\[\left(\left(1.1102230246251565 \cdot 10^{-16} < a \land a < 9007199254740992\right) \land \left(1.1102230246251565 \cdot 10^{-16} < b \land b < 9007199254740992\right)\right) \land \left(1.1102230246251565 \cdot 10^{-16} < c \land c < 9007199254740992\right)\]
Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{\left(-b\right) + \sqrt{b \cdot b - \left(4 \cdot a\right) \cdot c}}{2 \cdot a}
\]
↓
\[\begin{array}{l}
t_0 := \frac{{c}^{4}}{{b}^{6}}\\
-1 \cdot \frac{c}{b} + \left(\left(-2 \cdot \left({a}^{2} \cdot \frac{{c}^{3}}{{b}^{5}}\right) + -0.25 \cdot \left(\left(16 \cdot t_0 + 4 \cdot t_0\right) \cdot \frac{{a}^{3}}{b}\right)\right) + -1 \cdot \left(a \cdot \frac{{c}^{2}}{{b}^{3}}\right)\right)
\end{array}
\]
(FPCore (a b c)
:precision binary64
(/ (+ (- b) (sqrt (- (* b b) (* (* 4.0 a) c)))) (* 2.0 a))) ↓
(FPCore (a b c)
:precision binary64
(let* ((t_0 (/ (pow c 4.0) (pow b 6.0))))
(+
(* -1.0 (/ c b))
(+
(+
(* -2.0 (* (pow a 2.0) (/ (pow c 3.0) (pow b 5.0))))
(* -0.25 (* (+ (* 16.0 t_0) (* 4.0 t_0)) (/ (pow a 3.0) b))))
(* -1.0 (* a (/ (pow c 2.0) (pow b 3.0)))))))) double code(double a, double b, double c) {
return (-b + sqrt(((b * b) - ((4.0 * a) * c)))) / (2.0 * a);
}
↓
double code(double a, double b, double c) {
double t_0 = pow(c, 4.0) / pow(b, 6.0);
return (-1.0 * (c / b)) + (((-2.0 * (pow(a, 2.0) * (pow(c, 3.0) / pow(b, 5.0)))) + (-0.25 * (((16.0 * t_0) + (4.0 * t_0)) * (pow(a, 3.0) / b)))) + (-1.0 * (a * (pow(c, 2.0) / pow(b, 3.0)))));
}
real(8) function code(a, b, c)
real(8), intent (in) :: a
real(8), intent (in) :: b
real(8), intent (in) :: c
code = (-b + sqrt(((b * b) - ((4.0d0 * a) * c)))) / (2.0d0 * a)
end function
↓
real(8) function code(a, b, c)
real(8), intent (in) :: a
real(8), intent (in) :: b
real(8), intent (in) :: c
real(8) :: t_0
t_0 = (c ** 4.0d0) / (b ** 6.0d0)
code = ((-1.0d0) * (c / b)) + ((((-2.0d0) * ((a ** 2.0d0) * ((c ** 3.0d0) / (b ** 5.0d0)))) + ((-0.25d0) * (((16.0d0 * t_0) + (4.0d0 * t_0)) * ((a ** 3.0d0) / b)))) + ((-1.0d0) * (a * ((c ** 2.0d0) / (b ** 3.0d0)))))
end function
public static double code(double a, double b, double c) {
return (-b + Math.sqrt(((b * b) - ((4.0 * a) * c)))) / (2.0 * a);
}
↓
public static double code(double a, double b, double c) {
double t_0 = Math.pow(c, 4.0) / Math.pow(b, 6.0);
return (-1.0 * (c / b)) + (((-2.0 * (Math.pow(a, 2.0) * (Math.pow(c, 3.0) / Math.pow(b, 5.0)))) + (-0.25 * (((16.0 * t_0) + (4.0 * t_0)) * (Math.pow(a, 3.0) / b)))) + (-1.0 * (a * (Math.pow(c, 2.0) / Math.pow(b, 3.0)))));
}
def code(a, b, c):
