Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\left(3 \cdot \sqrt{x}\right) \cdot \left(\left(y + \frac{1}{x \cdot 9}\right) - 1\right)
\]
↓
\[\left(3 \cdot \sqrt{x}\right) \cdot \left(y + \left(\frac{\frac{1}{x}}{9} + -1\right)\right)
\]
(FPCore (x y)
:precision binary64
(* (* 3.0 (sqrt x)) (- (+ y (/ 1.0 (* x 9.0))) 1.0))) ↓
(FPCore (x y)
:precision binary64
(* (* 3.0 (sqrt x)) (+ y (+ (/ (/ 1.0 x) 9.0) -1.0)))) double code(double x, double y) {
return (3.0 * sqrt(x)) * ((y + (1.0 / (x * 9.0))) - 1.0);
}
↓
double code(double x, double y) {
return (3.0 * sqrt(x)) * (y + (((1.0 / x) / 9.0) + -1.0));
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (3.0d0 * sqrt(x)) * ((y + (1.0d0 / (x * 9.0d0))) - 1.0d0)
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (3.0d0 * sqrt(x)) * (y + (((1.0d0 / x) / 9.0d0) + (-1.0d0)))
end function
public static double code(double x, double y) {
return (3.0 * Math.sqrt(x)) * ((y + (1.0 / (x * 9.0))) - 1.0);
}
↓
public static double code(double x, double y) {
return (3.0 * Math.sqrt(x)) * (y + (((1.0 / x) / 9.0) + -1.0));
}
def code(x, y):
return (3.0 * math.sqrt(x)) * ((y + (1.0 / (x * 9.0))) - 1.0)
↓
def code(x, y):
return (3.0 * math.sqrt(x)) * (y + (((1.0 / x) / 9.0) + -1.0))
function code(x, y)
return Float64(Float64(3.0 * sqrt(x)) * Float64(Float64(y + Float64(1.0 / Float64(x * 9.0))) - 1.0))
end
↓
function code(x, y)
return Float64(Float64(3.0 * sqrt(x)) * Float64(y + Float64(Float64(Float64(1.0 / x) / 9.0) + -1.0)))
end
function tmp = code(x, y)
tmp = (3.0 * sqrt(x)) * ((y + (1.0 / (x * 9.0))) - 1.0);
end
↓
function tmp = code(x, y)
tmp = (3.0 * sqrt(x)) * (y + (((1.0 / x) / 9.0) + -1.0));
end
code[x_, y_] := N[(N[(3.0 * N[Sqrt[x], $MachinePrecision]), $MachinePrecision] * N[(N[(y + N[(1.0 / N[(x * 9.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_] := N[(N[(3.0 * N[Sqrt[x], $MachinePrecision]), $MachinePrecision] * N[(y + N[(N[(N[(1.0 / x), $MachinePrecision] / 9.0), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\left(3 \cdot \sqrt{x}\right) \cdot \left(\left(y + \frac{1}{x \cdot 9}\right) - 1\right)
↓
\left(3 \cdot \sqrt{x}\right) \cdot \left(y + \left(\frac{\frac{1}{x}}{9} + -1\right)\right)
Alternatives Alternative 1 Accuracy 99.4% Cost 7232
\[\left(3 \cdot \sqrt{x}\right) \cdot \left(y + \left(\frac{\frac{1}{x}}{9} + -1\right)\right)
\]
Alternative 2 Accuracy 63.0% Cost 7382
\[\begin{array}{l}
\mathbf{if}\;x \leq 4 \cdot 10^{-17}:\\
\;\;\;\;\sqrt{x} \cdot \frac{0.3333333333333333}{x}\\
\mathbf{elif}\;x \leq 3.3 \cdot 10^{+33} \lor \neg \left(x \leq 1.3 \cdot 10^{+89}\right) \land \left(x \leq 4.2 \cdot 10^{+215} \lor \neg \left(x \leq 2.9 \cdot 10^{+279}\right)\right):\\
\;\;\;\;3 \cdot \left(\sqrt{x} \cdot y\right)\\
\mathbf{else}:\\
\;\;\;\;\sqrt{x} \cdot -3\\
\end{array}
\]
Alternative 3 Accuracy 63.0% Cost 7380
\[\begin{array}{l}
t_0 := \sqrt{x} \cdot -3\\
t_1 := 3 \cdot \left(\sqrt{x} \cdot y\right)\\
