Trowbridge-Reitz Sample, near normal, slope_y

Percentage Accurate: 98.3% → 98.3%
Time: 5.1s
Alternatives: 12
Speedup: 1.0×

Specification

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

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

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 12 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: 98.3% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (sin (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * sinf((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))) * sin((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * sin(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * sin((single(6.28318530718) * u2));
end
\begin{array}{l}

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

Alternative 1: 98.3% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \left(\sqrt{\frac{u1}{2 - \left(u1 + u1\right)}} \cdot \sqrt{2}\right) \cdot \sin \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (* (sqrt (/ u1 (- 2.0 (+ u1 u1)))) (sqrt 2.0)) (sin (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return (sqrtf((u1 / (2.0f - (u1 + u1)))) * sqrtf(2.0f)) * sinf((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 / (2.0e0 - (u1 + u1)))) * sqrt(2.0e0)) * sin((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(Float32(sqrt(Float32(u1 / Float32(Float32(2.0) - Float32(u1 + u1)))) * sqrt(Float32(2.0))) * sin(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = (sqrt((u1 / (single(2.0) - (u1 + u1)))) * sqrt(single(2.0))) * sin((single(6.28318530718) * u2));
end
\begin{array}{l}

\\
\left(\sqrt{\frac{u1}{2 - \left(u1 + u1\right)}} \cdot \sqrt{2}\right) \cdot \sin \left(6.28318530718 \cdot u2\right)
\end{array}
Derivation
  1. Initial program 98.3%

    \[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  2. Applied rewrites98.3%

    \[\leadsto \color{blue}{\left(\sqrt{\frac{u1}{2 - \left(u1 + u1\right)}} \cdot \sqrt{2}\right)} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  3. Add Preprocessing

Alternative 2: 98.3% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- 1.0 u1))) (sin (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * sinf((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))) * sin((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * sin(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / (single(1.0) - u1))) * sin((single(6.28318530718) * u2));
end
\begin{array}{l}

\\
\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right)
\end{array}
Derivation
  1. Initial program 98.3%

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

Alternative 3: 96.7% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;u2 \leq 0.06499999761581421:\\ \;\;\;\;\mathsf{fma}\left(t\_0 \cdot u2, 6.28318530718, \left(\left(t\_0 \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right) \cdot u2\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1 \cdot \left(1 + u1\right)} \cdot \sin \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= u2 0.06499999761581421)
     (fma
      (* t_0 u2)
      6.28318530718
      (*
       (*
        (* t_0 (fma 81.6052492761019 (* u2 u2) -41.341702240407926))
        (* u2 u2))
       u2))
     (* (sqrt (* u1 (+ 1.0 u1))) (sin (* 6.28318530718 u2))))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sqrtf((u1 / (1.0f - u1)));
	float tmp;
	if (u2 <= 0.06499999761581421f) {
		tmp = fmaf((t_0 * u2), 6.28318530718f, (((t_0 * fmaf(81.6052492761019f, (u2 * u2), -41.341702240407926f)) * (u2 * u2)) * u2));
	} else {
		tmp = sqrtf((u1 * (1.0f + u1))) * sinf((6.28318530718f * u2));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
	tmp = Float32(0.0)
	if (u2 <= Float32(0.06499999761581421))
		tmp = fma(Float32(t_0 * u2), Float32(6.28318530718), Float32(Float32(Float32(t_0 * fma(Float32(81.6052492761019), Float32(u2 * u2), Float32(-41.341702240407926))) * Float32(u2 * u2)) * u2));
	else
		tmp = Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + u1))) * sin(Float32(Float32(6.28318530718) * u2)));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sqrt{\frac{u1}{1 - u1}}\\
\mathbf{if}\;u2 \leq 0.06499999761581421:\\
\;\;\;\;\mathsf{fma}\left(t\_0 \cdot u2, 6.28318530718, \left(\left(t\_0 \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right) \cdot u2\right)\\

\mathbf{else}:\\
\;\;\;\;\sqrt{u1 \cdot \left(1 + u1\right)} \cdot \sin \left(6.28318530718 \cdot u2\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u2 < 0.0649999976

