?

Average Error: 0.02% → 0.02%
Time: 9.0s
Precision: binary64
Cost: 7360

?

\[x - \frac{2.30753 + x \cdot 0.27061}{1 + \left(0.99229 + x \cdot 0.04481\right) \cdot x} \]
\[x + \frac{-2.30753 + x \cdot -0.27061}{\mathsf{fma}\left(x, x \cdot 0.04481 + 0.99229, 1\right)} \]
(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)}

Error?

Derivation?

  1. Initial program 0.02

    \[x - \frac{2.30753 + x \cdot 0.27061}{1 + \left(0.99229 + x \cdot 0.04481\right) \cdot x} \]
  2. Simplified0.02

    \[\leadsto \color{blue}{x - \frac{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}{\mathsf{fma}\left(x, \mathsf{fma}\left(x, 0.04481, 0.99229\right), 1\right)}} \]
    Proof

    [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

    \[ x - \frac{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}{\mathsf{fma}\left(x, \color{blue}{\mathsf{fma}\left(x, 0.04481, 0.99229\right)}, 1\right)} \]
  3. Applied egg-rr0.02

    \[\leadsto x - \frac{\mathsf{fma}\left(x, 0.27061, 2.30753\right)}{\mathsf{fma}\left(x, \color{blue}{x \cdot 0.04481 + 0.99229}, 1\right)} \]
  4. Applied egg-rr0.02

    \[\leadsto x - \frac{\color{blue}{x \cdot 0.27061 + 2.30753}}{\mathsf{fma}\left(x, x \cdot 0.04481 + 0.99229, 1\right)} \]
  5. Final simplification0.02

    \[\leadsto x + \frac{-2.30753 + x \cdot -0.27061}{\mathsf{fma}\left(x, x \cdot 0.04481 + 0.99229, 1\right)} \]

Alternatives

Alternative 1
Error0.02%
Cost1088
\[x + \frac{-2.30753 + x \cdot -0.27061}{1 + x \cdot \left(x \cdot 0.04481 + 0.99229\right)} \]
Alternative 2
Error1.16%
Cost832
\[x + \frac{-2.30753 + x \cdot -0.27061}{1 + x \cdot 0.99229} \]
Alternative 3
Error1.49%
Cost328
\[\begin{array}{l} \mathbf{if}\;x \leq -3.6:\\ \;\;\;\;x\\ \mathbf{elif}\;x \leq 1.2:\\ \;\;\;\;-2.30753\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]
Alternative 4
Error1.9%
Cost192
\[x + -2.30753 \]
Alternative 5
Error48.87%
Cost64
\[-2.30753 \]

Error

Reproduce?

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)))))