bug323 (missed optimization)

Percentage Accurate: 7.0% → 10.6%
Time: 4.7s
Alternatives: 6
Speedup: 1.0×

Specification

?
\[0 \leq x \land x \leq 0.5\]
\[\begin{array}{l} \\ \cos^{-1} \left(1 - x\right) \end{array} \]
(FPCore (x) :precision binary64 (acos (- 1.0 x)))
double code(double x) {
	return acos((1.0 - x));
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = acos((1.0d0 - x))
end function
public static double code(double x) {
	return Math.acos((1.0 - x));
}
def code(x):
	return math.acos((1.0 - x))
function code(x)
	return acos(Float64(1.0 - x))
end
function tmp = code(x)
	tmp = acos((1.0 - x));
end
code[x_] := N[ArcCos[N[(1.0 - x), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}

\\
\cos^{-1} \left(1 - x\right)
\end{array}

Sampling outcomes in binary64 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 6 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: 7.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \cos^{-1} \left(1 - x\right) \end{array} \]
(FPCore (x) :precision binary64 (acos (- 1.0 x)))
double code(double x) {
	return acos((1.0 - x));
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = acos((1.0d0 - x))
end function
public static double code(double x) {
	return Math.acos((1.0 - x));
}
def code(x):
	return math.acos((1.0 - x))
function code(x)
	return acos(Float64(1.0 - x))
end
function tmp = code(x)
	tmp = acos((1.0 - x));
end
code[x_] := N[ArcCos[N[(1.0 - x), $MachinePrecision]], $MachinePrecision]
\begin{array}{l}

\\
\cos^{-1} \left(1 - x\right)
\end{array}

Alternative 1: 10.6% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\sqrt{\pi}}\\ \mathsf{fma}\left(t\_0 \cdot t\_0, \sqrt{\pi} \cdot 0.5, -\sin^{-1} \left(1 - x\right)\right) \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (let* ((t_0 (sqrt (sqrt PI))))
   (fma (* t_0 t_0) (* (sqrt PI) 0.5) (- (asin (- 1.0 x))))))
double code(double x) {
	double t_0 = sqrt(sqrt(((double) M_PI)));
	return fma((t_0 * t_0), (sqrt(((double) M_PI)) * 0.5), -asin((1.0 - x)));
}
function code(x)
	t_0 = sqrt(sqrt(pi))
	return fma(Float64(t_0 * t_0), Float64(sqrt(pi) * 0.5), Float64(-asin(Float64(1.0 - x))))
end
code[x_] := Block[{t$95$0 = N[Sqrt[N[Sqrt[Pi], $MachinePrecision]], $MachinePrecision]}, N[(N[(t$95$0 * t$95$0), $MachinePrecision] * N[(N[Sqrt[Pi], $MachinePrecision] * 0.5), $MachinePrecision] + (-N[ArcSin[N[(1.0 - x), $MachinePrecision]], $MachinePrecision])), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sqrt{\sqrt{\pi}}\\
\mathsf{fma}\left(t\_0 \cdot t\_0, \sqrt{\pi} \cdot 0.5, -\sin^{-1} \left(1 - x\right)\right)
\end{array}
\end{array}
Derivation
  1. Initial program 7.7%

    \[\cos^{-1} \left(1 - x\right) \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \cos^{-1} \color{blue}{\left(-1 \cdot x\right)} \]
  4. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto \cos^{-1} \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]
    2. lower-neg.f647.0

      \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
  5. Applied rewrites7.0%

    \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
  6. Step-by-step derivation
    1. lift-acos.f64N/A

      \[\leadsto \color{blue}{\cos^{-1} \left(\mathsf{neg}\left(x\right)\right)} \]
    2. acos-asinN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} - \sin^{-1} \left(\mathsf{neg}\left(x\right)\right)} \]
    3. sub-negN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right)} \]
    4. div-invN/A

      \[\leadsto \color{blue}{\mathsf{PI}\left(\right) \cdot \frac{1}{2}} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    5. add-sqr-sqrtN/A

      \[\leadsto \color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \sqrt{\mathsf{PI}\left(\right)}\right)} \cdot \frac{1}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    6. associate-*l*N/A

      \[\leadsto \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    7. lower-fma.f64N/A

