Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{x + y}{1 - \frac{y}{z}}
\]
↓
\[\begin{array}{l}
t_0 := 1 - \frac{y}{z}\\
t_1 := \frac{x + y}{t_0}\\
\mathbf{if}\;t_1 \leq -2 \cdot 10^{-242}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t_1 \leq 0:\\
\;\;\;\;\frac{-z}{\frac{y}{y + x}}\\
\mathbf{else}:\\
\;\;\;\;\frac{y}{t_0} + \frac{x}{t_0}\\
\end{array}
\]
(FPCore (x y z) :precision binary64 (/ (+ x y) (- 1.0 (/ y z)))) ↓
(FPCore (x y z)
:precision binary64
(let* ((t_0 (- 1.0 (/ y z))) (t_1 (/ (+ x y) t_0)))
(if (<= t_1 -2e-242)
t_1
(if (<= t_1 0.0) (/ (- z) (/ y (+ y x))) (+ (/ y t_0) (/ x t_0)))))) double code(double x, double y, double z) {
return (x + y) / (1.0 - (y / z));
}
↓
double code(double x, double y, double z) {
double t_0 = 1.0 - (y / z);
double t_1 = (x + y) / t_0;
double tmp;
if (t_1 <= -2e-242) {
tmp = t_1;
} else if (t_1 <= 0.0) {
tmp = -z / (y / (y + x));
} else {
tmp = (y / t_0) + (x / t_0);
}
return tmp;
}
real(8) function code(x, y, z)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
code = (x + y) / (1.0d0 - (y / z))
end function
↓
real(8) function code(x, y, z)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = 1.0d0 - (y / z)
t_1 = (x + y) / t_0
if (t_1 <= (-2d-242)) then
tmp = t_1
else if (t_1 <= 0.0d0) then
tmp = -z / (y / (y + x))
else
tmp = (y / t_0) + (x / t_0)
end if
code = tmp
end function
public static double code(double x, double y, double z) {
return (x + y) / (1.0 - (y / z));
}
↓
public static double code(double x, double y, double z) {
double t_0 = 1.0 - (y / z);
double t_1 = (x + y) / t_0;
double tmp;
if (t_1 <= -2e-242) {
tmp = t_1;
} else if (t_1 <= 0.0) {
tmp = -z / (y / (y + x));
} else {
tmp = (y / t_0) + (x / t_0);
}
return tmp;
}
def code(x, y, z):
return (x + y) / (1.0 - (y / z))
↓
def code(x, y, z):
t_0 = 1.0 - (y / z)
t_1 = (x + y) / t_0
tmp = 0
if t_1 <= -2e-242:
tmp = t_1
elif t_1 <= 0.0:
tmp = -z / (y / (y + x))
else:
tmp = (y / t_0) + (x / t_0)
return tmp
function code(x, y, z)
return Float64(Float64(x + y) / Float64(1.0 - Float64(y / z)))
end
↓
function code(x, y, z)
t_0 = Float64(1.0 - Float64(y / z))
t_1 = Float64(Float64(x + y) / t_0)
tmp = 0.0
if (t_1 <= -2e-242)
tmp = t_1;
elseif (t_1 <= 0.0)
tmp = Float64(Float64(-z) / Float64(y / Float64(y + x)));
else
tmp = Float64(Float64(y / t_0) + Float64(x / t_0));
end
return tmp
end
function tmp = code(x, y, z)
tmp = (x + y) / (1.0 - (y / z));
end
↓
function tmp_2 = code(x, y, z)
t_0 = 1.0 - (y / z);
t_1 = (x + y) / t_0;
tmp = 0.0;
if (t_1 <= -2e-242)
tmp = t_1;
elseif (t_1 <= 0.0)
tmp = -z / (y / (y + x));
else
tmp = (y / t_0) + (x / t_0);
end
tmp_2 = tmp;
end
code[x_, y_, z_] := N[(N[(x + y), $MachinePrecision] / N[(1.0 - N[(y / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_] := Block[{t$95$0 = N[(1.0 - N[(y / z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(x + y), $MachinePrecision] / t$95$0), $MachinePrecision]}, If[LessEqual[t$95$1, -2e-242], t$95$1, If[LessEqual[t$95$1, 0.0], N[((-z) / N[(y / N[(y + x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(y / t$95$0), $MachinePrecision] + N[(x / t$95$0), $MachinePrecision]), $MachinePrecision]]]]]
