Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{x \cdot \left(y - z\right)}{y}
\]
↓
\[\frac{x}{\frac{y}{y - z}}
\]
(FPCore (x y z) :precision binary64 (/ (* x (- y z)) y)) ↓
(FPCore (x y z) :precision binary64 (/ x (/ y (- y z)))) double code(double x, double y, double z) {
return (x * (y - z)) / y;
}
↓
double code(double x, double y, double z) {
return x / (y / (y - z));
}
real(8) function code(x, y, z)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
code = (x * (y - z)) / y
end function
↓
real(8) function code(x, y, z)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
code = x / (y / (y - z))
end function
public static double code(double x, double y, double z) {
return (x * (y - z)) / y;
}
↓
public static double code(double x, double y, double z) {
return x / (y / (y - z));
}
def code(x, y, z):
return (x * (y - z)) / y
↓
def code(x, y, z):
return x / (y / (y - z))
function code(x, y, z)
return Float64(Float64(x * Float64(y - z)) / y)
end
↓
function code(x, y, z)
return Float64(x / Float64(y / Float64(y - z)))
end
function tmp = code(x, y, z)
tmp = (x * (y - z)) / y;
end
↓
function tmp = code(x, y, z)
tmp = x / (y / (y - z));
end
code[x_, y_, z_] := N[(N[(x * N[(y - z), $MachinePrecision]), $MachinePrecision] / y), $MachinePrecision]
↓
code[x_, y_, z_] := N[(x / N[(y / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{x \cdot \left(y - z\right)}{y}
↓
\frac{x}{\frac{y}{y - z}}