\[\left(\alpha > -1 \land \beta > -1\right) \land i > 0\]
\[\frac{\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) + 2} + 1}{2}
\]
↓
\[\begin{array}{l}
t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_1 := 2 + t_0\\
t_2 := 2 \cdot i + \left(\beta + 2\right)\\
t_3 := \beta + t_2\\
\mathbf{if}\;\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{t_0}}{t_1} \leq -0.5:\\
\;\;\;\;\frac{\mathsf{fma}\left(-2, \frac{i}{\frac{\alpha \cdot \alpha}{\beta + 2 \cdot i}}, \mathsf{fma}\left(-2, \frac{t_3}{\frac{\alpha}{\frac{i}{\alpha}}}, \frac{t_2 - \mathsf{fma}\left(-1, \beta, i \cdot -2\right)}{\alpha} - \frac{t_3}{\frac{\alpha \cdot \alpha}{t_2}}\right)\right)}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{\left(\beta - \alpha\right) \cdot \frac{\alpha + \beta}{\mathsf{fma}\left(2, i, \alpha + \beta\right)}}{t_1} + 1}{2}\\
\end{array}
\]
(FPCore (alpha beta i)
:precision binary64
(/
(+
(/
(/ (* (+ alpha beta) (- beta alpha)) (+ (+ alpha beta) (* 2.0 i)))
(+ (+ (+ alpha beta) (* 2.0 i)) 2.0))
1.0)
2.0))↓
(FPCore (alpha beta i)
:precision binary64
(let* ((t_0 (+ (+ alpha beta) (* 2.0 i)))
(t_1 (+ 2.0 t_0))
(t_2 (+ (* 2.0 i) (+ beta 2.0)))
(t_3 (+ beta t_2)))
(if (<= (/ (/ (* (+ alpha beta) (- beta alpha)) t_0) t_1) -0.5)
(/
(fma
-2.0
(/ i (/ (* alpha alpha) (+ beta (* 2.0 i))))
(fma
-2.0
(/ t_3 (/ alpha (/ i alpha)))
(-
(/ (- t_2 (fma -1.0 beta (* i -2.0))) alpha)
(/ t_3 (/ (* alpha alpha) t_2)))))
2.0)
(/
(+
(/ (* (- beta alpha) (/ (+ alpha beta) (fma 2.0 i (+ alpha beta)))) t_1)
1.0)
2.0))))double code(double alpha, double beta, double i) {
return (((((alpha + beta) * (beta - alpha)) / ((alpha + beta) + (2.0 * i))) / (((alpha + beta) + (2.0 * i)) + 2.0)) + 1.0) / 2.0;
}
↓
double code(double alpha, double beta, double i) {
double t_0 = (alpha + beta) + (2.0 * i);
double t_1 = 2.0 + t_0;
double t_2 = (2.0 * i) + (beta + 2.0);
double t_3 = beta + t_2;
double tmp;
if (((((alpha + beta) * (beta - alpha)) / t_0) / t_1) <= -0.5) {
tmp = fma(-2.0, (i / ((alpha * alpha) / (beta + (2.0 * i)))), fma(-2.0, (t_3 / (alpha / (i / alpha))), (((t_2 - fma(-1.0, beta, (i * -2.0))) / alpha) - (t_3 / ((alpha * alpha) / t_2))))) / 2.0;
} else {
tmp = ((((beta - alpha) * ((alpha + beta) / fma(2.0, i, (alpha + beta)))) / t_1) + 1.0) / 2.0;
}
return tmp;
}
function code(alpha, beta, i)
return Float64(Float64(Float64(Float64(Float64(Float64(alpha + beta) * Float64(beta - alpha)) / Float64(Float64(alpha + beta) + Float64(2.0 * i))) / Float64(Float64(Float64(alpha + beta) + Float64(2.0 * i)) + 2.0)) + 1.0) / 2.0)
end
↓
function code(alpha, beta, i)
t_0 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
t_1 = Float64(2.0 + t_0)
t_2 = Float64(Float64(2.0 * i) + Float64(beta + 2.0))
t_3 = Float64(beta + t_2)
tmp = 0.0
if (Float64(Float64(Float64(Float64(alpha + beta) * Float64(beta - alpha)) / t_0) / t_1) <= -0.5)
