Average Error: 0.0 → 0.0
Time: 5.8s
Precision: binary64
Cost: 13504
\[2 \cdot \tan^{-1} \left(\sqrt{\frac{1 - x}{1 + x}}\right) \]
\[2 \cdot \tan^{-1} \left(\sqrt{\frac{1}{1 + x} \cdot \left(1 - x\right)}\right) \]
(FPCore (x) :precision binary64 (* 2.0 (atan (sqrt (/ (- 1.0 x) (+ 1.0 x))))))
(FPCore (x)
 :precision binary64
 (* 2.0 (atan (sqrt (* (/ 1.0 (+ 1.0 x)) (- 1.0 x))))))
double code(double x) {
	return 2.0 * atan(sqrt(((1.0 - x) / (1.0 + x))));
}
double code(double x) {
	return 2.0 * atan(sqrt(((1.0 / (1.0 + x)) * (1.0 - x))));
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = 2.0d0 * atan(sqrt(((1.0d0 - x) / (1.0d0 + x))))
end function
real(8) function code(x)
    real(8), intent (in) :: x
    code = 2.0d0 * atan(sqrt(((1.0d0 / (1.0d0 + x)) * (1.0d0 - x))))
end function
public static double code(double x) {
	return 2.0 * Math.atan(Math.sqrt(((1.0 - x) / (1.0 + x))));
}
public static double code(double x) {
	return 2.0 * Math.atan(Math.sqrt(((1.0 / (1.0 + x)) * (1.0 - x))));
}
def code(x):
	return 2.0 * math.atan(math.sqrt(((1.0 - x) / (1.0 + x))))
def code(x):
	return 2.0 * math.atan(math.sqrt(((1.0 / (1.0 + x)) * (1.0 - x))))
function code(x)
	return Float64(2.0 * atan(sqrt(Float64(Float64(1.0 - x) / Float64(1.0 + x)))))
end
function code(x)
	return Float64(2.0 * atan(sqrt(Float64(Float64(1.0 / Float64(1.0 + x)) * Float64(1.0 - x)))))
end
function tmp = code(x)
	tmp = 2.0 * atan(sqrt(((1.0 - x) / (1.0 + x))));
end
function tmp = code(x)
	tmp = 2.0 * atan(sqrt(((1.0 / (1.0 + x)) * (1.0 - x))));
end
code[x_] := N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(1.0 - x), $MachinePrecision] / N[(1.0 + x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
code[x_] := N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(1.0 / N[(1.0 + x), $MachinePrecision]), $MachinePrecision] * N[(1.0 - x), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
2 \cdot \tan^{-1} \left(\sqrt{\frac{1 - x}{1 + x}}\right)
2 \cdot \tan^{-1} \left(\sqrt{\frac{1}{1 + x} \cdot \left(1 - x\right)}\right)

Error

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[2 \cdot \tan^{-1} \left(\sqrt{\frac{1 - x}{1 + x}}\right) \]
  2. Simplified0.0

    \[\leadsto \color{blue}{2 \cdot \tan^{-1} \left(\sqrt{\frac{1 - x}{x - -1}}\right)} \]
    Proof
    (*.f64 2 (atan.f64 (sqrt.f64 (/.f64 (-.f64 1 x) (-.f64 x -1))))): 0 points increase in error, 0 points decrease in error
    (*.f64 2 (atan.f64 (sqrt.f64 (/.f64 (-.f64 1 x) (Rewrite=> sub-neg_binary64 (+.f64 x (neg.f64 -1))))))): 0 points increase in error, 0 points decrease in error
    (*.f64 2 (atan.f64 (sqrt.f64 (/.f64 (-.f64 1 x) (+.f64 x (Rewrite=> metadata-eval 1)))))): 0 points increase in error, 0 points decrease in error
    (*.f64 2 (atan.f64 (sqrt.f64 (/.f64 (-.f64 1 x) (Rewrite<= +-commutative_binary64 (+.f64 1 x)))))): 0 points increase in error, 0 points decrease in error
  3. Applied egg-rr0.0

    \[\leadsto 2 \cdot \tan^{-1} \left(\sqrt{\color{blue}{\frac{1}{1 + x} \cdot \left(1 - x\right)}}\right) \]
  4. Final simplification0.0

    \[\leadsto 2 \cdot \tan^{-1} \left(\sqrt{\frac{1}{1 + x} \cdot \left(1 - x\right)}\right) \]

Alternatives

Alternative 1
Error0.0
Cost13376
\[2 \cdot \tan^{-1} \left(\sqrt{\frac{1 - x}{1 + x}}\right) \]
Alternative 2
Error0.3
Cost7360
\[2 \cdot \tan^{-1} \left(\left(1 - x\right) + \left(x \cdot x\right) \cdot \left(0.5 + x \cdot -0.5\right)\right) \]
Alternative 3
Error0.4
Cost7104
\[2 \cdot \tan^{-1} \left(\left(1 - x\right) + x \cdot \left(x \cdot 0.5\right)\right) \]
Alternative 4
Error0.6
Cost6848
\[2 \cdot \tan^{-1} \left(\frac{1}{1 + x}\right) \]
Alternative 5
Error0.6
Cost6720
\[2 \cdot \tan^{-1} \left(1 - x\right) \]
Alternative 6
Error1.3
Cost6592
\[2 \cdot \tan^{-1} 1 \]

Error

Reproduce

herbie shell --seed 2022313 
(FPCore (x)
  :name "arccos"
  :precision binary64
  (* 2.0 (atan (sqrt (/ (- 1.0 x) (+ 1.0 x))))))