\frac{x + y}{1 - \frac{y}{z}}
↓
\begin{array}{l}
t_0 := 1 - \frac{y}{z}\\
t_1 := \frac{x + y}{t_0}\\
\mathbf{if}\;t_1 \leq -2 \cdot 10^{-242}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t_1 \leq 0:\\
\;\;\;\;\frac{-z}{\frac{y}{y + x}}\\
\mathbf{else}:\\
\;\;\;\;\frac{y}{t_0} + \frac{x}{t_0}\\
\end{array}
Alternatives Alternative 1 Error 0.4 Cost 1864
\[\begin{array}{l}
t_0 := \frac{x + y}{1 - \frac{y}{z}}\\
\mathbf{if}\;t_0 \leq -2 \cdot 10^{-242}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;t_0 \leq 0:\\
\;\;\;\;\frac{-z}{\frac{y}{y + x}}\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 2 Error 16.5 Cost 1172
\[\begin{array}{l}
t_0 := \frac{-z}{\frac{y}{y + x}}\\
\mathbf{if}\;y \leq -7.8 \cdot 10^{+47}:\\
\;\;\;\;z \cdot \left(-1 - \frac{x}{y}\right)\\
\mathbf{elif}\;y \leq -9.2 \cdot 10^{+26}:\\
\;\;\;\;y + x\\
\mathbf{elif}\;y \leq -1.26 \cdot 10^{-14}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;y \leq 5.5 \cdot 10^{-173}:\\
\;\;\;\;\frac{x}{1 - \frac{y}{z}}\\
\mathbf{elif}\;y \leq 8.5 \cdot 10^{+24}:\\
\;\;\;\;y + x\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 3 Error 16.5 Cost 1108
\[\begin{array}{l}
t_0 := z \cdot \left(-1 - \frac{x}{y}\right)\\
\mathbf{if}\;y \leq -9.5 \cdot 10^{+47}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;y \leq -2.2 \cdot 10^{+27}:\\
\;\;\;\;y + x\\
\mathbf{elif}\;y \leq -1.35 \cdot 10^{-16}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;y \leq 1.15 \cdot 10^{-175}:\\
\;\;\;\;\frac{x}{1 - \frac{y}{z}}\\
\mathbf{elif}\;y \leq 8.2 \cdot 10^{+24}:\\
\;\;\;\;y + x\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 4 Error 20.6 Cost 780
\[\begin{array}{l}
\mathbf{if}\;y \leq -2.15 \cdot 10^{+58}:\\
\;\;\;\;-z\\
\mathbf{elif}\;y \leq 1.12 \cdot 10^{+25}:\\
\;\;\;\;y + x\\
\mathbf{elif}\;y \leq 8.8 \cdot 10^{+74}:\\
\;\;\;\;\frac{x}{y} \cdot \left(-z\right)\\
\mathbf{else}:\\
\;\;\;\;-z\\
\end{array}
\]
Alternative 5 Error 20.6 Cost 780
\[\begin{array}{l}
\mathbf{if}\;y \leq -1.9 \cdot 10^{+58}:\\
\;\;\;\;-z\\
\mathbf{elif}\;y \leq 9.2 \cdot 10^{+24}:\\
\;\;\;\;y + x\\
\mathbf{elif}\;y \leq 1.6 \cdot 10^{+77}:\\
\;\;\;\;\frac{-z}{\frac{y}{x}}\\
\mathbf{else}:\\
\;\;\;\;-z\\
\end{array}
\]
Alternative 6 Error 16.4 Cost 712
\[\begin{array}{l}
t_0 := z \cdot \left(-1 - \frac{x}{y}\right)\\
\mathbf{if}\;y \leq -8.2 \cdot 10^{+47}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;y \leq 8.5 \cdot 10^{+24}:\\
\;\;\;\;y + x\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 7 Error 20.5 Cost 456
\[\begin{array}{l}
\mathbf{if}\;y \leq -4 \cdot 10^{+58}:\\
\;\;\;\;-z\\
\mathbf{elif}\;y \leq 4.1 \cdot 10^{+26}:\\
\;\;\;\;y + x\\
\mathbf{else}:\\
\;\;\;\;-z\\
\end{array}
\]
Alternative 8 Error 26.8 Cost 392
\[\begin{array}{l}
\mathbf{if}\;y \leq -3.5 \cdot 10^{+58}:\\
\;\;\;\;-z\\
\mathbf{elif}\;y \leq 2 \cdot 10^{+26}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;-z\\
\end{array}
\]
Alternative 9 Error 41.9 Cost 64
\[x
\]