Average Error: 0.1 → 0.3
Time: 2.6s
Precision: 64
\[\frac{\left(x + y\right) - z}{t \cdot 2}\]
↓
\[\frac{1}{t} \cdot \frac{\left(x + y\right) - z}{2}\]
\frac{\left(x + y\right) - z}{t \cdot 2}
↓
\frac{1}{t} \cdot \frac{\left(x + y\right) - z}{2}
double f(double x, double y, double z, double t) {
        double r58064 = x;
        double r58065 = y;
        double r58066 = r58064 + r58065;
        double r58067 = z;
        double r58068 = r58066 - r58067;
        double r58069 = t;
        double r58070 = 2.0;
        double r58071 = r58069 * r58070;
        double r58072 = r58068 / r58071;
        return r58072;
}
↓
double f(double x, double y, double z, double t) {
        double r58073 = 1.0;
        double r58074 = t;
        double r58075 = r58073 / r58074;
        double r58076 = x;
        double r58077 = y;
        double r58078 = r58076 + r58077;
        double r58079 = z;
        double r58080 = r58078 - r58079;
        double r58081 = 2.0;
        double r58082 = r58080 / r58081;
        double r58083 = r58075 * r58082;
        return r58083;
}

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 *-un-lft-identity0.1

    \[\leadsto \frac{\color{blue}{1 \cdot \left(\left(x + y\right) - z\right)}}{t \cdot 2}\]

  4. Applied times-frac0.3

    \[\leadsto \color{blue}{\frac{1}{t} \cdot \frac{\left(x + y\right) - z}{2}}\]

  5. Final simplification0.3

    \[\leadsto \frac{1}{t} \cdot \frac{\left(x + y\right) - z}{2}\]

Reproduce

herbie shell --seed 2019356 
(FPCore (x y z t)
  :name "Optimisation.CirclePacking:place from circle-packing-0.1.0.4, B"
  :precision binary64
  (/ (- (+ x y) z) (* t 2)))