\[\frac{x - y}{2 - \left(x + y\right)}
\]
↓
\[\frac{x - y}{2 - \left(x + y\right)}
\]
(FPCore (x y) :precision binary64 (/ (- x y) (- 2.0 (+ x y))))
↓
(FPCore (x y) :precision binary64 (/ (- x y) (- 2.0 (+ x y))))
double code(double x, double y) {
return (x - y) / (2.0 - (x + y));
}
↓
double code(double x, double y) {
return (x - y) / (2.0 - (x + y));
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (x - y) / (2.0d0 - (x + y))
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (x - y) / (2.0d0 - (x + y))
end function
public static double code(double x, double y) {
return (x - y) / (2.0 - (x + y));
}
↓
public static double code(double x, double y) {
return (x - y) / (2.0 - (x + y));
}
def code(x, y):
return (x - y) / (2.0 - (x + y))
↓
def code(x, y):
return (x - y) / (2.0 - (x + y))
function code(x, y)
return Float64(Float64(x - y) / Float64(2.0 - Float64(x + y)))
end
↓
function code(x, y)
return Float64(Float64(x - y) / Float64(2.0 - Float64(x + y)))
end
function tmp = code(x, y)
tmp = (x - y) / (2.0 - (x + y));
end
↓
function tmp = code(x, y)
tmp = (x - y) / (2.0 - (x + y));
end
code[x_, y_] := N[(N[(x - y), $MachinePrecision] / N[(2.0 - N[(x + y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_] := N[(N[(x - y), $MachinePrecision] / N[(2.0 - N[(x + y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{x - y}{2 - \left(x + y\right)}
↓
\frac{x - y}{2 - \left(x + y\right)}
Alternatives
| Alternative 1 |
|---|
| Error | 40.43% |
|---|
| Cost | 1252 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -2:\\
\;\;\;\;-1\\
\mathbf{elif}\;x \leq -3.2 \cdot 10^{-40}:\\
\;\;\;\;x \cdot 0.5\\
\mathbf{elif}\;x \leq -1.16 \cdot 10^{-119}:\\
\;\;\;\;1\\
\mathbf{elif}\;x \leq -1.18 \cdot 10^{-209}:\\
\;\;\;\;x \cdot 0.5\\
\mathbf{elif}\;x \leq -1.5 \cdot 10^{-276}:\\
\;\;\;\;1\\
\mathbf{elif}\;x \leq -1.9 \cdot 10^{-302}:\\
\;\;\;\;y \cdot -0.5\\
\mathbf{elif}\;x \leq 5.2 \cdot 10^{-84}:\\
\;\;\;\;1\\
\mathbf{elif}\;x \leq 4.6 \cdot 10^{-7}:\\
\;\;\;\;x \cdot 0.5\\
\mathbf{elif}\;x \leq 2.8 \cdot 10^{+70}:\\
\;\;\;\;1\\
\mathbf{else}:\\
\;\;\;\;-1\\
\end{array}
\]
| Alternative 2 |
|---|
| Error | 27.77% |
|---|
| Cost | 848 |
|---|
\[\begin{array}{l}
t_0 := \frac{x}{2 - x}\\
\mathbf{if}\;y \leq -500000000:\\
\;\;\;\;1\\
\mathbf{elif}\;y \leq 7 \cdot 10^{-80}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;y \leq 4.1 \cdot 10^{-25}:\\
\;\;\;\;y \cdot -0.5\\
\mathbf{elif}\;y \leq 6 \cdot 10^{+119}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}
\]
| Alternative 3 |
|---|
| Error | 26.33% |
|---|
| Cost | 848 |
|---|
\[\begin{array}{l}
t_0 := \frac{x}{2 - x}\\
t_1 := \frac{y}{y + -2}\\
\mathbf{if}\;x \leq -8.5 \cdot 10^{-38}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;x \leq 5.1 \cdot 10^{-77}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 1.7 \cdot 10^{+35}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;x \leq 2.8 \cdot 10^{+70}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;-1\\
\end{array}
\]
| Alternative 4 |
|---|
| Error | 37.69% |
|---|
| Cost | 592 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -740000000000:\\
\;\;\;\;-1\\
\mathbf{elif}\;x \leq -6 \cdot 10^{-274}:\\
\;\;\;\;1\\
\mathbf{elif}\;x \leq -6.2 \cdot 10^{-303}:\\
\;\;\;\;y \cdot -0.5\\
\mathbf{elif}\;x \leq 2.9 \cdot 10^{+70}:\\
\;\;\;\;1\\
\mathbf{else}:\\
\;\;\;\;-1\\
\end{array}
\]
| Alternative 5 |
|---|
| Error | 37.67% |
|---|
| Cost | 328 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -650000000000:\\
\;\;\;\;-1\\
\mathbf{elif}\;x \leq 3 \cdot 10^{+70}:\\
\;\;\;\;1\\
\mathbf{else}:\\
\;\;\;\;-1\\
\end{array}
\]
| Alternative 6 |
|---|
| Error | 61.78% |
|---|
| Cost | 64 |
|---|
\[-1
\]