
(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 (* PI (* PI 0.4444444444444444)))
(t_1 (acos (/ g (- h))))
(t_2 (pow t_1 2.0))
(t_3 (fma 0.3333333333333333 t_1 (* PI -0.6666666666666666))))
(*
2.0
(fma
(sin (/ t_0 t_3))
(sin (* t_2 (/ 0.1111111111111111 t_3)))
(*
(+
(cos (fma 0.3333333333333333 t_1 (* PI 0.6666666666666666)))
(cos (* (/ 1.0 t_3) (fma t_2 0.1111111111111111 t_0))))
0.5)))))
double code(double g, double h) {
double t_0 = ((double) M_PI) * (((double) M_PI) * 0.4444444444444444);
double t_1 = acos((g / -h));
double t_2 = pow(t_1, 2.0);
double t_3 = fma(0.3333333333333333, t_1, (((double) M_PI) * -0.6666666666666666));
return 2.0 * fma(sin((t_0 / t_3)), sin((t_2 * (0.1111111111111111 / t_3))), ((cos(fma(0.3333333333333333, t_1, (((double) M_PI) * 0.6666666666666666))) + cos(((1.0 / t_3) * fma(t_2, 0.1111111111111111, t_0)))) * 0.5));
}
function code(g, h) t_0 = Float64(pi * Float64(pi * 0.4444444444444444)) t_1 = acos(Float64(g / Float64(-h))) t_2 = t_1 ^ 2.0 t_3 = fma(0.3333333333333333, t_1, Float64(pi * -0.6666666666666666)) return Float64(2.0 * fma(sin(Float64(t_0 / t_3)), sin(Float64(t_2 * Float64(0.1111111111111111 / t_3))), Float64(Float64(cos(fma(0.3333333333333333, t_1, Float64(pi * 0.6666666666666666))) + cos(Float64(Float64(1.0 / t_3) * fma(t_2, 0.1111111111111111, t_0)))) * 0.5))) end
code[g_, h_] := Block[{t$95$0 = N[(Pi * N[(Pi * 0.4444444444444444), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[ArcCos[N[(g / (-h)), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[t$95$1, 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(0.3333333333333333 * t$95$1 + N[(Pi * -0.6666666666666666), $MachinePrecision]), $MachinePrecision]}, N[(2.0 * N[(N[Sin[N[(t$95$0 / t$95$3), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(t$95$2 * N[(0.1111111111111111 / t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] + N[(N[(N[Cos[N[(0.3333333333333333 * t$95$1 + N[(Pi * 0.6666666666666666), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(N[(1.0 / t$95$3), $MachinePrecision] * N[(t$95$2 * 0.1111111111111111 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \pi \cdot \left(\pi \cdot 0.4444444444444444\right)\\
t_1 := \cos^{-1} \left(\frac{g}{-h}\right)\\
t_2 := {t\_1}^{2}\\
t_3 := \mathsf{fma}\left(0.3333333333333333, t\_1, \pi \cdot -0.6666666666666666\right)\\
2 \cdot \mathsf{fma}\left(\sin \left(\frac{t\_0}{t\_3}\right), \sin \left(t\_2 \cdot \frac{0.1111111111111111}{t\_3}\right), \left(\cos \left(\mathsf{fma}\left(0.3333333333333333, t\_1, \pi \cdot 0.6666666666666666\right)\right) + \cos \left(\frac{1}{t\_3} \cdot \mathsf{fma}\left(t\_2, 0.1111111111111111, t\_0\right)\right)\right) \cdot 0.5\right)
\end{array}
\end{array}
Initial program 98.5%
lift-+.f64N/A
lift-/.f64N/A
div-invN/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-fma.f64N/A
metadata-evalN/A
metadata-eval98.5
lift-/.f64N/A
div-invN/A
lower-*.f64N/A
lift-/.f64N/A
frac-2negN/A
lift-neg.f64N/A
remove-double-negN/A
lower-/.f64N/A
lower-neg.f64N/A
metadata-eval98.5
Applied rewrites98.5%
lift-cos.f64N/A
lift-fma.f64N/A
lift-*.f64N/A
+-commutativeN/A
flip-+N/A
unpow2N/A
lift-pow.f64N/A
div-subN/A
Applied rewrites98.4%
lift-fma.f64N/A
+-commutativeN/A
Applied rewrites100.0%
Final simplification100.0%
(FPCore (g h) :precision binary64 (let* ((t_0 (* 0.3333333333333333 (acos (/ g (- h)))))) (- (fma (sin t_0) (sqrt 3.0) (cos t_0)))))
double code(double g, double h) {
double t_0 = 0.3333333333333333 * acos((g / -h));
return -fma(sin(t_0), sqrt(3.0), cos(t_0));
}
function code(g, h) t_0 = Float64(0.3333333333333333 * acos(Float64(g / Float64(-h)))) return Float64(-fma(sin(t_0), sqrt(3.0), cos(t_0))) end
code[g_, h_] := Block[{t$95$0 = N[(0.3333333333333333 * N[ArcCos[N[(g / (-h)), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, (-N[(N[Sin[t$95$0], $MachinePrecision] * N[Sqrt[3.0], $MachinePrecision] + N[Cos[t$95$0], $MachinePrecision]), $MachinePrecision])]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := 0.3333333333333333 \cdot \cos^{-1} \left(\frac{g}{-h}\right)\\
-\mathsf{fma}\left(\sin t\_0, \sqrt{3}, \cos t\_0\right)
\end{array}
\end{array}
Initial program 98.5%
lift-cos.f64N/A
lift-+.f64N/A
cos-sumN/A
sub-negN/A
lower-fma.f64N/A
Applied rewrites98.4%
Taylor expanded in g around 0
+-commutativeN/A
distribute-lft-inN/A
Applied rewrites100.0%
(FPCore (g h) :precision binary64 (* 2.0 (cos (fma PI 0.6666666666666666 (* 0.3333333333333333 (acos (/ g (- h))))))))
double code(double g, double h) {
return 2.0 * cos(fma(((double) M_PI), 0.6666666666666666, (0.3333333333333333 * acos((g / -h)))));
}
function code(g, h) return Float64(2.0 * cos(fma(pi, 0.6666666666666666, Float64(0.3333333333333333 * acos(Float64(g / Float64(-h))))))) end
code[g_, h_] := N[(2.0 * N[Cos[N[(Pi * 0.6666666666666666 + N[(0.3333333333333333 * N[ArcCos[N[(g / (-h)), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
2 \cdot \cos \left(\mathsf{fma}\left(\pi, 0.6666666666666666, 0.3333333333333333 \cdot \cos^{-1} \left(\frac{g}{-h}\right)\right)\right)
\end{array}
Initial program 98.5%
lift-+.f64N/A
lift-/.f64N/A
div-invN/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-fma.f64N/A
metadata-evalN/A
metadata-eval98.5
lift-/.f64N/A
div-invN/A
lower-*.f64N/A
lift-/.f64N/A
frac-2negN/A
lift-neg.f64N/A
remove-double-negN/A
lower-/.f64N/A
lower-neg.f64N/A
metadata-eval98.5
Applied rewrites98.5%
Final simplification98.5%
herbie shell --seed 2024231
(FPCore (g h)
:name "2-ancestry mixing, negative discriminant"
:precision binary64
(* 2.0 (cos (+ (/ (* 2.0 PI) 3.0) (/ (acos (/ (- g) h)) 3.0)))))