\[\frac{x \cdot 100}{x + y}
\]
↓
\[\frac{x}{\frac{x + y}{100}}
\]
(FPCore (x y) :precision binary64 (/ (* x 100.0) (+ x y)))
↓
(FPCore (x y) :precision binary64 (/ x (/ (+ x y) 100.0)))
double code(double x, double y) {
return (x * 100.0) / (x + y);
}
↓
double code(double x, double y) {
return x / ((x + y) / 100.0);
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = (x * 100.0d0) / (x + y)
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = x / ((x + y) / 100.0d0)
end function
public static double code(double x, double y) {
return (x * 100.0) / (x + y);
}
↓
public static double code(double x, double y) {
return x / ((x + y) / 100.0);
}
def code(x, y):
return (x * 100.0) / (x + y)
↓
def code(x, y):
return x / ((x + y) / 100.0)
function code(x, y)
return Float64(Float64(x * 100.0) / Float64(x + y))
end
↓
function code(x, y)
return Float64(x / Float64(Float64(x + y) / 100.0))
end
function tmp = code(x, y)
tmp = (x * 100.0) / (x + y);
end
↓
function tmp = code(x, y)
tmp = x / ((x + y) / 100.0);
end
code[x_, y_] := N[(N[(x * 100.0), $MachinePrecision] / N[(x + y), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_] := N[(x / N[(N[(x + y), $MachinePrecision] / 100.0), $MachinePrecision]), $MachinePrecision]
\frac{x \cdot 100}{x + y}
↓
\frac{x}{\frac{x + y}{100}}
Alternatives
| Alternative 1 |
|---|
| Accuracy | 73.4% |
|---|
| Cost | 1114 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -6.6 \cdot 10^{+22}:\\
\;\;\;\;100\\
\mathbf{elif}\;x \leq -3.05 \cdot 10^{-12} \lor \neg \left(x \leq -1.6 \cdot 10^{-38}\right) \land \left(x \leq 3.4 \cdot 10^{-193} \lor \neg \left(x \leq 9.5 \cdot 10^{-181}\right) \land x \leq 1.3 \cdot 10^{+34}\right):\\
\;\;\;\;100 \cdot \frac{x}{y}\\
\mathbf{else}:\\
\;\;\;\;100\\
\end{array}
\]
| Alternative 2 |
|---|
| Accuracy | 73.5% |
|---|
| Cost | 1114 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -3.3 \cdot 10^{+15}:\\
\;\;\;\;100\\
\mathbf{elif}\;x \leq -1.46 \cdot 10^{-12} \lor \neg \left(x \leq -2.2 \cdot 10^{-38}\right) \land \left(x \leq 3.4 \cdot 10^{-193} \lor \neg \left(x \leq 9.5 \cdot 10^{-181}\right) \land x \leq 1.95 \cdot 10^{+33}\right):\\
\;\;\;\;x \cdot \frac{100}{y}\\
\mathbf{else}:\\
\;\;\;\;100\\
\end{array}
\]
| Alternative 3 |
|---|
| Accuracy | 73.5% |
|---|
| Cost | 1113 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -3.55 \cdot 10^{+16}:\\
\;\;\;\;100\\
\mathbf{elif}\;x \leq -2.1 \cdot 10^{-11}:\\
\;\;\;\;x \cdot \frac{100}{y}\\
\mathbf{elif}\;x \leq -8.5 \cdot 10^{-39}:\\
\;\;\;\;100\\
\mathbf{elif}\;x \leq 3.4 \cdot 10^{-193} \lor \neg \left(x \leq 9.5 \cdot 10^{-181}\right) \land x \leq 2 \cdot 10^{+33}:\\
\;\;\;\;\frac{x}{y \cdot 0.01}\\
\mathbf{else}:\\
\;\;\;\;100\\
\end{array}
\]
| Alternative 4 |
|---|
| Accuracy | 73.4% |
|---|
| Cost | 1112 |
|---|
\[\begin{array}{l}
\mathbf{if}\;x \leq -3.8 \cdot 10^{+18}:\\
\;\;\;\;100\\
\mathbf{elif}\;x \leq -1.15 \cdot 10^{-11}:\\
\;\;\;\;x \cdot \frac{100}{y}\\
\mathbf{elif}\;x \leq -5.2 \cdot 10^{-39}:\\
\;\;\;\;100\\
\mathbf{elif}\;x \leq 3.4 \cdot 10^{-193}:\\
\;\;\;\;\frac{x}{y \cdot 0.01}\\
\mathbf{elif}\;x \leq 9.5 \cdot 10^{-181}:\\
\;\;\;\;100\\
\mathbf{elif}\;x \leq 1.8 \cdot 10^{+33}:\\
\;\;\;\;\frac{x \cdot 100}{y}\\
\mathbf{else}:\\
\;\;\;\;100\\
\end{array}
\]
| Alternative 5 |
|---|
| Accuracy | 99.7% |
|---|
| Cost | 448 |
|---|
\[x \cdot \frac{100}{x + y}
\]
| Alternative 6 |
|---|
| Accuracy | 50.1% |
|---|
| Cost | 64 |
|---|
\[100
\]