Average Error: 0.2 → 0.1
Time: 1.9s
Precision: binary64
\[\left(x \cdot x\right) \cdot \left(3 - x \cdot 2\right) \]
\[3 \cdot {x}^{2} - 2 \cdot {x}^{3} \]
\left(x \cdot x\right) \cdot \left(3 - x \cdot 2\right)
3 \cdot {x}^{2} - 2 \cdot {x}^{3}
(FPCore (x) :precision binary64 (* (* x x) (- 3.0 (* x 2.0))))
(FPCore (x) :precision binary64 (- (* 3.0 (pow x 2.0)) (* 2.0 (pow x 3.0))))
double code(double x) {
	return (x * x) * (3.0 - (x * 2.0));
}
double code(double x) {
	return (3.0 * pow(x, 2.0)) - (2.0 * pow(x, 3.0));
}

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original0.2
Target0.2
Herbie0.1
\[x \cdot \left(x \cdot \left(3 - x \cdot 2\right)\right) \]

Derivation

  1. Initial program 0.2

    \[\left(x \cdot x\right) \cdot \left(3 - x \cdot 2\right) \]
  2. Taylor expanded around 0 0.1

    \[\leadsto \color{blue}{3 \cdot {x}^{2} - 2 \cdot {x}^{3}} \]
  3. Final simplification0.1

    \[\leadsto 3 \cdot {x}^{2} - 2 \cdot {x}^{3} \]

Reproduce

herbie shell --seed 2021204 
(FPCore (x)
  :name "Data.Spline.Key:interpolateKeys from smoothie-0.4.0.2"
  :precision binary64

  :herbie-target
  (* x (* x (- 3.0 (* x 2.0))))

  (* (* x x) (- 3.0 (* x 2.0))))