Average Error: 0.0 → 0.0
Time: 989.0ms
Precision: binary64
\[\left(1 - x\right) - y \]
↓
\[1 - \left(y + x\right) \]
(FPCore (x y) :precision binary64 (- (- 1.0 x) y))
↓
(FPCore (x y) :precision binary64 (- 1.0 (+ y x)))
double code(double x, double y) {
	return (1.0 - x) - y;
}
↓
double code(double x, double y) {
	return 1.0 - (y + x);
}

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (1.0d0 - x) - y
end function
↓
real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = 1.0d0 - (y + x)
end function

public static double code(double x, double y) {
	return (1.0 - x) - y;
}
↓
public static double code(double x, double y) {
	return 1.0 - (y + x);
}

def code(x, y):
	return (1.0 - x) - y
↓
def code(x, y):
	return 1.0 - (y + x)

function code(x, y)
	return Float64(Float64(1.0 - x) - y)
end
↓
function code(x, y)
	return Float64(1.0 - Float64(y + x))
end

function tmp = code(x, y)
	tmp = (1.0 - x) - y;
end
↓
function tmp = code(x, y)
	tmp = 1.0 - (y + x);
end

code[x_, y_] := N[(N[(1.0 - x), $MachinePrecision] - y), $MachinePrecision]
↓
code[x_, y_] := N[(1.0 - N[(y + x), $MachinePrecision]), $MachinePrecision]

\left(1 - x\right) - y
↓
1 - \left(y + x\right)

Error

Bits error versus x

Bits error versus y

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.0

    \[\left(1 - x\right) - y \]

  2. Taylor expanded in x around 0 0.0

    \[\leadsto \color{blue}{1 - \left(y + x\right)} \]

  3. Final simplification0.0

    \[\leadsto 1 - \left(y + x\right) \]

Reproduce

herbie shell --seed 2022165 
(FPCore (x y)
  :name "Data.Colour.CIE.Chromaticity:chromaCoords from colour-2.3.3"
  :precision binary64
  (- (- 1.0 x) y))