Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{x \cdot 2}{y \cdot z - t \cdot z}
\]
↓
\[\begin{array}{l}
t_1 := y \cdot z - z \cdot t\\
\mathbf{if}\;t_1 \leq -1 \cdot 10^{+165} \lor \neg \left(t_1 \leq 5 \cdot 10^{+209}\right):\\
\;\;\;\;\frac{x}{z} \cdot \frac{2}{y - t}\\
\mathbf{else}:\\
\;\;\;\;\frac{x \cdot 2}{t_1}\\
\end{array}
\]
(FPCore (x y z t) :precision binary64 (/ (* x 2.0) (- (* y z) (* t z)))) ↓
(FPCore (x y z t)
:precision binary64
(let* ((t_1 (- (* y z) (* z t))))
(if (or (<= t_1 -1e+165) (not (<= t_1 5e+209)))
(* (/ x z) (/ 2.0 (- y t)))
(/ (* x 2.0) t_1)))) double code(double x, double y, double z, double t) {
return (x * 2.0) / ((y * z) - (t * z));
}
↓
double code(double x, double y, double z, double t) {
double t_1 = (y * z) - (z * t);
double tmp;
if ((t_1 <= -1e+165) || !(t_1 <= 5e+209)) {
tmp = (x / z) * (2.0 / (y - t));
} else {
tmp = (x * 2.0) / t_1;
}
return tmp;
}
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 * 2.0d0) / ((y * z) - (t * z))
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
real(8) :: t_1
real(8) :: tmp
t_1 = (y * z) - (z * t)
if ((t_1 <= (-1d+165)) .or. (.not. (t_1 <= 5d+209))) then
tmp = (x / z) * (2.0d0 / (y - t))
else
tmp = (x * 2.0d0) / t_1
end if
code = tmp
end function
public static double code(double x, double y, double z, double t) {
return (x * 2.0) / ((y * z) - (t * z));
}
↓
public static double code(double x, double y, double z, double t) {
double t_1 = (y * z) - (z * t);
double tmp;
if ((t_1 <= -1e+165) || !(t_1 <= 5e+209)) {
tmp = (x / z) * (2.0 / (y - t));
} else {
tmp = (x * 2.0) / t_1;
}
return tmp;
}
def code(x, y, z, t):
return (x * 2.0) / ((y * z) - (t * z))
↓
def code(x, y, z, t):
t_1 = (y * z) - (z * t)
tmp = 0
if (t_1 <= -1e+165) or not (t_1 <= 5e+209):
tmp = (x / z) * (2.0 / (y - t))
else:
tmp = (x * 2.0) / t_1
return tmp
function code(x, y, z, t)
return Float64(Float64(x * 2.0) / Float64(Float64(y * z) - Float64(t * z)))
end
↓
function code(x, y, z, t)
t_1 = Float64(Float64(y * z) - Float64(z * t))
tmp = 0.0
if ((t_1 <= -1e+165) || !(t_1 <= 5e+209))
tmp = Float64(Float64(x / z) * Float64(2.0 / Float64(y - t)));
else
tmp = Float64(Float64(x * 2.0) / t_1);
end
return tmp
end
function tmp = code(x, y, z, t)
tmp = (x * 2.0) / ((y * z) - (t * z));
end
↓
function tmp_2 = code(x, y, z, t)
t_1 = (y * z) - (z * t);
tmp = 0.0;
if ((t_1 <= -1e+165) || ~((t_1 <= 5e+209)))
tmp = (x / z) * (2.0 / (y - t));
else
tmp = (x * 2.0) / t_1;
end
tmp_2 = tmp;
end
code[x_, y_, z_, t_] := N[(N[(x * 2.0), $MachinePrecision] / N[(N[(y * z), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_] := Block[{t$95$1 = N[(N[(y * z), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[t$95$1, -1e+165], N[Not[LessEqual[t$95$1, 5e+209]], $MachinePrecision]], N[(N[(x / z), $MachinePrecision] * N[(2.0 / N[(y - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * 2.0), $MachinePrecision] / t$95$1), $MachinePrecision]]]
\frac{x \cdot 2}{y \cdot z - t \cdot z}
↓
\begin{array}{l}
t_1 := y \cdot z - z \cdot t\\
