
(FPCore (g h) :precision binary64 (* 2.0 (cos (+ (/ (* 2.0 PI) 3.0) (/ (acos (/ (- g) h)) 3.0)))))
double code(double g, double h) {
return 2.0 * cos((((2.0 * ((double) M_PI)) / 3.0) + (acos((-g / h)) / 3.0)));
}
public static double code(double g, double h) {
return 2.0 * Math.cos((((2.0 * Math.PI) / 3.0) + (Math.acos((-g / h)) / 3.0)));
}
def code(g, h): return 2.0 * math.cos((((2.0 * math.pi) / 3.0) + (math.acos((-g / h)) / 3.0)))
function code(g, h) return Float64(2.0 * cos(Float64(Float64(Float64(2.0 * pi) / 3.0) + Float64(acos(Float64(Float64(-g) / h)) / 3.0)))) end
function tmp = code(g, h) tmp = 2.0 * cos((((2.0 * pi) / 3.0) + (acos((-g / h)) / 3.0))); end
code[g_, h_] := N[(2.0 * N[Cos[N[(N[(N[(2.0 * Pi), $MachinePrecision] / 3.0), $MachinePrecision] + N[(N[ArcCos[N[((-g) / h), $MachinePrecision]], $MachinePrecision] / 3.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \cos \left(\frac{2 \cdot \pi}{3} + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right)
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 4 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (g h) :precision binary64 (* 2.0 (cos (+ (/ (* 2.0 PI) 3.0) (/ (acos (/ (- g) h)) 3.0)))))
double code(double g, double h) {
return 2.0 * cos((((2.0 * ((double) M_PI)) / 3.0) + (acos((-g / h)) / 3.0)));
}
public static double code(double g, double h) {
return 2.0 * Math.cos((((2.0 * Math.PI) / 3.0) + (Math.acos((-g / h)) / 3.0)));
}
def code(g, h): return 2.0 * math.cos((((2.0 * math.pi) / 3.0) + (math.acos((-g / h)) / 3.0)))
function code(g, h) return Float64(2.0 * cos(Float64(Float64(Float64(2.0 * pi) / 3.0) + Float64(acos(Float64(Float64(-g) / h)) / 3.0)))) end
function tmp = code(g, h) tmp = 2.0 * cos((((2.0 * pi) / 3.0) + (acos((-g / h)) / 3.0))); end
code[g_, h_] := N[(2.0 * N[Cos[N[(N[(N[(2.0 * Pi), $MachinePrecision] / 3.0), $MachinePrecision] + N[(N[ArcCos[N[((-g) / h), $MachinePrecision]], $MachinePrecision] / 3.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \cos \left(\frac{2 \cdot \pi}{3} + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right)
\end{array}
(FPCore (g h)
:precision binary64
(*
2.0
(*
-0.5
(fma
(sin (* (acos (/ g (- h))) 0.3333333333333333))
(sqrt 3.0)
(cos
(* 0.3333333333333333 (fma (sqrt PI) (sqrt PI) (- (acos (/ g h))))))))))
double code(double g, double h) {
return 2.0 * (-0.5 * fma(sin((acos((g / -h)) * 0.3333333333333333)), sqrt(3.0), cos((0.3333333333333333 * fma(sqrt(((double) M_PI)), sqrt(((double) M_PI)), -acos((g / h)))))));
}
function code(g, h) return Float64(2.0 * Float64(-0.5 * fma(sin(Float64(acos(Float64(g / Float64(-h))) * 0.3333333333333333)), sqrt(3.0), cos(Float64(0.3333333333333333 * fma(sqrt(pi), sqrt(pi), Float64(-acos(Float64(g / h))))))))) end
