| Alternative 1 | |
|---|---|
| Error | 0.0 |
| Cost | 13824 |
\[\frac{\frac{1.3333333333333333}{\left(1 - v \cdot v\right) \cdot \pi}}{\sqrt{2 + \left(v \cdot v\right) \cdot -6}}
\]
(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 (- 1.0 (* v v))) (- PI)) (sqrt (+ 2.0 (* (* v v) -6.0)))))
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 / (1.0 - (v * v))) / -((double) M_PI)) / sqrt((2.0 + ((v * v) * -6.0)));
}
public static double code(double v) {
return 4.0 / (((3.0 * Math.PI) * (1.0 - (v * v))) * Math.sqrt((2.0 - (6.0 * (v * v)))));
}
public static double code(double v) {
return ((-1.3333333333333333 / (1.0 - (v * v))) / -Math.PI) / Math.sqrt((2.0 + ((v * v) * -6.0)));
}
def code(v): return 4.0 / (((3.0 * math.pi) * (1.0 - (v * v))) * math.sqrt((2.0 - (6.0 * (v * v)))))
def code(v): return ((-1.3333333333333333 / (1.0 - (v * v))) / -math.pi) / math.sqrt((2.0 + ((v * v) * -6.0)))
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 / Float64(1.0 - Float64(v * v))) / Float64(-pi)) / sqrt(Float64(2.0 + Float64(Float64(v * v) * -6.0)))) end
function tmp = code(v) tmp = 4.0 / (((3.0 * pi) * (1.0 - (v * v))) * sqrt((2.0 - (6.0 * (v * v))))); end
function tmp = code(v) tmp = ((-1.3333333333333333 / (1.0 - (v * v))) / -pi) / sqrt((2.0 + ((v * v) * -6.0))); 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[(1.0 - N[(v * v), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / (-Pi)), $MachinePrecision] / N[Sqrt[N[(2.0 + N[(N[(v * v), $MachinePrecision] * -6.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $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}{1 - v \cdot v}}{-\pi}}{\sqrt{2 + \left(v \cdot v\right) \cdot -6}}
Results
Initial program 1.0
Simplified0.0
Applied egg-rr0.0
Simplified0.0
Final simplification0.0
| Alternative 1 | |
|---|---|
| Error | 0.0 |
| Cost | 13824 |
| Alternative 2 | |
|---|---|
| Error | 0.6 |
| Cost | 13568 |
| Alternative 3 | |
|---|---|
| Error | 0.6 |
| Cost | 13440 |
| Alternative 4 | |
|---|---|
| Error | 1.6 |
| Cost | 13056 |
| Alternative 5 | |
|---|---|
| Error | 0.7 |
| Cost | 13056 |
herbie shell --seed 2022321
(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)))))))