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 17.6 Cost 1108
\[\begin{array}{l}
t_1 := \frac{x \cdot 0.5}{t}\\
t_2 := 0.5 \cdot \frac{y - z}{t}\\
\mathbf{if}\;x \leq -7.5 \cdot 10^{+161}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq -1 \cdot 10^{+111}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -3 \cdot 10^{+77}:\\
\;\;\;\;\frac{0.5}{\frac{t}{x}}\\
\mathbf{elif}\;x \leq -1.38 \cdot 10^{+51}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;x \leq -3.8 \cdot 10^{+25}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 2 Error 35.8 Cost 848
\[\begin{array}{l}
t_1 := \frac{z \cdot -0.5}{t}\\
t_2 := \frac{x \cdot 0.5}{t}\\
\mathbf{if}\;y \leq -1.9 \cdot 10^{-154}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 10^{-292}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 3 \cdot 10^{-217}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 7.5 \cdot 10^{-12}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;\frac{y \cdot 0.5}{t}\\
\end{array}
\]
Alternative 3 Error 10.0 Cost 712
\[\begin{array}{l}
t_1 := 0.5 \cdot \frac{y - z}{t}\\
\mathbf{if}\;z \leq -2.15 \cdot 10^{-15}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 3 \cdot 10^{-90}:\\
\;\;\;\;\frac{0.5}{t} \cdot \left(x + y\right)\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 4 Error 30.3 Cost 584
\[\begin{array}{l}
t_1 := \frac{z \cdot -0.5}{t}\\
\mathbf{if}\;z \leq -8 \cdot 10^{-24}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 1.65 \cdot 10^{-88}:\\
\;\;\;\;\frac{0.5}{\frac{t}{x}}\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 5 Error 30.2 Cost 584
\[\begin{array}{l}
t_1 := \frac{z \cdot -0.5}{t}\\
\mathbf{if}\;z \leq -6.4 \cdot 10^{-24}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 1.65 \cdot 10^{-88}:\\
\;\;\;\;\frac{x \cdot 0.5}{t}\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 6 Error 15.3 Cost 580
\[\begin{array}{l}
\mathbf{if}\;y \leq 2.5 \cdot 10^{-33}:\\
\;\;\;\;\frac{0.5}{t} \cdot \left(x - z\right)\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \frac{y - z}{t}\\
\end{array}
\]
Alternative 7 Error 0.3 Cost 576
\[\left(\left(z - x\right) - y\right) \cdot \frac{-0.5}{t}
\]
Alternative 8 Error 41.5 Cost 320
\[\frac{0.5}{\frac{t}{x}}
\]