Average Error: 0.1 → 0.1
Time: 12.2s
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 r25312 = x;
        double r25313 = y;
        double r25314 = r25312 + r25313;
        double r25315 = z;
        double r25316 = r25314 - r25315;
        double r25317 = t;
        double r25318 = 2.0;
        double r25319 = r25317 * r25318;
        double r25320 = r25316 / r25319;
        return r25320;
}
↓
double f(double x, double y, double z, double t) {
        double r25321 = x;
        double r25322 = y;
        double r25323 = r25321 + r25322;
        double r25324 = t;
        double r25325 = 2.0;
        double r25326 = r25324 * r25325;
        double r25327 = r25323 / r25326;
        double r25328 = z;
        double r25329 = r25328 / r25326;
        double r25330 = r25327 - r25329;
        return r25330;
}

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 2019326 
(FPCore (x y z t)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, B"
  :precision binary64
  (/ (- (+ x y) z) (* t 2)))