HairBSDF, gamma for a refracted ray

Percentage Accurate: 91.6% → 98.7%
Time: 14.0s
Alternatives: 5
Speedup: 1.5×

Specification

?
\[\left(\left(-1 \leq sinTheta\_O \land sinTheta\_O \leq 1\right) \land \left(-1 \leq h \land h \leq 1\right)\right) \land \left(0 \leq eta \land eta \leq 10\right)\]
\[\begin{array}{l} \\ \sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \end{array} \]
(FPCore (sinTheta_O h eta)
 :precision binary32
 (asin
  (/
   h
   (sqrt
    (-
     (* eta eta)
     (/
      (* sinTheta_O sinTheta_O)
      (sqrt (- 1.0 (* sinTheta_O sinTheta_O)))))))))
float code(float sinTheta_O, float h, float eta) {
	return asinf((h / sqrtf(((eta * eta) - ((sinTheta_O * sinTheta_O) / sqrtf((1.0f - (sinTheta_O * sinTheta_O))))))));
}
real(4) function code(sintheta_o, h, eta)
    real(4), intent (in) :: sintheta_o
    real(4), intent (in) :: h
    real(4), intent (in) :: eta
    code = asin((h / sqrt(((eta * eta) - ((sintheta_o * sintheta_o) / sqrt((1.0e0 - (sintheta_o * sintheta_o))))))))
end function
function code(sinTheta_O, h, eta)
	return asin(Float32(h / sqrt(Float32(Float32(eta * eta) - Float32(Float32(sinTheta_O * sinTheta_O) / sqrt(Float32(Float32(1.0) - Float32(sinTheta_O * sinTheta_O))))))))
end
function tmp = code(sinTheta_O, h, eta)
	tmp = asin((h / sqrt(((eta * eta) - ((sinTheta_O * sinTheta_O) / sqrt((single(1.0) - (sinTheta_O * sinTheta_O))))))));
end
\begin{array}{l}

\\
\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right)
\end{array}

Sampling outcomes in binary32 precision:

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 5 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: 91.6% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \end{array} \]
(FPCore (sinTheta_O h eta)
 :precision binary32
 (asin
  (/
   h
   (sqrt
    (-
     (* eta eta)
     (/
      (* sinTheta_O sinTheta_O)
      (sqrt (- 1.0 (* sinTheta_O sinTheta_O)))))))))
float code(float sinTheta_O, float h, float eta) {
	return asinf((h / sqrtf(((eta * eta) - ((sinTheta_O * sinTheta_O) / sqrtf((1.0f - (sinTheta_O * sinTheta_O))))))));
}
real(4) function code(sintheta_o, h, eta)
    real(4), intent (in) :: sintheta_o
    real(4), intent (in) :: h
    real(4), intent (in) :: eta
    code = asin((h / sqrt(((eta * eta) - ((sintheta_o * sintheta_o) / sqrt((1.0e0 - (sintheta_o * sintheta_o))))))))
end function
function code(sinTheta_O, h, eta)
	return asin(Float32(h / sqrt(Float32(Float32(eta * eta) - Float32(Float32(sinTheta_O * sinTheta_O) / sqrt(Float32(Float32(1.0) - Float32(sinTheta_O * sinTheta_O))))))))
end
function tmp = code(sinTheta_O, h, eta)
	tmp = asin((h / sqrt(((eta * eta) - ((sinTheta_O * sinTheta_O) / sqrt((single(1.0) - (sinTheta_O * sinTheta_O))))))));
end
\begin{array}{l}