    1. Initial program 98.3%

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

      \[\leadsto \color{blue}{u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
    3. Step-by-step derivation
      1. lower-*.f32N/A

        \[\leadsto u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      2. lower-fma.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \color{blue}{\sqrt{\frac{u1}{1 - u1}}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      3. lower-sqrt.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      4. lower-/.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      5. lower--.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      6. lower-*.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      7. lower-pow.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      8. lower-fma.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
    4. Applied rewrites91.4%

      \[\leadsto \color{blue}{u2 \cdot \mathsf{fma}\left(6.28318530718, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(-41.341702240407926, \sqrt{\frac{u1}{1 - u1}}, 81.6052492761019 \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
    5. Step-by-step derivation
      1. lift-*.f32N/A

        \[\leadsto u2 \cdot \color{blue}{\mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      2. lift-fma.f32N/A

        \[\leadsto u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \color{blue}{{u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)}\right) \]
      3. distribute-rgt-inN/A

        \[\leadsto \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 + \color{blue}{\left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \cdot u2} \]
      4. associate-*l*N/A

        \[\leadsto \frac{314159265359}{50000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot u2\right) + \color{blue}{\left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \cdot u2 \]
      5. *-commutativeN/A

        \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) + \left({u2}^{2} \cdot \color{blue}{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)}\right) \cdot u2 \]
      6. lift-*.f32N/A

        \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) + \left({u2}^{2} \cdot \color{blue}{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)}\right) \cdot u2 \]
      7. *-commutativeN/A

        \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) + u2 \cdot \color{blue}{\left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      8. *-commutativeN/A

        \[\leadsto \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot \frac{314159265359}{50000000000} + \color{blue}{u2} \cdot \left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      9. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}, \color{blue}{\frac{314159265359}{50000000000}}, u2 \cdot \left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)\right) \]
    6. Applied rewrites91.4%

      \[\leadsto \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}} \cdot u2, \color{blue}{6.28318530718}, \left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right) \cdot u2\right) \]

    if 0.0649999976 < u2

    1. Initial program 98.3%

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

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    3. Step-by-step derivation
      1. lower-*.f32N/A

        \[\leadsto \sqrt{u1 \cdot \color{blue}{\left(1 + u1\right)}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      2. lower-+.f3286.4

        \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{u1}\right)} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    4. Applied rewrites86.4%

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 4: 95.2% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;u2 \leq 0.06499999761581421:\\ \;\;\;\;\mathsf{fma}\left(t\_0 \cdot u2, 6.28318530718, \left(\left(t\_0 \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right) \cdot u2\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \sin \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
   (if (<= u2 0.06499999761581421)
     (fma
      (* t_0 u2)
      6.28318530718
      (*
       (*
        (* t_0 (fma 81.6052492761019 (* u2 u2) -41.341702240407926))
        (* u2 u2))
       u2))
     (* (sqrt u1) (sin (* 6.28318530718 u2))))))
float code(float cosTheta_i, float u1, float u2) {
	float t_0 = sqrtf((u1 / (1.0f - u1)));
	float tmp;
	if (u2 <= 0.06499999761581421f) {
		tmp = fmaf((t_0 * u2), 6.28318530718f, (((t_0 * fmaf(81.6052492761019f, (u2 * u2), -41.341702240407926f)) * (u2 * u2)) * u2));
	} else {
		tmp = sqrtf(u1) * sinf((6.28318530718f * u2));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
	tmp = Float32(0.0)
	if (u2 <= Float32(0.06499999761581421))
		tmp = fma(Float32(t_0 * u2), Float32(6.28318530718), Float32(Float32(Float32(t_0 * fma(Float32(81.6052492761019), Float32(u2 * u2), Float32(-41.341702240407926))) * Float32(u2 * u2)) * u2));
	else
		tmp = Float32(sqrt(u1) * sin(Float32(Float32(6.28318530718) * u2)));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sqrt{\frac{u1}{1 - u1}}\\
\mathbf{if}\;u2 \leq 0.06499999761581421:\\
\;\;\;\;\mathsf{fma}\left(t\_0 \cdot u2, 6.28318530718, \left(\left(t\_0 \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right) \cdot u2\right)\\

