\[\left(\alpha > -1 \land \beta > -1\right) \land i > 0\]
\[\frac{\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{\left(\alpha + \beta\right) + 2 \cdot i}}{\left(\left(\alpha + \beta\right) + 2 \cdot i\right) + 2} + 1}{2}
\]
↓
\[\begin{array}{l}
t_0 := 2 \cdot i - \left(-2 - \beta\right)\\
t_1 := \frac{\beta + t_0}{\alpha}\\
t_2 := \left(\alpha + \beta\right) + 2 \cdot i\\
\mathbf{if}\;\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{t_2}}{2 + t_2} \leq -0.999995:\\
\;\;\;\;\frac{\frac{\beta}{\alpha} + \left(\frac{t_0}{\alpha} + \mathsf{fma}\left(-2, i \cdot \frac{\beta - i \cdot -2}{\alpha \cdot \alpha}, \mathsf{fma}\left(2, \frac{i}{\alpha}, \mathsf{fma}\left(-2, \frac{i}{\alpha} \cdot t_1, t_1 \cdot \frac{i \cdot -2 + \left(-2 - \beta\right)}{\alpha}\right)\right)\right)\right)}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\mathsf{fma}\left(\frac{\alpha + \beta}{\beta + \mathsf{fma}\left(2, i, \alpha\right)}, \frac{\beta - \alpha}{\alpha + \left(\beta + \mathsf{fma}\left(2, i, 2\right)\right)}, 1\right)}{2}\\
\end{array}
\]
(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 (- (* 2.0 i) (- -2.0 beta)))
(t_1 (/ (+ beta t_0) alpha))
(t_2 (+ (+ alpha beta) (* 2.0 i))))
(if (<= (/ (/ (* (+ alpha beta) (- beta alpha)) t_2) (+ 2.0 t_2)) -0.999995)
(/
(+
(/ beta alpha)
(+
(/ t_0 alpha)
(fma
-2.0
(* i (/ (- beta (* i -2.0)) (* alpha alpha)))
(fma
2.0
(/ i alpha)
(fma
-2.0
(* (/ i alpha) t_1)
(* t_1 (/ (+ (* i -2.0) (- -2.0 beta)) alpha)))))))
2.0)
(/
(fma
(/ (+ alpha beta) (+ beta (fma 2.0 i alpha)))
(/ (- beta alpha) (+ alpha (+ beta (fma 2.0 i 2.0))))
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 = (2.0 * i) - (-2.0 - beta);
double t_1 = (beta + t_0) / alpha;
double t_2 = (alpha + beta) + (2.0 * i);
double tmp;
if (((((alpha + beta) * (beta - alpha)) / t_2) / (2.0 + t_2)) <= -0.999995) {
tmp = ((beta / alpha) + ((t_0 / alpha) + fma(-2.0, (i * ((beta - (i * -2.0)) / (alpha * alpha))), fma(2.0, (i / alpha), fma(-2.0, ((i / alpha) * t_1), (t_1 * (((i * -2.0) + (-2.0 - beta)) / alpha))))))) / 2.0;
} else {
tmp = fma(((alpha + beta) / (beta + fma(2.0, i, alpha))), ((beta - alpha) / (alpha + (beta + fma(2.0, i, 2.0)))), 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(2.0 * i) - Float64(-2.0 - beta))
t_1 = Float64(Float64(beta + t_0) / alpha)
t_2 = Float64(Float64(alpha + beta) + Float64(2.0 * i))
tmp = 0.0
if (Float64(Float64(Float64(Float64(alpha + beta) * Float64(beta - alpha)) / t_2) / Float64(2.0 + t_2)) <= -0.999995)
tmp = Float64(Float64(Float64(beta / alpha) + Float64(Float64(t_0 / alpha) + fma(-2.0, Float64(i * Float64(Float64(beta - Float64(i * -2.0)) / Float64(alpha * alpha))), fma(2.0, Float64(i / alpha), fma(-2.0, Float64(Float64(i / alpha) * t_1), Float64(t_1 * Float64(Float64(Float64(i * -2.0) + Float64(-2.0 - beta)) / alpha))))))) / 2.0);
else
