Average Error: 0.7 → 0.7
Time: 7.0s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{x}{\left(y - t\right) \cdot \left(y - z\right)}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{x}{\left(y - t\right) \cdot \left(y - z\right)}
double f(double x, double y, double z, double t) {
        double r86692 = 1.0;
        double r86693 = x;
        double r86694 = y;
        double r86695 = z;
        double r86696 = r86694 - r86695;
        double r86697 = t;
        double r86698 = r86694 - r86697;
        double r86699 = r86696 * r86698;
        double r86700 = r86693 / r86699;
        double r86701 = r86692 - r86700;
        return r86701;
}
↓
double f(double x, double y, double z, double t) {
        double r86702 = 1.0;
        double r86703 = x;
        double r86704 = y;
        double r86705 = t;
        double r86706 = r86704 - r86705;
        double r86707 = z;
        double r86708 = r86704 - r86707;
        double r86709 = r86706 * r86708;
        double r86710 = r86703 / r86709;
        double r86711 = r86702 - r86710;
        return r86711;
}

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 *-commutative0.7

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

  4. Final simplification0.7

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

Reproduce

herbie shell --seed 2020045 
(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)))))