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


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u2 < 0.0649999976

    1. Initial program 98.3%

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

      \[\leadsto \color{blue}{u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
    3. Step-by-step derivation
      1. lower-*.f32N/A

        \[\leadsto u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      2. lower-fma.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \color{blue}{\sqrt{\frac{u1}{1 - u1}}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      3. lower-sqrt.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      4. lower-/.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      5. lower--.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      6. lower-*.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      7. lower-pow.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      8. lower-fma.f32N/A

        \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
    4. Applied rewrites91.4%

      \[\leadsto \color{blue}{u2 \cdot \mathsf{fma}\left(6.28318530718, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(-41.341702240407926, \sqrt{\frac{u1}{1 - u1}}, 81.6052492761019 \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
    5. Step-by-step derivation
      1. lift-*.f32N/A

        \[\leadsto u2 \cdot \color{blue}{\mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      2. lift-fma.f32N/A

        \[\leadsto u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \color{blue}{{u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)}\right) \]
      3. distribute-rgt-inN/A

        \[\leadsto \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot u2 + \color{blue}{\left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \cdot u2} \]
      4. associate-*l*N/A

        \[\leadsto \frac{314159265359}{50000000000} \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot u2\right) + \color{blue}{\left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \cdot u2 \]
      5. *-commutativeN/A

        \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) + \left({u2}^{2} \cdot \color{blue}{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)}\right) \cdot u2 \]
      6. lift-*.f32N/A

        \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) + \left({u2}^{2} \cdot \color{blue}{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)}\right) \cdot u2 \]
      7. *-commutativeN/A

        \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) + u2 \cdot \color{blue}{\left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      8. *-commutativeN/A

        \[\leadsto \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \cdot \frac{314159265359}{50000000000} + \color{blue}{u2} \cdot \left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      9. lower-fma.f32N/A

        \[\leadsto \mathsf{fma}\left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}, \color{blue}{\frac{314159265359}{50000000000}}, u2 \cdot \left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)\right) \]
    6. Applied rewrites91.4%

      \[\leadsto \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}} \cdot u2, \color{blue}{6.28318530718}, \left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right) \cdot u2\right) \]

    if 0.0649999976 < u2

    1. Initial program 98.3%

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

      \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    3. Step-by-step derivation
      1. Applied rewrites74.6%

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

    Alternative 5: 95.2% accurate, 1.0× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;u2 \leq 0.06499999761581421:\\ \;\;\;\;u2 \cdot \mathsf{fma}\left(t\_0, 6.28318530718, \left(t\_0 \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \sin \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
       (if (<= u2 0.06499999761581421)
         (*
          u2
          (fma
           t_0
           6.28318530718
           (*
            (* t_0 (fma 81.6052492761019 (* u2 u2) -41.341702240407926))
            (* u2 u2))))
         (* (sqrt u1) (sin (* 6.28318530718 u2))))))
    float code(float cosTheta_i, float u1, float u2) {
    	float t_0 = sqrtf((u1 / (1.0f - u1)));
    	float tmp;
    	if (u2 <= 0.06499999761581421f) {
    		tmp = u2 * fmaf(t_0, 6.28318530718f, ((t_0 * fmaf(81.6052492761019f, (u2 * u2), -41.341702240407926f)) * (u2 * u2)));
    	} else {
    		tmp = sqrtf(u1) * sinf((6.28318530718f * u2));
    	}
    	return tmp;
    }
    
    function code(cosTheta_i, u1, u2)
    	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
    	tmp = Float32(0.0)
    	if (u2 <= Float32(0.06499999761581421))
    		tmp = Float32(u2 * fma(t_0, Float32(6.28318530718), Float32(Float32(t_0 * fma(Float32(81.6052492761019), Float32(u2 * u2), Float32(-41.341702240407926))) * Float32(u2 * u2))));
    	else
    		tmp = Float32(sqrt(u1) * sin(Float32(Float32(6.28318530718) * u2)));
    	end
    	return tmp
    end
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \sqrt{\frac{u1}{1 - u1}}\\
    \mathbf{if}\;u2 \leq 0.06499999761581421:\\
    \;\;\;\;u2 \cdot \mathsf{fma}\left(t\_0, 6.28318530718, \left(t\_0 \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\sqrt{u1} \cdot \sin \left(6.28318530718 \cdot u2\right)\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if u2 < 0.0649999976

