Trowbridge-Reitz Sample, near normal, slope_y

Percentage Accurate: 98.3% → 98.3%
Time: 4.7s
Alternatives: 15
Speedup: 1.0×

Specification

?
\[\left(\left(cosTheta\_i > 0.9999 \land cosTheta\_i \leq 1\right) \land \left(2.328306437 \cdot 10^{-10} \leq u1 \land u1 \leq 1\right)\right) \land \left(2.328306437 \cdot 10^{-10} \leq u2 \land u2 \leq 1\right)\]
\[\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
(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
\sqrt{\frac{u1}{1 - u1}} \cdot \sin \left(6.28318530718 \cdot u2\right)

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 15 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?

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

Alternative 1: 98.3% accurate, 1.0× speedup?

\[\sqrt{\frac{u1}{\left(0.5 - u1\right) - -0.5}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (* (sqrt (/ u1 (- (- 0.5 u1) -0.5))) (sin (* 6.28318530718 u2))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / ((0.5f - u1) - -0.5f))) * 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 / ((0.5e0 - u1) - (-0.5e0)))) * sin((6.28318530718e0 * u2))
end function
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(Float32(0.5) - u1) - Float32(-0.5)))) * sin(Float32(Float32(6.28318530718) * u2)))
end
function tmp = code(cosTheta_i, u1, u2)
	tmp = sqrt((u1 / ((single(0.5) - u1) - single(-0.5)))) * sin((single(6.28318530718) * u2));
end
\sqrt{\frac{u1}{\left(0.5 - u1\right) - -0.5}} \cdot \sin \left(6.28318530718 \cdot u2\right)
Derivation
  1. Initial program 98.3%

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

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

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(\frac{1}{2} + \frac{1}{2}\right)} - u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    3. associate--l+N/A

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

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\frac{1}{2} + \left(\frac{1}{2} - u1\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    5. lower--.f3298.3%

      \[\leadsto \sqrt{\frac{u1}{0.5 + \color{blue}{\left(0.5 - u1\right)}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  3. Applied rewrites98.3%

    \[\leadsto \sqrt{\frac{u1}{\color{blue}{0.5 + \left(0.5 - u1\right)}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  4. Step-by-step derivation
    1. lift-+.f32N/A

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

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(\frac{1}{2} - u1\right) + \frac{1}{2}}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    3. add-flipN/A

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

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(\frac{1}{2} - u1\right) - \left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
    5. metadata-eval98.3%

      \[\leadsto \sqrt{\frac{u1}{\left(0.5 - u1\right) - \color{blue}{-0.5}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  5. Applied rewrites98.3%

    \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(0.5 - u1\right) - -0.5}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
  6. Add Preprocessing

Alternative 2: 97.1% accurate, 0.9× speedup?

\[\begin{array}{l} \mathbf{if}\;u2 \leq 0.20999999344348907:\\ \;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), \left(\left(u2 \cdot u2\right) \cdot u2\right) \cdot u2, \mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\sqrt{\mathsf{fma}\left(u1, u1, u1\right)} \cdot \sin \left(6.28318530718 \cdot u2\right)\\ \end{array} \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (if (<= u2 0.20999999344348907)
   (*
    (sqrt (/ u1 (- 1.0 u1)))
    (*
     u2
     (fma
      (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
      (* (* (* u2 u2) u2) u2)
      (fma (* -41.341702240407926 u2) u2 6.28318530718))))
   (* (sqrt (fma u1 u1 u1)) (sin (* 6.28318530718 u2)))))
float code(float cosTheta_i, float u1, float u2) {
	float tmp;
	if (u2 <= 0.20999999344348907f) {
		tmp = sqrtf((u1 / (1.0f - u1))) * (u2 * fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (((u2 * u2) * u2) * u2), fmaf((-41.341702240407926f * u2), u2, 6.28318530718f)));
	} else {
		tmp = sqrtf(fmaf(u1, u1, u1)) * sinf((6.28318530718f * u2));
	}
	return tmp;
}
function code(cosTheta_i, u1, u2)
	tmp = Float32(0.0)
	if (u2 <= Float32(0.20999999344348907))
		tmp = Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(u2 * fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(Float32(Float32(u2 * u2) * u2) * u2), fma(Float32(Float32(-41.341702240407926) * u2), u2, Float32(6.28318530718)))));
	else
		tmp = Float32(sqrt(fma(u1, u1, u1)) * sin(Float32(Float32(6.28318530718) * u2)));
	end
	return tmp
end
\begin{array}{l}
\mathbf{if}\;u2 \leq 0.20999999344348907:\\
\;\;\;\;\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), \left(\left(u2 \cdot u2\right) \cdot u2\right) \cdot u2, \mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)\right)\right)\\

