Average Error: 0.7 → 0.7
Time: 5.5s
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 r192016 = 1.0;
        double r192017 = x;
        double r192018 = y;
        double r192019 = z;
        double r192020 = r192018 - r192019;
        double r192021 = t;
        double r192022 = r192018 - r192021;
        double r192023 = r192020 * r192022;
        double r192024 = r192017 / r192023;
        double r192025 = r192016 - r192024;
        return r192025;
}
↓
double f(double x, double y, double z, double t) {
        double r192026 = 1.0;
        double r192027 = x;
        double r192028 = y;
        double r192029 = z;
        double r192030 = r192028 - r192029;
        double r192031 = t;
        double r192032 = r192028 - r192031;
        double r192033 = r192030 * r192032;
        double r192034 = r192027 / r192033;
        double r192035 = r192026 - r192034;
        return r192035;
}

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 2019308 
(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)))))