      1. Initial program 98.3%

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

        \[\leadsto \color{blue}{u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      3. Step-by-step derivation
        1. lower-*.f32N/A

          \[\leadsto u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
        2. lower-fma.f32N/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \color{blue}{\sqrt{\frac{u1}{1 - u1}}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        3. lower-sqrt.f32N/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        4. lower-/.f32N/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        5. lower--.f32N/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        6. lower-*.f32N/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        7. lower-pow.f32N/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        8. lower-fma.f32N/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
      4. Applied rewrites91.4%

        \[\leadsto \color{blue}{u2 \cdot \mathsf{fma}\left(6.28318530718, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(-41.341702240407926, \sqrt{\frac{u1}{1 - u1}}, 81.6052492761019 \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
      5. Step-by-step derivation
        1. lift-fma.f32N/A

          \[\leadsto u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \color{blue}{{u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)}\right) \]
        2. *-commutativeN/A

          \[\leadsto u2 \cdot \left(\sqrt{\frac{u1}{1 - u1}} \cdot \frac{314159265359}{50000000000} + \color{blue}{{u2}^{2}} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        3. lower-fma.f3291.4

          \[\leadsto u2 \cdot \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, \color{blue}{6.28318530718}, {u2}^{2} \cdot \mathsf{fma}\left(-41.341702240407926, \sqrt{\frac{u1}{1 - u1}}, 81.6052492761019 \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        4. lift-*.f32N/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, \frac{314159265359}{50000000000}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        5. *-commutativeN/A

          \[\leadsto u2 \cdot \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, \frac{314159265359}{50000000000}, \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right) \cdot {u2}^{2}\right) \]
        6. lower-*.f3291.4

          \[\leadsto u2 \cdot \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, 6.28318530718, \mathsf{fma}\left(-41.341702240407926, \sqrt{\frac{u1}{1 - u1}}, 81.6052492761019 \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right) \cdot {u2}^{2}\right) \]
      6. Applied rewrites91.4%

        \[\leadsto u2 \cdot \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}}, \color{blue}{6.28318530718}, \left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right)\right) \cdot \left(u2 \cdot u2\right)\right) \]

      if 0.0649999976 < u2

      1. Initial program 98.3%

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

        \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. Step-by-step derivation
        1. Applied rewrites74.6%

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

      Alternative 6: 95.1% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ \mathbf{if}\;u2 \leq 0.06499999761581421:\\ \;\;\;\;\mathsf{fma}\left(t\_0 \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, t\_0 \cdot 6.28318530718\right) \cdot u2\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \sin \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
         (if (<= u2 0.06499999761581421)
           (*
            (fma
             (* t_0 (fma 81.6052492761019 (* u2 u2) -41.341702240407926))
             (* u2 u2)
             (* t_0 6.28318530718))
            u2)
           (* (sqrt u1) (sin (* 6.28318530718 u2))))))
      float code(float cosTheta_i, float u1, float u2) {
      	float t_0 = sqrtf((u1 / (1.0f - u1)));
      	float tmp;
      	if (u2 <= 0.06499999761581421f) {
      		tmp = fmaf((t_0 * fmaf(81.6052492761019f, (u2 * u2), -41.341702240407926f)), (u2 * u2), (t_0 * 6.28318530718f)) * u2;
      	} else {
      		tmp = sqrtf(u1) * sinf((6.28318530718f * u2));
      	}
      	return tmp;
      }
      
      function code(cosTheta_i, u1, u2)
      	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
      	tmp = Float32(0.0)
      	if (u2 <= Float32(0.06499999761581421))
      		tmp = Float32(fma(Float32(t_0 * fma(Float32(81.6052492761019), Float32(u2 * u2), Float32(-41.341702240407926))), Float32(u2 * u2), Float32(t_0 * Float32(6.28318530718))) * u2);
      	else
      		tmp = Float32(sqrt(u1) * sin(Float32(Float32(6.28318530718) * u2)));
      	end
      	return tmp
      end
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := \sqrt{\frac{u1}{1 - u1}}\\
      \mathbf{if}\;u2 \leq 0.06499999761581421:\\
      \;\;\;\;\mathsf{fma}\left(t\_0 \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, t\_0 \cdot 6.28318530718\right) \cdot u2\\
      
