\[\frac{x + y}{1 - \frac{y}{z}}
\]
↓
\[\begin{array}{l}
t_0 := \frac{x + y}{1 - \frac{y}{z}}\\
t_1 := \mathsf{fma}\left(x, z, z \cdot z\right)\\
\mathbf{if}\;t_0 \leq -2 \cdot 10^{-298} \lor \neg \left(t_0 \leq 0\right):\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;\left(\frac{-z}{\frac{y}{x}} - \left(\frac{t_1}{\frac{{y}^{3}}{z \cdot z}} + \left(z + \frac{t_1}{y} \cdot \frac{z}{y}\right)\right)\right) - \frac{z}{\frac{y}{z}}\\
\end{array}
\]
(FPCore (x y z) :precision binary64 (/ (+ x y) (- 1.0 (/ y z))))
↓
(FPCore (x y z)
:precision binary64
(let* ((t_0 (/ (+ x y) (- 1.0 (/ y z)))) (t_1 (fma x z (* z z))))
(if (or (<= t_0 -2e-298) (not (<= t_0 0.0)))
t_0
(-
(-
(/ (- z) (/ y x))
(+ (/ t_1 (/ (pow y 3.0) (* z z))) (+ z (* (/ t_1 y) (/ z y)))))
(/ z (/ y z))))))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 = (x + y) / (1.0 - (y / z));
double t_1 = fma(x, z, (z * z));
double tmp;
if ((t_0 <= -2e-298) || !(t_0 <= 0.0)) {
tmp = t_0;
} else {
tmp = ((-z / (y / x)) - ((t_1 / (pow(y, 3.0) / (z * z))) + (z + ((t_1 / y) * (z / y))))) - (z / (y / z));
}
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(Float64(x + y) / Float64(1.0 - Float64(y / z)))
t_1 = fma(x, z, Float64(z * z))
tmp = 0.0
if ((t_0 <= -2e-298) || !(t_0 <= 0.0))
tmp = t_0;
else
tmp = Float64(Float64(Float64(Float64(-z) / Float64(y / x)) - Float64(Float64(t_1 / Float64((y ^ 3.0) / Float64(z * z))) + Float64(z + Float64(Float64(t_1 / y) * Float64(z / y))))) - Float64(z / Float64(y / z)));
end
return 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[(N[(x + y), $MachinePrecision] / N[(1.0 - N[(y / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(x * z + N[(z * z), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[t$95$0, -2e-298], N[Not[LessEqual[t$95$0, 0.0]], $MachinePrecision]], t$95$0, N[(N[(N[((-z) / N[(y / x), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$1 / N[(N[Power[y, 3.0], $MachinePrecision] / N[(z * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z + N[(N[(t$95$1 / y), $MachinePrecision] * N[(z / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(z / N[(y / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\frac{x + y}{1 - \frac{y}{z}}
↓
\begin{array}{l}
t_0 := \frac{x + y}{1 - \frac{y}{z}}\\
t_1 := \mathsf{fma}\left(x, z, z \cdot z\right)\\
\mathbf{if}\;t_0 \leq -2 \cdot 10^{-298} \lor \neg \left(t_0 \leq 0\right):\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;\left(\frac{-z}{\frac{y}{x}} - \left(\frac{t_1}{\frac{{y}^{3}}{z \cdot z}} + \left(z + \frac{t_1}{y} \cdot \frac{z}{y}\right)\right)\right) - \frac{z}{\frac{y}{z}}\\
\end{array}