Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{e^{x \cdot \log \left(\frac{x}{x + y}\right)}}{x}
\]
↓
\[\begin{array}{l}
t_0 := \frac{x}{x + y}\\
t_1 := \log t_0\\
t_2 := \frac{e^{x \cdot t_1}}{x}\\
t_3 := e^{-y}\\
\mathbf{if}\;t_2 \leq -1 \cdot 10^{+19}:\\
\;\;\;\;\frac{1}{x}\\
\mathbf{elif}\;t_2 \leq -5 \cdot 10^{-290}:\\
\;\;\;\;\frac{t_3 + 0.5 \cdot \frac{t_3}{\frac{x}{y \cdot y}}}{x}\\
\mathbf{elif}\;t_2 \leq 0:\\
\;\;\;\;\frac{{\left(e^{x}\right)}^{t_1}}{x}\\
\mathbf{elif}\;t_2 \leq 10^{-55}:\\
\;\;\;\;\frac{t_3}{x}\\
\mathbf{else}:\\
\;\;\;\;\frac{{t_0}^{x}}{x}\\
\end{array}
\]
(FPCore (x y) :precision binary64 (/ (exp (* x (log (/ x (+ x y))))) x)) ↓
(FPCore (x y)
:precision binary64
(let* ((t_0 (/ x (+ x y)))
(t_1 (log t_0))
(t_2 (/ (exp (* x t_1)) x))
(t_3 (exp (- y))))
(if (<= t_2 -1e+19)
(/ 1.0 x)
(if (<= t_2 -5e-290)
(/ (+ t_3 (* 0.5 (/ t_3 (/ x (* y y))))) x)
(if (<= t_2 0.0)
(/ (pow (exp x) t_1) x)
(if (<= t_2 1e-55) (/ t_3 x) (/ (pow t_0 x) x))))))) double code(double x, double y) {
return exp((x * log((x / (x + y))))) / x;
}
↓
double code(double x, double y) {
double t_0 = x / (x + y);
double t_1 = log(t_0);
double t_2 = exp((x * t_1)) / x;
double t_3 = exp(-y);
double tmp;
if (t_2 <= -1e+19) {
tmp = 1.0 / x;
} else if (t_2 <= -5e-290) {
tmp = (t_3 + (0.5 * (t_3 / (x / (y * y))))) / x;
} else if (t_2 <= 0.0) {
tmp = pow(exp(x), t_1) / x;
} else if (t_2 <= 1e-55) {
tmp = t_3 / x;
} else {
tmp = pow(t_0, x) / x;
}
return tmp;
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = exp((x * log((x / (x + y))))) / x
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = x / (x + y)
t_1 = log(t_0)
t_2 = exp((x * t_1)) / x
t_3 = exp(-y)
if (t_2 <= (-1d+19)) then
tmp = 1.0d0 / x
else if (t_2 <= (-5d-290)) then
tmp = (t_3 + (0.5d0 * (t_3 / (x / (y * y))))) / x
else if (t_2 <= 0.0d0) then
tmp = (exp(x) ** t_1) / x
else if (t_2 <= 1d-55) then
tmp = t_3 / x
else
tmp = (t_0 ** x) / x
end if
code = tmp
end function
public static double code(double x, double y) {
return Math.exp((x * Math.log((x / (x + y))))) / x;
}
↓
public static double code(double x, double y) {
double t_0 = x / (x + y);
double t_1 = Math.log(t_0);
double t_2 = Math.exp((x * t_1)) / x;
double t_3 = Math.exp(-y);
double tmp;
if (t_2 <= -1e+19) {
tmp = 1.0 / x;
} else if (t_2 <= -5e-290) {
tmp = (t_3 + (0.5 * (t_3 / (x / (y * y))))) / x;
} else if (t_2 <= 0.0) {
tmp = Math.pow(Math.exp(x), t_1) / x;
} else if (t_2 <= 1e-55) {
tmp = t_3 / x;
} else {
tmp = Math.pow(t_0, x) / x;
}
return tmp;
}
def code(x, y):
return math.exp((x * math.log((x / (x + y))))) / x
↓
def code(x, y):
t_0 = x / (x + y)
t_1 = math.log(t_0)
t_2 = math.exp((x * t_1)) / x
t_3 = math.exp(-y)
