Numeric.SpecFunctions:invIncompleteGamma from math-functions-0.1.5.2, B

Percentage Accurate: 72.2% → 99.7%
Time: 12.6s
Alternatives: 8
Speedup: 1.0×

Specification

?
\[\begin{array}{l} \\ 1 - \log \left(1 - \frac{x - y}{1 - y}\right) \end{array} \]
(FPCore (x y) :precision binary64 (- 1.0 (log (- 1.0 (/ (- x y) (- 1.0 y))))))
double code(double x, double y) {
	return 1.0 - log((1.0 - ((x - y) / (1.0 - y))));
}
real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = 1.0d0 - log((1.0d0 - ((x - y) / (1.0d0 - y))))
end function
public static double code(double x, double y) {
	return 1.0 - Math.log((1.0 - ((x - y) / (1.0 - y))));
}
def code(x, y):
	return 1.0 - math.log((1.0 - ((x - y) / (1.0 - y))))
function code(x, y)
	return Float64(1.0 - log(Float64(1.0 - Float64(Float64(x - y) / Float64(1.0 - y)))))
end
function tmp = code(x, y)
	tmp = 1.0 - log((1.0 - ((x - y) / (1.0 - y))));
end
code[x_, y_] := N[(1.0 - N[Log[N[(1.0 - N[(N[(x - y), $MachinePrecision] / N[(1.0 - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
1 - \log \left(1 - \frac{x - y}{1 - y}\right)
\end{array}

Sampling outcomes in binary64 precision:

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 8 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 72.2% accurate, 1.0× speedup?

\[\begin{array}{l} \\ 1 - \log \left(1 - \frac{x - y}{1 - y}\right) \end{array} \]
(FPCore (x y) :precision binary64 (- 1.0 (log (- 1.0 (/ (- x y) (- 1.0 y))))))
double code(double x, double y) {
	return 1.0 - log((1.0 - ((x - y) / (1.0 - y))));
}
real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = 1.0d0 - log((1.0d0 - ((x - y) / (1.0d0 - y))))
end function
public static double code(double x, double y) {
	return 1.0 - Math.log((1.0 - ((x - y) / (1.0 - y))));
}
def code(x, y):
	return 1.0 - math.log((1.0 - ((x - y) / (1.0 - y))))
function code(x, y)
	return Float64(1.0 - log(Float64(1.0 - Float64(Float64(x - y) / Float64(1.0 - y)))))
end
function tmp = code(x, y)
	tmp = 1.0 - log((1.0 - ((x - y) / (1.0 - y))));
end
code[x_, y_] := N[(1.0 - N[Log[N[(1.0 - N[(N[(x - y), $MachinePrecision] / N[(1.0 - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
1 - \log \left(1 - \frac{x - y}{1 - y}\right)
\end{array}

Alternative 1: 99.7% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\frac{x - y}{1 - y} \leq 0.95:\\ \;\;\;\;1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)\\ \mathbf{else}:\\ \;\;\;\;1 + \log \left(\frac{y \cdot -2}{2 + x \cdot -2}\right)\\ \end{array} \end{array} \]
(FPCore (x y)
 :precision binary64
 (if (<= (/ (- x y) (- 1.0 y)) 0.95)
   (- 1.0 (log1p (/ (- x y) (+ y -1.0))))
   (+ 1.0 (log (/ (* y -2.0) (+ 2.0 (* x -2.0)))))))
double code(double x, double y) {
	double tmp;
	if (((x - y) / (1.0 - y)) <= 0.95) {
		tmp = 1.0 - log1p(((x - y) / (y + -1.0)));
	} else {
		tmp = 1.0 + log(((y * -2.0) / (2.0 + (x * -2.0))));
	}
	return tmp;
}
public static double code(double x, double y) {
	double tmp;
	if (((x - y) / (1.0 - y)) <= 0.95) {
		tmp = 1.0 - Math.log1p(((x - y) / (y + -1.0)));
	} else {
		tmp = 1.0 + Math.log(((y * -2.0) / (2.0 + (x * -2.0))));
	}
	return tmp;
}
def code(x, y):
	tmp = 0
	if ((x - y) / (1.0 - y)) <= 0.95:
		tmp = 1.0 - math.log1p(((x - y) / (y + -1.0)))
	else:
		tmp = 1.0 + math.log(((y * -2.0) / (2.0 + (x * -2.0))))
	return tmp
function code(x, y)
	tmp = 0.0
	if (Float64(Float64(x - y) / Float64(1.0 - y)) <= 0.95)
		tmp = Float64(1.0 - log1p(Float64(Float64(x - y) / Float64(y + -1.0))));
	else
		tmp = Float64(1.0 + log(Float64(Float64(y * -2.0) / Float64(2.0 + Float64(x * -2.0)))));
	end
	return tmp
end
code[x_, y_] := If[LessEqual[N[(N[(x - y), $MachinePrecision] / N[(1.0 - y), $MachinePrecision]), $MachinePrecision], 0.95], N[(1.0 - N[Log[1 + N[(N[(x - y), $MachinePrecision] / N[(y + -1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(1.0 + N[Log[N[(N[(y * -2.0), $MachinePrecision] / N[(2.0 + N[(x * -2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\frac{x - y}{1 - y} \leq 0.95:\\
\;\;\;\;1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)\\

