Average Error: 0.7 → 0.7
Time: 7.3s
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 r64105 = 1.0;
        double r64106 = x;
        double r64107 = y;
        double r64108 = z;
        double r64109 = r64107 - r64108;
        double r64110 = t;
        double r64111 = r64107 - r64110;
        double r64112 = r64109 * r64111;
        double r64113 = r64106 / r64112;
        double r64114 = r64105 - r64113;
        return r64114;
}
↓
double f(double x, double y, double z, double t) {
        double r64115 = 1.0;
        double r64116 = x;
        double r64117 = y;
        double r64118 = t;
        double r64119 = r64117 - r64118;
        double r64120 = z;
        double r64121 = r64117 - r64120;
        double r64122 = r64119 * r64121;
        double r64123 = r64116 / r64122;
        double r64124 = r64115 - r64123;
        return r64124;
}

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)))))