      \mathbf{else}:\\
      \;\;\;\;\sqrt{u1} \cdot \sin \left(6.28318530718 \cdot u2\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if u2 < 0.0649999976

        1. Initial program 98.3%

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

          \[\leadsto \color{blue}{u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
        3. Step-by-step derivation
          1. lower-*.f32N/A

            \[\leadsto u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
          2. lower-fma.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \color{blue}{\sqrt{\frac{u1}{1 - u1}}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
          3. lower-sqrt.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
          4. lower-/.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
          5. lower--.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
          6. lower-*.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
          7. lower-pow.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
          8. lower-fma.f32N/A

            \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
        4. Applied rewrites91.4%

          \[\leadsto \color{blue}{u2 \cdot \mathsf{fma}\left(6.28318530718, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(-41.341702240407926, \sqrt{\frac{u1}{1 - u1}}, 81.6052492761019 \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
        5. Step-by-step derivation
          1. lift-*.f32N/A

            \[\leadsto u2 \cdot \color{blue}{\mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
          2. *-commutativeN/A

            \[\leadsto \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \cdot \color{blue}{u2} \]
          3. lower-*.f3291.4

            \[\leadsto \mathsf{fma}\left(6.28318530718, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(-41.341702240407926, \sqrt{\frac{u1}{1 - u1}}, 81.6052492761019 \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \cdot \color{blue}{u2} \]
        6. Applied rewrites91.4%

          \[\leadsto \mathsf{fma}\left(\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, \sqrt{\frac{u1}{1 - u1}} \cdot 6.28318530718\right) \cdot \color{blue}{u2} \]

        if 0.0649999976 < u2

        1. Initial program 98.3%

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

          \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
        3. Step-by-step derivation
          1. Applied rewrites74.6%

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

        Alternative 7: 93.7% accurate, 1.1× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;u2 \leq 0.02500000037252903:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + -41.341702240407926 \cdot {u2}^{2}\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{u1} \cdot \sin \left(6.28318530718 \cdot u2\right)\\ \end{array} \end{array} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (if (<= u2 0.02500000037252903)
           (*
            (sqrt (/ u1 (- 1.0 u1)))
            (* u2 (+ 6.28318530718 (* -41.341702240407926 (pow u2 2.0)))))
           (* (sqrt u1) (sin (* 6.28318530718 u2)))))
        float code(float cosTheta_i, float u1, float u2) {
        	float tmp;
        	if (u2 <= 0.02500000037252903f) {
        		tmp = sqrtf((u1 / (1.0f - u1))) * (u2 * (6.28318530718f + (-41.341702240407926f * powf(u2, 2.0f))));
        	} else {
        		tmp = sqrtf(u1) * sinf((6.28318530718f * u2));
        	}
        	return tmp;
        }
        
        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
            real(4) :: tmp
            if (u2 <= 0.02500000037252903e0) then
                tmp = sqrt((u1 / (1.0e0 - u1))) * (u2 * (6.28318530718e0 + ((-41.341702240407926e0) * (u2 ** 2.0e0))))
            else
                tmp = sqrt(u1) * sin((6.28318530718e0 * u2))
            end if
            code = tmp
        end function
        
        function code(cosTheta_i, u1, u2)
        	tmp = Float32(0.0)
        	if (u2 <= Float32(0.02500000037252903))
        		tmp = Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(u2 * Float32(Float32(6.28318530718) + Float32(Float32(-41.341702240407926) * (u2 ^ Float32(2.0))))));
        	else
        		tmp = Float32(sqrt(u1) * sin(Float32(Float32(6.28318530718) * u2)));
        	end
        	return tmp
        end
        
        function tmp_2 = code(cosTheta_i, u1, u2)
        	tmp = single(0.0);
        	if (u2 <= single(0.02500000037252903))
        		tmp = sqrt((u1 / (single(1.0) - u1))) * (u2 * (single(6.28318530718) + (single(-41.341702240407926) * (u2 ^ single(2.0)))));
        	else
        		tmp = sqrt(u1) * sin((single(6.28318530718) * u2));
        	end
        	tmp_2 = tmp;
        end
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        \mathbf{if}\;u2 \leq 0.02500000037252903:\\
        \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + -41.341702240407926 \cdot {u2}^{2}\right)\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;\sqrt{u1} \cdot \sin \left(6.28318530718 \cdot u2\right)\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 2 regimes
        2. if u2 < 0.0250000004