\mathbf{else}:\\
\;\;\;\;1 + \log \left(\frac{y \cdot -2}{2 + x \cdot -2}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (/.f64 (-.f64 x y) (-.f64 #s(literal 1 binary64) y)) < 0.94999999999999996

    1. Initial program 99.9%

      \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
    2. Step-by-step derivation
      1. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      3. log1p-defineN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      4. log1p-lowering-log1p.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      5. distribute-neg-frac2N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      8. neg-sub0N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
      9. associate--r-N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
      11. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
      12. +-lowering-+.f64100.0%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    3. Simplified100.0%

      \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
    4. Add Preprocessing

    if 0.94999999999999996 < (/.f64 (-.f64 x y) (-.f64 #s(literal 1 binary64) y))

    1. Initial program 4.3%

      \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
    2. Step-by-step derivation
      1. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      3. log1p-defineN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      4. log1p-lowering-log1p.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      5. distribute-neg-frac2N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      8. neg-sub0N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
      9. associate--r-N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
      11. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
      12. +-lowering-+.f644.3%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    3. Simplified4.3%

      \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
    4. Add Preprocessing
    5. Step-by-step derivation
      1. clear-numN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{\frac{y + -1}{x - y}}\right)\right)\right) \]
      2. associate-/r/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{y + -1} \cdot \left(x - y\right)\right)\right)\right) \]
      3. flip-+N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{\frac{y \cdot y - -1 \cdot -1}{y - -1}} \cdot \left(x - y\right)\right)\right)\right) \]
      4. associate-/r/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\left(\frac{1}{y \cdot y - -1 \cdot -1} \cdot \left(y - -1\right)\right) \cdot \left(x - y\right)\right)\right)\right) \]
      5. associate-*l*N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{y \cdot y - -1 \cdot -1} \cdot \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      6. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\left(\frac{1}{y \cdot y - -1 \cdot -1}\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      7. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y - -1 \cdot -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      8. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y - 1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      9. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y + \left(\mathsf{neg}\left(1\right)\right)\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y + -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      11. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\left(y \cdot y\right), -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      12. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      13. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y - -1\right), \left(x - y\right)\right)\right)\right)\right) \]
      14. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y + \left(\mathsf{neg}\left(-1\right)\right)\right), \left(x - y\right)\right)\right)\right)\right) \]
      15. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y + 1\right), \left(x - y\right)\right)\right)\right)\right) \]
      16. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\mathsf{+.f64}\left(y, 1\right), \left(x - y\right)\right)\right)\right)\right) \]
      17. --lowering--.f642.9%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\mathsf{+.f64}\left(y, 1\right), \mathsf{\_.f64}\left(x, y\right)\right)\right)\right)\right) \]
    6. Applied egg-rr2.9%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}\right) \]
    7. Step-by-step derivation
      1. flip-+N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(\frac{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}\right)\right) \]
      2. clear-numN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(\frac{1}{\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}}\right)\right) \]
      3. log-recN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{neg}\left(\log \left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right)\right) \]
      4. neg-lowering-neg.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\log \left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right) \]
      5. log-lowering-log.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right)\right) \]
    8. Applied egg-rr3.9%

      \[\leadsto 1 - \color{blue}{\left(-\log \left(\frac{1 - \frac{1}{y + -1} \cdot \left(x - y\right)}{1 - \frac{\frac{1}{y + -1}}{y + -1} \cdot \left(\left(x - y\right) \cdot \left(x - y\right)\right)}\right)\right)} \]
    9. Taylor expanded in y around inf

