Average Error: 0.7 → 0.7
Time: 3.1s
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 r196774 = 1.0;
        double r196775 = x;
        double r196776 = y;
        double r196777 = z;
        double r196778 = r196776 - r196777;
        double r196779 = t;
        double r196780 = r196776 - r196779;
        double r196781 = r196778 * r196780;
        double r196782 = r196775 / r196781;
        double r196783 = r196774 - r196782;
        return r196783;
}
↓
double f(double x, double y, double z, double t) {
        double r196784 = 1.0;
        double r196785 = x;
        double r196786 = y;
        double r196787 = z;
        double r196788 = r196786 - r196787;
        double r196789 = t;
        double r196790 = r196786 - r196789;
        double r196791 = r196788 * r196790;
        double r196792 = r196785 / r196791;
        double r196793 = r196784 - r196792;
        return r196793;
}

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. Final simplification0.7

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

Reproduce

herbie shell --seed 2020081 +o rules:numerics
(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)))))