\\
\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right)
\end{array}

Alternative 1: 98.7% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;sinTheta\_O \cdot sinTheta\_O \leq 0:\\ \;\;\;\;\sin^{-1} \left(\frac{h}{eta}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, sinTheta\_O \cdot \left(-sinTheta\_O\right)\right)}}\right)\\ \end{array} \end{array} \]
(FPCore (sinTheta_O h eta)
 :precision binary32
 (if (<= (* sinTheta_O sinTheta_O) 0.0)
   (asin (/ h eta))
   (asin (/ h (sqrt (fma eta eta (* sinTheta_O (- sinTheta_O))))))))
float code(float sinTheta_O, float h, float eta) {
	float tmp;
	if ((sinTheta_O * sinTheta_O) <= 0.0f) {
		tmp = asinf((h / eta));
	} else {
		tmp = asinf((h / sqrtf(fmaf(eta, eta, (sinTheta_O * -sinTheta_O)))));
	}
	return tmp;
}
function code(sinTheta_O, h, eta)
	tmp = Float32(0.0)
	if (Float32(sinTheta_O * sinTheta_O) <= Float32(0.0))
		tmp = asin(Float32(h / eta));
	else
		tmp = asin(Float32(h / sqrt(fma(eta, eta, Float32(sinTheta_O * Float32(-sinTheta_O))))));
	end
	return tmp
end
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;sinTheta\_O \cdot sinTheta\_O \leq 0:\\
\;\;\;\;\sin^{-1} \left(\frac{h}{eta}\right)\\

\mathbf{else}:\\
\;\;\;\;\sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, sinTheta\_O \cdot \left(-sinTheta\_O\right)\right)}}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (*.f32 sinTheta_O sinTheta_O) < 0.0

    1. Initial program 90.8%

      \[\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in eta around inf

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]
    4. Step-by-step derivation
      1. lower-/.f3298.7

        \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]
    5. Applied rewrites98.7%

      \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]

    if 0.0 < (*.f32 sinTheta_O sinTheta_O)

    1. Initial program 99.5%

      \[\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \]
    2. Add Preprocessing
    3. Taylor expanded in sinTheta_O around 0

      \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{{sinTheta\_O}^{2} \cdot \left(\frac{-1}{2} \cdot {sinTheta\_O}^{2} - 1\right) + {eta}^{2}}}}\right) \]
    4. Step-by-step derivation
      1. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\left(sinTheta\_O \cdot sinTheta\_O\right)} \cdot \left(\frac{-1}{2} \cdot {sinTheta\_O}^{2} - 1\right) + {eta}^{2}}}\right) \]
      2. associate-*l*N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{sinTheta\_O \cdot \left(sinTheta\_O \cdot \left(\frac{-1}{2} \cdot {sinTheta\_O}^{2} - 1\right)\right)} + {eta}^{2}}}\right) \]
      3. lower-fma.f32N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \left(\frac{-1}{2} \cdot {sinTheta\_O}^{2} - 1\right), {eta}^{2}\right)}}}\right) \]
      4. lower-*.f32N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, \color{blue}{sinTheta\_O \cdot \left(\frac{-1}{2} \cdot {sinTheta\_O}^{2} - 1\right)}, {eta}^{2}\right)}}\right) \]
      5. sub-negN/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \color{blue}{\left(\frac{-1}{2} \cdot {sinTheta\_O}^{2} + \left(\mathsf{neg}\left(1\right)\right)\right)}, {eta}^{2}\right)}}\right) \]
      6. *-commutativeN/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \left(\color{blue}{{sinTheta\_O}^{2} \cdot \frac{-1}{2}} + \left(\mathsf{neg}\left(1\right)\right)\right), {eta}^{2}\right)}}\right) \]
      7. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \left(\color{blue}{\left(sinTheta\_O \cdot sinTheta\_O\right)} \cdot \frac{-1}{2} + \left(\mathsf{neg}\left(1\right)\right)\right), {eta}^{2}\right)}}\right) \]
      8. associate-*l*N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \left(\color{blue}{sinTheta\_O \cdot \left(sinTheta\_O \cdot \frac{-1}{2}\right)} + \left(\mathsf{neg}\left(1\right)\right)\right), {eta}^{2}\right)}}\right) \]
      9. metadata-evalN/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \left(sinTheta\_O \cdot \left(sinTheta\_O \cdot \frac{-1}{2}\right) + \color{blue}{-1}\right), {eta}^{2}\right)}}\right) \]
      10. lower-fma.f32N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \color{blue}{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \frac{-1}{2}, -1\right)}, {eta}^{2}\right)}}\right) \]
      11. lower-*.f32N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \mathsf{fma}\left(sinTheta\_O, \color{blue}{sinTheta\_O \cdot \frac{-1}{2}}, -1\right), {eta}^{2}\right)}}\right) \]
      12. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \frac{-1}{2}, -1\right), \color{blue}{eta \cdot eta}\right)}}\right) \]
      13. lower-*.f3299.5

