\[\frac{x}{x \cdot x + 1}
\]
↓
\[\frac{1}{\mathsf{hypot}\left(1, x\right)} \cdot \frac{x}{\mathsf{hypot}\left(1, x\right)}
\]
(FPCore (x) :precision binary64 (/ x (+ (* x x) 1.0)))
↓
(FPCore (x) :precision binary64 (* (/ 1.0 (hypot 1.0 x)) (/ x (hypot 1.0 x))))
double code(double x) {
return x / ((x * x) + 1.0);
}
↓
double code(double x) {
return (1.0 / hypot(1.0, x)) * (x / hypot(1.0, x));
}
public static double code(double x) {
return x / ((x * x) + 1.0);
}
↓
public static double code(double x) {
return (1.0 / Math.hypot(1.0, x)) * (x / Math.hypot(1.0, x));
}
def code(x):
return x / ((x * x) + 1.0)
↓
def code(x):
return (1.0 / math.hypot(1.0, x)) * (x / math.hypot(1.0, x))
function code(x)
return Float64(x / Float64(Float64(x * x) + 1.0))
end
↓
function code(x)
return Float64(Float64(1.0 / hypot(1.0, x)) * Float64(x / hypot(1.0, x)))
end
function tmp = code(x)
tmp = x / ((x * x) + 1.0);
end
↓
function tmp = code(x)
tmp = (1.0 / hypot(1.0, x)) * (x / hypot(1.0, x));
end
code[x_] := N[(x / N[(N[(x * x), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]
↓
code[x_] := N[(N[(1.0 / N[Sqrt[1.0 ^ 2 + x ^ 2], $MachinePrecision]), $MachinePrecision] * N[(x / N[Sqrt[1.0 ^ 2 + x ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{x}{x \cdot x + 1}
↓
\frac{1}{\mathsf{hypot}\left(1, x\right)} \cdot \frac{x}{\mathsf{hypot}\left(1, x\right)}