tmp = Float64(fma(Float64(Float64(alpha + beta) / Float64(beta + fma(2.0, i, alpha))), Float64(Float64(beta - alpha) / Float64(alpha + Float64(beta + fma(2.0, i, 2.0)))), 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[(2.0 * i), $MachinePrecision] - N[(-2.0 - beta), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(beta + t$95$0), $MachinePrecision] / alpha), $MachinePrecision]}, Block[{t$95$2 = N[(N[(alpha + beta), $MachinePrecision] + N[(2.0 * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(N[(N[(alpha + beta), $MachinePrecision] * N[(beta - alpha), $MachinePrecision]), $MachinePrecision] / t$95$2), $MachinePrecision] / N[(2.0 + t$95$2), $MachinePrecision]), $MachinePrecision], -0.999995], N[(N[(N[(beta / alpha), $MachinePrecision] + N[(N[(t$95$0 / alpha), $MachinePrecision] + N[(-2.0 * N[(i * N[(N[(beta - N[(i * -2.0), $MachinePrecision]), $MachinePrecision] / N[(alpha * alpha), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(2.0 * N[(i / alpha), $MachinePrecision] + N[(-2.0 * N[(N[(i / alpha), $MachinePrecision] * t$95$1), $MachinePrecision] + N[(t$95$1 * N[(N[(N[(i * -2.0), $MachinePrecision] + N[(-2.0 - beta), $MachinePrecision]), $MachinePrecision] / alpha), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision], N[(N[(N[(N[(alpha + beta), $MachinePrecision] / N[(beta + N[(2.0 * i + alpha), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(N[(beta - alpha), $MachinePrecision] / N[(alpha + N[(beta + N[(2.0 * i + 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $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 := 2 \cdot i - \left(-2 - \beta\right)\\
t_1 := \frac{\beta + t_0}{\alpha}\\
t_2 := \left(\alpha + \beta\right) + 2 \cdot i\\
\mathbf{if}\;\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{t_2}}{2 + t_2} \leq -0.999995:\\
\;\;\;\;\frac{\frac{\beta}{\alpha} + \left(\frac{t_0}{\alpha} + \mathsf{fma}\left(-2, i \cdot \frac{\beta - i \cdot -2}{\alpha \cdot \alpha}, \mathsf{fma}\left(2, \frac{i}{\alpha}, \mathsf{fma}\left(-2, \frac{i}{\alpha} \cdot t_1, t_1 \cdot \frac{i \cdot -2 + \left(-2 - \beta\right)}{\alpha}\right)\right)\right)\right)}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\mathsf{fma}\left(\frac{\alpha + \beta}{\beta + \mathsf{fma}\left(2, i, \alpha\right)}, \frac{\beta - \alpha}{\alpha + \left(\beta + \mathsf{fma}\left(2, i, 2\right)\right)}, 1\right)}{2}\\
\end{array}
Alternatives
| Alternative 1 |
|---|
| Error | 2.26% |
|---|
| Cost | 22340 |
|---|
\[\begin{array}{l}
t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
\mathbf{if}\;\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{t_0}}{2 + t_0} \leq -0.999995:\\
\;\;\;\;\frac{\frac{\left(\beta - \beta\right) + \left(\left(2 + \beta \cdot 2\right) + i \cdot 4\right)}{\alpha}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\mathsf{fma}\left(\frac{\alpha + \beta}{\beta + \mathsf{fma}\left(2, i, \alpha\right)}, \frac{\beta - \alpha}{\alpha + \left(\beta + \mathsf{fma}\left(2, i, 2\right)\right)}, 1\right)}{2}\\
\end{array}
\]
| Alternative 2 |
|---|
| Error | 3.16% |
|---|
| Cost | 2756 |
|---|
\[\begin{array}{l}