tmp = Float64(fma(-2.0, Float64(i / Float64(Float64(alpha * alpha) / Float64(beta + Float64(2.0 * i)))), fma(-2.0, Float64(t_3 / Float64(alpha / Float64(i / alpha))), Float64(Float64(Float64(t_2 - fma(-1.0, beta, Float64(i * -2.0))) / alpha) - Float64(t_3 / Float64(Float64(alpha * alpha) / t_2))))) / 2.0);
else
tmp = Float64(Float64(Float64(Float64(Float64(beta - alpha) * Float64(Float64(alpha + beta) / fma(2.0, i, Float64(alpha + beta)))) / t_1) + 1.0) / 2.0);
end
return tmp
end
code[alpha_, beta_, i_] := N[(N[(N[(N[(N[(N[(alpha + beta), $MachinePrecision] * N[(beta - alpha), $MachinePrecision]), $MachinePrecision] / N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision] + 2.0), $MachinePrecision]), $MachinePrecision] + 1.0), $MachinePrecision] / 2.0), $MachinePrecision]
↓
code[alpha_, beta_, i_] := Block[{t$95$0 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(2.0 + t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(2.0 * i), $MachinePrecision] + N[(beta + 2.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(beta + t$95$2), $MachinePrecision]}, If[LessEqual[N[(N[(N[(N[(alpha + beta), $MachinePrecision] * N[(beta - alpha), $MachinePrecision]), $MachinePrecision] / t$95$0), $MachinePrecision] / t$95$1), $MachinePrecision], -0.5], N[(N[(-2.0 * N[(i / N[(N[(alpha * alpha), $MachinePrecision] / N[(beta + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-2.0 * N[(t$95$3 / N[(alpha / N[(i / alpha), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t$95$2 - N[(-1.0 * beta + N[(i * -2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / alpha), $MachinePrecision] - N[(t$95$3 / N[(N[(alpha * alpha), $MachinePrecision] / t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision], N[(N[(N[(N[(N[(beta - alpha), $MachinePrecision] * N[(N[(alpha + beta), $MachinePrecision] / N[(2.0 * i + N[(alpha + beta), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$1), $MachinePrecision] + 1.0), $MachinePrecision] / 2.0), $MachinePrecision]]]]]]
\frac{\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) + 2} + 1}{2}
↓
\begin{array}{l}
t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_1 := 2 + t_0\\
t_2 := 2 \cdot i + \left(\beta + 2\right)\\
t_3 := \beta + t_2\\
\mathbf{if}\;\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{t_0}}{t_1} \leq -0.5:\\
\;\;\;\;\frac{\mathsf{fma}\left(-2, \frac{i}{\frac{\alpha \cdot \alpha}{\beta + 2 \cdot i}}, \mathsf{fma}\left(-2, \frac{t_3}{\frac{\alpha}{\frac{i}{\alpha}}}, \frac{t_2 - \mathsf{fma}\left(-1, \beta, i \cdot -2\right)}{\alpha} - \frac{t_3}{\frac{\alpha \cdot \alpha}{t_2}}\right)\right)}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{\left(\beta - \alpha\right) \cdot \frac{\alpha + \beta}{\mathsf{fma}\left(2, i, \alpha + \beta\right)}}{t_1} + 1}{2}\\
\end{array}
Alternatives
| Alternative 1 |
|---|
| Error | 1.4 |
|---|
| Cost | 9796 |
|---|
\[\begin{array}{l}
t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_1 := 2 + t_0\\
\mathbf{if}\;\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{t_0}}{t_1} \leq -0.99999996:\\