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\color{blue}{\left(-2 \cdot \frac{y}{2 + -2 \cdot x}\right)}\right)\right)\right) \]
    10. Step-by-step derivation
      1. associate-*r/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\left(\frac{-2 \cdot y}{2 + -2 \cdot x}\right)\right)\right)\right) \]
      2. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\left(-2 \cdot y\right), \left(2 + -2 \cdot x\right)\right)\right)\right)\right) \]
      3. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\mathsf{*.f64}\left(-2, y\right), \left(2 + -2 \cdot x\right)\right)\right)\right)\right) \]
      4. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\mathsf{*.f64}\left(-2, y\right), \mathsf{+.f64}\left(2, \left(-2 \cdot x\right)\right)\right)\right)\right)\right) \]
      5. *-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\mathsf{*.f64}\left(-2, y\right), \mathsf{+.f64}\left(2, \left(x \cdot -2\right)\right)\right)\right)\right)\right) \]
      6. *-lowering-*.f64100.0%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\mathsf{*.f64}\left(-2, y\right), \mathsf{+.f64}\left(2, \mathsf{*.f64}\left(x, -2\right)\right)\right)\right)\right)\right) \]
    11. Simplified100.0%

      \[\leadsto 1 - \left(-\log \color{blue}{\left(\frac{-2 \cdot y}{2 + x \cdot -2}\right)}\right) \]
  3. Recombined 2 regimes into one program.
  4. Final simplification100.0%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x - y}{1 - y} \leq 0.95:\\ \;\;\;\;1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)\\ \mathbf{else}:\\ \;\;\;\;1 + \log \left(\frac{y \cdot -2}{2 + x \cdot -2}\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 2: 81.3% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\frac{x - y}{1 - y} \leq 0.95:\\ \;\;\;\;1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)\\ \mathbf{else}:\\ \;\;\;\;1 + \log \left(\frac{y + -1}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y)
 :precision binary64
 (if (<= (/ (- x y) (- 1.0 y)) 0.95)
   (- 1.0 (log1p (/ (- x y) (+ y -1.0))))
   (+ 1.0 (log (/ (+ y -1.0) x)))))
double code(double x, double y) {
	double tmp;
	if (((x - y) / (1.0 - y)) <= 0.95) {
		tmp = 1.0 - log1p(((x - y) / (y + -1.0)));
	} else {
		tmp = 1.0 + log(((y + -1.0) / x));
	}
	return tmp;
}
public static double code(double x, double y) {
	double tmp;
	if (((x - y) / (1.0 - y)) <= 0.95) {
		tmp = 1.0 - Math.log1p(((x - y) / (y + -1.0)));
	} else {
		tmp = 1.0 + Math.log(((y + -1.0) / x));
	}
	return tmp;
}
def code(x, y):
	tmp = 0
	if ((x - y) / (1.0 - y)) <= 0.95:
		tmp = 1.0 - math.log1p(((x - y) / (y + -1.0)))
	else:
		tmp = 1.0 + math.log(((y + -1.0) / x))
	return tmp
function code(x, y)
	tmp = 0.0
	if (Float64(Float64(x - y) / Float64(1.0 - y)) <= 0.95)
		tmp = Float64(1.0 - log1p(Float64(Float64(x - y) / Float64(y + -1.0))));
	else
		tmp = Float64(1.0 + log(Float64(Float64(y + -1.0) / x)));
	end
	return tmp
end
code[x_, y_] := If[LessEqual[N[(N[(x - y), $MachinePrecision] / N[(1.0 - y), $MachinePrecision]), $MachinePrecision], 0.95], N[(1.0 - N[Log[1 + N[(N[(x - y), $MachinePrecision] / N[(y + -1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(1.0 + N[Log[N[(N[(y + -1.0), $MachinePrecision] / x), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\frac{x - y}{1 - y} \leq 0.95:\\
\;\;\;\;1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)\\

\mathbf{else}:\\
\;\;\;\;1 + \log \left(\frac{y + -1}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (/.f64 (-.f64 x y) (-.f64 #s(literal 1 binary64) y)) < 0.94999999999999996

    1. Initial program 99.9%

      \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
    2. Step-by-step derivation
      1. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      3. log1p-defineN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      4. log1p-lowering-log1p.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      5. distribute-neg-frac2N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      8. neg-sub0N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
      9. associate--r-N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
      11. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
      12. +-lowering-+.f64100.0%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    3. Simplified100.0%

      \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
    4. Add Preprocessing

    if 0.94999999999999996 < (/.f64 (-.f64 x y) (-.f64 #s(literal 1 binary64) y))