code[g_, h_] := N[(2.0 * N[(-0.5 * N[(N[Sin[N[(N[ArcCos[N[(g / (-h)), $MachinePrecision]], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]], $MachinePrecision] * N[Sqrt[3.0], $MachinePrecision] + N[Cos[N[(0.3333333333333333 * N[(N[Sqrt[Pi], $MachinePrecision] * N[Sqrt[Pi], $MachinePrecision] + (-N[ArcCos[N[(g / h), $MachinePrecision]], $MachinePrecision])), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \left(-0.5 \cdot \mathsf{fma}\left(\sin \left(\cos^{-1} \left(\frac{g}{-h}\right) \cdot 0.3333333333333333\right), \sqrt{3}, \cos \left(0.3333333333333333 \cdot \mathsf{fma}\left(\sqrt{\pi}, \sqrt{\pi}, -\cos^{-1} \left(\frac{g}{h}\right)\right)\right)\right)\right)
\end{array}
Initial program 98.5%
Applied egg-rr99.9%
Applied egg-rr100.0%
Taylor expanded in g around 0
distribute-lft-outN/A
lower-*.f64N/A
+-commutativeN/A
lower-fma.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-acos.f64N/A
mul-1-negN/A
distribute-neg-frac2N/A
mul-1-negN/A
lower-/.f64N/A
mul-1-negN/A
lower-neg.f64N/A
lower-sqrt.f64N/A
lower-cos.f64N/A
Simplified99.9%
distribute-frac-neg2N/A
acos-negN/A
lift-PI.f64N/A
sub-negN/A
rem-square-sqrtN/A
lift-sqrt.f64N/A
lift-sqrt.f64N/A
acos-asinN/A
unsub-negN/A
asin-negN/A
distribute-frac-neg2N/A
lift-neg.f64N/A
lift-/.f64N/A
lower-fma.f64N/A
lower-neg.f64N/A
lift-/.f64N/A
lift-neg.f64N/A
distribute-frac-neg2N/A
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (g h)
:precision binary64
(*
2.0
(*
-0.5
(fma
(sin (* (acos (/ g (- h))) 0.3333333333333333))
(sqrt 3.0)
(cos (* 0.3333333333333333 (- PI (acos (/ g h)))))))))
double code(double g, double h) {
return 2.0 * (-0.5 * fma(sin((acos((g / -h)) * 0.3333333333333333)), sqrt(3.0), cos((0.3333333333333333 * (((double) M_PI) - acos((g / h)))))));
}
function code(g, h) return Float64(2.0 * Float64(-0.5 * fma(sin(Float64(acos(Float64(g / Float64(-h))) * 0.3333333333333333)), sqrt(3.0), cos(Float64(0.3333333333333333 * Float64(pi - acos(Float64(g / h)))))))) end
code[g_, h_] := N[(2.0 * N[(-0.5 * N[(N[Sin[N[(N[ArcCos[N[(g / (-h)), $MachinePrecision]], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]], $MachinePrecision] * N[Sqrt[3.0], $MachinePrecision] + N[Cos[N[(0.3333333333333333 * N[(Pi - N[ArcCos[N[(g / h), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \left(-0.5 \cdot \mathsf{fma}\left(\sin \left(\cos^{-1} \left(\frac{g}{-h}\right) \cdot 0.3333333333333333\right), \sqrt{3}, \cos \left(0.3333333333333333 \cdot \left(\pi - \cos^{-1} \left(\frac{g}{h}\right)\right)\right)\right)\right)
\end{array}
Initial program 98.5%
Applied egg-rr99.9%
Applied egg-rr100.0%
Taylor expanded in g around 0
distribute-lft-outN/A
lower-*.f64N/A
+-commutativeN/A
lower-fma.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-acos.f64N/A
mul-1-negN/A
distribute-neg-frac2N/A
mul-1-negN/A
lower-/.f64N/A
mul-1-negN/A
lower-neg.f64N/A
lower-sqrt.f64N/A
lower-cos.f64N/A
Simplified99.9%