tmp = 0
if t_2 <= -1e+19:
tmp = 1.0 / x
elif t_2 <= -5e-290:
tmp = (t_3 + (0.5 * (t_3 / (x / (y * y))))) / x
elif t_2 <= 0.0:
tmp = math.pow(math.exp(x), t_1) / x
elif t_2 <= 1e-55:
tmp = t_3 / x
else:
tmp = math.pow(t_0, x) / x
return tmp
function code(x, y)
return Float64(exp(Float64(x * log(Float64(x / Float64(x + y))))) / x)
end
↓
function code(x, y)
t_0 = Float64(x / Float64(x + y))
t_1 = log(t_0)
t_2 = Float64(exp(Float64(x * t_1)) / x)
t_3 = exp(Float64(-y))
tmp = 0.0
if (t_2 <= -1e+19)
tmp = Float64(1.0 / x);
elseif (t_2 <= -5e-290)
tmp = Float64(Float64(t_3 + Float64(0.5 * Float64(t_3 / Float64(x / Float64(y * y))))) / x);
elseif (t_2 <= 0.0)
tmp = Float64((exp(x) ^ t_1) / x);
elseif (t_2 <= 1e-55)
tmp = Float64(t_3 / x);
else
tmp = Float64((t_0 ^ x) / x);
end
return tmp
end
function tmp = code(x, y)
tmp = exp((x * log((x / (x + y))))) / x;
end
↓
function tmp_2 = code(x, y)
t_0 = x / (x + y);
t_1 = log(t_0);
t_2 = exp((x * t_1)) / x;
t_3 = exp(-y);
tmp = 0.0;
if (t_2 <= -1e+19)
tmp = 1.0 / x;
elseif (t_2 <= -5e-290)
tmp = (t_3 + (0.5 * (t_3 / (x / (y * y))))) / x;
elseif (t_2 <= 0.0)
tmp = (exp(x) ^ t_1) / x;
elseif (t_2 <= 1e-55)
tmp = t_3 / x;
else
tmp = (t_0 ^ x) / x;
end
tmp_2 = tmp;
end
code[x_, y_] := N[(N[Exp[N[(x * N[Log[N[(x / N[(x + y), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / x), $MachinePrecision]
↓
code[x_, y_] := Block[{t$95$0 = N[(x / N[(x + y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Log[t$95$0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Exp[N[(x * t$95$1), $MachinePrecision]], $MachinePrecision] / x), $MachinePrecision]}, Block[{t$95$3 = N[Exp[(-y)], $MachinePrecision]}, If[LessEqual[t$95$2, -1e+19], N[(1.0 / x), $MachinePrecision], If[LessEqual[t$95$2, -5e-290], N[(N[(t$95$3 + N[(0.5 * N[(t$95$3 / N[(x / N[(y * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / x), $MachinePrecision], If[LessEqual[t$95$2, 0.0], N[(N[Power[N[Exp[x], $MachinePrecision], t$95$1], $MachinePrecision] / x), $MachinePrecision], If[LessEqual[t$95$2, 1e-55], N[(t$95$3 / x), $MachinePrecision], N[(N[Power[t$95$0, x], $MachinePrecision] / x), $MachinePrecision]]]]]]]]]
\frac{e^{x \cdot \log \left(\frac{x}{x + y}\right)}}{x}
↓
\begin{array}{l}
t_0 := \frac{x}{x + y}\\
t_1 := \log t_0\\
t_2 := \frac{e^{x \cdot t_1}}{x}\\
t_3 := e^{-y}\\
\mathbf{if}\;t_2 \leq -1 \cdot 10^{+19}:\\
\;\;\;\;\frac{1}{x}\\
\mathbf{elif}\;t_2 \leq -5 \cdot 10^{-290}:\\
\;\;\;\;\frac{t_3 + 0.5 \cdot \frac{t_3}{\frac{x}{y \cdot y}}}{x}\\
\mathbf{elif}\;t_2 \leq 0:\\
\;\;\;\;\frac{{\left(e^{x}\right)}^{t_1}}{x}\\
\mathbf{elif}\;t_2 \leq 10^{-55}:\\
\;\;\;\;\frac{t_3}{x}\\
\mathbf{else}:\\
\;\;\;\;\frac{{t_0}^{x}}{x}\\
\end{array}