Average Error: 0.1 → 0.1
Time: 2.1s
Precision: binary64
\[1 - x \cdot \left(0.253 + x \cdot 0.12\right) \]
\[1 + \left({x}^{2} \cdot -0.12 + x \cdot -0.253\right) \]
(FPCore (x) :precision binary64 (- 1.0 (* x (+ 0.253 (* x 0.12)))))
(FPCore (x) :precision binary64 (+ 1.0 (+ (* (pow x 2.0) -0.12) (* x -0.253))))
double code(double x) {
	return 1.0 - (x * (0.253 + (x * 0.12)));
}
double code(double x) {
	return 1.0 + ((pow(x, 2.0) * -0.12) + (x * -0.253));
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = 1.0d0 - (x * (0.253d0 + (x * 0.12d0)))
end function
real(8) function code(x)
    real(8), intent (in) :: x
    code = 1.0d0 + (((x ** 2.0d0) * (-0.12d0)) + (x * (-0.253d0)))
end function
public static double code(double x) {
	return 1.0 - (x * (0.253 + (x * 0.12)));
}
public static double code(double x) {
	return 1.0 + ((Math.pow(x, 2.0) * -0.12) + (x * -0.253));
}
def code(x):
	return 1.0 - (x * (0.253 + (x * 0.12)))
def code(x):
	return 1.0 + ((math.pow(x, 2.0) * -0.12) + (x * -0.253))
function code(x)
	return Float64(1.0 - Float64(x * Float64(0.253 + Float64(x * 0.12))))
end
function code(x)
	return Float64(1.0 + Float64(Float64((x ^ 2.0) * -0.12) + Float64(x * -0.253)))
end
function tmp = code(x)
	tmp = 1.0 - (x * (0.253 + (x * 0.12)));
end
function tmp = code(x)
	tmp = 1.0 + (((x ^ 2.0) * -0.12) + (x * -0.253));
end
code[x_] := N[(1.0 - N[(x * N[(0.253 + N[(x * 0.12), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_] := N[(1.0 + N[(N[(N[Power[x, 2.0], $MachinePrecision] * -0.12), $MachinePrecision] + N[(x * -0.253), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
1 - x \cdot \left(0.253 + x \cdot 0.12\right)
1 + \left({x}^{2} \cdot -0.12 + x \cdot -0.253\right)

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.1

    \[1 - x \cdot \left(0.253 + x \cdot 0.12\right) \]
  2. Simplified0.1

    \[\leadsto \color{blue}{\mathsf{fma}\left(x, \mathsf{fma}\left(x, -0.12, -0.253\right), 1\right)} \]
  3. Taylor expanded in x around 0 0.1

    \[\leadsto \color{blue}{1 - \left(0.12 \cdot {x}^{2} + 0.253 \cdot x\right)} \]
  4. Final simplification0.1

    \[\leadsto 1 + \left({x}^{2} \cdot -0.12 + x \cdot -0.253\right) \]

Reproduce

herbie shell --seed 2022162 
(FPCore (x)
  :name "Numeric.SpecFunctions:invIncompleteGamma from math-functions-0.1.5.2, A"
  :precision binary64
  (- 1.0 (* x (+ 0.253 (* x 0.12)))))