\[\frac{x \cdot \left(\frac{x}{y} + 1\right)}{x + 1}
\]
↓
\[\frac{x}{\frac{x + 1}{1 + \frac{x}{y}}}
\]
(FPCore (x y) :precision binary64 (/ (* x (+ (/ x y) 1.0)) (+ x 1.0)))
↓
(FPCore (x y) :precision binary64 (/ x (/ (+ x 1.0) (+ 1.0 (/ x y)))))
double code(double x, double y) {
return (x * ((x / y) + 1.0)) / (x + 1.0);
}
↓
double code(double x, double y) {
return x / ((x + 1.0) / (1.0 + (x / y)));
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (x * ((x / y) + 1.0d0)) / (x + 1.0d0)
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = x / ((x + 1.0d0) / (1.0d0 + (x / y)))
end function
public static double code(double x, double y) {
return (x * ((x / y) + 1.0)) / (x + 1.0);
}
↓
public static double code(double x, double y) {
return x / ((x + 1.0) / (1.0 + (x / y)));
}
def code(x, y):
return (x * ((x / y) + 1.0)) / (x + 1.0)
↓
def code(x, y):
return x / ((x + 1.0) / (1.0 + (x / y)))
function code(x, y)
return Float64(Float64(x * Float64(Float64(x / y) + 1.0)) / Float64(x + 1.0))
end
↓
function code(x, y)
return Float64(x / Float64(Float64(x + 1.0) / Float64(1.0 + Float64(x / y))))
end
function tmp = code(x, y)
tmp = (x * ((x / y) + 1.0)) / (x + 1.0);
end
↓
function tmp = code(x, y)
tmp = x / ((x + 1.0) / (1.0 + (x / y)));
end
code[x_, y_] := N[(N[(x * N[(N[(x / y), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision] / N[(x + 1.0), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_] := N[(x / N[(N[(x + 1.0), $MachinePrecision] / N[(1.0 + N[(x / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{x \cdot \left(\frac{x}{y} + 1\right)}{x + 1}
↓
\frac{x}{\frac{x + 1}{1 + \frac{x}{y}}}
Alternatives
| Alternative 1 |
|---|
| Accuracy | 98.1% |
|---|
| Cost | 968 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -1:\\
\;\;\;\;1 + \frac{x + -1}{y}\\
\mathbf{elif}\;x \leq 1:\\
\;\;\;\;x + x \cdot \left(x \cdot \left(-1 + \frac{1}{y}\right)\right)\\
\mathbf{else}:\\
\;\;\;\;\frac{-1}{y} + \left(1 + \frac{x}{y}\right)\\
\end{array}
\]
| Alternative 2 |
|---|
| Accuracy | 84.8% |
|---|
| Cost | 840 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -17000:\\
\;\;\;\;1 + \frac{x + -1}{y}\\
\mathbf{elif}\;x \leq 61:\\
\;\;\;\;\frac{x}{x + 1}\\
\mathbf{else}:\\
\;\;\;\;\frac{-1}{y} + \left(1 + \frac{x}{y}\right)\\
\end{array}
\]
| Alternative 3 |
|---|
| Accuracy | 84.8% |
|---|
| Cost | 713 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -29000 \lor \neg \left(x \leq 63\right):\\
\;\;\;\;1 + \frac{x + -1}{y}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{x + 1}\\
\end{array}
\]
| Alternative 4 |
|---|
| Accuracy | 70.2% |
|---|
| Cost | 588 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -2 \cdot 10^{+65}:\\
\;\;\;\;\frac{x}{y}\\
\mathbf{elif}\;x \leq -0.0075:\\
\;\;\;\;1\\
\mathbf{elif}\;x \leq 0.082:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{y}\\
\end{array}
\]
| Alternative 5 |
|---|
| Accuracy | 83.9% |
|---|
| Cost | 585 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -1 \lor \neg \left(x \leq 0.055\right):\\
\;\;\;\;1 + \frac{x}{y}\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
| Alternative 6 |
|---|
| Accuracy | 84.2% |
|---|
| Cost | 585 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -1 \lor \neg \left(x \leq 0.065\right):\\
\;\;\;\;1 + \frac{x}{y}\\
\mathbf{else}:\\
\;\;\;\;x - x \cdot x\\
\end{array}
\]
| Alternative 7 |
|---|
| Accuracy | 84.5% |
|---|
| Cost | 585 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -41000 \lor \neg \left(x \leq 0.082\right):\\
\;\;\;\;1 + \frac{x}{y}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{x + 1}\\
\end{array}
\]
| Alternative 8 |
|---|
| Accuracy | 55.7% |
|---|
| Cost | 328 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -0.0075:\\
\;\;\;\;1\\
\mathbf{elif}\;x \leq 3.5 \cdot 10^{+28}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}
\]
| Alternative 9 |
|---|
| Accuracy | 16.2% |
|---|
| Cost | 64 |
|---|
\[1
\]