Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{\tan \left(\frac{x}{y \cdot 2}\right)}{\sin \left(\frac{x}{y \cdot 2}\right)}
\]
↓
\[\begin{array}{l}
t_0 := \frac{x}{y \cdot 2}\\
\mathbf{if}\;\frac{\tan t_0}{\sin t_0} \leq 15:\\
\;\;\;\;-1 + \left(1 - \frac{\tan \left(x \cdot \frac{0.5}{y}\right)}{\sin \left(\frac{\frac{x}{y}}{-2}\right)}\right)\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}
\]
(FPCore (x y)
:precision binary64
(/ (tan (/ x (* y 2.0))) (sin (/ x (* y 2.0))))) ↓
(FPCore (x y)
:precision binary64
(let* ((t_0 (/ x (* y 2.0))))
(if (<= (/ (tan t_0) (sin t_0)) 15.0)
(+ -1.0 (- 1.0 (/ (tan (* x (/ 0.5 y))) (sin (/ (/ x y) -2.0)))))
1.0))) double code(double x, double y) {
return tan((x / (y * 2.0))) / sin((x / (y * 2.0)));
}
↓
double code(double x, double y) {
double t_0 = x / (y * 2.0);
double tmp;
if ((tan(t_0) / sin(t_0)) <= 15.0) {
tmp = -1.0 + (1.0 - (tan((x * (0.5 / y))) / sin(((x / y) / -2.0))));
} else {
tmp = 1.0;
}
return tmp;
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = tan((x / (y * 2.0d0))) / sin((x / (y * 2.0d0)))
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8) :: t_0
real(8) :: tmp
t_0 = x / (y * 2.0d0)
if ((tan(t_0) / sin(t_0)) <= 15.0d0) then
tmp = (-1.0d0) + (1.0d0 - (tan((x * (0.5d0 / y))) / sin(((x / y) / (-2.0d0)))))
else
tmp = 1.0d0
end if
code = tmp
end function
public static double code(double x, double y) {
return Math.tan((x / (y * 2.0))) / Math.sin((x / (y * 2.0)));
}
↓
public static double code(double x, double y) {
double t_0 = x / (y * 2.0);
double tmp;
if ((Math.tan(t_0) / Math.sin(t_0)) <= 15.0) {
tmp = -1.0 + (1.0 - (Math.tan((x * (0.5 / y))) / Math.sin(((x / y) / -2.0))));
} else {
tmp = 1.0;
}
return tmp;
}
def code(x, y):
return math.tan((x / (y * 2.0))) / math.sin((x / (y * 2.0)))
↓
def code(x, y):
t_0 = x / (y * 2.0)
tmp = 0
if (math.tan(t_0) / math.sin(t_0)) <= 15.0:
tmp = -1.0 + (1.0 - (math.tan((x * (0.5 / y))) / math.sin(((x / y) / -2.0))))
else:
tmp = 1.0
return tmp
function code(x, y)
return Float64(tan(Float64(x / Float64(y * 2.0))) / sin(Float64(x / Float64(y * 2.0))))
end
↓
function code(x, y)
t_0 = Float64(x / Float64(y * 2.0))
tmp = 0.0
if (Float64(tan(t_0) / sin(t_0)) <= 15.0)
tmp = Float64(-1.0 + Float64(1.0 - Float64(tan(Float64(x * Float64(0.5 / y))) / sin(Float64(Float64(x / y) / -2.0)))));
else
tmp = 1.0;
end
return tmp
end
function tmp = code(x, y)
tmp = tan((x / (y * 2.0))) / sin((x / (y * 2.0)));
end
↓
function tmp_2 = code(x, y)
t_0 = x / (y * 2.0);
tmp = 0.0;
if ((tan(t_0) / sin(t_0)) <= 15.0)
tmp = -1.0 + (1.0 - (tan((x * (0.5 / y))) / sin(((x / y) / -2.0))));
else
tmp = 1.0;
end
tmp_2 = tmp;
end
code[x_, y_] := N[(N[Tan[N[(x / N[(y * 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sin[N[(x / N[(y * 2.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_] := Block[{t$95$0 = N[(x / N[(y * 2.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[Tan[t$95$0], $MachinePrecision] / N[Sin[t$95$0], $MachinePrecision]), $MachinePrecision], 15.0], N[(-1.0 + N[(1.0 - N[(N[Tan[N[(x * N[(0.5 / y), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sin[N[(N[(x / y), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 1.0]]
\frac{\tan \left(\frac{x}{y \cdot 2}\right)}{\sin \left(\frac{x}{y \cdot 2}\right)}
↓
\begin{array}{l}
t_0 := \frac{x}{y \cdot 2}\\
\mathbf{if}\;\frac{\tan t_0}{\sin t_0} \leq 15:\\
\;\;\;\;-1 + \left(1 - \frac{\tan \left(x \cdot \frac{0.5}{y}\right)}{\sin \left(\frac{\frac{x}{y}}{-2}\right)}\right)\\
\mathbf{else}:\\
\;\;\;\;1\\
\end{array}