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right)} \]
    8. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    9. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\color{blue}{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    10. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    11. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    12. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\color{blue}{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    13. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    14. lower-neg.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \color{blue}{\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)}\right) \]
    15. lower-asin.f647.0

      \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\color{blue}{\sin^{-1} \left(-x\right)}\right) \]
  7. Applied rewrites7.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} x\right)} \]
  8. Taylor expanded in x around 0

    \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \color{blue}{\left(1 + -1 \cdot x\right)}\right)\right) \]
  9. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)}\right)\right)\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \color{blue}{\left(1 - x\right)}\right)\right) \]
    3. lower--.f645.9

      \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} \color{blue}{\left(1 - x\right)}\right) \]
  10. Applied rewrites5.9%

    \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} \color{blue}{\left(1 - x\right)}\right) \]
  11. Step-by-step derivation
    1. lift-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    2. pow1/2N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{{\mathsf{PI}\left(\right)}^{\frac{1}{2}}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    3. sqr-powN/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{{\mathsf{PI}\left(\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    4. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{{\mathsf{PI}\left(\right)}^{\left(\frac{\frac{1}{2}}{2}\right)} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    5. sqrt-pow1N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{{\mathsf{PI}\left(\right)}^{\frac{1}{2}}}} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    6. pow1/2N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    7. lift-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    8. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\sqrt{\mathsf{PI}\left(\right)}}} \cdot {\mathsf{PI}\left(\right)}^{\left(\frac{\frac{1}{2}}{2}\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    9. sqrt-pow1N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\sqrt{\mathsf{PI}\left(\right)}} \cdot \color{blue}{\sqrt{{\mathsf{PI}\left(\right)}^{\frac{1}{2}}}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    10. pow1/2N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\sqrt{\mathsf{PI}\left(\right)}} \cdot \sqrt{\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    11. lift-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\sqrt{\mathsf{PI}\left(\right)}} \cdot \sqrt{\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 - x\right)\right)\right) \]
    12. lower-sqrt.f6411.1

      \[\leadsto \mathsf{fma}\left(\sqrt{\sqrt{\pi}} \cdot \color{blue}{\sqrt{\sqrt{\pi}}}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} \left(1 - x\right)\right) \]
  12. Applied rewrites11.1%

    \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\sqrt{\pi}} \cdot \sqrt{\sqrt{\pi}}}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} \left(1 - x\right)\right) \]
  13. Add Preprocessing

Alternative 2: 10.5% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \sqrt{\pi} \cdot 0.5\\ \mathsf{fma}\left(\sqrt{\pi}, t\_0, -\mathsf{fma}\left(t\_0, \sqrt{\pi}, -\cos^{-1} \left(1 - x\right)\right)\right) \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (let* ((t_0 (* (sqrt PI) 0.5)))
   (fma (sqrt PI) t_0 (- (fma t_0 (sqrt PI) (- (acos (- 1.0 x))))))))
double code(double x) {
	double t_0 = sqrt(((double) M_PI)) * 0.5;
	return fma(sqrt(((double) M_PI)), t_0, -fma(t_0, sqrt(((double) M_PI)), -acos((1.0 - x))));
}
function code(x)
	t_0 = Float64(sqrt(pi) * 0.5)
	return fma(sqrt(pi), t_0, Float64(-fma(t_0, sqrt(pi), Float64(-acos(Float64(1.0 - x))))))
end
code[x_] := Block[{t$95$0 = N[(N[Sqrt[Pi], $MachinePrecision] * 0.5), $MachinePrecision]}, N[(N[Sqrt[Pi], $MachinePrecision] * t$95$0 + (-N[(t$95$0 * N[Sqrt[Pi], $MachinePrecision] + (-N[ArcCos[N[(1.0 - x), $MachinePrecision]], $MachinePrecision])), $MachinePrecision])), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \sqrt{\pi} \cdot 0.5\\
\mathsf{fma}\left(\sqrt{\pi}, t\_0, -\mathsf{fma}\left(t\_0, \sqrt{\pi}, -\cos^{-1} \left(1 - x\right)\right)\right)
\end{array}
\end{array}
Derivation
  1. Initial program 7.7%

    \[\cos^{-1} \left(1 - x\right) \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \cos^{-1} \color{blue}{\left(-1 \cdot x\right)} \]
  4. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto \cos^{-1} \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]
    2. lower-neg.f647.0

