| Alternative 1 | |
|---|---|
| Error | 0.02% |
| Cost | 1088 |
\[x + \frac{-2.30753 + x \cdot -0.27061}{1 + x \cdot \left(x \cdot 0.04481 + 0.99229\right)}
\]
(FPCore (x) :precision binary64 (- x (/ (+ 2.30753 (* x 0.27061)) (+ 1.0 (* (+ 0.99229 (* x 0.04481)) x)))))
(FPCore (x) :precision binary64 (+ x (/ (+ -2.30753 (* x -0.27061)) (fma x (+ (* x 0.04481) 0.99229) 1.0))))
double code(double x) {
return x - ((2.30753 + (x * 0.27061)) / (1.0 + ((0.99229 + (x * 0.04481)) * x)));
}
double code(double x) {
return x + ((-2.30753 + (x * -0.27061)) / fma(x, ((x * 0.04481) + 0.99229), 1.0));
}
function code(x) return Float64(x - Float64(Float64(2.30753 + Float64(x * 0.27061)) / Float64(1.0 + Float64(Float64(0.99229 + Float64(x * 0.04481)) * x)))) end
function code(x) return Float64(x + Float64(Float64(-2.30753 + Float64(x * -0.27061)) / fma(x, Float64(Float64(x * 0.04481) + 0.99229), 1.0))) end
code[x_] := N[(x - N[(N[(2.30753 + N[(x * 0.27061), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[(0.99229 + N[(x * 0.04481), $MachinePrecision]), $MachinePrecision] * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_] := N[(x + N[(N[(-2.30753 + N[(x * -0.27061), $MachinePrecision]), $MachinePrecision] / N[(x * N[(N[(x * 0.04481), $MachinePrecision] + 0.99229), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
x - \frac{2.30753 + x \cdot 0.27061}{1 + \left(0.99229 + x \cdot 0.04481\right) \cdot x}
x + \frac{-2.30753 + x \cdot -0.27061}{\mathsf{fma}\left(x, x \cdot 0.04481 + 0.99229, 1\right)}
Initial program 0.02
Simplified0.02
[Start]0.02 | \[ x - \frac{2.30753 + x \cdot 0.27061}{1 + \left(0.99229 + x \cdot 0.04481\right) \cdot x}
\] |
|---|---|
+-commutative [=>]0.02 | \[ x - \frac{\color{blue}{x \cdot 0.27061 + 2.30753}}{1 + \left(0.99229 + x \cdot 0.04481\right) \cdot x}
\] |
fma-def [=>]0.02 | \[ x - \frac{\color{blue}{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}}{1 + \left(0.99229 + x \cdot 0.04481\right) \cdot x}
\] |
+-commutative [=>]0.02 | \[ x - \frac{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}{\color{blue}{\left(0.99229 + x \cdot 0.04481\right) \cdot x + 1}}
\] |
*-commutative [=>]0.02 | \[ x - \frac{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}{\color{blue}{x \cdot \left(0.99229 + x \cdot 0.04481\right)} + 1}
\] |
fma-def [=>]0.02 | \[ x - \frac{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}{\color{blue}{\mathsf{fma}\left(x, 0.99229 + x \cdot 0.04481, 1\right)}}
\] |
+-commutative [=>]0.02 | \[ x - \frac{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}{\mathsf{fma}\left(x, \color{blue}{x \cdot 0.04481 + 0.99229}, 1\right)}
\] |
fma-def [=>]0.02 | \[ x - \frac{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}{\mathsf{fma}\left(x, \color{blue}{\mathsf{fma}\left(x, 0.04481, 0.99229\right)}, 1\right)}
\] |
Applied egg-rr0.02
Applied egg-rr0.02
Final simplification0.02
| Alternative 1 | |
|---|---|
| Error | 0.02% |
| Cost | 1088 |
| Alternative 2 | |
|---|---|
| Error | 1.16% |
| Cost | 832 |
| Alternative 3 | |
|---|---|
| Error | 1.49% |
| Cost | 328 |
| Alternative 4 | |
|---|---|
| Error | 1.9% |
| Cost | 192 |
| Alternative 5 | |
|---|---|
| Error | 48.87% |
| Cost | 64 |
herbie shell --seed 2023121
(FPCore (x)
:name "Numeric.SpecFunctions:invIncompleteBetaWorker from math-functions-0.1.5.2, D"
:precision binary64
(- x (/ (+ 2.30753 (* x 0.27061)) (+ 1.0 (* (+ 0.99229 (* x 0.04481)) x)))))