\[lo < -1 \cdot 10^{+308} \land hi > 10^{+308}\]
Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{x - lo}{hi - lo}
\]
↓
\[\begin{array}{l}
t_0 := \frac{x - lo}{hi}\\
t_1 := {t_0}^{2}\\
\frac{{\left(\frac{lo}{\frac{hi \cdot hi}{x}}\right)}^{3} + t_0 \cdot t_1}{{\left(\left(x - lo\right) \cdot \frac{lo}{hi \cdot hi}\right)}^{2} + \left(t_1 - t_1 \cdot \frac{lo}{hi}\right)}
\end{array}
\]
(FPCore (lo hi x) :precision binary64 (/ (- x lo) (- hi lo))) ↓
(FPCore (lo hi x)
:precision binary64
(let* ((t_0 (/ (- x lo) hi)) (t_1 (pow t_0 2.0)))
(/
(+ (pow (/ lo (/ (* hi hi) x)) 3.0) (* t_0 t_1))
(+ (pow (* (- x lo) (/ lo (* hi hi))) 2.0) (- t_1 (* t_1 (/ lo hi))))))) double code(double lo, double hi, double x) {
return (x - lo) / (hi - lo);
}
↓
double code(double lo, double hi, double x) {
double t_0 = (x - lo) / hi;
double t_1 = pow(t_0, 2.0);
return (pow((lo / ((hi * hi) / x)), 3.0) + (t_0 * t_1)) / (pow(((x - lo) * (lo / (hi * hi))), 2.0) + (t_1 - (t_1 * (lo / hi))));
}
real(8) function code(lo, hi, x)
real(8), intent (in) :: lo
real(8), intent (in) :: hi
real(8), intent (in) :: x
code = (x - lo) / (hi - lo)
end function
↓
real(8) function code(lo, hi, x)
real(8), intent (in) :: lo
real(8), intent (in) :: hi
real(8), intent (in) :: x
real(8) :: t_0
real(8) :: t_1
t_0 = (x - lo) / hi
t_1 = t_0 ** 2.0d0
code = (((lo / ((hi * hi) / x)) ** 3.0d0) + (t_0 * t_1)) / ((((x - lo) * (lo / (hi * hi))) ** 2.0d0) + (t_1 - (t_1 * (lo / hi))))
end function
public static double code(double lo, double hi, double x) {
return (x - lo) / (hi - lo);
}
↓
public static double code(double lo, double hi, double x) {
double t_0 = (x - lo) / hi;
double t_1 = Math.pow(t_0, 2.0);
return (Math.pow((lo / ((hi * hi) / x)), 3.0) + (t_0 * t_1)) / (Math.pow(((x - lo) * (lo / (hi * hi))), 2.0) + (t_1 - (t_1 * (lo / hi))));
}
def code(lo, hi, x):
return (x - lo) / (hi - lo)
↓
def code(lo, hi, x):
t_0 = (x - lo) / hi
t_1 = math.pow(t_0, 2.0)
return (math.pow((lo / ((hi * hi) / x)), 3.0) + (t_0 * t_1)) / (math.pow(((x - lo) * (lo / (hi * hi))), 2.0) + (t_1 - (t_1 * (lo / hi))))
function code(lo, hi, x)
return Float64(Float64(x - lo) / Float64(hi - lo))
end
↓
function code(lo, hi, x)
t_0 = Float64(Float64(x - lo) / hi)
t_1 = t_0 ^ 2.0
return Float64(Float64((Float64(lo / Float64(Float64(hi * hi) / x)) ^ 3.0) + Float64(t_0 * t_1)) / Float64((Float64(Float64(x - lo) * Float64(lo / Float64(hi * hi))) ^ 2.0) + Float64(t_1 - Float64(t_1 * Float64(lo / hi)))))
end
function tmp = code(lo, hi, x)
tmp = (x - lo) / (hi - lo);
end
↓
function tmp = code(lo, hi, x)
t_0 = (x - lo) / hi;
t_1 = t_0 ^ 2.0;
tmp = (((lo / ((hi * hi) / x)) ^ 3.0) + (t_0 * t_1)) / ((((x - lo) * (lo / (hi * hi))) ^ 2.0) + (t_1 - (t_1 * (lo / hi))));
end
code[lo_, hi_, x_] := N[(N[(x - lo), $MachinePrecision] / N[(hi - lo), $MachinePrecision]), $MachinePrecision]
↓
code[lo_, hi_, x_] := Block[{t$95$0 = N[(N[(x - lo), $MachinePrecision] / hi), $MachinePrecision]}, Block[{t$95$1 = N[Power[t$95$0, 2.0], $MachinePrecision]}, N[(N[(N[Power[N[(lo / N[(N[(hi * hi), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision], 3.0], $MachinePrecision] + N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] / N[(N[Power[N[(N[(x - lo), $MachinePrecision] * N[(lo / N[(hi * hi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 - N[(t$95$1 * N[(lo / hi), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\frac{x - lo}{hi - lo}
↓
\begin{array}{l}
t_0 := \frac{x - lo}{hi}\\
t_1 := {t_0}^{2}\\
\frac{{\left(\frac{lo}{\frac{hi \cdot hi}{x}}\right)}^{3} + t_0 \cdot t_1}{{\left(\left(x - lo\right) \cdot \frac{lo}{hi \cdot hi}\right)}^{2} + \left(t_1 - t_1 \cdot \frac{lo}{hi}\right)}
\end{array}