?

Average Error: 93.3% → 91.83%
Time: 21.2s
Precision: binary64
Cost: 38912

?

\[\frac{\pi}{2} - 2 \cdot \sin^{-1} \left(\sqrt{\frac{1 - x}{2}}\right) \]
\[\log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + -0.5 \cdot \pi}\right) \]
(FPCore (x)
 :precision binary64
 (- (/ PI 2.0) (* 2.0 (asin (sqrt (/ (- 1.0 x) 2.0))))))
(FPCore (x)
 :precision binary64
 (log (exp (+ (* 2.0 (acos (sqrt (fma -0.5 x 0.5)))) (* -0.5 PI)))))
double code(double x) {
	return (((double) M_PI) / 2.0) - (2.0 * asin(sqrt(((1.0 - x) / 2.0))));
}
double code(double x) {
	return log(exp(((2.0 * acos(sqrt(fma(-0.5, x, 0.5)))) + (-0.5 * ((double) M_PI)))));
}
function code(x)
	return Float64(Float64(pi / 2.0) - Float64(2.0 * asin(sqrt(Float64(Float64(1.0 - x) / 2.0)))))
end
function code(x)
	return log(exp(Float64(Float64(2.0 * acos(sqrt(fma(-0.5, x, 0.5)))) + Float64(-0.5 * pi))))
end
code[x_] := N[(N[(Pi / 2.0), $MachinePrecision] - N[(2.0 * N[ArcSin[N[Sqrt[N[(N[(1.0 - x), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_] := N[Log[N[Exp[N[(N[(2.0 * N[ArcCos[N[Sqrt[N[(-0.5 * x + 0.5), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(-0.5 * Pi), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]
\frac{\pi}{2} - 2 \cdot \sin^{-1} \left(\sqrt{\frac{1 - x}{2}}\right)
\log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + -0.5 \cdot \pi}\right)

Error?

Target

Original93.3%
Target0%
Herbie91.83%
\[\sin^{-1} x \]

Derivation?

  1. Initial program 93.3

    \[\frac{\pi}{2} - 2 \cdot \sin^{-1} \left(\sqrt{\frac{1 - x}{2}}\right) \]
  2. Applied egg-rr93.31

    \[\leadsto \color{blue}{\log \left(e^{\mathsf{fma}\left(\pi, 0.5, \sin^{-1} \left(\sqrt{0.5 - x \cdot 0.5}\right) \cdot -2\right)}\right)} \]
  3. Applied egg-rr91.83

    \[\leadsto \log \left(e^{\mathsf{fma}\left(\pi, 0.5, \color{blue}{\left(\pi \cdot 0.5 - \cos^{-1} \left(\sqrt{0.5 + x \cdot -0.5}\right)\right)} \cdot -2\right)}\right) \]
  4. Applied egg-rr91.91

    \[\leadsto \log \left(e^{\color{blue}{\frac{-2}{\frac{2}{\pi}} + \left(-2 \cdot \left(-\cos^{-1} \left(\sqrt{\mathsf{fma}\left(x, -0.5, 0.5\right)}\right)\right) + \pi \cdot 0.5\right)}}\right) \]
  5. Simplified91.83

    \[\leadsto \log \left(e^{\color{blue}{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + \pi \cdot -0.5}}\right) \]
    Proof

    [Start]91.91

    \[ \log \left(e^{\frac{-2}{\frac{2}{\pi}} + \left(-2 \cdot \left(-\cos^{-1} \left(\sqrt{\mathsf{fma}\left(x, -0.5, 0.5\right)}\right)\right) + \pi \cdot 0.5\right)}\right) \]

    +-commutative [=>]91.91

    \[ \log \left(e^{\color{blue}{\left(-2 \cdot \left(-\cos^{-1} \left(\sqrt{\mathsf{fma}\left(x, -0.5, 0.5\right)}\right)\right) + \pi \cdot 0.5\right) + \frac{-2}{\frac{2}{\pi}}}}\right) \]

    associate-+r+ [<=]91.83

    \[ \log \left(e^{\color{blue}{-2 \cdot \left(-\cos^{-1} \left(\sqrt{\mathsf{fma}\left(x, -0.5, 0.5\right)}\right)\right) + \left(\pi \cdot 0.5 + \frac{-2}{\frac{2}{\pi}}\right)}}\right) \]

    distribute-rgt-neg-out [=>]91.83

    \[ \log \left(e^{\color{blue}{\left(--2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(x, -0.5, 0.5\right)}\right)\right)} + \left(\pi \cdot 0.5 + \frac{-2}{\frac{2}{\pi}}\right)}\right) \]

    distribute-lft-neg-in [=>]91.83

    \[ \log \left(e^{\color{blue}{\left(--2\right) \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(x, -0.5, 0.5\right)}\right)} + \left(\pi \cdot 0.5 + \frac{-2}{\frac{2}{\pi}}\right)}\right) \]

    metadata-eval [=>]91.83

    \[ \log \left(e^{\color{blue}{2} \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(x, -0.5, 0.5\right)}\right) + \left(\pi \cdot 0.5 + \frac{-2}{\frac{2}{\pi}}\right)}\right) \]

    fma-udef [=>]91.83

    \[ \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\color{blue}{x \cdot -0.5 + 0.5}}\right) + \left(\pi \cdot 0.5 + \frac{-2}{\frac{2}{\pi}}\right)}\right) \]

    *-commutative [<=]91.83

    \[ \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\color{blue}{-0.5 \cdot x} + 0.5}\right) + \left(\pi \cdot 0.5 + \frac{-2}{\frac{2}{\pi}}\right)}\right) \]

    fma-def [=>]91.83

    \[ \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\color{blue}{\mathsf{fma}\left(-0.5, x, 0.5\right)}}\right) + \left(\pi \cdot 0.5 + \frac{-2}{\frac{2}{\pi}}\right)}\right) \]

    *-commutative [=>]91.83

    \[ \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + \left(\color{blue}{0.5 \cdot \pi} + \frac{-2}{\frac{2}{\pi}}\right)}\right) \]

    associate-/r/ [=>]91.83

    \[ \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + \left(0.5 \cdot \pi + \color{blue}{\frac{-2}{2} \cdot \pi}\right)}\right) \]

    distribute-rgt-out [=>]91.83

    \[ \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + \color{blue}{\pi \cdot \left(0.5 + \frac{-2}{2}\right)}}\right) \]

    metadata-eval [=>]91.83

    \[ \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + \pi \cdot \left(0.5 + \color{blue}{-1}\right)}\right) \]

    metadata-eval [=>]91.83

    \[ \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + \pi \cdot \color{blue}{-0.5}}\right) \]
  6. Final simplification91.83

    \[\leadsto \log \left(e^{2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(-0.5, x, 0.5\right)}\right) + -0.5 \cdot \pi}\right) \]

Alternatives

Alternative 1
Error91.82%
Cost26112
\[-0.5 \cdot \pi + 2 \cdot \cos^{-1} \left(\sqrt{\mathsf{fma}\left(x, -0.5, 0.5\right)}\right) \]
Alternative 2
Error93.3%
Cost19840
\[\frac{\pi}{2} + -2 \cdot \sin^{-1} \left(\sqrt{\frac{1 - x}{2}}\right) \]

Error

Reproduce?

herbie shell --seed 2023089 
(FPCore (x)
  :name "Ian Simplification"
  :precision binary64

  :herbie-target
  (asin x)

  (- (/ PI 2.0) (* 2.0 (asin (sqrt (/ (- 1.0 x) 2.0))))))