\[\cosh x \cdot \frac{\sin y}{y}
\]
↓
\[\frac{\sin y}{\frac{y}{\cosh x}}
\]
(FPCore (x y) :precision binary64 (* (cosh x) (/ (sin y) y)))
↓
(FPCore (x y) :precision binary64 (/ (sin y) (/ y (cosh x))))
double code(double x, double y) {
return cosh(x) * (sin(y) / y);
}
↓
double code(double x, double y) {
return sin(y) / (y / cosh(x));
}
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = cosh(x) * (sin(y) / y)
end function
↓
real(8) function code(x, y)
real(8), intent (in) :: x
real(8), intent (in) :: y
code = sin(y) / (y / cosh(x))
end function
public static double code(double x, double y) {
return Math.cosh(x) * (Math.sin(y) / y);
}
↓
public static double code(double x, double y) {
return Math.sin(y) / (y / Math.cosh(x));
}
def code(x, y):
return math.cosh(x) * (math.sin(y) / y)
↓
def code(x, y):
return math.sin(y) / (y / math.cosh(x))
function code(x, y)
return Float64(cosh(x) * Float64(sin(y) / y))
end
↓
function code(x, y)
return Float64(sin(y) / Float64(y / cosh(x)))
end
function tmp = code(x, y)
tmp = cosh(x) * (sin(y) / y);
end
↓
function tmp = code(x, y)
tmp = sin(y) / (y / cosh(x));
end
code[x_, y_] := N[(N[Cosh[x], $MachinePrecision] * N[(N[Sin[y], $MachinePrecision] / y), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_] := N[(N[Sin[y], $MachinePrecision] / N[(y / N[Cosh[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\cosh x \cdot \frac{\sin y}{y}
↓
\frac{\sin y}{\frac{y}{\cosh x}}