      \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
  5. Applied rewrites7.0%

    \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
  6. Step-by-step derivation
    1. lift-acos.f64N/A

      \[\leadsto \color{blue}{\cos^{-1} \left(\mathsf{neg}\left(x\right)\right)} \]
    2. acos-asinN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} - \sin^{-1} \left(\mathsf{neg}\left(x\right)\right)} \]
    3. sub-negN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right)} \]
    4. div-invN/A

      \[\leadsto \color{blue}{\mathsf{PI}\left(\right) \cdot \frac{1}{2}} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    5. add-sqr-sqrtN/A

      \[\leadsto \color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \sqrt{\mathsf{PI}\left(\right)}\right)} \cdot \frac{1}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    6. associate-*l*N/A

      \[\leadsto \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    7. lower-fma.f64N/A

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right)} \]
    8. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    9. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\color{blue}{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    10. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    11. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    12. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\color{blue}{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    13. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    14. lower-neg.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \color{blue}{\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)}\right) \]
    15. lower-asin.f647.0

      \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\color{blue}{\sin^{-1} \left(-x\right)}\right) \]
  7. Applied rewrites7.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} x\right)} \]
  8. Taylor expanded in x around 0

    \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \color{blue}{\left(1 + -1 \cdot x\right)}\right)\right) \]
  9. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(1 + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)}\right)\right)\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \color{blue}{\left(1 - x\right)}\right)\right) \]
    3. lower--.f645.9

      \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} \color{blue}{\left(1 - x\right)}\right) \]
  10. Applied rewrites5.9%

    \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} \color{blue}{\left(1 - x\right)}\right) \]
  11. Step-by-step derivation
    1. lift-asin.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\color{blue}{\sin^{-1} \left(1 - x\right)}\right)\right) \]
    2. asin-acosN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\color{blue}{\left(\frac{\mathsf{PI}\left(\right)}{2} - \cos^{-1} \left(1 - x\right)\right)}\right)\right) \]
    3. lift-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\frac{\color{blue}{\mathsf{PI}\left(\right)}}{2} - \cos^{-1} \left(1 - x\right)\right)\right)\right) \]
    4. div-invN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\color{blue}{\mathsf{PI}\left(\right) \cdot \frac{1}{2}} - \cos^{-1} \left(1 - x\right)\right)\right)\right) \]
    5. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\mathsf{PI}\left(\right) \cdot \color{blue}{\frac{1}{2}} - \cos^{-1} \left(1 - x\right)\right)\right)\right) \]
    6. rem-square-sqrtN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \sqrt{\mathsf{PI}\left(\right)}\right)} \cdot \frac{1}{2} - \cos^{-1} \left(1 - x\right)\right)\right)\right) \]
    7. lift-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)}} \cdot \sqrt{\mathsf{PI}\left(\right)}\right) \cdot \frac{1}{2} - \cos^{-1} \left(1 - x\right)\right)\right)\right) \]
    8. lift-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \color{blue}{\sqrt{\mathsf{PI}\left(\right)}}\right) \cdot \frac{1}{2} - \cos^{-1} \left(1 - x\right)\right)\right)\right) \]
    9. associate-*r*N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} - \cos^{-1} \left(1 - x\right)\right)\right)\right) \]
    10. lift-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} - \cos^{-1} \left(1 - x\right)\right)\right)\right) \]
    11. sub-negN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right) + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)}\right)\right) \]
    12. *-commutativeN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\left(\color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right) \cdot \sqrt{\mathsf{PI}\left(\right)}} + \left(\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right)\right) \]
    13. lower-fma.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \sqrt{\mathsf{PI}\left(\right)}, \mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)}\right)\right) \]
    14. lift-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\mathsf{fma}\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}}, \sqrt{\mathsf{PI}\left(\right)}, \mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    15. *-commutativeN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\mathsf{fma}\left(\color{blue}{\frac{1}{2} \cdot \sqrt{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)}, \mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    16. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\mathsf{fma}\left(\color{blue}{\frac{1}{2} \cdot \sqrt{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)}, \mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)\right)\right)\right) \]
    17. lower-neg.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\mathsf{fma}\left(\frac{1}{2} \cdot \sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\mathsf{neg}\left(\cos^{-1} \left(1 - x\right)\right)}\right)\right)\right) \]
    18. lower-acos.f6411.1