    1. Initial program 4.3%

      \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
    2. Step-by-step derivation
      1. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      3. log1p-defineN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      4. log1p-lowering-log1p.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      5. distribute-neg-frac2N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      8. neg-sub0N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
      9. associate--r-N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
      11. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
      12. +-lowering-+.f644.3%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    3. Simplified4.3%

      \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
    4. Add Preprocessing
    5. Step-by-step derivation
      1. clear-numN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{\frac{y + -1}{x - y}}\right)\right)\right) \]
      2. associate-/r/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{y + -1} \cdot \left(x - y\right)\right)\right)\right) \]
      3. flip-+N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{\frac{y \cdot y - -1 \cdot -1}{y - -1}} \cdot \left(x - y\right)\right)\right)\right) \]
      4. associate-/r/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\left(\frac{1}{y \cdot y - -1 \cdot -1} \cdot \left(y - -1\right)\right) \cdot \left(x - y\right)\right)\right)\right) \]
      5. associate-*l*N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{y \cdot y - -1 \cdot -1} \cdot \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      6. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\left(\frac{1}{y \cdot y - -1 \cdot -1}\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      7. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y - -1 \cdot -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      8. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y - 1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      9. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y + \left(\mathsf{neg}\left(1\right)\right)\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y + -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      11. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\left(y \cdot y\right), -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      12. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      13. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y - -1\right), \left(x - y\right)\right)\right)\right)\right) \]
      14. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y + \left(\mathsf{neg}\left(-1\right)\right)\right), \left(x - y\right)\right)\right)\right)\right) \]
      15. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y + 1\right), \left(x - y\right)\right)\right)\right)\right) \]
      16. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\mathsf{+.f64}\left(y, 1\right), \left(x - y\right)\right)\right)\right)\right) \]
      17. --lowering--.f642.9%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\mathsf{+.f64}\left(y, 1\right), \mathsf{\_.f64}\left(x, y\right)\right)\right)\right)\right) \]
    6. Applied egg-rr2.9%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}\right) \]
    7. Step-by-step derivation
      1. flip-+N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(\frac{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}\right)\right) \]
      2. clear-numN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(\frac{1}{\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}}\right)\right) \]
      3. log-recN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{neg}\left(\log \left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right)\right) \]
      4. neg-lowering-neg.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\log \left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right) \]
      5. log-lowering-log.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right)\right) \]
    8. Applied egg-rr3.9%

      \[\leadsto 1 - \color{blue}{\left(-\log \left(\frac{1 - \frac{1}{y + -1} \cdot \left(x - y\right)}{1 - \frac{\frac{1}{y + -1}}{y + -1} \cdot \left(\left(x - y\right) \cdot \left(x - y\right)\right)}\right)\right)} \]
    9. Taylor expanded in x around inf

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\color{blue}{\left(\frac{y - 1}{x}\right)}\right)\right)\right) \]
    10. Step-by-step derivation
      1. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\left(y - 1\right), x\right)\right)\right)\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\left(y + \left(\mathsf{neg}\left(1\right)\right)\right), x\right)\right)\right)\right) \]
      3. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\left(y + -1\right), x\right)\right)\right)\right) \]
      4. +-lowering-+.f6441.1%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(y, -1\right), x\right)\right)\right)\right) \]
    11. Simplified41.1%

