?

Average Accuracy: 87.7% → 99.6%
Time: 9.6s
Precision: binary64
Cost: 6720

?

\[0.999 \leq x \land x \leq 1.001\]
\[\frac{10}{1 - x \cdot x} \]
\[\frac{-10}{\mathsf{fma}\left(x, x, -1\right)} \]
(FPCore (x) :precision binary64 (/ 10.0 (- 1.0 (* x x))))
(FPCore (x) :precision binary64 (/ -10.0 (fma x x -1.0)))
double code(double x) {
	return 10.0 / (1.0 - (x * x));
}
double code(double x) {
	return -10.0 / fma(x, x, -1.0);
}
function code(x)
	return Float64(10.0 / Float64(1.0 - Float64(x * x)))
end
function code(x)
	return Float64(-10.0 / fma(x, x, -1.0))
end
code[x_] := N[(10.0 / N[(1.0 - N[(x * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_] := N[(-10.0 / N[(x * x + -1.0), $MachinePrecision]), $MachinePrecision]
\frac{10}{1 - x \cdot x}
\frac{-10}{\mathsf{fma}\left(x, x, -1\right)}

Error?

Derivation?

  1. Initial program 87.7%

    \[\frac{10}{1 - x \cdot x} \]
  2. Simplified99.6%

    \[\leadsto \color{blue}{\frac{-10}{\mathsf{fma}\left(x, x, -1\right)}} \]
    Proof

    [Start]87.7

    \[ \frac{10}{1 - x \cdot x} \]

    sub-neg [=>]87.7

    \[ \frac{10}{\color{blue}{1 + \left(-x \cdot x\right)}} \]

    +-commutative [=>]87.7

    \[ \frac{10}{\color{blue}{\left(-x \cdot x\right) + 1}} \]

    neg-sub0 [=>]87.7

    \[ \frac{10}{\color{blue}{\left(0 - x \cdot x\right)} + 1} \]

    associate-+l- [=>]87.7

    \[ \frac{10}{\color{blue}{0 - \left(x \cdot x - 1\right)}} \]

    sub0-neg [=>]87.7

    \[ \frac{10}{\color{blue}{-\left(x \cdot x - 1\right)}} \]

    neg-mul-1 [=>]87.7

    \[ \frac{10}{\color{blue}{-1 \cdot \left(x \cdot x - 1\right)}} \]

    associate-/r* [=>]87.7

    \[ \color{blue}{\frac{\frac{10}{-1}}{x \cdot x - 1}} \]

    metadata-eval [=>]87.7

    \[ \frac{\color{blue}{-10}}{x \cdot x - 1} \]

    fma-neg [=>]99.6

    \[ \frac{-10}{\color{blue}{\mathsf{fma}\left(x, x, -1\right)}} \]

    metadata-eval [=>]99.6

    \[ \frac{-10}{\mathsf{fma}\left(x, x, \color{blue}{-1}\right)} \]
  3. Final simplification99.6%

    \[\leadsto \frac{-10}{\mathsf{fma}\left(x, x, -1\right)} \]

Alternatives

Alternative 1
Accuracy13.5%
Cost580
\[\begin{array}{l} \mathbf{if}\;x \cdot x \leq 1:\\ \;\;\;\;10\\ \mathbf{else}:\\ \;\;\;\;\frac{-10}{x \cdot x}\\ \end{array} \]
Alternative 2
Accuracy87.7%
Cost576
\[\frac{1}{1 - x \cdot x} \cdot 10 \]
Alternative 3
Accuracy99.4%
Cost576
\[\frac{-10}{\left(x + 1\right) \cdot \left(x + -1\right)} \]
Alternative 4
Accuracy87.7%
Cost448
\[\frac{10}{1 - x \cdot x} \]
Alternative 5
Accuracy18.8%
Cost320
\[\frac{-10}{x + -1} \]
Alternative 6
Accuracy9.6%
Cost64
\[10 \]

Error

Reproduce?

herbie shell --seed 2023133 
(FPCore (x)
  :name "ENA, Section 1.4, Mentioned, B"
  :precision binary64
  :pre (and (<= 0.999 x) (<= x 1.001))
  (/ 10.0 (- 1.0 (* x x))))