Average Error: 0.0 → 0.0
Time: 1.8s
Precision: binary64
\[\frac{x - y}{1 - y} \]
\[\frac{x - y}{1 - y} \]
(FPCore (x y) :precision binary64 (/ (- x y) (- 1.0 y)))
(FPCore (x y) :precision binary64 (/ (- x y) (- 1.0 y)))
double code(double x, double y) {
	return (x - y) / (1.0 - y);
}
double code(double x, double y) {
	return (x - y) / (1.0 - y);
}
real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (x - y) / (1.0d0 - y)
end function
real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (x - y) / (1.0d0 - y)
end function
public static double code(double x, double y) {
	return (x - y) / (1.0 - y);
}
public static double code(double x, double y) {
	return (x - y) / (1.0 - y);
}
def code(x, y):
	return (x - y) / (1.0 - y)
def code(x, y):
	return (x - y) / (1.0 - y)
function code(x, y)
	return Float64(Float64(x - y) / Float64(1.0 - y))
end
function code(x, y)
	return Float64(Float64(x - y) / Float64(1.0 - y))
end
function tmp = code(x, y)
	tmp = (x - y) / (1.0 - y);
end
function tmp = code(x, y)
	tmp = (x - y) / (1.0 - y);
end
code[x_, y_] := N[(N[(x - y), $MachinePrecision] / N[(1.0 - y), $MachinePrecision]), $MachinePrecision]
code[x_, y_] := N[(N[(x - y), $MachinePrecision] / N[(1.0 - y), $MachinePrecision]), $MachinePrecision]
\frac{x - y}{1 - y}
\frac{x - y}{1 - y}

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

    \[\frac{x - y}{1 - y} \]
  2. Final simplification0.0

    \[\leadsto \frac{x - y}{1 - y} \]

Reproduce

herbie shell --seed 2022151 
(FPCore (x y)
  :name "Diagrams.Trail:splitAtParam  from diagrams-lib-1.3.0.3, C"
  :precision binary64
  (/ (- x y) (- 1.0 y)))