      \[\leadsto 1 - \left(-\log \color{blue}{\left(\frac{y + -1}{x}\right)}\right) \]
  3. Recombined 2 regimes into one program.
  4. Final simplification80.9%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{x - y}{1 - y} \leq 0.95:\\ \;\;\;\;1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)\\ \mathbf{else}:\\ \;\;\;\;1 + \log \left(\frac{y + -1}{x}\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 3: 81.7% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := 1 + \log \left(\frac{y + -1}{x}\right)\\ \mathbf{if}\;x \leq -115000000:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;1 - \mathsf{log1p}\left(\frac{x}{y + -1}\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
(FPCore (x y)
 :precision binary64
 (let* ((t_0 (+ 1.0 (log (/ (+ y -1.0) x)))))
   (if (<= x -115000000.0)
     t_0
     (if (<= x 1.0) (- 1.0 (log1p (/ x (+ y -1.0)))) t_0))))
double code(double x, double y) {
	double t_0 = 1.0 + log(((y + -1.0) / x));
	double tmp;
	if (x <= -115000000.0) {
		tmp = t_0;
	} else if (x <= 1.0) {
		tmp = 1.0 - log1p((x / (y + -1.0)));
	} else {
		tmp = t_0;
	}
	return tmp;
}
public static double code(double x, double y) {
	double t_0 = 1.0 + Math.log(((y + -1.0) / x));
	double tmp;
	if (x <= -115000000.0) {
		tmp = t_0;
	} else if (x <= 1.0) {
		tmp = 1.0 - Math.log1p((x / (y + -1.0)));
	} else {
		tmp = t_0;
	}
	return tmp;
}
def code(x, y):
	t_0 = 1.0 + math.log(((y + -1.0) / x))
	tmp = 0
	if x <= -115000000.0:
		tmp = t_0
	elif x <= 1.0:
		tmp = 1.0 - math.log1p((x / (y + -1.0)))
	else:
		tmp = t_0
	return tmp
function code(x, y)
	t_0 = Float64(1.0 + log(Float64(Float64(y + -1.0) / x)))
	tmp = 0.0
	if (x <= -115000000.0)
		tmp = t_0;
	elseif (x <= 1.0)
		tmp = Float64(1.0 - log1p(Float64(x / Float64(y + -1.0))));
	else
		tmp = t_0;
	end
	return tmp
end
code[x_, y_] := Block[{t$95$0 = N[(1.0 + N[Log[N[(N[(y + -1.0), $MachinePrecision] / x), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -115000000.0], t$95$0, If[LessEqual[x, 1.0], N[(1.0 - N[Log[1 + N[(x / N[(y + -1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], t$95$0]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := 1 + \log \left(\frac{y + -1}{x}\right)\\
\mathbf{if}\;x \leq -115000000:\\
\;\;\;\;t\_0\\

\mathbf{elif}\;x \leq 1:\\
\;\;\;\;1 - \mathsf{log1p}\left(\frac{x}{y + -1}\right)\\

\mathbf{else}:\\
\;\;\;\;t\_0\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < -1.15e8 or 1 < x

    1. Initial program 70.3%

      \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
    2. Step-by-step derivation
      1. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      3. log1p-defineN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      4. log1p-lowering-log1p.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      5. distribute-neg-frac2N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      8. neg-sub0N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
      9. associate--r-N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
      11. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
      12. +-lowering-+.f6470.3%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    3. Simplified70.3%

      \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
    4. Add Preprocessing
    5. Step-by-step derivation
      1. clear-numN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{\frac{y + -1}{x - y}}\right)\right)\right) \]
      2. associate-/r/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{y + -1} \cdot \left(x - y\right)\right)\right)\right) \]
      3. flip-+N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{\frac{y \cdot y - -1 \cdot -1}{y - -1}} \cdot \left(x - y\right)\right)\right)\right) \]
      4. associate-/r/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\left(\frac{1}{y \cdot y - -1 \cdot -1} \cdot \left(y - -1\right)\right) \cdot \left(x - y\right)\right)\right)\right) \]
      5. associate-*l*N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{1}{y \cdot y - -1 \cdot -1} \cdot \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      6. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\left(\frac{1}{y \cdot y - -1 \cdot -1}\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      7. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y - -1 \cdot -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      8. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y - 1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      9. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y + \left(\mathsf{neg}\left(1\right)\right)\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(y \cdot y + -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      11. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\left(y \cdot y\right), -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      12. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \left(\left(y - -1\right) \cdot \left(x - y\right)\right)\right)\right)\right) \]
      13. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y - -1\right), \left(x - y\right)\right)\right)\right)\right) \]
      14. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y + \left(\mathsf{neg}\left(-1\right)\right)\right), \left(x - y\right)\right)\right)\right)\right) \]
      15. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\left(y + 1\right), \left(x - y\right)\right)\right)\right)\right) \]
      16. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\mathsf{+.f64}\left(y, 1\right), \left(x - y\right)\right)\right)\right)\right) \]
      17. --lowering--.f6457.8%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(\mathsf{*.f64}\left(y, y\right), -1\right)\right), \mathsf{*.f64}\left(\mathsf{+.f64}\left(y, 1\right), \mathsf{\_.f64}\left(x, y\right)\right)\right)\right)\right) \]
    6. Applied egg-rr57.8%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}\right) \]
    7. Step-by-step derivation
      1. flip-+N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(\frac{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}\right)\right) \]
      2. clear-numN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(\frac{1}{\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}}\right)\right) \]
      3. log-recN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{neg}\left(\log \left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right)\right) \]
      4. neg-lowering-neg.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\log \left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right) \]
      5. log-lowering-log.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\left(\frac{1 - \frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)}{1 \cdot 1 - \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right) \cdot \left(\frac{1}{y \cdot y + -1} \cdot \left(\left(y + 1\right) \cdot \left(x - y\right)\right)\right)}\right)\right)\right)\right) \]
    8. Applied egg-rr32.9%

      \[\leadsto 1 - \color{blue}{\left(-\log \left(\frac{1 - \frac{1}{y + -1} \cdot \left(x - y\right)}{1 - \frac{\frac{1}{y + -1}}{y + -1} \cdot \left(\left(x - y\right) \cdot \left(x - y\right)\right)}\right)\right)} \]
    9. Taylor expanded in x around inf

