Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{\left(-b_2\right) + \sqrt{b_2 \cdot b_2 - a \cdot c}}{a}
\]
↓
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -6.5 \cdot 10^{+53}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{elif}\;b_2 \leq 1.3 \cdot 10^{-9}:\\
\;\;\;\;\frac{{\left(b_2 \cdot b_2 - a \cdot c\right)}^{0.5} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
(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 -6.5e+53)
(* -2.0 (/ b_2 a))
(if (<= b_2 1.3e-9)
(/ (- (pow (- (* b_2 b_2) (* a c)) 0.5) 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 <= -6.5e+53) {
tmp = -2.0 * (b_2 / a);
} else if (b_2 <= 1.3e-9) {
tmp = (pow(((b_2 * b_2) - (a * c)), 0.5) - b_2) / a;
} else {
tmp = (c * -0.5) / b_2;
}
return tmp;
}
real(8) function code(a, b_2, c)
real(8), intent (in) :: a
real(8), intent (in) :: b_2
real(8), intent (in) :: c
code = (-b_2 + sqrt(((b_2 * b_2) - (a * c)))) / a
end function
↓
real(8) function code(a, b_2, c)
real(8), intent (in) :: a
real(8), intent (in) :: b_2
real(8), intent (in) :: c
real(8) :: tmp
if (b_2 <= (-6.5d+53)) then
tmp = (-2.0d0) * (b_2 / a)
else if (b_2 <= 1.3d-9) then
tmp = ((((b_2 * b_2) - (a * c)) ** 0.5d0) - b_2) / a
else
tmp = (c * (-0.5d0)) / b_2
end if
code = tmp
end function
public static double code(double a, double b_2, double c) {
return (-b_2 + Math.sqrt(((b_2 * b_2) - (a * c)))) / a;
}
↓
public static double code(double a, double b_2, double c) {
double tmp;
if (b_2 <= -6.5e+53) {
tmp = -2.0 * (b_2 / a);
} else if (b_2 <= 1.3e-9) {
tmp = (Math.pow(((b_2 * b_2) - (a * c)), 0.5) - b_2) / a;
} else {
tmp = (c * -0.5) / b_2;
}
return tmp;
}
def code(a, b_2, c):
return (-b_2 + math.sqrt(((b_2 * b_2) - (a * c)))) / a
↓
def code(a, b_2, c):
tmp = 0
if b_2 <= -6.5e+53:
tmp = -2.0 * (b_2 / a)
elif b_2 <= 1.3e-9:
tmp = (math.pow(((b_2 * b_2) - (a * c)), 0.5) - 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 <= -6.5e+53)
tmp = Float64(-2.0 * Float64(b_2 / a));
elseif (b_2 <= 1.3e-9)
tmp = Float64(Float64((Float64(Float64(b_2 * b_2) - Float64(a * c)) ^ 0.5) - b_2) / a);
else
tmp = Float64(Float64(c * -0.5) / b_2);
end
return tmp
end
function tmp = code(a, b_2, c)
tmp = (-b_2 + sqrt(((b_2 * b_2) - (a * c)))) / a;
end
↓
function tmp_2 = code(a, b_2, c)
tmp = 0.0;
if (b_2 <= -6.5e+53)
tmp = -2.0 * (b_2 / a);
elseif (b_2 <= 1.3e-9)
tmp = ((((b_2 * b_2) - (a * c)) ^ 0.5) - b_2) / a;
else
tmp = (c * -0.5) / b_2;
end
tmp_2 = 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, -6.5e+53], N[(-2.0 * N[(b$95$2 / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[b$95$2, 1.3e-9], N[(N[(N[Power[N[(N[(b$95$2 * b$95$2), $MachinePrecision] - N[(a * c), $MachinePrecision]), $MachinePrecision], 0.5], $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 -6.5 \cdot 10^{+53}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{elif}\;b_2 \leq 1.3 \cdot 10^{-9}:\\
\;\;\;\;\frac{{\left(b_2 \cdot b_2 - a \cdot c\right)}^{0.5} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
Alternatives Alternative 1 Accuracy 83.1% Cost 7368
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -6.5 \cdot 10^{+53}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{elif}\;b_2 \leq 5.6 \cdot 10^{-9}:\\
\;\;\;\;\frac{\sqrt{b_2 \cdot b_2 - a \cdot c} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 2 Accuracy 77.2% Cost 7240
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -4.5 \cdot 10^{-140}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a} + 0.5 \cdot \frac{c}{b_2}\\
\mathbf{elif}\;b_2 \leq 1.12 \cdot 10^{-14}:\\
\;\;\;\;\frac{{\left(a \cdot \left(-c\right)\right)}^{0.5} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 3 Accuracy 77.2% Cost 7176
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -4.5 \cdot 10^{-140}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a} + 0.5 \cdot \frac{c}{b_2}\\
\mathbf{elif}\;b_2 \leq 9.2 \cdot 10^{-15}:\\
\;\;\;\;\frac{\sqrt{a \cdot \left(-c\right)} - b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 4 Accuracy 39.0% Cost 452
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -1 \cdot 10^{-309}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;0\\
\end{array}
\]
Alternative 5 Accuracy 64.8% Cost 452
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq 1.05 \cdot 10^{-187}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;c \cdot \frac{-0.5}{b_2}\\
\end{array}
\]
Alternative 6 Accuracy 64.9% Cost 452
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq 1.05 \cdot 10^{-187}:\\
\;\;\;\;-2 \cdot \frac{b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;\frac{c \cdot -0.5}{b_2}\\
\end{array}
\]
Alternative 7 Accuracy 17.3% Cost 388
\[\begin{array}{l}
\mathbf{if}\;b_2 \leq -1 \cdot 10^{-309}:\\
\;\;\;\;\frac{-b_2}{a}\\
\mathbf{else}:\\
\;\;\;\;0\\
\end{array}
\]
Alternative 8 Accuracy 12.5% Cost 64
\[0
\]