\[\frac{x}{y} + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z}
\]
↓
\[\frac{x}{y} + \left(-2 + \frac{2 + \frac{2}{z}}{t}\right)
\]
(FPCore (x y z t)
:precision binary64
(+ (/ x y) (/ (+ 2.0 (* (* z 2.0) (- 1.0 t))) (* t z))))
↓
(FPCore (x y z t)
:precision binary64
(+ (/ x y) (+ -2.0 (/ (+ 2.0 (/ 2.0 z)) t))))
double code(double x, double y, double z, double t) {
return (x / y) + ((2.0 + ((z * 2.0) * (1.0 - t))) / (t * z));
}
↓
double code(double x, double y, double z, double t) {
return (x / y) + (-2.0 + ((2.0 + (2.0 / z)) / t));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = (x / y) + ((2.0d0 + ((z * 2.0d0) * (1.0d0 - t))) / (t * z))
end function
↓
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = (x / y) + ((-2.0d0) + ((2.0d0 + (2.0d0 / z)) / t))
end function
public static double code(double x, double y, double z, double t) {
return (x / y) + ((2.0 + ((z * 2.0) * (1.0 - t))) / (t * z));
}
↓
public static double code(double x, double y, double z, double t) {
return (x / y) + (-2.0 + ((2.0 + (2.0 / z)) / t));
}
def code(x, y, z, t):
return (x / y) + ((2.0 + ((z * 2.0) * (1.0 - t))) / (t * z))
↓
def code(x, y, z, t):
return (x / y) + (-2.0 + ((2.0 + (2.0 / z)) / t))
function code(x, y, z, t)
return Float64(Float64(x / y) + Float64(Float64(2.0 + Float64(Float64(z * 2.0) * Float64(1.0 - t))) / Float64(t * z)))
end
↓
function code(x, y, z, t)
return Float64(Float64(x / y) + Float64(-2.0 + Float64(Float64(2.0 + Float64(2.0 / z)) / t)))
end
function tmp = code(x, y, z, t)
tmp = (x / y) + ((2.0 + ((z * 2.0) * (1.0 - t))) / (t * z));
end
↓
function tmp = code(x, y, z, t)
tmp = (x / y) + (-2.0 + ((2.0 + (2.0 / z)) / t));
end
code[x_, y_, z_, t_] := N[(N[(x / y), $MachinePrecision] + N[(N[(2.0 + N[(N[(z * 2.0), $MachinePrecision] * N[(1.0 - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_] := N[(N[(x / y), $MachinePrecision] + N[(-2.0 + N[(N[(2.0 + N[(2.0 / z), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{x}{y} + \frac{2 + \left(z \cdot 2\right) \cdot \left(1 - t\right)}{t \cdot z}
↓
\frac{x}{y} + \left(-2 + \frac{2 + \frac{2}{z}}{t}\right)
Alternatives
| Alternative 1 |
|---|
| Error | 5.3 |
|---|
| Cost | 1096 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\frac{x}{y} \leq -5 \cdot 10^{-13}:\\
\;\;\;\;\frac{x}{y} + \left(-2 + \frac{2}{t}\right)\\
\mathbf{elif}\;\frac{x}{y} \leq 4 \cdot 10^{+34}:\\
\;\;\;\;-2 + \frac{2 + \frac{2}{z}}{t}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{y} + \frac{2}{z \cdot t}\\
\end{array}
\]
| Alternative 2 |
|---|
| Error | 19.2 |
|---|
| Cost | 976 |
|---|
\[\begin{array}{l}
t_1 := -2 + \frac{2}{z \cdot t}\\
t_2 := \frac{x}{y} + -2\\
\mathbf{if}\;t \leq -1.7 \cdot 10^{+123}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;t \leq -0.7:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq 2 \cdot 10^{-72}:\\
\;\;\;\;-2 + \frac{2}{t}\\