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot -0.5, -1\right), \color{blue}{eta \cdot eta}\right)}}\right) \]
    5. Applied rewrites99.5%

      \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot -0.5, -1\right), eta \cdot eta\right)}}}\right) \]
    6. Taylor expanded in sinTheta_O around 0

      \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{-1 \cdot {sinTheta\_O}^{2} + {eta}^{2}}}}\right) \]
    7. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{{eta}^{2} + -1 \cdot {sinTheta\_O}^{2}}}}\right) \]
      2. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{eta \cdot eta} + -1 \cdot {sinTheta\_O}^{2}}}\right) \]
      3. lower-fma.f32N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\mathsf{fma}\left(eta, eta, -1 \cdot {sinTheta\_O}^{2}\right)}}}\right) \]
      4. mul-1-negN/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, \color{blue}{\mathsf{neg}\left({sinTheta\_O}^{2}\right)}\right)}}\right) \]
      5. unpow2N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, \mathsf{neg}\left(\color{blue}{sinTheta\_O \cdot sinTheta\_O}\right)\right)}}\right) \]
      6. distribute-rgt-neg-inN/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, \color{blue}{sinTheta\_O \cdot \left(\mathsf{neg}\left(sinTheta\_O\right)\right)}\right)}}\right) \]
      7. mul-1-negN/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, sinTheta\_O \cdot \color{blue}{\left(-1 \cdot sinTheta\_O\right)}\right)}}\right) \]
      8. lower-*.f32N/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, \color{blue}{sinTheta\_O \cdot \left(-1 \cdot sinTheta\_O\right)}\right)}}\right) \]
      9. mul-1-negN/A

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, sinTheta\_O \cdot \color{blue}{\left(\mathsf{neg}\left(sinTheta\_O\right)\right)}\right)}}\right) \]
      10. lower-neg.f3299.5

        \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\mathsf{fma}\left(eta, eta, sinTheta\_O \cdot \color{blue}{\left(-sinTheta\_O\right)}\right)}}\right) \]
    8. Applied rewrites99.5%

      \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\mathsf{fma}\left(eta, eta, sinTheta\_O \cdot \left(-sinTheta\_O\right)\right)}}}\right) \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 2: 96.7% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \sin^{-1} \left(\frac{\mathsf{fma}\left(\frac{sinTheta\_O}{eta}, sinTheta\_O \cdot 0.5, eta\right)}{eta \cdot \frac{eta}{h}}\right) \end{array} \]
(FPCore (sinTheta_O h eta)
 :precision binary32
 (asin (/ (fma (/ sinTheta_O eta) (* sinTheta_O 0.5) eta) (* eta (/ eta h)))))
float code(float sinTheta_O, float h, float eta) {
	return asinf((fmaf((sinTheta_O / eta), (sinTheta_O * 0.5f), eta) / (eta * (eta / h))));
}
function code(sinTheta_O, h, eta)
	return asin(Float32(fma(Float32(sinTheta_O / eta), Float32(sinTheta_O * Float32(0.5)), eta) / Float32(eta * Float32(eta / h))))
end
\begin{array}{l}

\\
\sin^{-1} \left(\frac{\mathsf{fma}\left(\frac{sinTheta\_O}{eta}, sinTheta\_O \cdot 0.5, eta\right)}{eta \cdot \frac{eta}{h}}\right)
\end{array}
Derivation
  1. Initial program 94.9%

    \[\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \]
  2. Add Preprocessing
  3. Taylor expanded in sinTheta_O around 0

    \[\leadsto \sin^{-1} \color{blue}{\left(\frac{1}{2} \cdot \frac{h \cdot {sinTheta\_O}^{2}}{{eta}^{3}} + \frac{h}{eta}\right)} \]
  4. Step-by-step derivation
    1. associate-*r/N/A