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\color{blue}{\left(\frac{y - 1}{x}\right)}\right)\right)\right) \]
    10. Step-by-step derivation
      1. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\left(y - 1\right), x\right)\right)\right)\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\left(y + \left(\mathsf{neg}\left(1\right)\right)\right), x\right)\right)\right)\right) \]
      3. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\left(y + -1\right), x\right)\right)\right)\right) \]
      4. +-lowering-+.f6499.2%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{neg.f64}\left(\mathsf{log.f64}\left(\mathsf{/.f64}\left(\mathsf{+.f64}\left(y, -1\right), x\right)\right)\right)\right) \]
    11. Simplified99.2%

      \[\leadsto 1 - \left(-\log \color{blue}{\left(\frac{y + -1}{x}\right)}\right) \]

    if -1.15e8 < x < 1

    1. Initial program 68.1%

      \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
    2. Step-by-step derivation
      1. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      3. log1p-defineN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      4. log1p-lowering-log1p.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      5. distribute-neg-frac2N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      8. neg-sub0N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
      9. associate--r-N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
      11. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
      12. +-lowering-+.f6468.1%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    3. Simplified68.1%

      \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
    4. Add Preprocessing
    5. Taylor expanded in x around inf

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(\frac{x}{y - 1}\right)}\right)\right) \]
    6. Step-by-step derivation
      1. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y - 1\right)\right)\right)\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right)\right)\right) \]
      3. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + -1\right)\right)\right)\right) \]
      4. +-lowering-+.f6470.4%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    7. Simplified70.4%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{x}{y + -1}}\right) \]
  3. Recombined 2 regimes into one program.
  4. Final simplification81.7%

    \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -115000000:\\ \;\;\;\;1 + \log \left(\frac{y + -1}{x}\right)\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;1 - \mathsf{log1p}\left(\frac{x}{y + -1}\right)\\ \mathbf{else}:\\ \;\;\;\;1 + \log \left(\frac{y + -1}{x}\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 4: 72.4% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := 1 - \mathsf{log1p}\left(\frac{x}{y}\right)\\ \mathbf{if}\;y \leq -1:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;y \leq 1.9 \cdot 10^{-9}:\\ \;\;\;\;1 - \mathsf{log1p}\left(0 - x\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
(FPCore (x y)
 :precision binary64
 (let* ((t_0 (- 1.0 (log1p (/ x y)))))
   (if (<= y -1.0) t_0 (if (<= y 1.9e-9) (- 1.0 (log1p (- 0.0 x))) t_0))))
double code(double x, double y) {
	double t_0 = 1.0 - log1p((x / y));
	double tmp;
	if (y <= -1.0) {
		tmp = t_0;
	} else if (y <= 1.9e-9) {
		tmp = 1.0 - log1p((0.0 - x));
	} else {
		tmp = t_0;
	}
	return tmp;
}
public static double code(double x, double y) {
	double t_0 = 1.0 - Math.log1p((x / y));
	double tmp;
	if (y <= -1.0) {
		tmp = t_0;
	} else if (y <= 1.9e-9) {
		tmp = 1.0 - Math.log1p((0.0 - x));
	} else {
		tmp = t_0;
	}
	return tmp;
}
def code(x, y):
	t_0 = 1.0 - math.log1p((x / y))
	tmp = 0
	if y <= -1.0:
		tmp = t_0
	elif y <= 1.9e-9:
		tmp = 1.0 - math.log1p((0.0 - x))
	else:
		tmp = t_0
	return tmp
function code(x, y)
	t_0 = Float64(1.0 - log1p(Float64(x / y)))
	tmp = 0.0
	if (y <= -1.0)
		tmp = t_0;
	elseif (y <= 1.9e-9)
		tmp = Float64(1.0 - log1p(Float64(0.0 - x)));
	else
		tmp = t_0;
	end
	return tmp
end
code[x_, y_] := Block[{t$95$0 = N[(1.0 - N[Log[1 + N[(x / y), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -1.0], t$95$0, If[LessEqual[y, 1.9e-9], N[(1.0 - N[Log[1 + N[(0.0 - x), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], t$95$0]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := 1 - \mathsf{log1p}\left(\frac{x}{y}\right)\\
\mathbf{if}\;y \leq -1:\\
\;\;\;\;t\_0\\