          1. Initial program 98.3%

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
          3. Step-by-step derivation
            1. lower-*.f32N/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)}\right) \]
            2. lower-+.f32N/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}}\right)\right) \]
            3. lower-*.f32N/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \color{blue}{{u2}^{2}}\right)\right) \]
            4. lower-pow.f3288.9

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + -41.341702240407926 \cdot {u2}^{\color{blue}{2}}\right)\right) \]
          4. Applied rewrites88.9%

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + -41.341702240407926 \cdot {u2}^{2}\right)\right)} \]

          if 0.0250000004 < u2

          1. Initial program 98.3%

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

            \[\leadsto \sqrt{\color{blue}{u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
          3. Step-by-step derivation
            1. Applied rewrites74.6%

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

          Alternative 8: 88.9% accurate, 1.3× speedup?

          \[\begin{array}{l} \\ \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + -41.341702240407926 \cdot {u2}^{2}\right)\right) \end{array} \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (*
            (sqrt (/ u1 (- 1.0 u1)))
            (* u2 (+ 6.28318530718 (* -41.341702240407926 (pow u2 2.0))))))
          float code(float cosTheta_i, float u1, float u2) {
          	return sqrtf((u1 / (1.0f - u1))) * (u2 * (6.28318530718f + (-41.341702240407926f * powf(u2, 2.0f))));
          }
          
          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 = sqrt((u1 / (1.0e0 - u1))) * (u2 * (6.28318530718e0 + ((-41.341702240407926e0) * (u2 ** 2.0e0))))
          end function
          
          function code(cosTheta_i, u1, u2)
          	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(u2 * Float32(Float32(6.28318530718) + Float32(Float32(-41.341702240407926) * (u2 ^ Float32(2.0))))))
          end
          
          function tmp = code(cosTheta_i, u1, u2)
          	tmp = sqrt((u1 / (single(1.0) - u1))) * (u2 * (single(6.28318530718) + (single(-41.341702240407926) * (u2 ^ single(2.0)))));
          end
          
          \begin{array}{l}
          
          \\
          \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + -41.341702240407926 \cdot {u2}^{2}\right)\right)
          \end{array}
          
          Derivation
          1. Initial program 98.3%

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)\right)} \]
          3. Step-by-step derivation
            1. lower-*.f32N/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}\right)}\right) \]
            2. lower-+.f32N/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot {u2}^{2}}\right)\right) \]
            3. lower-*.f32N/A

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \color{blue}{{u2}^{2}}\right)\right) \]
            4. lower-pow.f3288.9

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + -41.341702240407926 \cdot {u2}^{\color{blue}{2}}\right)\right) \]
          4. Applied rewrites88.9%

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + -41.341702240407926 \cdot {u2}^{2}\right)\right)} \]
          5. Add Preprocessing

          Alternative 9: 88.8% accurate, 1.4× speedup?

          \[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\frac{u1}{1 - u1}}\\ u2 \cdot \mathsf{fma}\left(\left(t\_0 \cdot u2\right) \cdot u2, -41.341702240407926, t\_0 \cdot 6.28318530718\right) \end{array} \end{array} \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (let* ((t_0 (sqrt (/ u1 (- 1.0 u1)))))
             (* u2 (fma (* (* t_0 u2) u2) -41.341702240407926 (* t_0 6.28318530718)))))
          float code(float cosTheta_i, float u1, float u2) {
          	float t_0 = sqrtf((u1 / (1.0f - u1)));
          	return u2 * fmaf(((t_0 * u2) * u2), -41.341702240407926f, (t_0 * 6.28318530718f));
          }
          
          function code(cosTheta_i, u1, u2)
          	t_0 = sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))
          	return Float32(u2 * fma(Float32(Float32(t_0 * u2) * u2), Float32(-41.341702240407926), Float32(t_0 * Float32(6.28318530718))))
          end
          
          \begin{array}{l}
          
          \\
          \begin{array}{l}
          t_0 := \sqrt{\frac{u1}{1 - u1}}\\
          u2 \cdot \mathsf{fma}\left(\left(t\_0 \cdot u2\right) \cdot u2, -41.341702240407926, t\_0 \cdot 6.28318530718\right)
          \end{array}
          \end{array}
          