\mathbf{if}\;t_1 \leq -1 \cdot 10^{+165} \lor \neg \left(t_1 \leq 5 \cdot 10^{+209}\right):\\
\;\;\;\;\frac{x}{z} \cdot \frac{2}{y - t}\\
\mathbf{else}:\\
\;\;\;\;\frac{x \cdot 2}{t_1}\\
\end{array}
Alternatives Alternative 1 Error 18.0 Cost 977
\[\begin{array}{l}
t_1 := \frac{2}{z} \cdot \frac{x}{y}\\
\mathbf{if}\;y \leq -0.00023:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq -1.45 \cdot 10^{-49}:\\
\;\;\;\;\frac{x}{t} \cdot \frac{-2}{z}\\
\mathbf{elif}\;y \leq -3.9 \cdot 10^{-81} \lor \neg \left(y \leq 1.58 \cdot 10^{+87}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;x \cdot \frac{\frac{-2}{t}}{z}\\
\end{array}
\]
Alternative 2 Error 2.5 Cost 841
\[\begin{array}{l}
\mathbf{if}\;z \leq -3 \cdot 10^{-47} \lor \neg \left(z \leq 2.3 \cdot 10^{-56}\right):\\
\;\;\;\;\frac{x}{z} \cdot \frac{2}{y - t}\\
\mathbf{else}:\\
\;\;\;\;x \cdot \frac{2}{z \cdot \left(y - t\right)}\\
\end{array}
\]
Alternative 3 Error 2.3 Cost 841
\[\begin{array}{l}
\mathbf{if}\;z \leq -5.4 \cdot 10^{-53} \lor \neg \left(z \leq 2.8 \cdot 10^{-29}\right):\\
\;\;\;\;\frac{x}{z} \cdot \frac{2}{y - t}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{\frac{z \cdot \left(y - t\right)}{2}}\\
\end{array}
\]
Alternative 4 Error 2.9 Cost 841
\[\begin{array}{l}
\mathbf{if}\;z \leq -9.2 \cdot 10^{+126} \lor \neg \left(z \leq 10^{-19}\right):\\
\;\;\;\;\frac{\frac{2}{z}}{\frac{y - t}{x}}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{\frac{z \cdot \left(y - t\right)}{2}}\\
\end{array}
\]
Alternative 5 Error 17.2 Cost 713
\[\begin{array}{l}
\mathbf{if}\;t \leq -250000000 \lor \neg \left(t \leq 82000000000000\right):\\
\;\;\;\;x \cdot \frac{\frac{-2}{t}}{z}\\
\mathbf{else}:\\
\;\;\;\;x \cdot \frac{2}{y \cdot z}\\
\end{array}
\]
Alternative 6 Error 17.6 Cost 713
\[\begin{array}{l}
\mathbf{if}\;t \leq -6.5 \cdot 10^{+27} \lor \neg \left(t \leq 1.2 \cdot 10^{+14}\right):\\
\;\;\;\;x \cdot \frac{\frac{-2}{t}}{z}\\
\mathbf{else}:\\
\;\;\;\;\frac{2}{z} \cdot \frac{x}{y}\\
\end{array}
\]
Alternative 7 Error 17.7 Cost 712
\[\begin{array}{l}
\mathbf{if}\;t \leq -6 \cdot 10^{+31}:\\
\;\;\;\;x \cdot \frac{\frac{-2}{t}}{z}\\
\mathbf{elif}\;t \leq 11000000000000:\\
\;\;\;\;\frac{2}{z} \cdot \frac{x}{y}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{z} \cdot \frac{-2}{t}\\
\end{array}
\]
Alternative 8 Error 17.9 Cost 712
\[\begin{array}{l}
\mathbf{if}\;t \leq -1.9 \cdot 10^{+31}:\\
\;\;\;\;x \cdot \frac{\frac{-2}{t}}{z}\\
\mathbf{elif}\;t \leq 4250000000000:\\
\;\;\;\;\frac{2}{z \cdot \frac{y}{x}}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{z} \cdot \frac{-2}{t}\\
\end{array}
\]
Alternative 9 Error 18.0 Cost 712
\[\begin{array}{l}
\mathbf{if}\;t \leq -3.6 \cdot 10^{+27}:\\
\;\;\;\;\frac{x \cdot -2}{z \cdot t}\\
\mathbf{elif}\;t \leq 1850000000000:\\
\;\;\;\;\frac{2}{z \cdot \frac{y}{x}}\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{z} \cdot \frac{-2}{t}\\
\end{array}
\]
Alternative 10 Error 6.0 Cost 576
\[x \cdot \frac{2}{z \cdot \left(y - t\right)}
\]
Alternative 11 Error 32.0 Cost 448
\[x \cdot \frac{2}{y \cdot z}
\]