      \[\leadsto \sin^{-1} \left(\color{blue}{\frac{\frac{1}{2} \cdot \left(h \cdot {sinTheta\_O}^{2}\right)}{{eta}^{3}}} + \frac{h}{eta}\right) \]
    2. associate-*r*N/A

      \[\leadsto \sin^{-1} \left(\frac{\color{blue}{\left(\frac{1}{2} \cdot h\right) \cdot {sinTheta\_O}^{2}}}{{eta}^{3}} + \frac{h}{eta}\right) \]
    3. associate-*l/N/A

      \[\leadsto \sin^{-1} \left(\color{blue}{\frac{\frac{1}{2} \cdot h}{{eta}^{3}} \cdot {sinTheta\_O}^{2}} + \frac{h}{eta}\right) \]
    4. associate-*r/N/A

      \[\leadsto \sin^{-1} \left(\color{blue}{\left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right)} \cdot {sinTheta\_O}^{2} + \frac{h}{eta}\right) \]
    5. *-commutativeN/A

      \[\leadsto \sin^{-1} \left(\color{blue}{{sinTheta\_O}^{2} \cdot \left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right)} + \frac{h}{eta}\right) \]
    6. unpow2N/A

      \[\leadsto \sin^{-1} \left(\color{blue}{\left(sinTheta\_O \cdot sinTheta\_O\right)} \cdot \left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right) + \frac{h}{eta}\right) \]
    7. associate-*l*N/A

      \[\leadsto \sin^{-1} \left(\color{blue}{sinTheta\_O \cdot \left(sinTheta\_O \cdot \left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right)\right)} + \frac{h}{eta}\right) \]
    8. lower-fma.f32N/A

      \[\leadsto \sin^{-1} \color{blue}{\left(\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right), \frac{h}{eta}\right)\right)} \]
    9. associate-*r/N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \color{blue}{\frac{\frac{1}{2} \cdot h}{{eta}^{3}}}, \frac{h}{eta}\right)\right) \]
    10. associate-*r/N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \color{blue}{\frac{sinTheta\_O \cdot \left(\frac{1}{2} \cdot h\right)}{{eta}^{3}}}, \frac{h}{eta}\right)\right) \]
    11. lower-/.f32N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \color{blue}{\frac{sinTheta\_O \cdot \left(\frac{1}{2} \cdot h\right)}{{eta}^{3}}}, \frac{h}{eta}\right)\right) \]
    12. lower-*.f32N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{\color{blue}{sinTheta\_O \cdot \left(\frac{1}{2} \cdot h\right)}}{{eta}^{3}}, \frac{h}{eta}\right)\right) \]
    13. *-commutativeN/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \color{blue}{\left(h \cdot \frac{1}{2}\right)}}{{eta}^{3}}, \frac{h}{eta}\right)\right) \]
    14. lower-*.f32N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \color{blue}{\left(h \cdot \frac{1}{2}\right)}}{{eta}^{3}}, \frac{h}{eta}\right)\right) \]
    15. cube-multN/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{\color{blue}{eta \cdot \left(eta \cdot eta\right)}}, \frac{h}{eta}\right)\right) \]
    16. unpow2N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{eta \cdot \color{blue}{{eta}^{2}}}, \frac{h}{eta}\right)\right) \]
    17. lower-*.f32N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{\color{blue}{eta \cdot {eta}^{2}}}, \frac{h}{eta}\right)\right) \]
    18. unpow2N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{eta \cdot \color{blue}{\left(eta \cdot eta\right)}}, \frac{h}{eta}\right)\right) \]
    19. lower-*.f32N/A

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{eta \cdot \color{blue}{\left(eta \cdot eta\right)}}, \frac{h}{eta}\right)\right) \]
    20. lower-/.f3279.8

