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 47.5% Cost 850
\[\begin{array}{l}
\mathbf{if}\;z \leq -2.6 \cdot 10^{+87} \lor \neg \left(z \leq -2.25 \cdot 10^{+35}\right) \land \left(z \leq -3 \cdot 10^{-22} \lor \neg \left(z \leq 6.4 \cdot 10^{+19}\right)\right):\\
\;\;\;\;\frac{-0.5}{\frac{t}{z}}\\
\mathbf{else}:\\
\;\;\;\;y \cdot \frac{0.5}{t}\\
\end{array}
\]
Alternative 2 Error 55.27% Cost 848
\[\begin{array}{l}
t_1 := \frac{-0.5}{\frac{t}{z}}\\
t_2 := \frac{x}{\frac{t}{0.5}}\\
\mathbf{if}\;y \leq -1.26 \cdot 10^{-194}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 1.22 \cdot 10^{-232}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 2.85 \cdot 10^{-155}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 0.115:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;y \cdot \frac{0.5}{t}\\
\end{array}
\]
Alternative 3 Error 55.26% Cost 848
\[\begin{array}{l}
t_1 := \frac{-0.5}{\frac{t}{z}}\\
t_2 := \frac{x}{\frac{t}{0.5}}\\
\mathbf{if}\;y \leq -1.15 \cdot 10^{-192}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 1.32 \cdot 10^{-232}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 1.02 \cdot 10^{-154}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 0.115:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;\frac{y}{\frac{t}{0.5}}\\
\end{array}
\]
Alternative 4 Error 55.17% Cost 848
\[\begin{array}{l}
t_1 := \frac{z \cdot -0.5}{t}\\
t_2 := \frac{x}{\frac{t}{0.5}}\\
\mathbf{if}\;y \leq -2.6 \cdot 10^{-194}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 1.45 \cdot 10^{-232}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 5 \cdot 10^{-155}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 0.11:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;\frac{y}{\frac{t}{0.5}}\\
\end{array}
\]
Alternative 5 Error 27.38% Cost 580
\[\begin{array}{l}
\mathbf{if}\;x \leq -3.3 \cdot 10^{+44}:\\
\;\;\;\;\frac{x}{\frac{t}{0.5}}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 6 Error 23.56% Cost 580
\[\begin{array}{l}
\mathbf{if}\;x \leq -0.0265:\\
\;\;\;\;\left(x + y\right) \cdot \frac{0.5}{t}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 7 Error 24.09% Cost 580
\[\begin{array}{l}
\mathbf{if}\;y \leq 5 \cdot 10^{-48}:\\
\;\;\;\;\frac{-0.5 \cdot \left(z - x\right)}{t}\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 8 Error 0.41% Cost 576
\[\left(z - \left(x + y\right)\right) \cdot \frac{-0.5}{t}
\]
Alternative 9 Error 63.86% Cost 320
\[y \cdot \frac{0.5}{t}
\]