Average Error: 0.1 → 0.1
Time: 2.1s
Precision: 64
\[\frac{\left(x + y\right) - z}{t \cdot 2}\]
↓
\[\frac{x + y}{t \cdot 2} - \frac{z}{t \cdot 2}\]
\frac{\left(x + y\right) - z}{t \cdot 2}
↓
\frac{x + y}{t \cdot 2} - \frac{z}{t \cdot 2}
double f(double x, double y, double z, double t) {
        double r50900 = x;
        double r50901 = y;
        double r50902 = r50900 + r50901;
        double r50903 = z;
        double r50904 = r50902 - r50903;
        double r50905 = t;
        double r50906 = 2.0;
        double r50907 = r50905 * r50906;
        double r50908 = r50904 / r50907;
        return r50908;
}
↓
double f(double x, double y, double z, double t) {
        double r50909 = x;
        double r50910 = y;
        double r50911 = r50909 + r50910;
        double r50912 = t;
        double r50913 = 2.0;
        double r50914 = r50912 * r50913;
        double r50915 = r50911 / r50914;
        double r50916 = z;
        double r50917 = r50916 / r50914;
        double r50918 = r50915 - r50917;
        return r50918;
}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Bits error versus t

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.1

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

  3. Applied div-sub0.1

    \[\leadsto \color{blue}{\frac{x + y}{t \cdot 2} - \frac{z}{t \cdot 2}}\]

  4. Final simplification0.1

    \[\leadsto \frac{x + y}{t \cdot 2} - \frac{z}{t \cdot 2}\]

Reproduce

herbie shell --seed 2020062 
(FPCore (x y z t)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, B"
  :precision binary64
  (/ (- (+ x y) z) (* t 2)))