\mathbf{elif}\;y \leq 1.9 \cdot 10^{-9}:\\
\;\;\;\;1 - \mathsf{log1p}\left(0 - x\right)\\

\mathbf{else}:\\
\;\;\;\;t\_0\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if y < -1 or 1.90000000000000006e-9 < y

    1. Initial program 29.0%

      \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
    2. Step-by-step derivation
      1. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      3. log1p-defineN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      4. log1p-lowering-log1p.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      5. distribute-neg-frac2N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      8. neg-sub0N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
      9. associate--r-N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
      11. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
      12. +-lowering-+.f6429.1%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    3. Simplified29.1%

      \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
    4. Add Preprocessing
    5. Taylor expanded in x around inf

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(\frac{x}{y - 1}\right)}\right)\right) \]
    6. Step-by-step derivation
      1. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y - 1\right)\right)\right)\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right)\right)\right) \]
      3. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + -1\right)\right)\right)\right) \]
      4. +-lowering-+.f6433.8%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    7. Simplified33.8%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{x}{y + -1}}\right) \]
    8. Taylor expanded in y around inf

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(\frac{x}{y}\right)}\right)\right) \]
    9. Step-by-step derivation
      1. /-lowering-/.f6433.5%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, y\right)\right)\right) \]
    10. Simplified33.5%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{x}{y}}\right) \]

    if -1 < y < 1.90000000000000006e-9

    1. Initial program 100.0%

      \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
    2. Step-by-step derivation
      1. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
      2. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      3. log1p-defineN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      4. log1p-lowering-log1p.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
      5. distribute-neg-frac2N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
      8. neg-sub0N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
      9. associate--r-N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
      10. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
      11. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
      12. +-lowering-+.f64100.0%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
    3. Simplified100.0%

      \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
    4. Add Preprocessing
    5. Step-by-step derivation
      1. div-invN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\left(x - y\right) \cdot \frac{1}{y + -1}\right)\right)\right) \]
      2. flip--N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x \cdot x - y \cdot y}{x + y} \cdot \frac{1}{y + -1}\right)\right)\right) \]
      3. associate-*l/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{\left(x \cdot x - y \cdot y\right) \cdot \frac{1}{y + -1}}{x + y}\right)\right)\right) \]
      4. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(\left(x \cdot x - y \cdot y\right) \cdot \frac{1}{y + -1}\right), \left(x + y\right)\right)\right)\right) \]
      5. un-div-invN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(\frac{x \cdot x - y \cdot y}{y + -1}\right), \left(x + y\right)\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\left(x \cdot x - y \cdot y\right), \left(y + -1\right)\right), \left(x + y\right)\right)\right)\right) \]
      7. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(x \cdot x\right), \left(y \cdot y\right)\right), \left(y + -1\right)\right), \left(x + y\right)\right)\right)\right) \]
      8. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(y \cdot y\right)\right), \left(y + -1\right)\right), \left(x + y\right)\right)\right)\right) \]
      9. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{*.f64}\left(y, y\right)\right), \left(y + -1\right)\right), \left(x + y\right)\right)\right)\right) \]
      10. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{*.f64}\left(y, y\right)\right), \mathsf{+.f64}\left(y, -1\right)\right), \left(x + y\right)\right)\right)\right) \]
      11. +-lowering-+.f6487.9%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{*.f64}\left(y, y\right)\right), \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{+.f64}\left(x, y\right)\right)\right)\right) \]
    6. Applied egg-rr87.9%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{\frac{x \cdot x - y \cdot y}{y + -1}}{x + y}}\right) \]
    7. Taylor expanded in x around inf

