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 Error 10.2 Cost 977
\[\begin{array}{l}
t_1 := \frac{0.5}{\frac{t}{x - z}}\\
\mathbf{if}\;z \leq -1.15 \cdot 10^{-83}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 5.5 \cdot 10^{-14}:\\
\;\;\;\;0.5 \cdot \frac{x + y}{t}\\
\mathbf{elif}\;z \leq 1.95 \cdot 10^{+96} \lor \neg \left(z \leq 2.4 \cdot 10^{+194}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;\left(y - z\right) \cdot \frac{0.5}{t}\\
\end{array}
\]
Alternative 2 Error 10.1 Cost 977
\[\begin{array}{l}
t_1 := \frac{-0.5 \cdot \left(z - x\right)}{t}\\
\mathbf{if}\;z \leq -1.9 \cdot 10^{-84}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 1.7 \cdot 10^{-14}:\\
\;\;\;\;0.5 \cdot \frac{x + y}{t}\\
\mathbf{elif}\;z \leq 2.7 \cdot 10^{+96} \lor \neg \left(z \leq 5.5 \cdot 10^{+191}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;\left(y - z\right) \cdot \frac{0.5}{t}\\
\end{array}
\]
Alternative 3 Error 36.3 Cost 848
\[\begin{array}{l}
t_1 := 0.5 \cdot \frac{x}{t}\\
t_2 := -0.5 \cdot \frac{z}{t}\\
\mathbf{if}\;x \leq -2.6 \cdot 10^{+68}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -7.5 \cdot 10^{+36}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -1.25 \cdot 10^{-59}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 1.4 \cdot 10^{-204}:\\
\;\;\;\;t_2\\
\mathbf{else}:\\
\;\;\;\;\frac{y \cdot 0.5}{t}\\
\end{array}
\]
Alternative 4 Error 16.0 Cost 845
\[\begin{array}{l}
\mathbf{if}\;x \leq -5.2 \cdot 10^{+71} \lor \neg \left(x \leq -1.7 \cdot 10^{+37}\right) \land x \leq -1.8 \cdot 10^{-63}:\\
\;\;\;\;0.5 \cdot \frac{x + y}{t}\\
\mathbf{else}:\\
\;\;\;\;\left(y - z\right) \cdot \frac{0.5}{t}\\
\end{array}
\]
Alternative 5 Error 36.3 Cost 717
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.65 \cdot 10^{+69} \lor \neg \left(x \leq -1.95 \cdot 10^{+37}\right) \land x \leq -1.25 \cdot 10^{-59}:\\
\;\;\;\;0.5 \cdot \frac{x}{t}\\
\mathbf{else}:\\
\;\;\;\;-0.5 \cdot \frac{z}{t}\\
\end{array}
\]
Alternative 6 Error 13.1 Cost 713
\[\begin{array}{l}
\mathbf{if}\;z \leq -2.2 \cdot 10^{+102} \lor \neg \left(z \leq 5.8 \cdot 10^{+96}\right):\\
\;\;\;\;-0.5 \cdot \frac{z}{t}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{x + y}{t}\\
\end{array}
\]
Alternative 7 Error 0.3 Cost 576
\[\left(z - \left(x + y\right)\right) \cdot \frac{-0.5}{t}
\]
Alternative 8 Error 41.1 Cost 320
\[0.5 \cdot \frac{x}{t}
\]