Average Error: 1.0 → 0.0
Time: 18.3s
Precision: binary64
Cost: 26368
\[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
\[\frac{\frac{\frac{-1.3333333333333333}{\mathsf{fma}\left(v, v, -1\right)}}{\sqrt{\mathsf{fma}\left(v \cdot v, -6, 2\right)}}}{\pi} \]
(FPCore (v)
 :precision binary64
 (/ 4.0 (* (* (* 3.0 PI) (- 1.0 (* v v))) (sqrt (- 2.0 (* 6.0 (* v v)))))))
(FPCore (v)
 :precision binary64
 (/
  (/ (/ -1.3333333333333333 (fma v v -1.0)) (sqrt (fma (* v v) -6.0 2.0)))
  PI))
double code(double v) {
	return 4.0 / (((3.0 * ((double) M_PI)) * (1.0 - (v * v))) * sqrt((2.0 - (6.0 * (v * v)))));
}
double code(double v) {
	return ((-1.3333333333333333 / fma(v, v, -1.0)) / sqrt(fma((v * v), -6.0, 2.0))) / ((double) M_PI);
}
function code(v)
	return Float64(4.0 / Float64(Float64(Float64(3.0 * pi) * Float64(1.0 - Float64(v * v))) * sqrt(Float64(2.0 - Float64(6.0 * Float64(v * v))))))
end
function code(v)
	return Float64(Float64(Float64(-1.3333333333333333 / fma(v, v, -1.0)) / sqrt(fma(Float64(v * v), -6.0, 2.0))) / pi)
end
code[v_] := N[(4.0 / N[(N[(N[(3.0 * Pi), $MachinePrecision] * N[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[Sqrt[N[(2.0 - N[(6.0 * N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[v_] := N[(N[(N[(-1.3333333333333333 / N[(v * v + -1.0), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(N[(v * v), $MachinePrecision] * -6.0 + 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / Pi), $MachinePrecision]
\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}}
\frac{\frac{\frac{-1.3333333333333333}{\mathsf{fma}\left(v, v, -1\right)}}{\sqrt{\mathsf{fma}\left(v \cdot v, -6, 2\right)}}}{\pi}

Error

Derivation

  1. Initial program 1.0

    \[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]
  2. Simplified0.0

    \[\leadsto \color{blue}{\frac{1.3333333333333333}{\left(\pi \cdot \left(-\mathsf{fma}\left(v, v, -1\right)\right)\right) \cdot \sqrt{\mathsf{fma}\left(v \cdot v, -6, 2\right)}}} \]
    Proof
  3. Applied egg-rr0.0

    \[\leadsto \color{blue}{\frac{\frac{\frac{-1.3333333333333333}{\mathsf{fma}\left(v, v, -1\right)}}{\sqrt{\mathsf{fma}\left(v \cdot v, -6, 2\right)}}}{\pi}} \]

Alternatives

Alternative 1
Error0.0
Cost20160
\[\frac{1.3333333333333333}{\left(\left(-v \cdot v\right) + 1\right) \cdot \left(\sqrt{\mathsf{fma}\left(v \cdot v, -6, 2\right)} \cdot \pi\right)} \]
Alternative 2
Error0.6
Cost19712
\[\frac{\frac{1.3333333333333333}{\sqrt{\mathsf{fma}\left(v \cdot v, -6, 2\right)}}}{\pi} \]
Alternative 3
Error1.0
Cost13952
\[\frac{4}{\left(\left(3 \cdot \pi\right) \cdot \left(1 - v \cdot v\right)\right) \cdot \sqrt{2 - 6 \cdot \left(v \cdot v\right)}} \]

Error

Reproduce

herbie shell --seed 2023010 
(FPCore (v)
  :name "Falkner and Boettcher, Equation (22+)"
  :precision binary64
  (/ 4.0 (* (* (* 3.0 PI) (- 1.0 (* v v))) (sqrt (- 2.0 (* 6.0 (* v v)))))))