      \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot 0.5\right)}{eta \cdot \left(eta \cdot eta\right)}, \color{blue}{\frac{h}{eta}}\right)\right) \]
  5. Applied rewrites79.8%

    \[\leadsto \sin^{-1} \color{blue}{\left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot 0.5\right)}{eta \cdot \left(eta \cdot eta\right)}, \frac{h}{eta}\right)\right)} \]
  6. Step-by-step derivation
    1. Applied rewrites92.2%

      \[\leadsto \sin^{-1} \left(\frac{\mathsf{fma}\left(\frac{sinTheta\_O \cdot \left(sinTheta\_O \cdot \left(h \cdot 0.5\right)\right)}{eta \cdot eta}, \frac{eta}{h}, eta \cdot 1\right)}{\color{blue}{eta \cdot \frac{eta}{h}}}\right) \]
    2. Step-by-step derivation
      1. Applied rewrites96.3%

        \[\leadsto \sin^{-1} \left(\frac{\mathsf{fma}\left(\frac{sinTheta\_O}{eta}, \left(\left(h \cdot 0.5\right) \cdot \frac{sinTheta\_O}{eta}\right) \cdot \frac{eta}{h}, eta\right)}{\color{blue}{eta} \cdot \frac{eta}{h}}\right) \]
      2. Taylor expanded in h around 0

        \[\leadsto \sin^{-1} \left(\frac{\mathsf{fma}\left(\frac{sinTheta\_O}{eta}, \frac{1}{2} \cdot sinTheta\_O, eta\right)}{eta \cdot \frac{eta}{h}}\right) \]
      3. Step-by-step derivation
        1. Applied rewrites96.3%

          \[\leadsto \sin^{-1} \left(\frac{\mathsf{fma}\left(\frac{sinTheta\_O}{eta}, 0.5 \cdot sinTheta\_O, eta\right)}{eta \cdot \frac{eta}{h}}\right) \]
        2. Final simplification96.3%

          \[\leadsto \sin^{-1} \left(\frac{\mathsf{fma}\left(\frac{sinTheta\_O}{eta}, sinTheta\_O \cdot 0.5, eta\right)}{eta \cdot \frac{eta}{h}}\right) \]
        3. Add Preprocessing

        Alternative 3: 96.2% accurate, 1.1× speedup?

        \[\begin{array}{l} \\ \sin^{-1} \left(\frac{\mathsf{fma}\left(0.5, \frac{sinTheta\_O \cdot sinTheta\_O}{eta}, eta\right)}{eta \cdot \frac{eta}{h}}\right) \end{array} \]
        (FPCore (sinTheta_O h eta)
         :precision binary32
         (asin (/ (fma 0.5 (/ (* sinTheta_O sinTheta_O) eta) eta) (* eta (/ eta h)))))
        float code(float sinTheta_O, float h, float eta) {
        	return asinf((fmaf(0.5f, ((sinTheta_O * sinTheta_O) / eta), eta) / (eta * (eta / h))));
        }
        
        function code(sinTheta_O, h, eta)
        	return asin(Float32(fma(Float32(0.5), Float32(Float32(sinTheta_O * sinTheta_O) / eta), eta) / Float32(eta * Float32(eta / h))))
        end
        
        \begin{array}{l}
        
        \\
        \sin^{-1} \left(\frac{\mathsf{fma}\left(0.5, \frac{sinTheta\_O \cdot sinTheta\_O}{eta}, eta\right)}{eta \cdot \frac{eta}{h}}\right)
        \end{array}
        
        Derivation
        1. Initial program 94.9%

          \[\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \]
        2. Add Preprocessing
        3. Taylor expanded in sinTheta_O around 0

          \[\leadsto \sin^{-1} \color{blue}{\left(\frac{1}{2} \cdot \frac{h \cdot {sinTheta\_O}^{2}}{{eta}^{3}} + \frac{h}{eta}\right)} \]
        4. Step-by-step derivation
          1. associate-*r/N/A

            \[\leadsto \sin^{-1} \left(\color{blue}{\frac{\frac{1}{2} \cdot \left(h \cdot {sinTheta\_O}^{2}\right)}{{eta}^{3}}} + \frac{h}{eta}\right) \]
          2. associate-*r*N/A

            \[\leadsto \sin^{-1} \left(\frac{\color{blue}{\left(\frac{1}{2} \cdot h\right) \cdot {sinTheta\_O}^{2}}}{{eta}^{3}} + \frac{h}{eta}\right) \]
          3. associate-*l/N/A

