Average Error: 25.2 → 9.4
Time: 14.8s
Precision: binary64
\[x - \frac{\log \left(\left(1 - y\right) + y \cdot e^{z}\right)}{t}\]
\[\begin{array}{l} \mathbf{if}\;z \leq -2.7393459773838706 \cdot 10^{-11}:\\ \;\;\;\;x - \frac{\log \left(1 - \left(y - y \cdot e^{z}\right)\right)}{t}\\ \mathbf{else}:\\ \;\;\;\;x - \frac{z \cdot y + \left(0.5 \cdot \left(z \cdot \left(z \cdot y\right)\right)\right) \cdot \left(1 - y\right)}{t}\\ \end{array}\]
x - \frac{\log \left(\left(1 - y\right) + y \cdot e^{z}\right)}{t}
\begin{array}{l}
\mathbf{if}\;z \leq -2.7393459773838706 \cdot 10^{-11}:\\
\;\;\;\;x - \frac{\log \left(1 - \left(y - y \cdot e^{z}\right)\right)}{t}\\

\mathbf{else}:\\
\;\;\;\;x - \frac{z \cdot y + \left(0.5 \cdot \left(z \cdot \left(z \cdot y\right)\right)\right) \cdot \left(1 - y\right)}{t}\\

\end{array}
(FPCore (x y z t)
 :precision binary64
 (- x (/ (log (+ (- 1.0 y) (* y (exp z)))) t)))
(FPCore (x y z t)
 :precision binary64
 (if (<= z -2.7393459773838706e-11)
   (- x (/ (log (- 1.0 (- y (* y (exp z))))) t))
   (- x (/ (+ (* z y) (* (* 0.5 (* z (* z y))) (- 1.0 y))) t))))
double code(double x, double y, double z, double t) {
	return x - (log((1.0 - y) + (y * exp(z))) / t);
}
double code(double x, double y, double z, double t) {
	double tmp;
	if (z <= -2.7393459773838706e-11) {
		tmp = x - (log(1.0 - (y - (y * exp(z)))) / t);
	} else {
		tmp = x - (((z * y) + ((0.5 * (z * (z * y))) * (1.0 - y))) / t);
	}
	return tmp;
}

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

Target

Original25.2
Target15.9
Herbie9.4
\[\begin{array}{l} \mathbf{if}\;z < -2.8874623088207947 \cdot 10^{+119}:\\ \;\;\;\;\left(x - \frac{\frac{-0.5}{y \cdot t}}{z \cdot z}\right) - \frac{-0.5}{y \cdot t} \cdot \frac{\frac{2}{z}}{z \cdot z}\\ \mathbf{else}:\\ \;\;\;\;x - \frac{\log \left(1 + z \cdot y\right)}{t}\\ \end{array}\]

Derivation

  1. Split input into 2 regimes
  2. if z < -2.7393459773838706e-11

    1. Initial program 11.9

      \[x - \frac{\log \left(\left(1 - y\right) + y \cdot e^{z}\right)}{t}\]
    2. Using strategy rm
    3. Applied associate-+l-_binary64_853811.9

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

    if -2.7393459773838706e-11 < z

    1. Initial program 31.0

      \[x - \frac{\log \left(\left(1 - y\right) + y \cdot e^{z}\right)}{t}\]
    2. Taylor expanded around 0 14.4

      \[\leadsto x - \frac{\color{blue}{\left(0.5 \cdot \left({z}^{2} \cdot y\right) + z \cdot y\right) - 0.5 \cdot \left({z}^{2} \cdot {y}^{2}\right)}}{t}\]
    3. Simplified8.1

      \[\leadsto x - \frac{\color{blue}{y \cdot z + \left(0.5 \cdot \left(y \cdot \left(z \cdot z\right)\right)\right) \cdot \left(1 - y\right)}}{t}\]
    4. Using strategy rm
    5. Applied associate-*r*_binary64_85438.2

      \[\leadsto x - \frac{y \cdot z + \left(0.5 \cdot \color{blue}{\left(\left(y \cdot z\right) \cdot z\right)}\right) \cdot \left(1 - y\right)}{t}\]
  3. Recombined 2 regimes into one program.
  4. Final simplification9.4

    \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.7393459773838706 \cdot 10^{-11}:\\ \;\;\;\;x - \frac{\log \left(1 - \left(y - y \cdot e^{z}\right)\right)}{t}\\ \mathbf{else}:\\ \;\;\;\;x - \frac{z \cdot y + \left(0.5 \cdot \left(z \cdot \left(z \cdot y\right)\right)\right) \cdot \left(1 - y\right)}{t}\\ \end{array}\]

Reproduce

herbie shell --seed 2020342 
(FPCore (x y z t)
  :name "System.Random.MWC.Distributions:truncatedExp from mwc-random-0.13.3.2"
  :precision binary64

  :herbie-target
  (if (< z -2.8874623088207947e+119) (- (- x (/ (/ (- 0.5) (* y t)) (* z z))) (* (/ (- 0.5) (* y t)) (/ (/ 2.0 z) (* z z)))) (- x (/ (log (+ 1.0 (* z y))) t)))

  (- x (/ (log (+ (- 1.0 y) (* y (exp z)))) t)))