\mathbf{elif}\;t \leq 2 \cdot 10^{+77}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
| Alternative 3 |
|---|
| Error | 6.7 |
|---|
| Cost | 972 |
|---|
\[\begin{array}{l}
t_1 := \frac{2}{z \cdot t}\\
t_2 := \frac{x}{y} + \left(-2 + \frac{2}{t}\right)\\
\mathbf{if}\;z \leq -1.08 \cdot 10^{-32}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;z \leq 4.5 \cdot 10^{-258}:\\
\;\;\;\;\frac{x}{y} + t_1\\
\mathbf{elif}\;z \leq 2.4 \cdot 10^{-7}:\\
\;\;\;\;-2 + t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
| Alternative 4 |
|---|
| Error | 0.7 |
|---|
| Cost | 969 |
|---|
\[\begin{array}{l}
\mathbf{if}\;z \leq -21.5 \lor \neg \left(z \leq 4.4 \cdot 10^{-7}\right):\\
\;\;\;\;\frac{x}{y} + \left(-2 + \frac{2}{t}\right)\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{y} + \left(-2 + \frac{2}{z \cdot t}\right)\\
\end{array}
\]
| Alternative 5 |
|---|
| Error | 13.0 |
|---|
| Cost | 844 |
|---|
\[\begin{array}{l}
t_1 := \frac{x}{y} + -2\\
\mathbf{if}\;t \leq -4.9 \cdot 10^{+125}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq -120000000:\\
\;\;\;\;-2 + \frac{2}{z \cdot t}\\
\mathbf{elif}\;t \leq 2.1 \cdot 10^{+65}:\\
\;\;\;\;\frac{2 + \frac{2}{z}}{t}\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
| Alternative 6 |
|---|
| Error | 20.1 |
|---|
| Cost | 841 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\frac{x}{y} \leq -20000000000 \lor \neg \left(\frac{x}{y} \leq 4 \cdot 10^{+34}\right):\\
\;\;\;\;\frac{x}{y}\\
\mathbf{else}:\\
\;\;\;\;-2 + \frac{2}{t}\\
\end{array}
\]
| Alternative 7 |
|---|
| Error | 8.7 |
|---|
| Cost | 841 |
|---|
\[\begin{array}{l}
\mathbf{if}\;z \leq -2.7 \cdot 10^{-153} \lor \neg \left(z \leq 1.6 \cdot 10^{-7}\right):\\
\;\;\;\;\frac{x}{y} + \left(-2 + \frac{2}{t}\right)\\
\mathbf{else}:\\
\;\;\;\;-2 + \frac{2}{z \cdot t}\\
\end{array}
\]
| Alternative 8 |
|---|
| Error | 20.1 |
|---|
| Cost | 840 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\frac{x}{y} \leq -20000000000:\\
\;\;\;\;\frac{x}{y} + -2\\
\mathbf{elif}\;\frac{x}{y} \leq 4 \cdot 10^{+34}:\\
\;\;\;\;-2 + \frac{2}{t}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{y}\\
\end{array}
\]
| Alternative 9 |
|---|
| Error | 20.5 |
|---|
| Cost | 716 |
|---|
\[\begin{array}{l}
t_1 := \frac{x}{y} + -2\\
\mathbf{if}\;t \leq -0.38:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq 4.2 \cdot 10^{-77}:\\
\;\;\;\;-2 + \frac{2}{t}\\
\mathbf{elif}\;t \leq 2.2 \cdot 10^{+65}:\\
\;\;\;\;\frac{2}{z \cdot t}\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
| Alternative 10 |
|---|
| Error | 35.2 |
|---|
| Cost | 712 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\frac{x}{y} \leq -20000000000:\\
\;\;\;\;\frac{x}{y}\\
\mathbf{elif}\;\frac{x}{y} \leq 4 \cdot 10^{+34}:\\
\;\;\;\;\frac{2}{t}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{y}\\
\end{array}
\]
| Alternative 11 |
|---|
| Error | 48.4 |
|---|
| Cost | 192 |
|---|
\[\frac{2}{t}
\]