            \[\leadsto \sin^{-1} \left(\color{blue}{\frac{\frac{1}{2} \cdot h}{{eta}^{3}} \cdot {sinTheta\_O}^{2}} + \frac{h}{eta}\right) \]
          4. associate-*r/N/A

            \[\leadsto \sin^{-1} \left(\color{blue}{\left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right)} \cdot {sinTheta\_O}^{2} + \frac{h}{eta}\right) \]
          5. *-commutativeN/A

            \[\leadsto \sin^{-1} \left(\color{blue}{{sinTheta\_O}^{2} \cdot \left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right)} + \frac{h}{eta}\right) \]
          6. unpow2N/A

            \[\leadsto \sin^{-1} \left(\color{blue}{\left(sinTheta\_O \cdot sinTheta\_O\right)} \cdot \left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right) + \frac{h}{eta}\right) \]
          7. associate-*l*N/A

            \[\leadsto \sin^{-1} \left(\color{blue}{sinTheta\_O \cdot \left(sinTheta\_O \cdot \left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right)\right)} + \frac{h}{eta}\right) \]
          8. lower-fma.f32N/A

            \[\leadsto \sin^{-1} \color{blue}{\left(\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \left(\frac{1}{2} \cdot \frac{h}{{eta}^{3}}\right), \frac{h}{eta}\right)\right)} \]
          9. associate-*r/N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, sinTheta\_O \cdot \color{blue}{\frac{\frac{1}{2} \cdot h}{{eta}^{3}}}, \frac{h}{eta}\right)\right) \]
          10. associate-*r/N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \color{blue}{\frac{sinTheta\_O \cdot \left(\frac{1}{2} \cdot h\right)}{{eta}^{3}}}, \frac{h}{eta}\right)\right) \]
          11. lower-/.f32N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \color{blue}{\frac{sinTheta\_O \cdot \left(\frac{1}{2} \cdot h\right)}{{eta}^{3}}}, \frac{h}{eta}\right)\right) \]
          12. lower-*.f32N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{\color{blue}{sinTheta\_O \cdot \left(\frac{1}{2} \cdot h\right)}}{{eta}^{3}}, \frac{h}{eta}\right)\right) \]
          13. *-commutativeN/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \color{blue}{\left(h \cdot \frac{1}{2}\right)}}{{eta}^{3}}, \frac{h}{eta}\right)\right) \]
          14. lower-*.f32N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \color{blue}{\left(h \cdot \frac{1}{2}\right)}}{{eta}^{3}}, \frac{h}{eta}\right)\right) \]
          15. cube-multN/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{\color{blue}{eta \cdot \left(eta \cdot eta\right)}}, \frac{h}{eta}\right)\right) \]
          16. unpow2N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{eta \cdot \color{blue}{{eta}^{2}}}, \frac{h}{eta}\right)\right) \]
          17. lower-*.f32N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{\color{blue}{eta \cdot {eta}^{2}}}, \frac{h}{eta}\right)\right) \]
          18. unpow2N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{eta \cdot \color{blue}{\left(eta \cdot eta\right)}}, \frac{h}{eta}\right)\right) \]
          19. lower-*.f32N/A

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot \frac{1}{2}\right)}{eta \cdot \color{blue}{\left(eta \cdot eta\right)}}, \frac{h}{eta}\right)\right) \]
          20. lower-/.f3279.8

            \[\leadsto \sin^{-1} \left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot 0.5\right)}{eta \cdot \left(eta \cdot eta\right)}, \color{blue}{\frac{h}{eta}}\right)\right) \]
        5. Applied rewrites79.8%

          \[\leadsto \sin^{-1} \color{blue}{\left(\mathsf{fma}\left(sinTheta\_O, \frac{sinTheta\_O \cdot \left(h \cdot 0.5\right)}{eta \cdot \left(eta \cdot eta\right)}, \frac{h}{eta}\right)\right)} \]
        6. Step-by-step derivation
          1. Applied rewrites92.2%