\mathbf{if}\;x \leq 2.3 \cdot 10^{-17}:\\
\;\;\;\;\sqrt{x} \cdot \frac{0.3333333333333333}{x}\\
\mathbf{elif}\;x \leq 4.6 \cdot 10^{+33}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 1.7 \cdot 10^{+89}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;x \leq 8.5 \cdot 10^{+215}:\\
\;\;\;\;\sqrt{x} \cdot \left(3 \cdot y\right)\\
\mathbf{elif}\;x \leq 1.8 \cdot 10^{+280}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 4 Accuracy 63.0% Cost 7380
\[\begin{array}{l}
t_0 := \sqrt{x} \cdot -3\\
t_1 := 3 \cdot \left(\sqrt{x} \cdot y\right)\\
\mathbf{if}\;x \leq 1.2 \cdot 10^{-17}:\\
\;\;\;\;\sqrt{x} \cdot \frac{0.3333333333333333}{x}\\
\mathbf{elif}\;x \leq 3.3 \cdot 10^{+33}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 2.15 \cdot 10^{+89}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;x \leq 3.15 \cdot 10^{+215}:\\
\;\;\;\;\left(3 \cdot \sqrt{x}\right) \cdot y\\
\mathbf{elif}\;x \leq 1.15 \cdot 10^{+282}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 5 Accuracy 63.0% Cost 7380
\[\begin{array}{l}
t_0 := \sqrt{x} \cdot -3\\
t_1 := 3 \cdot \left(\sqrt{x} \cdot y\right)\\
\mathbf{if}\;x \leq 1.16 \cdot 10^{-17}:\\
\;\;\;\;\sqrt{x} \cdot \left(3 \cdot \frac{0.1111111111111111}{x}\right)\\
\mathbf{elif}\;x \leq 9.5 \cdot 10^{+33}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 1.55 \cdot 10^{+89}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;x \leq 3.5 \cdot 10^{+215}:\\
\;\;\;\;\left(3 \cdot \sqrt{x}\right) \cdot y\\
\mathbf{elif}\;x \leq 4.7 \cdot 10^{+277}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 6 Accuracy 84.6% Cost 7249
\[\begin{array}{l}
\mathbf{if}\;y \leq -2.4 \cdot 10^{+35}:\\
\;\;\;\;\left(3 \cdot \sqrt{x}\right) \cdot y\\
\mathbf{elif}\;y \leq 6.8:\\
\;\;\;\;\sqrt{x} \cdot \left(\frac{0.3333333333333333}{x} + -3\right)\\
\mathbf{elif}\;y \leq 6.6 \cdot 10^{+85} \lor \neg \left(y \leq 1.8 \cdot 10^{+131}\right):\\
\;\;\;\;\sqrt{x} \cdot \left(3 \cdot y\right)\\
\mathbf{else}:\\
\;\;\;\;\sqrt{x} \cdot \frac{0.3333333333333333}{x}\\
\end{array}
\]
Alternative 7 Accuracy 99.4% Cost 7104
\[\sqrt{x} \cdot \left(3 \cdot \left(\frac{0.1111111111111111}{x} + \left(y + -1\right)\right)\right)
\]
Alternative 8 Accuracy 99.4% Cost 7104
\[\left(3 \cdot \sqrt{x}\right) \cdot \left(\frac{0.1111111111111111}{x} + \left(y + -1\right)\right)
\]
Alternative 9 Accuracy 60.7% Cost 6985
\[\begin{array}{l}
\mathbf{if}\;y \leq -10.6 \lor \neg \left(y \leq 3 \cdot 10^{-12}\right):\\
\;\;\;\;3 \cdot \left(\sqrt{x} \cdot y\right)\\
\mathbf{else}:\\
\;\;\;\;\sqrt{x} \cdot -3\\
\end{array}
\]
Alternative 10 Accuracy 86.9% Cost 6980
\[\begin{array}{l}
\mathbf{if}\;x \leq 5.2 \cdot 10^{-18}:\\
\;\;\;\;\sqrt{x} \cdot \left(3 \cdot \frac{0.1111111111111111}{x}\right)\\
\mathbf{else}:\\
\;\;\;\;\sqrt{x} \cdot \left(3 \cdot y - 3\right)\\
\end{array}
\]
Alternative 11 Accuracy 3.3% Cost 6592
\[\sqrt{x \cdot 9}
\]
Alternative 12 Accuracy 25.7% Cost 6592
\[\sqrt{x} \cdot -3
\]