
(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 3 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
(let* ((t_0 (acos (- (/ g h))))
(t_1 (fma PI -2.0 t_0))
(t_2
(/ (pow (* t_0 0.3333333333333333) 2.0) (* t_1 -0.3333333333333333))))
(*
2.0
(fma
(cos (/ (* (* PI PI) 1.3333333333333333) t_1))
(cos t_2)
(* (sin (* (/ -3.0 t_1) (* PI (* PI 0.4444444444444444)))) (sin t_2))))))
double code(double g, double h) {
double t_0 = acos(-(g / h));
double t_1 = fma(((double) M_PI), -2.0, t_0);
double t_2 = pow((t_0 * 0.3333333333333333), 2.0) / (t_1 * -0.3333333333333333);
return 2.0 * fma(cos((((((double) M_PI) * ((double) M_PI)) * 1.3333333333333333) / t_1)), cos(t_2), (sin(((-3.0 / t_1) * (((double) M_PI) * (((double) M_PI) * 0.4444444444444444)))) * sin(t_2)));
}
function code(g, h) t_0 = acos(Float64(-Float64(g / h))) t_1 = fma(pi, -2.0, t_0) t_2 = Float64((Float64(t_0 * 0.3333333333333333) ^ 2.0) / Float64(t_1 * -0.3333333333333333)) return Float64(2.0 * fma(cos(Float64(Float64(Float64(pi * pi) * 1.3333333333333333) / t_1)), cos(t_2), Float64(sin(Float64(Float64(-3.0 / t_1) * Float64(pi * Float64(pi * 0.4444444444444444)))) * sin(t_2)))) end
code[g_, h_] := Block[{t$95$0 = N[ArcCos[(-N[(g / h), $MachinePrecision])], $MachinePrecision]}, Block[{t$95$1 = N[(Pi * -2.0 + t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[Power[N[(t$95$0 * 0.3333333333333333), $MachinePrecision], 2.0], $MachinePrecision] / N[(t$95$1 * -0.3333333333333333), $MachinePrecision]), $MachinePrecision]}, N[(2.0 * N[(N[Cos[N[(N[(N[(Pi * Pi), $MachinePrecision] * 1.3333333333333333), $MachinePrecision] / t$95$1), $MachinePrecision]], $MachinePrecision] * N[Cos[t$95$2], $MachinePrecision] + N[(N[Sin[N[(N[(-3.0 / t$95$1), $MachinePrecision] * N[(Pi * N[(Pi * 0.4444444444444444), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sin[t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos^{-1} \left(-\frac{g}{h}\right)\\
t_1 := \mathsf{fma}\left(\pi, -2, t\_0\right)\\
t_2 := \frac{{\left(t\_0 \cdot 0.3333333333333333\right)}^{2}}{t\_1 \cdot -0.3333333333333333}\\
2 \cdot \mathsf{fma}\left(\cos \left(\frac{\left(\pi \cdot \pi\right) \cdot 1.3333333333333333}{t\_1}\right), \cos t\_2, \sin \left(\frac{-3}{t\_1} \cdot \left(\pi \cdot \left(\pi \cdot 0.4444444444444444\right)\right)\right) \cdot \sin t\_2\right)
\end{array}
\end{array}
Initial program 98.5%
Applied egg-rr98.4%
lift-PI.f64N/A
lift-PI.f64N/A
lift-*.f64N/A
lift-PI.f64N/A
lift-neg.f64N/A
lift-/.f64N/A
lift-acos.f64N/A
lift-fma.f64N/A
lift-*.f64N/A
lift-*.f64N/A
div-invN/A
lift-*.f64N/A
Applied egg-rr99.9%
lift-PI.f64N/A
lift-PI.f64N/A
lift-*.f64N/A
lift-PI.f64N/A
lift-neg.f64N/A
lift-/.f64N/A
lift-acos.f64N/A
lift-fma.f64N/A
times-fracN/A
metadata-evalN/A
associate-*l/N/A
lift-*.f64N/A
Applied egg-rr100.0%
Final simplification100.0%
(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(-Float64(g / 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
*-commutativeN/A
associate-/l*N/A
metadata-evalN/A
metadata-evalN/A
metadata-evalN/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%
Final simplification98.5%
(FPCore (g h) :precision binary64 (* 2.0 (cos (* 0.3333333333333333 (fma 2.0 PI (acos (- (/ g h))))))))
double code(double g, double h) {
return 2.0 * cos((0.3333333333333333 * fma(2.0, ((double) M_PI), acos(-(g / h)))));
}
function code(g, h) return Float64(2.0 * cos(Float64(0.3333333333333333 * fma(2.0, pi, acos(Float64(-Float64(g / h))))))) end
code[g_, h_] := N[(2.0 * N[Cos[N[(0.3333333333333333 * N[(2.0 * Pi + N[ArcCos[(-N[(g / h), $MachinePrecision])], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \cos \left(0.3333333333333333 \cdot \mathsf{fma}\left(2, \pi, \cos^{-1} \left(-\frac{g}{h}\right)\right)\right)
\end{array}
Initial program 98.5%
lift-PI.f64N/A
lift-*.f64N/A
frac-2negN/A
lift-neg.f64N/A
lift-/.f64N/A
lift-acos.f64N/A
frac-2negN/A
frac-2negN/A
div-invN/A
frac-2negN/A
div-invN/A
distribute-rgt-outN/A
lower-*.f64N/A
metadata-evalN/A
lift-*.f64N/A
lower-fma.f6498.5
lift-/.f64N/A
frac-2negN/A
Applied egg-rr98.5%
Final simplification98.5%
herbie shell --seed 2024208
(FPCore (g h)
:name "2-ancestry mixing, negative discriminant"
:precision binary64
(* 2.0 (cos (+ (/ (* 2.0 PI) 3.0) (/ (acos (/ (- g) h)) 3.0)))))