            \[\leadsto \sin^{-1} \left(\frac{\mathsf{fma}\left(\frac{sinTheta\_O \cdot \left(sinTheta\_O \cdot \left(h \cdot 0.5\right)\right)}{eta \cdot eta}, \frac{eta}{h}, eta \cdot 1\right)}{\color{blue}{eta \cdot \frac{eta}{h}}}\right) \]
          2. Taylor expanded in sinTheta_O around 0

            \[\leadsto \sin^{-1} \left(\frac{eta + \frac{1}{2} \cdot \frac{{sinTheta\_O}^{2}}{eta}}{\color{blue}{eta} \cdot \frac{eta}{h}}\right) \]
          3. Step-by-step derivation
            1. Applied rewrites96.0%

              \[\leadsto \sin^{-1} \left(\frac{\mathsf{fma}\left(0.5, \frac{sinTheta\_O \cdot sinTheta\_O}{eta}, eta\right)}{\color{blue}{eta} \cdot \frac{eta}{h}}\right) \]
            2. Add Preprocessing

            Alternative 4: 98.7% accurate, 1.1× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;sinTheta\_O \cdot sinTheta\_O \leq 0:\\ \;\;\;\;\sin^{-1} \left(\frac{h}{eta}\right)\\ \mathbf{else}:\\ \;\;\;\;\sin^{-1} \left(\frac{h}{\sqrt{\left(eta + sinTheta\_O\right) \cdot \left(eta - sinTheta\_O\right)}}\right)\\ \end{array} \end{array} \]
            (FPCore (sinTheta_O h eta)
             :precision binary32
             (if (<= (* sinTheta_O sinTheta_O) 0.0)
               (asin (/ h eta))
               (asin (/ h (sqrt (* (+ eta sinTheta_O) (- eta sinTheta_O)))))))
            float code(float sinTheta_O, float h, float eta) {
            	float tmp;
            	if ((sinTheta_O * sinTheta_O) <= 0.0f) {
            		tmp = asinf((h / eta));
            	} else {
            		tmp = asinf((h / sqrtf(((eta + sinTheta_O) * (eta - sinTheta_O)))));
            	}
            	return tmp;
            }
            
            real(4) function code(sintheta_o, h, eta)
                real(4), intent (in) :: sintheta_o
                real(4), intent (in) :: h
                real(4), intent (in) :: eta
                real(4) :: tmp
                if ((sintheta_o * sintheta_o) <= 0.0e0) then
                    tmp = asin((h / eta))
                else
                    tmp = asin((h / sqrt(((eta + sintheta_o) * (eta - sintheta_o)))))
                end if
                code = tmp
            end function
            
            function code(sinTheta_O, h, eta)
            	tmp = Float32(0.0)
            	if (Float32(sinTheta_O * sinTheta_O) <= Float32(0.0))
            		tmp = asin(Float32(h / eta));
            	else
            		tmp = asin(Float32(h / sqrt(Float32(Float32(eta + sinTheta_O) * Float32(eta - sinTheta_O)))));
            	end
            	return tmp
            end
            
            function tmp_2 = code(sinTheta_O, h, eta)
            	tmp = single(0.0);
            	if ((sinTheta_O * sinTheta_O) <= single(0.0))
            		tmp = asin((h / eta));
            	else
            		tmp = asin((h / sqrt(((eta + sinTheta_O) * (eta - sinTheta_O)))));
            	end
            	tmp_2 = tmp;
            end
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            \mathbf{if}\;sinTheta\_O \cdot sinTheta\_O \leq 0:\\
            \;\;\;\;\sin^{-1} \left(\frac{h}{eta}\right)\\
            
            \mathbf{else}:\\
            \;\;\;\;\sin^{-1} \left(\frac{h}{\sqrt{\left(eta + sinTheta\_O\right) \cdot \left(eta - sinTheta\_O\right)}}\right)\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if (*.f32 sinTheta_O sinTheta_O) < 0.0

              1. Initial program 90.8%

                \[\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in eta around inf

                \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]
              4. Step-by-step derivation
                1. lower-/.f3298.7

                  \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]
              5. Applied rewrites98.7%

                \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]

              if 0.0 < (*.f32 sinTheta_O sinTheta_O)

