Average Error: 0.7 → 0.7
Time: 3.3s
Precision: 64
\[1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}\]
↓
\[1 - \frac{1}{\frac{\left(y - z\right) \cdot \left(y - t\right)}{x}}\]
1 - \frac{x}{\left(y - z\right) \cdot \left(y - t\right)}
↓
1 - \frac{1}{\frac{\left(y - z\right) \cdot \left(y - t\right)}{x}}
double f(double x, double y, double z, double t) {
        double r253464 = 1.0;
        double r253465 = x;
        double r253466 = y;
        double r253467 = z;
        double r253468 = r253466 - r253467;
        double r253469 = t;
        double r253470 = r253466 - r253469;
        double r253471 = r253468 * r253470;
        double r253472 = r253465 / r253471;
        double r253473 = r253464 - r253472;
        return r253473;
}
↓
double f(double x, double y, double z, double t) {
        double r253474 = 1.0;
        double r253475 = 1.0;
        double r253476 = y;
        double r253477 = z;
        double r253478 = r253476 - r253477;
        double r253479 = t;
        double r253480 = r253476 - r253479;
        double r253481 = r253478 * r253480;
        double r253482 = x;
        double r253483 = r253481 / r253482;
        double r253484 = r253475 / r253483;
        double r253485 = r253474 - r253484;
        return r253485;
}

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 clear-num0.7

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

  4. Final simplification0.7

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

Reproduce

herbie shell --seed 2020089 
(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)))))