Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{x + \frac{y \cdot z - x}{t \cdot z - x}}{x + 1}
\]
↓
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.005719935295823 \cdot 10^{+98}:\\
\;\;\;\;1\\
\mathbf{elif}\;x \leq -4.1731864673707804 \cdot 10^{-13}:\\
\;\;\;\;\frac{x + \left(1 - \frac{y \cdot z}{x}\right)}{x + 1}\\
\mathbf{elif}\;x \leq 1.0888255954359132 \cdot 10^{-32}:\\
\;\;\;\;\frac{x + \frac{y}{t}}{x + 1}\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}
\]
(FPCore (x y z t)
:precision binary64
(/ (+ x (/ (- (* y z) x) (- (* t z) x))) (+ x 1.0))) ↓
(FPCore (x y z t)
:precision binary64
(if (<= x -1.005719935295823e+98)
1.0
(if (<= x -4.1731864673707804e-13)
(/ (+ x (- 1.0 (/ (* y z) x))) (+ x 1.0))
(if (<= x 1.0888255954359132e-32) (/ (+ x (/ y t)) (+ x 1.0)) 1.0)))) double code(double x, double y, double z, double t) {
return (x + (((y * z) - x) / ((t * z) - x))) / (x + 1.0);
}
↓
double code(double x, double y, double z, double t) {
double tmp;
if (x <= -1.005719935295823e+98) {
tmp = 1.0;
} else if (x <= -4.1731864673707804e-13) {
tmp = (x + (1.0 - ((y * z) / x))) / (x + 1.0);
} else if (x <= 1.0888255954359132e-32) {
tmp = (x + (y / t)) / (x + 1.0);
} else {
tmp = 1.0;
}
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 + (((y * z) - x) / ((t * z) - x))) / (x + 1.0d0)
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
real(8) :: tmp
if (x <= (-1.005719935295823d+98)) then
tmp = 1.0d0
else if (x <= (-4.1731864673707804d-13)) then
tmp = (x + (1.0d0 - ((y * z) / x))) / (x + 1.0d0)
else if (x <= 1.0888255954359132d-32) then
tmp = (x + (y / t)) / (x + 1.0d0)
else
tmp = 1.0d0
end if
code = tmp
end function
public static double code(double x, double y, double z, double t) {
return (x + (((y * z) - x) / ((t * z) - x))) / (x + 1.0);
}
↓
public static double code(double x, double y, double z, double t) {
double tmp;
if (x <= -1.005719935295823e+98) {
tmp = 1.0;
} else if (x <= -4.1731864673707804e-13) {
tmp = (x + (1.0 - ((y * z) / x))) / (x + 1.0);
} else if (x <= 1.0888255954359132e-32) {
tmp = (x + (y / t)) / (x + 1.0);
} else {
tmp = 1.0;
}
return tmp;
}
def code(x, y, z, t):
return (x + (((y * z) - x) / ((t * z) - x))) / (x + 1.0)
↓
def code(x, y, z, t):
tmp = 0
if x <= -1.005719935295823e+98:
tmp = 1.0
elif x <= -4.1731864673707804e-13:
tmp = (x + (1.0 - ((y * z) / x))) / (x + 1.0)
elif x <= 1.0888255954359132e-32:
tmp = (x + (y / t)) / (x + 1.0)
else:
tmp = 1.0
return tmp
function code(x, y, z, t)
return Float64(Float64(x + Float64(Float64(Float64(y * z) - x) / Float64(Float64(t * z) - x))) / Float64(x + 1.0))
end
↓
function code(x, y, z, t)
tmp = 0.0
if (x <= -1.005719935295823e+98)
tmp = 1.0;
elseif (x <= -4.1731864673707804e-13)
tmp = Float64(Float64(x + Float64(1.0 - Float64(Float64(y * z) / x))) / Float64(x + 1.0));
elseif (x <= 1.0888255954359132e-32)
tmp = Float64(Float64(x + Float64(y / t)) / Float64(x + 1.0));
else
tmp = 1.0;
end
return tmp
end
function tmp = code(x, y, z, t)
tmp = (x + (((y * z) - x) / ((t * z) - x))) / (x + 1.0);
end
↓
function tmp_2 = code(x, y, z, t)
tmp = 0.0;
if (x <= -1.005719935295823e+98)
tmp = 1.0;
elseif (x <= -4.1731864673707804e-13)
tmp = (x + (1.0 - ((y * z) / x))) / (x + 1.0);
elseif (x <= 1.0888255954359132e-32)
tmp = (x + (y / t)) / (x + 1.0);
else
tmp = 1.0;
end
tmp_2 = tmp;
end
code[x_, y_, z_, t_] := N[(N[(x + N[(N[(N[(y * z), $MachinePrecision] - x), $MachinePrecision] / N[(N[(t * z), $MachinePrecision] - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(x + 1.0), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_] := If[LessEqual[x, -1.005719935295823e+98], 1.0, If[LessEqual[x, -4.1731864673707804e-13], N[(N[(x + N[(1.0 - N[(N[(y * z), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(x + 1.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.0888255954359132e-32], N[(N[(x + N[(y / t), $MachinePrecision]), $MachinePrecision] / N[(x + 1.0), $MachinePrecision]), $MachinePrecision], 1.0]]]
\frac{x + \frac{y \cdot z - x}{t \cdot z - x}}{x + 1}
↓
\begin{array}{l}
\mathbf{if}\;x \leq -1.005719935295823 \cdot 10^{+98}:\\
\;\;\;\;1\\
\mathbf{elif}\;x \leq -4.1731864673707804 \cdot 10^{-13}:\\
\;\;\;\;\frac{x + \left(1 - \frac{y \cdot z}{x}\right)}{x + 1}\\
\mathbf{elif}\;x \leq 1.0888255954359132 \cdot 10^{-32}:\\
\;\;\;\;\frac{x + \frac{y}{t}}{x + 1}\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}