              1. Initial program 99.5%

                \[\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \]
              2. Add Preprocessing
              3. Taylor expanded in sinTheta_O around 0

                \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{-1 \cdot {sinTheta\_O}^{2} + {eta}^{2}}}}\right) \]
              4. Step-by-step derivation
                1. +-commutativeN/A

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{{eta}^{2} + -1 \cdot {sinTheta\_O}^{2}}}}\right) \]
                2. mul-1-negN/A

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{{eta}^{2} + \color{blue}{\left(\mathsf{neg}\left({sinTheta\_O}^{2}\right)\right)}}}\right) \]
                3. unsub-negN/A

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{{eta}^{2} - {sinTheta\_O}^{2}}}}\right) \]
                4. unpow2N/A

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{eta \cdot eta} - {sinTheta\_O}^{2}}}\right) \]
                5. unpow2N/A

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \color{blue}{sinTheta\_O \cdot sinTheta\_O}}}\right) \]
                6. difference-of-squaresN/A

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\left(eta + sinTheta\_O\right) \cdot \left(eta - sinTheta\_O\right)}}}\right) \]
                7. lower-*.f32N/A

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\left(eta + sinTheta\_O\right) \cdot \left(eta - sinTheta\_O\right)}}}\right) \]
                8. lower-+.f32N/A

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\left(eta + sinTheta\_O\right)} \cdot \left(eta - sinTheta\_O\right)}}\right) \]
                9. lower--.f3299.5

                  \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\left(eta + sinTheta\_O\right) \cdot \color{blue}{\left(eta - sinTheta\_O\right)}}}\right) \]
              5. Applied rewrites99.5%

                \[\leadsto \sin^{-1} \left(\frac{h}{\sqrt{\color{blue}{\left(eta + sinTheta\_O\right) \cdot \left(eta - sinTheta\_O\right)}}}\right) \]
            3. Recombined 2 regimes into one program.
            4. Add Preprocessing

            Alternative 5: 95.5% accurate, 1.5× speedup?

            \[\begin{array}{l} \\ \sin^{-1} \left(\frac{h}{eta}\right) \end{array} \]
            (FPCore (sinTheta_O h eta) :precision binary32 (asin (/ h eta)))
            float code(float sinTheta_O, float h, float eta) {
            	return asinf((h / eta));
            }
            
            real(4) function code(sintheta_o, h, eta)
                real(4), intent (in) :: sintheta_o
                real(4), intent (in) :: h
                real(4), intent (in) :: eta
                code = asin((h / eta))
            end function
            
            function code(sinTheta_O, h, eta)
            	return asin(Float32(h / eta))
            end
            
            function tmp = code(sinTheta_O, h, eta)
            	tmp = asin((h / eta));
            end
            
            \begin{array}{l}
            
            \\
            \sin^{-1} \left(\frac{h}{eta}\right)
            \end{array}
            
            Derivation
            1. Initial program 94.9%

              \[\sin^{-1} \left(\frac{h}{\sqrt{eta \cdot eta - \frac{sinTheta\_O \cdot sinTheta\_O}{\sqrt{1 - sinTheta\_O \cdot sinTheta\_O}}}}\right) \]
            2. Add Preprocessing
            3. Taylor expanded in eta around inf

              \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]
            4. Step-by-step derivation
              1. lower-/.f3294.5

                \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]
            5. Applied rewrites94.5%

              \[\leadsto \sin^{-1} \color{blue}{\left(\frac{h}{eta}\right)} \]
            6. Add Preprocessing

            Reproduce

            ?
            herbie shell --seed 2024214 
            (FPCore (sinTheta_O h eta)
              :name "HairBSDF, gamma for a refracted ray"
              :precision binary32
              :pre (and (and (and (<= -1.0 sinTheta_O) (<= sinTheta_O 1.0)) (and (<= -1.0 h) (<= h 1.0))) (and (<= 0.0 eta) (<= eta 10.0)))
              (asin (/ h (sqrt (- (* eta eta) (/ (* sinTheta_O sinTheta_O) (sqrt (- 1.0 (* sinTheta_O sinTheta_O)))))))))