\;\;\;\;\frac{\frac{\left(\beta - \beta\right) + \left(i \cdot 4 + \left(2 + \beta \cdot 2\right)\right)}{\alpha}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{\left(\beta - \alpha\right) \cdot \frac{\alpha + \beta}{\mathsf{fma}\left(2, i, \alpha + \beta\right)}}{t_1} + 1}{2}\\
\end{array}
\]
| Alternative 2 |
|---|
| Error | 2.4 |
|---|
| Cost | 2756 |
|---|
\[\begin{array}{l}
t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_1 := 2 + t_0\\
\mathbf{if}\;\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{t_0}}{t_1} \leq -0.5:\\
\;\;\;\;\frac{\frac{\left(\beta - \beta\right) + \left(i \cdot 4 + \left(2 + \beta \cdot 2\right)\right)}{\alpha}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{1 + \frac{\beta}{t_1}}{2}\\
\end{array}
\]
| Alternative 3 |
|---|
| Error | 7.9 |
|---|
| Cost | 1484 |
|---|
\[\begin{array}{l}
t_0 := \frac{1 + \frac{\beta}{2 + \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{2}\\
\mathbf{if}\;\alpha \leq 1.4 \cdot 10^{+76}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;\alpha \leq 9 \cdot 10^{+97}:\\
\;\;\;\;\frac{\frac{2 + \beta \cdot 2}{\alpha}}{2}\\
\mathbf{elif}\;\alpha \leq 8.5 \cdot 10^{+156}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{\left(\beta + 2 \cdot i\right) + \left(2 \cdot i + \left(\beta + 2\right)\right)}{\alpha}}{2}\\
\end{array}
\]
| Alternative 4 |
|---|
| Error | 10.9 |
|---|
| Cost | 1357 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 3.45 \cdot 10^{+75} \lor \neg \left(\alpha \leq 3.15 \cdot 10^{+97}\right) \land \alpha \leq 1.95 \cdot 10^{+169}:\\
\;\;\;\;\frac{1 + \frac{\beta}{2 + \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{2 + \beta \cdot 2}{\alpha}}{2}\\
\end{array}
\]
| Alternative 5 |
|---|
| Error | 14.1 |
|---|
| Cost | 1101 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 1.55 \cdot 10^{+76} \lor \neg \left(\alpha \leq 2.3 \cdot 10^{+97}\right) \land \alpha \leq 1.6 \cdot 10^{+170}:\\
\;\;\;\;\frac{1 + \frac{\beta}{\beta + \left(\alpha + 2\right)}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{2 + \beta \cdot 2}{\alpha}}{2}\\
\end{array}
\]
| Alternative 6 |
|---|
| Error | 14.8 |
|---|
| Cost | 973 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 1.55 \cdot 10^{+76}:\\
\;\;\;\;\frac{1 + \frac{\beta}{\beta + 2}}{2}\\
\mathbf{elif}\;\alpha \leq 4.4 \cdot 10^{+98} \lor \neg \left(\alpha \leq 5.5 \cdot 10^{+170}\right):\\
\;\;\;\;\frac{\frac{2 + \beta \cdot 2}{\alpha}}{2}\\
\mathbf{else}:\\
\;\;\;\;0.5\\
\end{array}
\]
| Alternative 7 |
|---|
| Error | 15.7 |
|---|
| Cost | 708 |
|---|
\[\begin{array}{l}
\mathbf{if}\;i \leq 1.6 \cdot 10^{+168}:\\
\;\;\;\;\frac{1 + \frac{\beta}{\beta + 2}}{2}\\
\mathbf{else}:\\
\;\;\;\;0.5\\
\end{array}
\]
| Alternative 8 |
|---|
| Error | 17.5 |
|---|
| Cost | 196 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\beta \leq 1.38 \cdot 10^{+45}:\\
\;\;\;\;0.5\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}
\]
| Alternative 9 |
|---|
| Error | 25.1 |
|---|
| Cost | 64 |
|---|
\[0.5
\]