t_0 := \left(\alpha + \beta\right) + 2 \cdot i\\
t_1 := 2 + t_0\\
\mathbf{if}\;\frac{\frac{\left(\alpha + \beta\right) \cdot \left(\beta - \alpha\right)}{t_0}}{t_1} \leq -0.999995:\\
\;\;\;\;\frac{\frac{\left(\beta - \beta\right) + \left(\left(2 + \beta \cdot 2\right) + i \cdot 4\right)}{\alpha}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{1 + \frac{\beta - \alpha}{t_1}}{2}\\
\end{array}
\]
| Alternative 3 |
|---|
| Error | 16.46% |
|---|
| Cost | 1229 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 2.15 \cdot 10^{+138} \lor \neg \left(\alpha \leq 2.6 \cdot 10^{+166}\right) \land \alpha \leq 4.5 \cdot 10^{+201}:\\
\;\;\;\;\frac{1 + \frac{\beta}{\beta + \left(2 + 2 \cdot i\right)}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{2 - -2 \cdot \left(\beta + i\right)}{\alpha}}{2}\\
\end{array}
\]
| Alternative 4 |
|---|
| Error | 10.75% |
|---|
| Cost | 1220 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 1.1 \cdot 10^{+134}:\\
\;\;\;\;\frac{1 + \frac{\beta - \alpha}{2 + \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{\beta + \left(i \cdot 4 - \left(-2 - \beta\right)\right)}{\alpha}}{2}\\
\end{array}
\]
| Alternative 5 |
|---|
| Error | 11.57% |
|---|
| Cost | 1092 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 2 \cdot 10^{+138}:\\
\;\;\;\;\frac{1 + \frac{\beta}{2 + \left(\left(\alpha + \beta\right) + 2 \cdot i\right)}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{\beta + \left(i \cdot 4 - \left(-2 - \beta\right)\right)}{\alpha}}{2}\\
\end{array}
\]
| Alternative 6 |
|---|
| Error | 11.57% |
|---|
| Cost | 964 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 1.85 \cdot 10^{+138}:\\
\;\;\;\;\frac{1 + \frac{\beta}{\beta + \left(2 + 2 \cdot i\right)}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{\beta + \left(i \cdot 4 - \left(-2 - \beta\right)\right)}{\alpha}}{2}\\
\end{array}
\]
| Alternative 7 |
|---|
| Error | 24.31% |
|---|
| Cost | 836 |
|---|
\[\begin{array}{l}
\mathbf{if}\;2 \cdot i \leq 5 \cdot 10^{+114}:\\
\;\;\;\;\frac{1 + \frac{\beta}{\beta + 2}}{2}\\
\mathbf{else}:\\
\;\;\;\;0.5\\
\end{array}
\]
| Alternative 8 |
|---|
| Error | 21.67% |
|---|
| Cost | 836 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 1.8 \cdot 10^{+138}:\\
\;\;\;\;\frac{1 + \frac{\beta}{\beta + 2}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{2 - -2 \cdot \left(\beta + i\right)}{\alpha}}{2}\\
\end{array}
\]
| Alternative 9 |
|---|
| Error | 22.38% |
|---|
| Cost | 708 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\alpha \leq 1.8 \cdot 10^{+138}:\\
\;\;\;\;\frac{1 + \frac{\beta}{\beta + 2}}{2}\\
\mathbf{else}:\\
\;\;\;\;\frac{\frac{2 + \beta \cdot 2}{\alpha}}{2}\\
\end{array}
\]
| Alternative 10 |
|---|
| Error | 27.46% |
|---|
| Cost | 196 |
|---|
\[\begin{array}{l}
\mathbf{if}\;\beta \leq 1.65 \cdot 10^{+59}:\\
\;\;\;\;0.5\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}
\]
| Alternative 11 |
|---|
| Error | 67.75% |
|---|
| Cost | 64 |
|---|
\[1
\]