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


\end{array}
Derivation
  1. Split input into 2 regimes
  2. if u2 < 0.209999993

    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

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
    3. Step-by-step derivation
      1. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
      2. lower-+.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
      3. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
      4. lower-pow.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      5. lower--.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
      6. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      7. lower-pow.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      8. lower-+.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      9. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      10. lower-pow.f3294.0%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
    4. Applied rewrites94.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
    5. Applied rewrites94.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), \color{blue}{\left(\left(u2 \cdot u2\right) \cdot u2\right) \cdot u2}, \mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)\right)\right) \]

    if 0.209999993 < u2

    1. Initial program 98.3%

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

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(\frac{1}{2} + \frac{1}{2}\right)} - u1}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. associate--l+N/A

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\frac{1}{2} + \left(\frac{1}{2} - u1\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. lower--.f3298.3%

        \[\leadsto \sqrt{\frac{u1}{0.5 + \color{blue}{\left(0.5 - u1\right)}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    3. Applied rewrites98.3%

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{0.5 + \left(0.5 - u1\right)}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    4. Step-by-step derivation
      1. lift-+.f32N/A

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(\frac{1}{2} - u1\right) + \frac{1}{2}}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      3. add-flipN/A

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

        \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(\frac{1}{2} - u1\right) - \left(\mathsf{neg}\left(\frac{1}{2}\right)\right)}}} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      5. metadata-eval98.3%

        \[\leadsto \sqrt{\frac{u1}{\left(0.5 - u1\right) - \color{blue}{-0.5}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    5. Applied rewrites98.3%

      \[\leadsto \sqrt{\frac{u1}{\color{blue}{\left(0.5 - u1\right) - -0.5}}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    6. Taylor expanded in u1 around 0

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    7. 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-+.f3286.7%

        \[\leadsto \sqrt{u1 \cdot \left(1 + \color{blue}{u1}\right)} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    8. Applied rewrites86.7%

      \[\leadsto \sqrt{\color{blue}{u1 \cdot \left(1 + u1\right)}} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    9. Step-by-step derivation
      1. lift-*.f32N/A

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

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

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

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

        \[\leadsto \sqrt{u1 \cdot u1 + u1} \cdot \sin \left(\frac{314159265359}{50000000000} \cdot u2\right) \]
      6. lower-fma.f3286.7%

        \[\leadsto \sqrt{\mathsf{fma}\left(u1, \color{blue}{u1}, u1\right)} \cdot \sin \left(6.28318530718 \cdot u2\right) \]
    10. Applied rewrites86.7%

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

Alternative 3: 94.0% accurate, 1.0× speedup?

\[\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\left(\left(u2 \cdot u2\right) \cdot \left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right) \cdot u2\right)\right) \cdot u2 + \mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)\right)\right) \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (sqrt (/ u1 (- 1.0 u1)))
  (*
   u2
   (+
    (*
     (* (* u2 u2) (* (fma -76.70585975309672 (* u2 u2) 81.6052492761019) u2))
     u2)
    (fma (* -41.341702240407926 u2) u2 6.28318530718)))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * (u2 * ((((u2 * u2) * (fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f) * u2)) * u2) + fmaf((-41.341702240407926f * u2), u2, 6.28318530718f)));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(u2 * Float32(Float32(Float32(Float32(u2 * u2) * Float32(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)) * u2)) * u2) + fma(Float32(Float32(-41.341702240407926) * u2), u2, Float32(6.28318530718)))))
end
\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\left(\left(u2 \cdot u2\right) \cdot \left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right) \cdot u2\right)\right) \cdot u2 + \mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)\right)\right)
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