      \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\mathsf{fma}\left(0.5 \cdot \sqrt{\pi}, \sqrt{\pi}, -\color{blue}{\cos^{-1} \left(1 - x\right)}\right)\right) \]
  12. Applied rewrites11.1%

    \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\color{blue}{\mathsf{fma}\left(0.5 \cdot \sqrt{\pi}, \sqrt{\pi}, -\cos^{-1} \left(1 - x\right)\right)}\right) \]
  13. Final simplification11.1%

    \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\mathsf{fma}\left(\sqrt{\pi} \cdot 0.5, \sqrt{\pi}, -\cos^{-1} \left(1 - x\right)\right)\right) \]
  14. Add Preprocessing

Alternative 3: 10.5% accurate, 0.7× speedup?

\[\begin{array}{l} \\ \pi \cdot 0.5 - \mathsf{fma}\left(\sqrt{\pi} \cdot 0.5, \sqrt{\pi}, -\cos^{-1} \left(1 - x\right)\right) \end{array} \]
(FPCore (x)
 :precision binary64
 (- (* PI 0.5) (fma (* (sqrt PI) 0.5) (sqrt PI) (- (acos (- 1.0 x))))))
double code(double x) {
	return (((double) M_PI) * 0.5) - fma((sqrt(((double) M_PI)) * 0.5), sqrt(((double) M_PI)), -acos((1.0 - x)));
}
function code(x)
	return Float64(Float64(pi * 0.5) - fma(Float64(sqrt(pi) * 0.5), sqrt(pi), Float64(-acos(Float64(1.0 - x)))))
end
code[x_] := N[(N[(Pi * 0.5), $MachinePrecision] - N[(N[(N[Sqrt[Pi], $MachinePrecision] * 0.5), $MachinePrecision] * N[Sqrt[Pi], $MachinePrecision] + (-N[ArcCos[N[(1.0 - x), $MachinePrecision]], $MachinePrecision])), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\pi \cdot 0.5 - \mathsf{fma}\left(\sqrt{\pi} \cdot 0.5, \sqrt{\pi}, -\cos^{-1} \left(1 - x\right)\right)
\end{array}
Derivation
  1. Initial program 7.7%

    \[\cos^{-1} \left(1 - x\right) \]
  2. Add Preprocessing
  3. Taylor expanded in x around inf

    \[\leadsto \cos^{-1} \color{blue}{\left(-1 \cdot x\right)} \]
  4. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto \cos^{-1} \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]
    2. lower-neg.f647.0

      \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
  5. Applied rewrites7.0%

    \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
  6. Step-by-step derivation
    1. lift-acos.f64N/A

      \[\leadsto \color{blue}{\cos^{-1} \left(\mathsf{neg}\left(x\right)\right)} \]
    2. acos-asinN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} - \sin^{-1} \left(\mathsf{neg}\left(x\right)\right)} \]
    3. sub-negN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right)}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right)} \]
    4. div-invN/A

      \[\leadsto \color{blue}{\mathsf{PI}\left(\right) \cdot \frac{1}{2}} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    5. add-sqr-sqrtN/A

      \[\leadsto \color{blue}{\left(\sqrt{\mathsf{PI}\left(\right)} \cdot \sqrt{\mathsf{PI}\left(\right)}\right)} \cdot \frac{1}{2} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    6. associate-*l*N/A

      \[\leadsto \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \left(\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}\right)} + \left(\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    7. lower-fma.f64N/A

