Math FPCore C Julia Wolfram TeX \[\frac{\left(-b_2\right) + \sqrt{b_2 \cdot b_2 - a \cdot c}}{a}
\]
↓
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -1.26 \cdot 10^{+142}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{elif}\;b_2 \leq 2.7 \cdot 10^{-48}:\\
\;\;\;\;\frac{\sqrt{b_2 \cdot b_2 + \mathsf{fma}\left(a, -c, \mathsf{fma}\left(a, -c, a \cdot c\right)\right)} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
(FPCore (a b_2 c)
:precision binary64
(/ (+ (- b_2) (sqrt (- (* b_2 b_2) (* a c)))) a)) ↓
(FPCore (a b_2 c)
:precision binary64
(if (<= b_2 -1.26e+142)
(* -2.0 (/ b_2 a))
(if (<= b_2 2.7e-48)
(/ (- (sqrt (+ (* b_2 b_2) (fma a (- c) (fma a (- c) (* a c))))) b_2) a)
(/ (* c -0.5) b_2)))) double code(double a, double b_2, double c) {
return (-b_2 + sqrt(((b_2 * b_2) - (a * c)))) / a;
}
↓
double code(double a, double b_2, double c) {
double tmp;
if (b_2 <= -1.26e+142) {
tmp = -2.0 * (b_2 / a);
} else if (b_2 <= 2.7e-48) {
tmp = (sqrt(((b_2 * b_2) + fma(a, -c, fma(a, -c, (a * c))))) - b_2) / a;
} else {
tmp = (c * -0.5) / b_2;
}
return tmp;
}
function code(a, b_2, c)
return Float64(Float64(Float64(-b_2) + sqrt(Float64(Float64(b_2 * b_2) - Float64(a * c)))) / a)
end
↓
function code(a, b_2, c)
tmp = 0.0
if (b_2 <= -1.26e+142)
tmp = Float64(-2.0 * Float64(b_2 / a));
elseif (b_2 <= 2.7e-48)
tmp = Float64(Float64(sqrt(Float64(Float64(b_2 * b_2) + fma(a, Float64(-c), fma(a, Float64(-c), Float64(a * c))))) - b_2) / a);
else
tmp = Float64(Float64(c * -0.5) / b_2);
end
return tmp
end
code[a_, b$95$2_, c_] := N[(N[((-b$95$2) + N[Sqrt[N[(N[(b$95$2 * b$95$2), $MachinePrecision] - N[(a * c), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / a), $MachinePrecision]
↓
code[a_, b$95$2_, c_] := If[LessEqual[b$95$2, -1.26e+142], N[(-2.0 * N[(b$95$2 / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[b$95$2, 2.7e-48], N[(N[(N[Sqrt[N[(N[(b$95$2 * b$95$2), $MachinePrecision] + N[(a * (-c) + N[(a * (-c) + N[(a * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] - b$95$2), $MachinePrecision] / a), $MachinePrecision], N[(N[(c * -0.5), $MachinePrecision] / b$95$2), $MachinePrecision]]]
\frac{\left(-b_2\right) + \sqrt{b_2 \cdot b_2 - a \cdot c}}{a}
↓
\begin{array}{l}
\mathbf{if}\;b_2 \leq -1.26 \cdot 10^{+142}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{elif}\;b_2 \leq 2.7 \cdot 10^{-48}:\\
\;\;\;\;\frac{\sqrt{b_2 \cdot b_2 + \mathsf{fma}\left(a, -c, \mathsf{fma}\left(a, -c, a \cdot c\right)\right)} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
Alternatives Alternative 1 Error 9.8 Cost 7368
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -1.26 \cdot 10^{+142}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{elif}\;b_2 \leq 2.7 \cdot 10^{-48}:\\
\;\;\;\;\frac{\sqrt{b_2 \cdot b_2 - a \cdot c} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 2 Error 13.4 Cost 7176
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -2.8 \cdot 10^{-65}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{elif}\;b_2 \leq 2.7 \cdot 10^{-48}:\\
\;\;\;\;\frac{\sqrt{a \cdot \left(-c\right)} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 3 Error 36.9 Cost 452
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq 2.6 \cdot 10^{-226}:\\
\;\;\;\;\frac{-b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 4 Error 22.9 Cost 452
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq 2.6 \cdot 10^{-226}:\\
\;\;\;\;b_2 \cdot \frac{-2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 5 Error 22.8 Cost 452
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq 2.6 \cdot 10^{-226}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 6 Error 53.2 Cost 388
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -2.7 \cdot 10^{-286}:\\
\;\;\;\;\frac{-b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{0}{a}\\
\end{array}
\]
Alternative 7 Error 56.3 Cost 192
\[\frac{0}{a}
\]