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
  3. Step-by-step derivation
    1. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
    2. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    3. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    4. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    5. lower--.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
    6. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    7. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    8. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    9. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    10. lower-pow.f3294.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
  4. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
  5. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\left(\left(u2 \cdot u2\right) \cdot \left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right) \cdot u2\right)\right) \cdot u2 + \color{blue}{\mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)}\right)\right) \]
  6. Add Preprocessing

Alternative 4: 94.0% accurate, 1.1× speedup?

\[\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), \left(\left(u2 \cdot u2\right) \cdot u2\right) \cdot u2, \mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)\right)\right) \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (sqrt (/ u1 (- 1.0 u1)))
  (*
   u2
   (fma
    (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
    (* (* (* u2 u2) u2) u2)
    (fma (* -41.341702240407926 u2) u2 6.28318530718)))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * (u2 * fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (((u2 * u2) * u2) * u2), fmaf((-41.341702240407926f * u2), u2, 6.28318530718f)));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(u2 * fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(Float32(Float32(u2 * u2) * u2) * u2), fma(Float32(Float32(-41.341702240407926) * u2), u2, Float32(6.28318530718)))))
end
\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), \left(\left(u2 \cdot u2\right) \cdot u2\right) \cdot u2, \mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)\right)\right)
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

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
  3. Step-by-step derivation
    1. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
    2. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    3. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    4. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    5. lower--.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
    6. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    7. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    8. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    9. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    10. lower-pow.f3294.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
  4. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
  5. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), \color{blue}{\left(\left(u2 \cdot u2\right) \cdot u2\right) \cdot u2}, \mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right)\right)\right) \]
  6. Add Preprocessing

Alternative 5: 94.0% accurate, 1.2× speedup?

\[\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot \left(u2 \cdot u2\right)\right)\right) \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (sqrt (/ u1 (- 1.0 u1)))
  (*
   u2
   (+
    6.28318530718
    (*
     (fma
      (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
      (* u2 u2)
      -41.341702240407926)
     (* u2 u2))))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * (u2 * (6.28318530718f + (fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (u2 * u2), -41.341702240407926f) * (u2 * u2))));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(u2 * Float32(Float32(6.28318530718) + Float32(fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(u2 * u2), Float32(-41.341702240407926)) * Float32(u2 * u2)))))
end
\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot \left(u2 \cdot u2\right)\right)\right)
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

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
  3. Step-by-step derivation
    1. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
    2. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    3. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    4. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    5. lower--.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
    6. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    7. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    8. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    9. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    10. lower-pow.f3294.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
  4. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
  5. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    2. *-commutativeN/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot \color{blue}{{u2}^{2}}\right)\right) \]
    3. lower-*.f3294.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right) \cdot \color{blue}{{u2}^{2}}\right)\right) \]
    4. lift--.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {\color{blue}{u2}}^{2}\right)\right) \]
    5. sub-flipN/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \cdot {\color{blue}{u2}}^{2}\right)\right) \]
    6. lift-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \cdot {u2}^{2}\right)\right) \]
    7. *-commutativeN/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \left(\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) \cdot {u2}^{2} + \left(\mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \cdot {u2}^{2}\right)\right) \]
    8. lower-fma.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}, {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {\color{blue}{u2}}^{2}\right)\right) \]
    9. lift-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}, {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    10. +-commutativeN/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}, {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    11. lift-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2} + \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}, {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    12. lower-fma.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    13. lift-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, {u2}^{2}, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    14. unpow2N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    15. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    16. lift-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), {u2}^{2}, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    17. unpow2N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    18. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \mathsf{neg}\left(\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right) \cdot {u2}^{2}\right)\right) \]
    19. metadata-eval94.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot {u2}^{2}\right)\right) \]
    20. lift-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {u2}^{\color{blue}{2}}\right)\right) \]
    21. unpow2N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \mathsf{fma}\left(\mathsf{fma}\left(\frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000}, u2 \cdot u2, \frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}\right), u2 \cdot u2, \frac{-31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot \left(u2 \cdot \color{blue}{u2}\right)\right)\right) \]
    22. lower-*.f3294.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot \left(u2 \cdot \color{blue}{u2}\right)\right)\right) \]
  6. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + \mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot \color{blue}{\left(u2 \cdot u2\right)}\right)\right) \]
  7. Add Preprocessing