distribute-frac-neg2N/A
acos-negN/A
lift-PI.f64N/A
acos-asinN/A
unsub-negN/A
asin-negN/A
distribute-frac-neg2N/A
lift-neg.f64N/A
lift-/.f64N/A
lower--.f64N/A
lift-/.f64N/A
lift-neg.f64N/A
distribute-frac-neg2N/A
asin-negN/A
unsub-negN/A
acos-asinN/A
lower-acos.f64N/A
lower-/.f64100.0
Applied egg-rr100.0%
Final simplification100.0%
(FPCore (g h) :precision binary64 (let* ((t_0 (* (acos (/ g (- h))) 0.3333333333333333))) (* 2.0 (* -0.5 (fma (sin t_0) (sqrt 3.0) (cos t_0))))))
double code(double g, double h) {
double t_0 = acos((g / -h)) * 0.3333333333333333;
return 2.0 * (-0.5 * fma(sin(t_0), sqrt(3.0), cos(t_0)));
}
function code(g, h) t_0 = Float64(acos(Float64(g / Float64(-h))) * 0.3333333333333333) return Float64(2.0 * Float64(-0.5 * fma(sin(t_0), sqrt(3.0), cos(t_0)))) end
code[g_, h_] := Block[{t$95$0 = N[(N[ArcCos[N[(g / (-h)), $MachinePrecision]], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]}, N[(2.0 * N[(-0.5 * N[(N[Sin[t$95$0], $MachinePrecision] * N[Sqrt[3.0], $MachinePrecision] + N[Cos[t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos^{-1} \left(\frac{g}{-h}\right) \cdot 0.3333333333333333\\
2 \cdot \left(-0.5 \cdot \mathsf{fma}\left(\sin t\_0, \sqrt{3}, \cos t\_0\right)\right)
\end{array}
\end{array}
Initial program 98.5%
Applied egg-rr99.9%
Applied egg-rr100.0%
Taylor expanded in g around 0
distribute-lft-outN/A
lower-*.f64N/A
+-commutativeN/A
lower-fma.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-acos.f64N/A
mul-1-negN/A
distribute-neg-frac2N/A
mul-1-negN/A
lower-/.f64N/A
mul-1-negN/A
lower-neg.f64N/A
lower-sqrt.f64N/A
lower-cos.f64N/A
Simplified99.9%
(FPCore (g h) :precision binary64 (* 2.0 (cos (fma PI 0.6666666666666666 (* (acos (/ g (- h))) 0.3333333333333333)))))
double code(double g, double h) {
return 2.0 * cos(fma(((double) M_PI), 0.6666666666666666, (acos((g / -h)) * 0.3333333333333333)));
}
function code(g, h) return Float64(2.0 * cos(fma(pi, 0.6666666666666666, Float64(acos(Float64(g / Float64(-h))) * 0.3333333333333333)))) end
code[g_, h_] := N[(2.0 * N[Cos[N[(Pi * 0.6666666666666666 + N[(N[ArcCos[N[(g / (-h)), $MachinePrecision]], $MachinePrecision] * 0.3333333333333333), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \cos \left(\mathsf{fma}\left(\pi, 0.6666666666666666, \cos^{-1} \left(\frac{g}{-h}\right) \cdot 0.3333333333333333\right)\right)
\end{array}
Initial program 98.5%
lift-PI.f64N/A
lift-*.f64N/A
div-invN/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lift-neg.f64N/A
lift-/.f64N/A
lift-acos.f64N/A
lift-/.f64N/A
lower-fma.f64N/A
metadata-evalN/A
metadata-eval98.5
lift-/.f64N/A
div-invN/A
lower-*.f64N/A
Applied egg-rr98.5%
herbie shell --seed 2024221
(FPCore (g h)
:name "2-ancestry mixing, negative discriminant"
:precision binary64
(* 2.0 (cos (+ (/ (* 2.0 PI) 3.0) (/ (acos (/ (- g) h)) 3.0)))))