lower--.f3279.8

                  \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \]
              5. Applied rewrites79.8%

                \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
              6. Step-by-step derivation
                1. Applied rewrites61.6%

                  \[\leadsto \sqrt{\frac{u1}{u1 + 1}} \]
                2. Taylor expanded in u1 around -inf

                  \[\leadsto {\left(\sqrt{-1}\right)}^{\color{blue}{2}} \]
                3. Step-by-step derivation
                  1. Applied rewrites4.2%

                    \[\leadsto -1 \]
                  2. Taylor expanded in u1 around 0

                    \[\leadsto \sqrt{u1} \]
                  3. Step-by-step derivation
                    1. Applied rewrites63.2%

                      \[\leadsto \sqrt{u1} \]
                    2. Add Preprocessing

                    Alternative 8: 4.2% accurate, 135.0× speedup?

                    \[\begin{array}{l} \\ -1 \end{array} \]
                    (FPCore (cosTheta_i u1 u2) :precision binary32 -1.0)
                    float code(float cosTheta_i, float u1, float u2) {
                    	return -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(costheta_i, u1, u2)
                    use fmin_fmax_functions
                        real(4), intent (in) :: costheta_i
                        real(4), intent (in) :: u1
                        real(4), intent (in) :: u2
                        code = -1.0e0
                    end function
                    
                    function code(cosTheta_i, u1, u2)
                    	return Float32(-1.0)
                    end
                    
                    function tmp = code(cosTheta_i, u1, u2)
                    	tmp = single(-1.0);
                    end
                    
                    \begin{array}{l}
                    
                    \\
                    -1
                    \end{array}
                    
                    Derivation
                    1. Initial program 99.1%

                      \[\sqrt{\frac{u1}{1 - u1}} \cdot \cos \left(6.28318530718 \cdot u2\right) \]
                    2. Add Preprocessing
                    3. Taylor expanded in u2 around 0

                      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                    4. Step-by-step derivation
                      1. lower-sqrt.f32N/A

                        \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                      2. lower-/.f32N/A

                        \[\leadsto \sqrt{\color{blue}{\frac{u1}{1 - u1}}} \]
                      3. lower--.f3279.8

                        \[\leadsto \sqrt{\frac{u1}{\color{blue}{1 - u1}}} \]
                    5. Applied rewrites79.8%

                      \[\leadsto \color{blue}{\sqrt{\frac{u1}{1 - u1}}} \]
                    6. Step-by-step derivation
                      1. Applied rewrites61.6%

                        \[\leadsto \sqrt{\frac{u1}{u1 + 1}} \]
                      2. Taylor expanded in u1 around -inf

                        \[\leadsto {\left(\sqrt{-1}\right)}^{\color{blue}{2}} \]
                      3. Step-by-step derivation
                        1. Applied rewrites4.2%

                          \[\leadsto -1 \]
                        2. Add Preprocessing

                        Reproduce

                        ?
                        herbie shell --seed 2024346 
                        (FPCore (cosTheta_i u1 u2)
                          :name "Trowbridge-Reitz Sample, near normal, slope_x"
                          :precision binary32
                          :pre (and (and (and (> cosTheta_i 0.9999) (<= cosTheta_i 1.0)) (and (<= 2.328306437e-10 u1) (<= u1 1.0))) (and (<= 2.328306437e-10 u2) (<= u2 1.0)))
                          (* (sqrt (/ u1 (- 1.0 u1))) (cos (* 6.28318530718 u2))))