Alternative 6: 94.0% accurate, 1.2× speedup?

\[\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right)\right) \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (sqrt (/ u1 (- 1.0 u1)))
  (*
   u2
   (fma
    (fma
     (fma -76.70585975309672 (* u2 u2) 81.6052492761019)
     (* u2 u2)
     -41.341702240407926)
    (* u2 u2)
    6.28318530718))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * (u2 * fmaf(fmaf(fmaf(-76.70585975309672f, (u2 * u2), 81.6052492761019f), (u2 * u2), -41.341702240407926f), (u2 * u2), 6.28318530718f));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * Float32(u2 * fma(fma(fma(Float32(-76.70585975309672), Float32(u2 * u2), Float32(81.6052492761019)), Float32(u2 * u2), Float32(-41.341702240407926)), Float32(u2 * u2), Float32(6.28318530718))))
end
\sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), u2 \cdot u2, 6.28318530718\right)\right)
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

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
  3. Step-by-step derivation
    1. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
    2. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    3. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    4. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    5. lower--.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
    6. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    7. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    8. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    9. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    10. lower-pow.f3294.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
  4. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
  5. Step-by-step derivation
    1. lift-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    2. +-commutativeN/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) + \color{blue}{\frac{314159265359}{50000000000}}\right)\right) \]
    3. lift-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left({u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) + \frac{314159265359}{50000000000}\right)\right) \]
    4. *-commutativeN/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right) \cdot {u2}^{2} + \frac{314159265359}{50000000000}\right)\right) \]
    5. lower-fma.f3294.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926, \color{blue}{{u2}^{2}}, 6.28318530718\right)\right) \]
  6. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right), \color{blue}{u2 \cdot u2}, 6.28318530718\right)\right) \]
  7. Add Preprocessing

Alternative 7: 91.8% accurate, 1.3× speedup?

\[\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, 6.28318530718, \left(-\left(-u2\right)\right) \cdot \left(\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right) \cdot u2\right) \cdot u2\right)\right) \]
(FPCore (cosTheta_i u1 u2)
 :precision binary32
 (*
  (sqrt (/ u1 (- 1.0 u1)))
  (fma
   u2
   6.28318530718
   (*
    (- (- u2))
    (* (* (fma 81.6052492761019 (* u2 u2) -41.341702240407926) u2) u2)))))
float code(float cosTheta_i, float u1, float u2) {
	return sqrtf((u1 / (1.0f - u1))) * fmaf(u2, 6.28318530718f, (-(-u2) * ((fmaf(81.6052492761019f, (u2 * u2), -41.341702240407926f) * u2) * u2)));
}
function code(cosTheta_i, u1, u2)
	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(u2, Float32(6.28318530718), Float32(Float32(-Float32(-u2)) * Float32(Float32(fma(Float32(81.6052492761019), Float32(u2 * u2), Float32(-41.341702240407926)) * u2) * u2))))
end
\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, 6.28318530718, \left(-\left(-u2\right)\right) \cdot \left(\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right) \cdot u2\right) \cdot u2\right)\right)
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

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
  3. Step-by-step derivation
    1. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
    2. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    3. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
    4. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    5. lower--.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
    6. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    7. lower-pow.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    8. lower-+.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    9. lower-*.f32N/A