          Derivation
          1. Initial program 98.3%

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

            \[\leadsto \color{blue}{u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
          3. Step-by-step derivation
            1. lower-*.f32N/A

              \[\leadsto u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
            2. lower-fma.f32N/A

              \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \color{blue}{\sqrt{\frac{u1}{1 - u1}}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
            3. lower-sqrt.f32N/A

              \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
            4. lower-/.f32N/A

              \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
            5. lower--.f32N/A

              \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
            6. lower-*.f32N/A

              \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
            7. lower-pow.f32N/A

              \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
            8. lower-fma.f32N/A

              \[\leadsto u2 \cdot \mathsf{fma}\left(\frac{314159265359}{50000000000}, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) \]
          4. Applied rewrites91.4%

            \[\leadsto \color{blue}{u2 \cdot \mathsf{fma}\left(6.28318530718, \sqrt{\frac{u1}{1 - u1}}, {u2}^{2} \cdot \mathsf{fma}\left(-41.341702240407926, \sqrt{\frac{u1}{1 - u1}}, 81.6052492761019 \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right)} \]
          5. Step-by-step derivation
            1. lift-fma.f32N/A

              \[\leadsto u2 \cdot \left(\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \color{blue}{{u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)}\right) \]
            2. +-commutativeN/A

              \[\leadsto u2 \cdot \left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right) + \color{blue}{\frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}}\right) \]
            3. lift-*.f32N/A

              \[\leadsto u2 \cdot \left({u2}^{2} \cdot \mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right) + \color{blue}{\frac{314159265359}{50000000000}} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
            4. lift-fma.f32N/A

              \[\leadsto u2 \cdot \left({u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right) + \frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
            5. distribute-lft-inN/A

              \[\leadsto u2 \cdot \left(\left({u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) + {u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right)\right) + \color{blue}{\frac{314159265359}{50000000000}} \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
            6. associate-+l+N/A

              \[\leadsto u2 \cdot \left({u2}^{2} \cdot \left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right) + \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} \cdot \left({u2}^{2} \cdot \sqrt{\frac{u1}{1 - u1}}\right)\right) + \frac{314159265359}{50000000000} \cdot \sqrt{\frac{u1}{1 - u1}}\right)}\right) \]
          6. Applied rewrites91.4%

            \[\leadsto u2 \cdot \mathsf{fma}\left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot u2\right) \cdot u2, \color{blue}{-41.341702240407926}, \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2 \cdot u2, 81.6052492761019 \cdot \left(u2 \cdot u2\right), 6.28318530718\right)\right) \]
          7. Taylor expanded in u2 around 0

            \[\leadsto u2 \cdot \mathsf{fma}\left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot u2\right) \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}, \sqrt{\frac{u1}{1 - u1}} \cdot \frac{314159265359}{50000000000}\right) \]
          8. Step-by-step derivation
            1. Applied rewrites88.8%

              \[\leadsto u2 \cdot \mathsf{fma}\left(\left(\sqrt{\frac{u1}{1 - u1}} \cdot u2\right) \cdot u2, -41.341702240407926, \sqrt{\frac{u1}{1 - u1}} \cdot 6.28318530718\right) \]
            2. Add Preprocessing

            Alternative 10: 81.0% accurate, 3.2× speedup?

            \[\begin{array}{l} \\ 6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (* 6.28318530718 (* u2 (sqrt (/ u1 (- 1.0 u1))))))
            float code(float cosTheta_i, float u1, float u2) {
            	return 6.28318530718f * (u2 * 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 = 6.28318530718e0 * (u2 * sqrt((u1 / (1.0e0 - u1))))
            end function
            
            function code(cosTheta_i, u1, u2)
            	return Float32(Float32(6.28318530718) * Float32(u2 * sqrt(Float32(u1 / Float32(Float32(1.0) - u1)))))
            end
            
            function tmp = code(cosTheta_i, u1, u2)
            	tmp = single(6.28318530718) * (u2 * sqrt((u1 / (single(1.0) - u1))));
            end
            
            \begin{array}{l}
            
            \\
            6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right)
            \end{array}
            