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right)} \]
    8. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\color{blue}{\sqrt{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    9. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\color{blue}{\mathsf{PI}\left(\right)}}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    10. lower-*.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    11. lower-sqrt.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \color{blue}{\sqrt{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    12. lower-PI.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\color{blue}{\mathsf{PI}\left(\right)}} \cdot \frac{1}{2}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    13. metadata-evalN/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \color{blue}{\frac{1}{2}}, \mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    14. lower-neg.f64N/A

      \[\leadsto \mathsf{fma}\left(\sqrt{\mathsf{PI}\left(\right)}, \sqrt{\mathsf{PI}\left(\right)} \cdot \frac{1}{2}, \color{blue}{\mathsf{neg}\left(\sin^{-1} \left(\mathsf{neg}\left(x\right)\right)\right)}\right) \]
    15. lower-asin.f647.0

      \[\leadsto \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\color{blue}{\sin^{-1} \left(-x\right)}\right) \]
  7. Applied rewrites7.0%

    \[\leadsto \color{blue}{\mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi} \cdot 0.5, -\sin^{-1} x\right)} \]
  8. Taylor expanded in x around 0

    \[\leadsto \color{blue}{\frac{1}{2} \cdot \mathsf{PI}\left(\right) - \sin^{-1} \left(1 - x\right)} \]
  9. Step-by-step derivation
    1. sub-negN/A

      \[\leadsto \frac{1}{2} \cdot \mathsf{PI}\left(\right) - \sin^{-1} \color{blue}{\left(1 + \left(\mathsf{neg}\left(x\right)\right)\right)} \]
    2. mul-1-negN/A

      \[\leadsto \frac{1}{2} \cdot \mathsf{PI}\left(\right) - \sin^{-1} \left(1 + \color{blue}{-1 \cdot x}\right) \]
    3. lower--.f64N/A

      \[\leadsto \color{blue}{\frac{1}{2} \cdot \mathsf{PI}\left(\right) - \sin^{-1} \left(1 + -1 \cdot x\right)} \]
    4. lower-*.f64N/A

      \[\leadsto \color{blue}{\frac{1}{2} \cdot \mathsf{PI}\left(\right)} - \sin^{-1} \left(1 + -1 \cdot x\right) \]
    5. lower-PI.f64N/A

      \[\leadsto \frac{1}{2} \cdot \color{blue}{\mathsf{PI}\left(\right)} - \sin^{-1} \left(1 + -1 \cdot x\right) \]
    6. lower-asin.f64N/A

      \[\leadsto \frac{1}{2} \cdot \mathsf{PI}\left(\right) - \color{blue}{\sin^{-1} \left(1 + -1 \cdot x\right)} \]
    7. mul-1-negN/A

      \[\leadsto \frac{1}{2} \cdot \mathsf{PI}\left(\right) - \sin^{-1} \left(1 + \color{blue}{\left(\mathsf{neg}\left(x\right)\right)}\right) \]
    8. sub-negN/A

      \[\leadsto \frac{1}{2} \cdot \mathsf{PI}\left(\right) - \sin^{-1} \color{blue}{\left(1 - x\right)} \]
    9. lower--.f647.7

      \[\leadsto 0.5 \cdot \pi - \sin^{-1} \color{blue}{\left(1 - x\right)} \]
  10. Applied rewrites7.7%

    \[\leadsto \color{blue}{0.5 \cdot \pi - \sin^{-1} \left(1 - x\right)} \]
  11. Step-by-step derivation
    1. Applied rewrites11.1%

      \[\leadsto 0.5 \cdot \pi - \mathsf{fma}\left(0.5 \cdot \sqrt{\pi}, \color{blue}{\sqrt{\pi}}, -\cos^{-1} \left(1 - x\right)\right) \]
    2. Final simplification11.1%

      \[\leadsto \pi \cdot 0.5 - \mathsf{fma}\left(\sqrt{\pi} \cdot 0.5, \sqrt{\pi}, -\cos^{-1} \left(1 - x\right)\right) \]
    3. Add Preprocessing