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
    10. lower-pow.f3294.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
  4. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
  5. Applied rewrites94.0%

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, \color{blue}{6.28318530718}, \left(-\left(-u2\right)\right) \cdot \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot u2\right) \cdot u2\right)\right) \]
  6. Taylor expanded in u2 around 0

    \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, 6.28318530718, \left(-\left(-u2\right)\right) \cdot \left(\left(\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}, u2 \cdot u2, -41.341702240407926\right) \cdot u2\right) \cdot u2\right)\right) \]
  7. Step-by-step derivation
    1. Applied rewrites91.8%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, 6.28318530718, \left(-\left(-u2\right)\right) \cdot \left(\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right) \cdot u2\right) \cdot u2\right)\right) \]
    2. Add Preprocessing

    Alternative 8: 91.6% accurate, 1.4× speedup?

    \[\sqrt{u1} \cdot \frac{\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right) \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}} \]
    (FPCore (cosTheta_i u1 u2)
     :precision binary32
     (*
      (sqrt u1)
      (/
       (*
        (fma
         (* (fma 81.6052492761019 (* u2 u2) -41.341702240407926) u2)
         u2
         6.28318530718)
        u2)
       (sqrt (- 1.0 u1)))))
    float code(float cosTheta_i, float u1, float u2) {
    	return sqrtf(u1) * ((fmaf((fmaf(81.6052492761019f, (u2 * u2), -41.341702240407926f) * u2), u2, 6.28318530718f) * u2) / sqrtf((1.0f - u1)));
    }
    
    function code(cosTheta_i, u1, u2)
    	return Float32(sqrt(u1) * Float32(Float32(fma(Float32(fma(Float32(81.6052492761019), Float32(u2 * u2), Float32(-41.341702240407926)) * u2), u2, Float32(6.28318530718)) * u2) / sqrt(Float32(Float32(1.0) - u1))))
    end
    
    \sqrt{u1} \cdot \frac{\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right) \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}}
    
    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

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
    3. Step-by-step derivation
      1. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
      2. lower-+.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
      3. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
      4. lower-pow.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      5. lower--.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
      6. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      7. lower-pow.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      8. lower-+.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      9. lower-*.f32N/A

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
      10. lower-pow.f3294.0%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
    4. Applied rewrites94.0%

      \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
    5. Applied rewrites93.7%

      \[\leadsto \color{blue}{\sqrt{u1} \cdot \frac{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}}} \]
    6. Taylor expanded in u2 around 0

      \[\leadsto \sqrt{u1} \cdot \frac{\mathsf{fma}\left(\mathsf{fma}\left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000}, u2 \cdot u2, -41.341702240407926\right) \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}} \]
    7. Step-by-step derivation
      1. Applied rewrites91.6%

        \[\leadsto \sqrt{u1} \cdot \frac{\mathsf{fma}\left(\mathsf{fma}\left(81.6052492761019, u2 \cdot u2, -41.341702240407926\right) \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}} \]
      2. Add Preprocessing

      Alternative 9: 89.3% accurate, 1.7× speedup?

      \[\sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, 6.28318530718, \left(-\left(-u2\right)\right) \cdot \left(\left(-41.341702240407926 \cdot u2\right) \cdot u2\right)\right) \]
      (FPCore (cosTheta_i u1 u2)
       :precision binary32
       (*
        (sqrt (/ u1 (- 1.0 u1)))
        (fma u2 6.28318530718 (* (- (- u2)) (* (* -41.341702240407926 u2) u2)))))
      float code(float cosTheta_i, float u1, float u2) {
      	return sqrtf((u1 / (1.0f - u1))) * fmaf(u2, 6.28318530718f, (-(-u2) * ((-41.341702240407926f * u2) * u2)));
      }
      
      function code(cosTheta_i, u1, u2)
      	return Float32(sqrt(Float32(u1 / Float32(Float32(1.0) - u1))) * fma(u2, Float32(6.28318530718), Float32(Float32(-Float32(-u2)) * Float32(Float32(Float32(-41.341702240407926) * u2) * u2))))
      end
      
