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 43.8% Cost 1377
\[\begin{array}{l}
t_1 := y \cdot \frac{0.5}{t}\\
t_2 := \frac{-0.5}{\frac{t}{z}}\\
t_3 := z \cdot \frac{-0.5}{t}\\
\mathbf{if}\;x \leq -1.55 \cdot 10^{+61}:\\
\;\;\;\;x \cdot \frac{0.5}{t}\\
\mathbf{elif}\;x \leq -5.8 \cdot 10^{+16}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;x \leq -4.2 \cdot 10^{-27}:\\
\;\;\;\;\frac{0.5}{\frac{t}{x}}\\
\mathbf{elif}\;x \leq -1.08 \cdot 10^{-186}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -1.5 \cdot 10^{-214}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 2.4 \cdot 10^{-197}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;x \leq 7.5 \cdot 10^{-132} \lor \neg \left(x \leq 3.3 \cdot 10^{-78}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 2 Accuracy 44.0% Cost 1377
\[\begin{array}{l}
t_1 := \frac{x}{\frac{t}{0.5}}\\
t_2 := \frac{-0.5}{\frac{t}{z}}\\
t_3 := y \cdot \frac{0.5}{t}\\
t_4 := z \cdot \frac{-0.5}{t}\\
\mathbf{if}\;x \leq -2.9 \cdot 10^{+59}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -4.5 \cdot 10^{+16}:\\
\;\;\;\;t_4\\
\mathbf{elif}\;x \leq -4.8 \cdot 10^{-27}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -1.5 \cdot 10^{-186}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -9 \cdot 10^{-213}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;x \leq 2.05 \cdot 10^{-197}:\\
\;\;\;\;t_4\\
\mathbf{elif}\;x \leq 4.7 \cdot 10^{-129} \lor \neg \left(x \leq 8.8 \cdot 10^{-79}\right):\\
\;\;\;\;t_3\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 3 Accuracy 43.9% Cost 1377
\[\begin{array}{l}
t_1 := \frac{x}{\frac{t}{0.5}}\\
t_2 := \frac{-0.5}{\frac{t}{z}}\\
t_3 := \frac{y}{\frac{t}{0.5}}\\
t_4 := z \cdot \frac{-0.5}{t}\\
\mathbf{if}\;x \leq -1.8 \cdot 10^{+63}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -5.8 \cdot 10^{+16}:\\
\;\;\;\;t_4\\
\mathbf{elif}\;x \leq -5 \cdot 10^{-28}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -4.4 \cdot 10^{-187}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -5 \cdot 10^{-214}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;x \leq 2.3 \cdot 10^{-197}:\\
\;\;\;\;t_4\\
\mathbf{elif}\;x \leq 2.3 \cdot 10^{-130} \lor \neg \left(x \leq 2.3 \cdot 10^{-78}\right):\\
\;\;\;\;t_3\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 4 Accuracy 44.4% Cost 1114
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.1 \cdot 10^{+61}:\\
\;\;\;\;x \cdot \frac{0.5}{t}\\
\mathbf{elif}\;x \leq -8.8 \cdot 10^{-187} \lor \neg \left(x \leq -6.2 \cdot 10^{-215}\right) \land \left(x \leq 1.75 \cdot 10^{-197} \lor \neg \left(x \leq 3 \cdot 10^{-118}\right) \land x \leq 3.5 \cdot 10^{-84}\right):\\
\;\;\;\;z \cdot \frac{-0.5}{t}\\
\mathbf{else}:\\
\;\;\;\;y \cdot \frac{0.5}{t}\\
\end{array}
\]
Alternative 5 Accuracy 44.5% Cost 1114
\[\begin{array}{l}
\mathbf{if}\;x \leq -4 \cdot 10^{+65}:\\
\;\;\;\;\frac{x}{\frac{t}{0.5}}\\
\mathbf{elif}\;x \leq -5.4 \cdot 10^{-187} \lor \neg \left(x \leq -8.8 \cdot 10^{-214}\right) \land \left(x \leq 1.9 \cdot 10^{-197} \lor \neg \left(x \leq 3.2 \cdot 10^{-121}\right) \land x \leq 7.4 \cdot 10^{-84}\right):\\
\;\;\;\;\frac{z \cdot -0.5}{t}\\
\mathbf{else}:\\
\;\;\;\;\frac{y}{\frac{t}{0.5}}\\
\end{array}
\]
Alternative 6 Accuracy 44.2% Cost 1113
\[\begin{array}{l}
t_1 := y \cdot \frac{0.5}{t}\\
t_2 := \frac{-0.5}{\frac{t}{z}}\\
\mathbf{if}\;x \leq -9 \cdot 10^{+58}:\\
\;\;\;\;x \cdot \frac{0.5}{t}\\
\mathbf{elif}\;x \leq -5.4 \cdot 10^{-187}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -3.45 \cdot 10^{-214}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 2.3 \cdot 10^{-197}:\\
\;\;\;\;z \cdot \frac{-0.5}{t}\\
\mathbf{elif}\;x \leq 8.5 \cdot 10^{-124} \lor \neg \left(x \leq 1.06 \cdot 10^{-78}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 7 Accuracy 44.4% Cost 1113
\[\begin{array}{l}
t_1 := \frac{z \cdot -0.5}{t}\\
\mathbf{if}\;x \leq -3.5 \cdot 10^{+63}:\\
\;\;\;\;\frac{x}{\frac{t}{0.5}}\\
\mathbf{elif}\;x \leq -5 \cdot 10^{-187}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -1.15 \cdot 10^{-214}:\\
\;\;\;\;\frac{-0.5}{\frac{-t}{y}}\\
\mathbf{elif}\;x \leq 1.7 \cdot 10^{-197} \lor \neg \left(x \leq 6.5 \cdot 10^{-125}\right) \land x \leq 3.5 \cdot 10^{-78}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;\frac{y}{\frac{t}{0.5}}\\
\end{array}
\]
Alternative 8 Accuracy 44.2% Cost 717
\[\begin{array}{l}
\mathbf{if}\;y \leq 3.5 \cdot 10^{-90} \lor \neg \left(y \leq 5.1 \cdot 10^{-23}\right) \land y \leq 1.75:\\
\;\;\;\;x \cdot \frac{0.5}{t}\\
\mathbf{else}:\\
\;\;\;\;y \cdot \frac{0.5}{t}\\
\end{array}
\]
Alternative 9 Accuracy 73.7% Cost 580
\[\begin{array}{l}
\mathbf{if}\;x \leq -2.8 \cdot 10^{+104}:\\
\;\;\;\;\frac{x}{\frac{t}{0.5}}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 10 Accuracy 75.2% Cost 580
\[\begin{array}{l}
\mathbf{if}\;y \leq 1.3 \cdot 10^{-89}:\\
\;\;\;\;\frac{-0.5}{t} \cdot \left(z - x\right)\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 11 Accuracy 75.1% Cost 580
\[\begin{array}{l}
\mathbf{if}\;y \leq 1.15 \cdot 10^{-89}:\\
\;\;\;\;\frac{-0.5}{\frac{t}{z - x}}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 12 Accuracy 75.4% Cost 580
\[\begin{array}{l}
\mathbf{if}\;y \leq 9 \cdot 10^{-90}:\\
\;\;\;\;\frac{-0.5 \cdot \left(z - x\right)}{t}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 13 Accuracy 99.6% Cost 576
\[\left(z - \left(x + y\right)\right) \cdot \frac{-0.5}{t}
\]
Alternative 14 Accuracy 36.3% Cost 320
\[x \cdot \frac{0.5}{t}
\]