\[\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1}
\]
↓
\[\begin{array}{l}
t_0 := \mathsf{fma}\left(i, 2, \beta + \alpha\right)\\
t_1 := \beta + i \cdot 2\\
\mathbf{if}\;\beta \leq 8.2 \cdot 10^{+136}:\\
\;\;\;\;\left(\frac{i}{t_1} \cdot \frac{\beta + i}{t_1}\right) \cdot 0.25\\
\mathbf{else}:\\
\;\;\;\;\left(\frac{i}{t_0} \cdot \frac{i + \left(\beta + \alpha\right)}{t_0}\right) \cdot \left(\frac{i}{\frac{\beta \cdot \beta}{i + \alpha}} + \left(\left(\frac{\alpha}{\beta} + \frac{i}{\beta}\right) - \frac{i + \alpha}{\frac{\beta \cdot \beta}{\mathsf{fma}\left(4, i, 2 \cdot \alpha\right)}}\right)\right)\\
\end{array}
\]
double code(double alpha, double beta, double i) {
return (((i * ((alpha + beta) + i)) * ((beta * alpha) + (i * ((alpha + beta) + i)))) / (((alpha + beta) + (2.0 * i)) * ((alpha + beta) + (2.0 * i)))) / ((((alpha + beta) + (2.0 * i)) * ((alpha + beta) + (2.0 * i))) - 1.0);
}
↓
double code(double alpha, double beta, double i) {
double t_0 = fma(i, 2.0, (beta + alpha));
double t_1 = beta + (i * 2.0);
double tmp;
if (beta <= 8.2e+136) {
tmp = ((i / t_1) * ((beta + i) / t_1)) * 0.25;
} else {
tmp = ((i / t_0) * ((i + (beta + alpha)) / t_0)) * ((i / ((beta * beta) / (i + alpha))) + (((alpha / beta) + (i / beta)) - ((i + alpha) / ((beta * beta) / fma(4.0, i, (2.0 * alpha))))));
}
return tmp;
}
function code(alpha, beta, i)
return Float64(Float64(Float64(Float64(i * Float64(Float64(alpha + beta) + i)) * Float64(Float64(beta * alpha) + Float64(i * Float64(Float64(alpha + beta) + i)))) / Float64(Float64(Float64(alpha + beta) + Float64(2.0 * i)) * Float64(Float64(alpha + beta) + Float64(2.0 * i)))) / Float64(Float64(Float64(Float64(alpha + beta) + Float64(2.0 * i)) * Float64(Float64(alpha + beta) + Float64(2.0 * i))) - 1.0))
end
↓
function code(alpha, beta, i)
t_0 = fma(i, 2.0, Float64(beta + alpha))
t_1 = Float64(beta + Float64(i * 2.0))
tmp = 0.0
if (beta <= 8.2e+136)
tmp = Float64(Float64(Float64(i / t_1) * Float64(Float64(beta + i) / t_1)) * 0.25);
else
tmp = Float64(Float64(Float64(i / t_0) * Float64(Float64(i + Float64(beta + alpha)) / t_0)) * Float64(Float64(i / Float64(Float64(beta * beta) / Float64(i + alpha))) + Float64(Float64(Float64(alpha / beta) + Float64(i / beta)) - Float64(Float64(i + alpha) / Float64(Float64(beta * beta) / fma(4.0, i, Float64(2.0 * alpha)))))));
end
return tmp
end
code[alpha_, beta_, i_] := N[(N[(N[(N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision] * N[(N[(beta * alpha), $MachinePrecision] + N[(i * N[(N[(alpha + beta), $MachinePrecision] + i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision] * N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision] * N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision]
↓
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(i * 2.0 + N[(beta + alpha), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(beta + N[(i * 2.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[beta, 8.2e+136], N[(N[(N[(i / t$95$1), $MachinePrecision] * N[(N[(beta + i), $MachinePrecision] / t$95$1), $MachinePrecision]), $MachinePrecision] * 0.25), $MachinePrecision], N[(N[(N[(i / t$95$0), $MachinePrecision] * N[(N[(i + N[(beta + alpha), $MachinePrecision]), $MachinePrecision] / t$95$0), $MachinePrecision]), $MachinePrecision] * N[(N[(i / N[(N[(beta * beta), $MachinePrecision] / N[(i + alpha), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(alpha / beta), $MachinePrecision] + N[(i / beta), $MachinePrecision]), $MachinePrecision] - N[(N[(i + alpha), $MachinePrecision] / N[(N[(beta * beta), $MachinePrecision] / N[(4.0 * i + N[(2.0 * alpha), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\frac{\frac{\left(i \cdot \left(\left(\alpha + \beta\right) + i\right)\right) \cdot \left(\beta \cdot \alpha + i \cdot \left(\left(\alpha + \beta\right) + i\right)\right)}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) \cdot \left(\left(\alpha + \beta\right) + 2 \cdot i\right) - 1}
↓
\begin{array}{l}
t_0 := \mathsf{fma}\left(i, 2, \beta + \alpha\right)\\
t_1 := \beta + i \cdot 2\\
\mathbf{if}\;\beta \leq 8.2 \cdot 10^{+136}:\\
\;\;\;\;\left(\frac{i}{t_1} \cdot \frac{\beta + i}{t_1}\right) \cdot 0.25\\
\mathbf{else}:\\
\;\;\;\;\left(\frac{i}{t_0} \cdot \frac{i + \left(\beta + \alpha\right)}{t_0}\right) \cdot \left(\frac{i}{\frac{\beta \cdot \beta}{i + \alpha}} + \left(\left(\frac{\alpha}{\beta} + \frac{i}{\beta}\right) - \frac{i + \alpha}{\frac{\beta \cdot \beta}{\mathsf{fma}\left(4, i, 2 \cdot \alpha\right)}}\right)\right)\\
\end{array}