Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\left(1 - x\right) \cdot y + x \cdot z
\]
↓
\[y - x \cdot \left(y - z\right)
\]
(FPCore (x y z) :precision binary64 (+ (* (- 1.0 x) y) (* x z))) ↓
(FPCore (x y z) :precision binary64 (- y (* x (- y z)))) double code(double x, double y, double z) {
return ((1.0 - x) * y) + (x * z);
}
↓
double code(double x, double y, double z) {
return y - (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 = ((1.0d0 - x) * 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 = y - (x * (y - z))
end function
public static double code(double x, double y, double z) {
return ((1.0 - x) * y) + (x * z);
}
↓
public static double code(double x, double y, double z) {
return y - (x * (y - z));
}
def code(x, y, z):
return ((1.0 - x) * y) + (x * z)
↓
def code(x, y, z):
return y - (x * (y - z))
function code(x, y, z)
return Float64(Float64(Float64(1.0 - x) * y) + Float64(x * z))
end
↓
function code(x, y, z)
return Float64(y - Float64(x * Float64(y - z)))
end
function tmp = code(x, y, z)
tmp = ((1.0 - x) * y) + (x * z);
end
↓
function tmp = code(x, y, z)
tmp = y - (x * (y - z));
end
code[x_, y_, z_] := N[(N[(N[(1.0 - x), $MachinePrecision] * y), $MachinePrecision] + N[(x * z), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_] := N[(y - N[(x * N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\left(1 - x\right) \cdot y + x \cdot z
↓
y - x \cdot \left(y - z\right)