      \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, 6.28318530718, \left(-\left(-u2\right)\right) \cdot \left(\left(-41.341702240407926 \cdot u2\right) \cdot u2\right)\right)
      
      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

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
      3. Step-by-step derivation
        1. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
        2. lower-+.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
        3. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
        4. lower-pow.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
        5. lower--.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
        6. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
        7. lower-pow.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
        8. lower-+.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
        9. lower-*.f32N/A

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
        10. lower-pow.f3294.0%

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
      4. Applied rewrites94.0%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
      5. Applied rewrites94.0%

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, \color{blue}{6.28318530718}, \left(-\left(-u2\right)\right) \cdot \left(\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot u2\right) \cdot u2\right)\right) \]
      6. Taylor expanded in u2 around 0

        \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \mathsf{fma}\left(u2, 6.28318530718, \left(-\left(-u2\right)\right) \cdot \left(\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot u2\right) \cdot u2\right)\right) \]
      7. Step-by-step derivation
        1. Applied rewrites89.3%

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

        Alternative 10: 89.0% accurate, 1.9× speedup?

        \[\sqrt{u1} \cdot \frac{\mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}} \]
        (FPCore (cosTheta_i u1 u2)
         :precision binary32
         (*
          (sqrt u1)
          (/
           (* (fma (* -41.341702240407926 u2) u2 6.28318530718) u2)
           (sqrt (- 1.0 u1)))))
        float code(float cosTheta_i, float u1, float u2) {
        	return sqrtf(u1) * ((fmaf((-41.341702240407926f * u2), u2, 6.28318530718f) * u2) / sqrtf((1.0f - u1)));
        }
        
        function code(cosTheta_i, u1, u2)
        	return Float32(sqrt(u1) * Float32(Float32(fma(Float32(Float32(-41.341702240407926) * u2), u2, Float32(6.28318530718)) * u2) / sqrt(Float32(Float32(1.0) - u1))))
        end
        
        \sqrt{u1} \cdot \frac{\mathsf{fma}\left(-41.341702240407926 \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}}
        
        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

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right)} \]
        3. Step-by-step derivation
          1. lower-*.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \color{blue}{\left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)}\right) \]
          2. lower-+.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + \color{blue}{{u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
          3. lower-*.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \color{blue}{\left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)}\right)\right) \]
          4. lower-pow.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left(\color{blue}{{u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right)} - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
          5. lower--.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \color{blue}{\frac{31006276680305942139213528068663279}{750000000000000000000000000000000}}\right)\right)\right) \]
          6. lower-*.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
          7. lower-pow.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
          8. lower-+.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
          9. lower-*.f32N/A

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(\frac{314159265359}{50000000000} + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(\frac{3060196847853821555298148281676017575122444629042460390799}{37500000000000000000000000000000000000000000000000000000} + \frac{-302029322777818351566783844332719832329455959975176141755859165754785028165295919}{3937500000000000000000000000000000000000000000000000000000000000000000000000000} \cdot {u2}^{2}\right) - \frac{31006276680305942139213528068663279}{750000000000000000000000000000000}\right)\right)\right) \]
          10. lower-pow.f3294.0%

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right) \]
        4. Applied rewrites94.0%

          \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(u2 \cdot \left(6.28318530718 + {u2}^{2} \cdot \left({u2}^{2} \cdot \left(81.6052492761019 + -76.70585975309672 \cdot {u2}^{2}\right) - 41.341702240407926\right)\right)\right)} \]
        5. Applied rewrites93.7%

          \[\leadsto \color{blue}{\sqrt{u1} \cdot \frac{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(-76.70585975309672, u2 \cdot u2, 81.6052492761019\right), u2 \cdot u2, -41.341702240407926\right) \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}}} \]
        6. Taylor expanded in u2 around 0

          \[\leadsto \sqrt{u1} \cdot \frac{\mathsf{fma}\left(\frac{-31006276680305942139213528068663279}{750000000000000000000000000000000} \cdot u2, u2, 6.28318530718\right) \cdot u2}{\sqrt{1 - u1}} \]
        7. Step-by-step derivation
          1. Applied rewrites89.0%

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

          Alternative 11: 81.6% accurate, 3.2× speedup?

