Average Error: 6.3 → 2.5
Time: 1.8s
Precision: 64
\[x + \frac{y \cdot \left(z - t\right)}{a}\]
↓
\[x + \frac{1}{\frac{\frac{a}{y}}{z - t}}\]
x + \frac{y \cdot \left(z - t\right)}{a}
↓
x + \frac{1}{\frac{\frac{a}{y}}{z - t}}
double code(double x, double y, double z, double t, double a) {
	return (x + ((y * (z - t)) / a));
}
↓
double code(double x, double y, double z, double t, double a) {
	return (x + (1.0 / ((a / y) / (z - t))));
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Bits error versus a

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original6.3
Target0.7
Herbie2.5
\[\begin{array}{l} \mathbf{if}\;y \lt -1.07612662163899753 \cdot 10^{-10}:\\ \;\;\;\;x + \frac{1}{\frac{\frac{a}{z - t}}{y}}\\ \mathbf{elif}\;y \lt 2.8944268627920891 \cdot 10^{-49}:\\ \;\;\;\;x + \frac{y \cdot \left(z - t\right)}{a}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y}{\frac{a}{z - t}}\\ \end{array}\]

Derivation

  1. Initial program 6.3

    \[x + \frac{y \cdot \left(z - t\right)}{a}\]
  2. Using strategy rm

  3. Applied *-commutative6.3

    \[\leadsto x + \frac{\color{blue}{\left(z - t\right) \cdot y}}{a}\]

  4. Applied associate-/l*2.5

    \[\leadsto x + \color{blue}{\frac{z - t}{\frac{a}{y}}}\]
  5. Using strategy rm

  6. Applied clear-num2.5

    \[\leadsto x + \color{blue}{\frac{1}{\frac{\frac{a}{y}}{z - t}}}\]

  7. Final simplification2.5

    \[\leadsto x + \frac{1}{\frac{\frac{a}{y}}{z - t}}\]

Reproduce

herbie shell --seed 2020071 +o rules:numerics
(FPCore (x y z t a)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, E"
  :precision binary64

  :herbie-target
  (if (< y -1.0761266216389975e-10) (+ x (/ 1 (/ (/ a (- z t)) y))) (if (< y 2.894426862792089e-49) (+ x (/ (* y (- z t)) a)) (+ x (/ y (/ a (- z t))))))

  (+ x (/ (* y (- z t)) a)))