            Derivation
            1. Initial program 98.3%

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

              \[\leadsto \color{blue}{\frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
            3. Step-by-step derivation
              1. lower-*.f32N/A

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

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

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

                \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
              5. lower--.f3281.0

                \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
            4. Applied rewrites81.0%

              \[\leadsto \color{blue}{6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
            5. Add Preprocessing

            Alternative 11: 72.7% accurate, 3.3× speedup?

            \[\begin{array}{l} \\ 6.28318530718 \cdot \left(u2 \cdot \sqrt{u1 \cdot \left(1 + u1\right)}\right) \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (* 6.28318530718 (* u2 (sqrt (* u1 (+ 1.0 u1))))))
            float code(float cosTheta_i, float u1, float u2) {
            	return 6.28318530718f * (u2 * 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 = 6.28318530718e0 * (u2 * sqrt((u1 * (1.0e0 + u1))))
            end function
            
            function code(cosTheta_i, u1, u2)
            	return Float32(Float32(6.28318530718) * Float32(u2 * sqrt(Float32(u1 * Float32(Float32(1.0) + u1)))))
            end
            
            function tmp = code(cosTheta_i, u1, u2)
            	tmp = single(6.28318530718) * (u2 * sqrt((u1 * (single(1.0) + u1))));
            end
            
            \begin{array}{l}
            
            \\
            6.28318530718 \cdot \left(u2 \cdot \sqrt{u1 \cdot \left(1 + u1\right)}\right)
            \end{array}
            
            Derivation
            1. Initial program 98.3%

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

              \[\leadsto \color{blue}{\frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
            3. Step-by-step derivation
              1. lower-*.f32N/A

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

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

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

                \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
              5. lower--.f3281.0

                \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
            4. Applied rewrites81.0%

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

              \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{u1 \cdot \left(1 + u1\right)}\right) \]
            6. Step-by-step derivation
              1. lower-*.f32N/A

                \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{u1 \cdot \left(1 + u1\right)}\right) \]
              2. lower-+.f3272.7

                \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{u1 \cdot \left(1 + u1\right)}\right) \]
            7. Applied rewrites72.7%

              \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{u1 \cdot \left(1 + u1\right)}\right) \]
            8. Add Preprocessing

            Alternative 12: 64.6% accurate, 5.3× speedup?

            \[\begin{array}{l} \\ 6.28318530718 \cdot \left(u2 \cdot \sqrt{u1}\right) \end{array} \]
            (FPCore (cosTheta_i u1 u2)
             :precision binary32
             (* 6.28318530718 (* u2 (sqrt u1))))
            float code(float cosTheta_i, float u1, float u2) {
            	return 6.28318530718f * (u2 * 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 = 6.28318530718e0 * (u2 * sqrt(u1))
            end function
            
            function code(cosTheta_i, u1, u2)
            	return Float32(Float32(6.28318530718) * Float32(u2 * sqrt(u1)))
            end
            
            function tmp = code(cosTheta_i, u1, u2)
            	tmp = single(6.28318530718) * (u2 * sqrt(u1));
            end
            
            \begin{array}{l}
            
            \\
            6.28318530718 \cdot \left(u2 \cdot \sqrt{u1}\right)
            \end{array}
            
            Derivation
            1. Initial program 98.3%

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

              \[\leadsto \color{blue}{\frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right)} \]
            3. Step-by-step derivation
              1. lower-*.f32N/A

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

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

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

                \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
              5. lower--.f3281.0

                \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
            4. Applied rewrites81.0%

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

              \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{u1}\right) \]
            6. Step-by-step derivation
              1. lower-sqrt.f3264.6

                \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{u1}\right) \]
            7. Applied rewrites64.6%

              \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{u1}\right) \]
            8. Add Preprocessing

            Reproduce

            ?
            herbie shell --seed 2025154 
            (FPCore (cosTheta_i u1 u2)
              :name "Trowbridge-Reitz Sample, near normal, slope_y"
              :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))) (sin (* 6.28318530718 u2))))