return (-b + math.sqrt(((b * b) - ((4.0 * a) * c)))) / (2.0 * a)
↓
def code(a, b, c):
t_0 = math.pow(c, 4.0) / math.pow(b, 6.0)
return (-1.0 * (c / b)) + (((-2.0 * (math.pow(a, 2.0) * (math.pow(c, 3.0) / math.pow(b, 5.0)))) + (-0.25 * (((16.0 * t_0) + (4.0 * t_0)) * (math.pow(a, 3.0) / b)))) + (-1.0 * (a * (math.pow(c, 2.0) / math.pow(b, 3.0)))))
function code(a, b, c)
return Float64(Float64(Float64(-b) + sqrt(Float64(Float64(b * b) - Float64(Float64(4.0 * a) * c)))) / Float64(2.0 * a))
end
↓
function code(a, b, c)
t_0 = Float64((c ^ 4.0) / (b ^ 6.0))
return Float64(Float64(-1.0 * Float64(c / b)) + Float64(Float64(Float64(-2.0 * Float64((a ^ 2.0) * Float64((c ^ 3.0) / (b ^ 5.0)))) + Float64(-0.25 * Float64(Float64(Float64(16.0 * t_0) + Float64(4.0 * t_0)) * Float64((a ^ 3.0) / b)))) + Float64(-1.0 * Float64(a * Float64((c ^ 2.0) / (b ^ 3.0))))))
end
function tmp = code(a, b, c)
tmp = (-b + sqrt(((b * b) - ((4.0 * a) * c)))) / (2.0 * a);
end
↓
function tmp = code(a, b, c)
t_0 = (c ^ 4.0) / (b ^ 6.0);
tmp = (-1.0 * (c / b)) + (((-2.0 * ((a ^ 2.0) * ((c ^ 3.0) / (b ^ 5.0)))) + (-0.25 * (((16.0 * t_0) + (4.0 * t_0)) * ((a ^ 3.0) / b)))) + (-1.0 * (a * ((c ^ 2.0) / (b ^ 3.0)))));
end
code[a_, b_, c_] := N[(N[((-b) + N[Sqrt[N[(N[(b * b), $MachinePrecision] - N[(N[(4.0 * a), $MachinePrecision] * c), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[(2.0 * a), $MachinePrecision]), $MachinePrecision]
↓
code[a_, b_, c_] := Block[{t$95$0 = N[(N[Power[c, 4.0], $MachinePrecision] / N[Power[b, 6.0], $MachinePrecision]), $MachinePrecision]}, N[(N[(-1.0 * N[(c / b), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(-2.0 * N[(N[Power[a, 2.0], $MachinePrecision] * N[(N[Power[c, 3.0], $MachinePrecision] / N[Power[b, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-0.25 * N[(N[(N[(16.0 * t$95$0), $MachinePrecision] + N[(4.0 * t$95$0), $MachinePrecision]), $MachinePrecision] * N[(N[Power[a, 3.0], $MachinePrecision] / b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-1.0 * N[(a * N[(N[Power[c, 2.0], $MachinePrecision] / N[Power[b, 3.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\frac{\left(-b\right) + \sqrt{b \cdot b - \left(4 \cdot a\right) \cdot c}}{2 \cdot a}
↓
\begin{array}{l}
t_0 := \frac{{c}^{4}}{{b}^{6}}\\
-1 \cdot \frac{c}{b} + \left(\left(-2 \cdot \left({a}^{2} \cdot \frac{{c}^{3}}{{b}^{5}}\right) + -0.25 \cdot \left(\left(16 \cdot t_0 + 4 \cdot t_0\right) \cdot \frac{{a}^{3}}{b}\right)\right) + -1 \cdot \left(a \cdot \frac{{c}^{2}}{{b}^{3}}\right)\right)
\end{array}