    Alternative 4: 9.5% accurate, 0.9× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;1 - x \leq 0.9999999999999997:\\ \;\;\;\;\cos^{-1} \left(1 - x\right)\\ \mathbf{else}:\\ \;\;\;\;\cos^{-1} x\\ \end{array} \end{array} \]
    (FPCore (x)
     :precision binary64
     (if (<= (- 1.0 x) 0.9999999999999997) (acos (- 1.0 x)) (acos x)))
    double code(double x) {
    	double tmp;
    	if ((1.0 - x) <= 0.9999999999999997) {
    		tmp = acos((1.0 - x));
    	} else {
    		tmp = acos(x);
    	}
    	return tmp;
    }
    
    real(8) function code(x)
        real(8), intent (in) :: x
        real(8) :: tmp
        if ((1.0d0 - x) <= 0.9999999999999997d0) then
            tmp = acos((1.0d0 - x))
        else
            tmp = acos(x)
        end if
        code = tmp
    end function
    
    public static double code(double x) {
    	double tmp;
    	if ((1.0 - x) <= 0.9999999999999997) {
    		tmp = Math.acos((1.0 - x));
    	} else {
    		tmp = Math.acos(x);
    	}
    	return tmp;
    }
    
    def code(x):
    	tmp = 0
    	if (1.0 - x) <= 0.9999999999999997:
    		tmp = math.acos((1.0 - x))
    	else:
    		tmp = math.acos(x)
    	return tmp
    
    function code(x)
    	tmp = 0.0
    	if (Float64(1.0 - x) <= 0.9999999999999997)
    		tmp = acos(Float64(1.0 - x));
    	else
    		tmp = acos(x);
    	end
    	return tmp
    end
    
    function tmp_2 = code(x)
    	tmp = 0.0;
    	if ((1.0 - x) <= 0.9999999999999997)
    		tmp = acos((1.0 - x));
    	else
    		tmp = acos(x);
    	end
    	tmp_2 = tmp;
    end
    
    code[x_] := If[LessEqual[N[(1.0 - x), $MachinePrecision], 0.9999999999999997], N[ArcCos[N[(1.0 - x), $MachinePrecision]], $MachinePrecision], N[ArcCos[x], $MachinePrecision]]
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    \mathbf{if}\;1 - x \leq 0.9999999999999997:\\
    \;\;\;\;\cos^{-1} \left(1 - x\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\cos^{-1} x\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (-.f64 #s(literal 1 binary64) x) < 0.999999999999999667

      1. Initial program 58.5%

        \[\cos^{-1} \left(1 - x\right) \]
      2. Add Preprocessing

      if 0.999999999999999667 < (-.f64 #s(literal 1 binary64) x)

      1. Initial program 3.9%

        \[\cos^{-1} \left(1 - x\right) \]
      2. Add Preprocessing
      3. Taylor expanded in x around inf

        \[\leadsto \cos^{-1} \color{blue}{\left(-1 \cdot x\right)} \]
      4. Step-by-step derivation
        1. mul-1-negN/A

          \[\leadsto \cos^{-1} \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]
        2. lower-neg.f646.5

          \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
      5. Applied rewrites6.5%

        \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
      6. Step-by-step derivation
        1. Applied rewrites6.5%

          \[\leadsto \color{blue}{\cos^{-1} x} \]
      7. Recombined 2 regimes into one program.
      8. Add Preprocessing

