Average Error: 0.7 → 0.7
Time: 13.1s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
double f(double x, double y, double z, double t) {
        double r166767 = 1.0;
        double r166768 = x;
        double r166769 = y;
        double r166770 = z;
        double r166771 = r166769 - r166770;
        double r166772 = t;
        double r166773 = r166769 - r166772;
        double r166774 = r166771 * r166773;
        double r166775 = r166768 / r166774;
        double r166776 = r166767 - r166775;
        return r166776;
}
↓
double f(double x, double y, double z, double t) {
        double r166777 = 1.0;
        double r166778 = x;
        double r166779 = y;
        double r166780 = z;
        double r166781 = r166779 - r166780;
        double r166782 = t;
        double r166783 = r166779 - r166782;
        double r166784 = r166781 * r166783;
        double r166785 = r166778 / r166784;
        double r166786 = r166777 - r166785;
        return r166786;
}

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 *-un-lft-identity0.7

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

  4. Final simplification0.7

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

Reproduce

herbie shell --seed 2019306 
(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)))))