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

            \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \color{blue}{\left(\frac{314159265359}{50000000000} \cdot u2\right)} \]
          3. Step-by-step derivation
            1. lower-*.f3281.6%

              \[\leadsto \sqrt{\frac{u1}{1 - u1}} \cdot \left(6.28318530718 \cdot \color{blue}{u2}\right) \]
          4. Applied rewrites81.6%

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

          Alternative 12: 81.6% accurate, 3.2× speedup?

          \[6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
          (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
          
          6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right)
          
          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--.f3281.6%

              \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
          4. Applied rewrites81.6%

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

          Alternative 13: 73.3% accurate, 3.3× speedup?

          \[\left(\sqrt{u1 \cdot \left(1 + u1\right)} \cdot 6.28318530718\right) \cdot u2 \]
          (FPCore (cosTheta_i u1 u2)
           :precision binary32
           (* (* (sqrt (* u1 (+ 1.0 u1))) 6.28318530718) u2))
          float code(float cosTheta_i, float u1, float u2) {
          	return (sqrtf((u1 * (1.0f + u1))) * 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))) * 6.28318530718e0) * u2
          end function
          
          function code(cosTheta_i, u1, u2)
          	return Float32(Float32(sqrt(Float32(u1 * Float32(Float32(1.0) + u1))) * Float32(6.28318530718)) * u2)
          end
          
          function tmp = code(cosTheta_i, u1, u2)
          	tmp = (sqrt((u1 * (single(1.0) + u1))) * single(6.28318530718)) * u2;
          end
          
          \left(\sqrt{u1 \cdot \left(1 + u1\right)} \cdot 6.28318530718\right) \cdot u2
          
          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--.f3281.6%

              \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
          4. Applied rewrites81.6%

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

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

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

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

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

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

              \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot \frac{314159265359}{50000000000}\right) \cdot \color{blue}{u2} \]
            7. lower-*.f3281.6%

              \[\leadsto \left(\sqrt{\frac{u1}{1 - u1}} \cdot 6.28318530718\right) \cdot u2 \]
          6. Applied rewrites81.6%

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

            \[\leadsto \left(\sqrt{u1 \cdot \left(1 + u1\right)} \cdot 6.28318530718\right) \cdot u2 \]
          8. Step-by-step derivation
            1. lower-*.f32N/A

              \[\leadsto \left(\sqrt{u1 \cdot \left(1 + u1\right)} \cdot \frac{314159265359}{50000000000}\right) \cdot u2 \]
            2. lower-+.f3273.3%

              \[\leadsto \left(\sqrt{u1 \cdot \left(1 + u1\right)} \cdot 6.28318530718\right) \cdot u2 \]
          9. Applied rewrites73.3%

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

          Alternative 14: 65.2% accurate, 5.3× speedup?

          \[6.28318530718 \cdot \left(u2 \cdot \sqrt{u1}\right) \]
          (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
          
          6.28318530718 \cdot \left(u2 \cdot \sqrt{u1}\right)
          
          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--.f3281.6%

              \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{\frac{u1}{1 - u1}}\right) \]
          4. Applied rewrites81.6%

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

            \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \color{blue}{\sqrt{u1}}\right) \]
          6. Step-by-step derivation
            1. lower-*.f32N/A

              \[\leadsto \frac{314159265359}{50000000000} \cdot \left(u2 \cdot \sqrt{u1}\right) \]
            2. lower-sqrt.f3265.2%

              \[\leadsto 6.28318530718 \cdot \left(u2 \cdot \sqrt{u1}\right) \]
          7. Applied rewrites65.2%

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

          Reproduce

          ?
          herbie shell --seed 2025191 
          (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))))