Average Error: 0.8 → 1.1
Time: 10.1s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{1}{\left(y - z\right) \cdot \frac{y - t}{x}}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{1}{\left(y - z\right) \cdot \frac{y - t}{x}}
double f(double x, double y, double z, double t) {
        double r153660 = 1.0;
        double r153661 = x;
        double r153662 = y;
        double r153663 = z;
        double r153664 = r153662 - r153663;
        double r153665 = t;
        double r153666 = r153662 - r153665;
        double r153667 = r153664 * r153666;
        double r153668 = r153661 / r153667;
        double r153669 = r153660 - r153668;
        return r153669;
}
↓
double f(double x, double y, double z, double t) {
        double r153670 = 1.0;
        double r153671 = 1.0;
        double r153672 = y;
        double r153673 = z;
        double r153674 = r153672 - r153673;
        double r153675 = t;
        double r153676 = r153672 - r153675;
        double r153677 = x;
        double r153678 = r153676 / r153677;
        double r153679 = r153674 * r153678;
        double r153680 = r153671 / r153679;
        double r153681 = r153670 - r153680;
        return r153681;
}

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 0.8

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

  3. Applied *-un-lft-identity0.8

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

  4. Applied times-frac1.2

    \[\leadsto 1 - \color{blue}{\frac{1}{y - z} \cdot \frac{x}{y - t}}\]
  5. Using strategy rm

  6. Applied clear-num1.3

    \[\leadsto 1 - \frac{1}{y - z} \cdot \color{blue}{\frac{1}{\frac{y - t}{x}}}\]
  7. Using strategy rm

  8. Applied frac-times1.1

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

  9. Simplified1.1

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

  10. Final simplification1.1

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

Reproduce

herbie shell --seed 2019298 
(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)))))