Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\left(\frac{x}{2} + y \cdot x\right) + z
\]
↓
\[\left(\frac{x}{2} + x \cdot y\right) + z
\]
(FPCore (x y z) :precision binary64 (+ (+ (/ x 2.0) (* y x)) z)) ↓
(FPCore (x y z) :precision binary64 (+ (+ (/ x 2.0) (* x y)) z)) double code(double x, double y, double z) {
return ((x / 2.0) + (y * x)) + z;
}
↓
double code(double x, double y, double z) {
return ((x / 2.0) + (x * 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 / 2.0d0) + (y * x)) + z
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 / 2.0d0) + (x * y)) + z
end function
public static double code(double x, double y, double z) {
return ((x / 2.0) + (y * x)) + z;
}
↓
public static double code(double x, double y, double z) {
return ((x / 2.0) + (x * y)) + z;
}
def code(x, y, z):
return ((x / 2.0) + (y * x)) + z
↓
def code(x, y, z):
return ((x / 2.0) + (x * y)) + z
function code(x, y, z)
return Float64(Float64(Float64(x / 2.0) + Float64(y * x)) + z)
end
↓
function code(x, y, z)
return Float64(Float64(Float64(x / 2.0) + Float64(x * y)) + z)
end
function tmp = code(x, y, z)
tmp = ((x / 2.0) + (y * x)) + z;
end
↓
function tmp = code(x, y, z)
tmp = ((x / 2.0) + (x * y)) + z;
end
code[x_, y_, z_] := N[(N[(N[(x / 2.0), $MachinePrecision] + N[(y * x), $MachinePrecision]), $MachinePrecision] + z), $MachinePrecision]
↓
code[x_, y_, z_] := N[(N[(N[(x / 2.0), $MachinePrecision] + N[(x * y), $MachinePrecision]), $MachinePrecision] + z), $MachinePrecision]
\left(\frac{x}{2} + y \cdot x\right) + z
↓
\left(\frac{x}{2} + x \cdot y\right) + z