      Alternative 5: 7.0% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \cos^{-1} x \end{array} \]
      (FPCore (x) :precision binary64 (acos x))
      double code(double x) {
      	return acos(x);
      }
      
      real(8) function code(x)
          real(8), intent (in) :: x
          code = acos(x)
      end function
      
      public static double code(double x) {
      	return Math.acos(x);
      }
      
      def code(x):
      	return math.acos(x)
      
      function code(x)
      	return acos(x)
      end
      
      function tmp = code(x)
      	tmp = acos(x);
      end
      
      code[x_] := N[ArcCos[x], $MachinePrecision]
      
      \begin{array}{l}
      
      \\
      \cos^{-1} x
      \end{array}
      
      Derivation
      1. Initial program 7.7%

        \[\cos^{-1} \left(1 - x\right) \]
      2. Add Preprocessing
      3. Taylor expanded in x around inf

        \[\leadsto \cos^{-1} \color{blue}{\left(-1 \cdot x\right)} \]
      4. Step-by-step derivation
        1. mul-1-negN/A

          \[\leadsto \cos^{-1} \color{blue}{\left(\mathsf{neg}\left(x\right)\right)} \]
        2. lower-neg.f647.0

          \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
      5. Applied rewrites7.0%

        \[\leadsto \cos^{-1} \color{blue}{\left(-x\right)} \]
      6. Step-by-step derivation
        1. Applied rewrites7.0%

          \[\leadsto \color{blue}{\cos^{-1} x} \]
        2. Add Preprocessing

        Alternative 6: 3.8% accurate, 1.0× speedup?

        \[\begin{array}{l} \\ \cos^{-1} 1 \end{array} \]
        (FPCore (x) :precision binary64 (acos 1.0))
        double code(double x) {
        	return acos(1.0);
        }
        
        real(8) function code(x)
            real(8), intent (in) :: x
            code = acos(1.0d0)
        end function
        
        public static double code(double x) {
        	return Math.acos(1.0);
        }
        
        def code(x):
        	return math.acos(1.0)
        
        function code(x)
        	return acos(1.0)
        end
        
        function tmp = code(x)
        	tmp = acos(1.0);
        end
        
        code[x_] := N[ArcCos[1.0], $MachinePrecision]
        
        \begin{array}{l}
        
        \\
        \cos^{-1} 1
        \end{array}
        
        Derivation
        1. Initial program 7.7%

          \[\cos^{-1} \left(1 - x\right) \]
        2. Add Preprocessing
        3. Taylor expanded in x around 0

          \[\leadsto \cos^{-1} \color{blue}{1} \]
        4. Step-by-step derivation
          1. Applied rewrites3.8%

            \[\leadsto \cos^{-1} \color{blue}{1} \]
          2. Add Preprocessing

          Developer Target 1: 100.0% accurate, 0.8× speedup?

          \[\begin{array}{l} \\ 2 \cdot \sin^{-1} \left(\sqrt{\frac{x}{2}}\right) \end{array} \]
          (FPCore (x) :precision binary64 (* 2.0 (asin (sqrt (/ x 2.0)))))
          double code(double x) {
          	return 2.0 * asin(sqrt((x / 2.0)));
          }
          
          real(8) function code(x)
              real(8), intent (in) :: x
              code = 2.0d0 * asin(sqrt((x / 2.0d0)))
          end function
          
          public static double code(double x) {
          	return 2.0 * Math.asin(Math.sqrt((x / 2.0)));
          }
          
          def code(x):
          	return 2.0 * math.asin(math.sqrt((x / 2.0)))
          
          function code(x)
          	return Float64(2.0 * asin(sqrt(Float64(x / 2.0))))
          end
          
          function tmp = code(x)
          	tmp = 2.0 * asin(sqrt((x / 2.0)));
          end
          
          code[x_] := N[(2.0 * N[ArcSin[N[Sqrt[N[(x / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
          
          \begin{array}{l}
          
          \\
          2 \cdot \sin^{-1} \left(\sqrt{\frac{x}{2}}\right)
          \end{array}
          

          Reproduce

          ?
          herbie shell --seed 2024214 
          (FPCore (x)
            :name "bug323 (missed optimization)"
            :precision binary64
            :pre (and (<= 0.0 x) (<= x 0.5))
          
            :alt
            (! :herbie-platform default (* 2 (asin (sqrt (/ x 2)))))
          
            (acos (- 1.0 x)))