Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{\left(x + y\right) - z}{t \cdot 2}
\]
↓
\[\frac{\left(x + y\right) - z}{t \cdot 2}
\]
(FPCore (x y z t) :precision binary64 (/ (- (+ x y) z) (* t 2.0))) ↓
(FPCore (x y z t) :precision binary64 (/ (- (+ x y) z) (* t 2.0))) double code(double x, double y, double z, double t) {
return ((x + y) - z) / (t * 2.0);
}
↓
double code(double x, double y, double z, double t) {
return ((x + y) - z) / (t * 2.0);
}
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) - z) / (t * 2.0d0)
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) - z) / (t * 2.0d0)
end function
public static double code(double x, double y, double z, double t) {
return ((x + y) - z) / (t * 2.0);
}
↓
public static double code(double x, double y, double z, double t) {
return ((x + y) - z) / (t * 2.0);
}
def code(x, y, z, t):
return ((x + y) - z) / (t * 2.0)
↓
def code(x, y, z, t):
return ((x + y) - z) / (t * 2.0)
function code(x, y, z, t)
return Float64(Float64(Float64(x + y) - z) / Float64(t * 2.0))
end
↓
function code(x, y, z, t)
return Float64(Float64(Float64(x + y) - z) / Float64(t * 2.0))
end
function tmp = code(x, y, z, t)
tmp = ((x + y) - z) / (t * 2.0);
end
↓
function tmp = code(x, y, z, t)
tmp = ((x + y) - z) / (t * 2.0);
end
code[x_, y_, z_, t_] := N[(N[(N[(x + y), $MachinePrecision] - z), $MachinePrecision] / N[(t * 2.0), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_] := N[(N[(N[(x + y), $MachinePrecision] - z), $MachinePrecision] / N[(t * 2.0), $MachinePrecision]), $MachinePrecision]
\frac{\left(x + y\right) - z}{t \cdot 2}
↓
\frac{\left(x + y\right) - z}{t \cdot 2}
Alternatives Alternative 1 Accuracy 44.9% Cost 1112
\[\begin{array}{l}
t_1 := z \cdot \frac{-0.5}{t}\\
t_2 := y \cdot \frac{0.5}{t}\\
t_3 := \frac{x}{\frac{t}{0.5}}\\
\mathbf{if}\;y \leq 10^{-245}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;y \leq 1.6 \cdot 10^{-37}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 27:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 2 \cdot 10^{+35}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;y \leq 2.3 \cdot 10^{+48}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 5 \cdot 10^{+56}:\\
\;\;\;\;t_3\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 2 Accuracy 44.9% Cost 1112
\[\begin{array}{l}
t_1 := z \cdot \frac{-0.5}{t}\\
t_2 := \frac{y}{\frac{t}{0.5}}\\
t_3 := \frac{x}{\frac{t}{0.5}}\\
\mathbf{if}\;y \leq 2.25 \cdot 10^{-243}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;y \leq 4.9 \cdot 10^{-37}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 0.102:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 8.8 \cdot 10^{+33}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;y \leq 2.25 \cdot 10^{+48}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 1.12 \cdot 10^{+57}:\\
\;\;\;\;t_3\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 3 Accuracy 45.0% Cost 1112
\[\begin{array}{l}
t_1 := \frac{y}{\frac{t}{0.5}}\\
t_2 := \frac{x}{\frac{t}{0.5}}\\
\mathbf{if}\;y \leq 1.3 \cdot 10^{-243}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 8 \cdot 10^{-37}:\\
\;\;\;\;\frac{z \cdot -0.5}{t}\\
\mathbf{elif}\;y \leq 0.85:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 1.35 \cdot 10^{+32}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 2.22 \cdot 10^{+48}:\\
\;\;\;\;z \cdot \frac{-0.5}{t}\\
\mathbf{elif}\;y \leq 1.05 \cdot 10^{+55}:\\
\;\;\;\;t_2\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 4 Accuracy 75.2% Cost 845
\[\begin{array}{l}
\mathbf{if}\;y \leq 1.5 \cdot 10^{-58} \lor \neg \left(y \leq 39\right) \land y \leq 5.5 \cdot 10^{+55}:\\
\;\;\;\;\frac{-0.5}{t} \cdot \left(z - x\right)\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 5 Accuracy 75.5% Cost 845
\[\begin{array}{l}
\mathbf{if}\;y \leq 1.5 \cdot 10^{-58} \lor \neg \left(y \leq 0.46\right) \land y \leq 1.6 \cdot 10^{+55}:\\
\;\;\;\;\frac{-0.5 \cdot \left(z - x\right)}{t}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 6 Accuracy 73.8% Cost 580
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.9 \cdot 10^{+107}:\\
\;\;\;\;\frac{x}{\frac{t}{0.5}}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 7 Accuracy 99.6% Cost 576
\[\left(z - \left(x + y\right)\right) \cdot \frac{-0.5}{t}
\]
Alternative 8 Accuracy 43.8% Cost 452
\[\begin{array}{l}
\mathbf{if}\;y \leq 7.5 \cdot 10^{-37}:\\
\;\;\;\;z \cdot \frac{-0.5}{t}\\
\mathbf{else}:\\
\;\;\;\;y \cdot \frac{0.5}{t}\\
\end{array}
\]
Alternative 9 Accuracy 36.3% Cost 320
\[y \cdot \frac{0.5}{t}
\]