?

Average Error: 1.0 → 1.0
Time: 4.9s
Precision: binary64
Cost: 19904

?

\[2 \cdot \cos \left(\frac{2 \cdot \pi}{3} + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right) \]
↓
\[2 \cdot \cos \left(\pi \cdot 0.6666666666666666 + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right) \]
(FPCore (g h)
 :precision binary64
 (* 2.0 (cos (+ (/ (* 2.0 PI) 3.0) (/ (acos (/ (- g) h)) 3.0)))))
↓
(FPCore (g h)
 :precision binary64
 (* 2.0 (cos (+ (* PI 0.6666666666666666) (/ (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)));
}
↓
double code(double g, double h) {
	return 2.0 * cos(((((double) M_PI) * 0.6666666666666666) + (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)));
}
↓
public static double code(double g, double h) {
	return 2.0 * Math.cos(((Math.PI * 0.6666666666666666) + (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)))
↓
def code(g, h):
	return 2.0 * math.cos(((math.pi * 0.6666666666666666) + (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 code(g, h)
	return Float64(2.0 * cos(Float64(Float64(pi * 0.6666666666666666) + 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
↓
function tmp = code(g, h)
	tmp = 2.0 * cos(((pi * 0.6666666666666666) + (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]
↓
code[g_, h_] := N[(2.0 * N[Cos[N[(N[(Pi * 0.6666666666666666), $MachinePrecision] + N[(N[ArcCos[N[((-g) / h), $MachinePrecision]], $MachinePrecision] / 3.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

2 \cdot \cos \left(\frac{2 \cdot \pi}{3} + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right)
↓
2 \cdot \cos \left(\pi \cdot 0.6666666666666666 + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right)

Error?

Try it out?

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation?

  1. Initial program 1.0

    \[2 \cdot \cos \left(\frac{2 \cdot \pi}{3} + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right) \]

  2. Simplified1.0

    \[\leadsto \color{blue}{2 \cdot \cos \left(\pi \cdot 0.6666666666666666 + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right)} \]
    Proof

    [Start]1.0

    \[ 2 \cdot \cos \left(\frac{2 \cdot \pi}{3} + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right) \]

    rational.json-simplify-49 [=>]1.0

    \[ 2 \cdot \cos \left(\color{blue}{\pi \cdot \frac{2}{3}} + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right) \]

    metadata-eval [=>]1.0

    \[ 2 \cdot \cos \left(\pi \cdot \color{blue}{0.6666666666666666} + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right) \]

  3. Final simplification1.0

    \[\leadsto 2 \cdot \cos \left(\pi \cdot 0.6666666666666666 + \frac{\cos^{-1} \left(\frac{-g}{h}\right)}{3}\right) \]

Reproduce?

herbie shell --seed 2023064 
(FPCore (g h)
  :name "2-ancestry mixing, negative discriminant"
  :precision binary64
  (* 2.0 (cos (+ (/ (* 2.0 PI) 3.0) (/ (acos (/ (- g) h)) 3.0)))))