Average Error: 0.7 → 1.0
Time: 12.9s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{\frac{x}{y - z}}{y - t}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{\frac{x}{y - z}}{y - t}
double f(double x, double y, double z, double t) {
        double r173783 = 1.0;
        double r173784 = x;
        double r173785 = y;
        double r173786 = z;
        double r173787 = r173785 - r173786;
        double r173788 = t;
        double r173789 = r173785 - r173788;
        double r173790 = r173787 * r173789;
        double r173791 = r173784 / r173790;
        double r173792 = r173783 - r173791;
        return r173792;
}
↓
double f(double x, double y, double z, double t) {
        double r173793 = 1.0;
        double r173794 = x;
        double r173795 = y;
        double r173796 = z;
        double r173797 = r173795 - r173796;
        double r173798 = r173794 / r173797;
        double r173799 = t;
        double r173800 = r173795 - r173799;
        double r173801 = r173798 / r173800;
        double r173802 = r173793 - r173801;
        return r173802;
}

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 0.7

    \[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
  2. Using strategy rm

  3. Applied associate-/r*1.0

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

  4. Final simplification1.0

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

Reproduce

herbie shell --seed 2019326 
(FPCore (x y z t)
  :name "Data.Random.Distribution.Triangular:triangularCDF from random-fu-0.2.6.2, A"
  :precision binary64
  (- 1 (/ x (* (- y z) (- y t)))))