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(x \cdot \left(-1 \cdot \frac{y}{x \cdot \left(y - 1\right)} + \frac{1}{y - 1}\right)\right)}\right)\right) \]
    8. Step-by-step derivation
      1. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \left(-1 \cdot \frac{y}{x \cdot \left(y - 1\right)} + \frac{1}{y - 1}\right)\right)\right)\right) \]
      2. +-commutativeN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \left(\frac{1}{y - 1} + -1 \cdot \frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right) \]
      3. mul-1-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \left(\frac{1}{y - 1} + \left(\mathsf{neg}\left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right)\right) \]
      4. unsub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \left(\frac{1}{y - 1} - \frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right) \]
      5. --lowering--.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\frac{1}{y - 1}\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
      6. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \left(y - 1\right)\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
      7. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
      8. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \left(y + -1\right)\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
      9. +-lowering-+.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
      10. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \left(x \cdot \left(y - 1\right)\right)\right)\right)\right)\right)\right) \]
      11. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \mathsf{*.f64}\left(x, \left(y - 1\right)\right)\right)\right)\right)\right)\right) \]
      12. sub-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \mathsf{*.f64}\left(x, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right)\right)\right)\right)\right)\right) \]
      13. metadata-evalN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \mathsf{*.f64}\left(x, \left(y + -1\right)\right)\right)\right)\right)\right)\right) \]
      14. +-lowering-+.f64100.0%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right)\right)\right)\right)\right) \]
    9. Simplified100.0%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{x \cdot \left(\frac{1}{y + -1} - \frac{y}{x \cdot \left(y + -1\right)}\right)}\right) \]
    10. Step-by-step derivation
      1. clear-numN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \left(\frac{1}{\frac{x \cdot \left(y + -1\right)}{y}}\right)\right)\right)\right)\right) \]
      2. associate-/r/N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \left(\frac{1}{x \cdot \left(y + -1\right)} \cdot y\right)\right)\right)\right)\right) \]
      3. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{*.f64}\left(\left(\frac{1}{x \cdot \left(y + -1\right)}\right), y\right)\right)\right)\right)\right) \]
      4. /-lowering-/.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(x \cdot \left(y + -1\right)\right)\right), y\right)\right)\right)\right)\right) \]
      5. *-lowering-*.f64N/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{*.f64}\left(x, \left(y + -1\right)\right)\right), y\right)\right)\right)\right)\right) \]
      6. +-lowering-+.f64100.0%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right), y\right)\right)\right)\right)\right) \]
    11. Applied egg-rr100.0%

      \[\leadsto 1 - \mathsf{log1p}\left(x \cdot \left(\frac{1}{y + -1} - \color{blue}{\frac{1}{x \cdot \left(y + -1\right)} \cdot y}\right)\right) \]
    12. Taylor expanded in y around 0

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(-1 \cdot x\right)}\right)\right) \]
    13. Step-by-step derivation
      1. mul-1-negN/A

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
      2. neg-lowering-neg.f6499.9%

        \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{neg.f64}\left(x\right)\right)\right) \]
    14. Simplified99.9%

      \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{-x}\right) \]
  3. Recombined 2 regimes into one program.
  4. Final simplification70.8%

    \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1:\\ \;\;\;\;1 - \mathsf{log1p}\left(\frac{x}{y}\right)\\ \mathbf{elif}\;y \leq 1.9 \cdot 10^{-9}:\\ \;\;\;\;1 - \mathsf{log1p}\left(0 - x\right)\\ \mathbf{else}:\\ \;\;\;\;1 - \mathsf{log1p}\left(\frac{x}{y}\right)\\ \end{array} \]
  5. Add Preprocessing

Alternative 5: 73.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ 1 - \mathsf{log1p}\left(\frac{x}{y + -1}\right) \end{array} \]
(FPCore (x y) :precision binary64 (- 1.0 (log1p (/ x (+ y -1.0)))))
double code(double x, double y) {
	return 1.0 - log1p((x / (y + -1.0)));
}
public static double code(double x, double y) {
	return 1.0 - Math.log1p((x / (y + -1.0)));
}
def code(x, y):
	return 1.0 - math.log1p((x / (y + -1.0)))
function code(x, y)
	return Float64(1.0 - log1p(Float64(x / Float64(y + -1.0))))
end
code[x_, y_] := N[(1.0 - N[Log[1 + N[(x / N[(y + -1.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
1 - \mathsf{log1p}\left(\frac{x}{y + -1}\right)
\end{array}
Derivation
  1. Initial program 68.9%

    \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
  2. Step-by-step derivation
    1. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    3. log1p-defineN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    4. log1p-lowering-log1p.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    5. distribute-neg-frac2N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
    6. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
    7. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
    8. neg-sub0N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
    9. associate--r-N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
    10. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
    11. +-commutativeN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
    12. +-lowering-+.f6469.0%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
  3. Simplified69.0%

    \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
  4. Add Preprocessing
  5. Taylor expanded in x around inf

    \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(\frac{x}{y - 1}\right)}\right)\right) \]
  6. Step-by-step derivation
    1. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y - 1\right)\right)\right)\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right)\right)\right) \]
    3. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + -1\right)\right)\right)\right) \]
    4. +-lowering-+.f6471.0%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
  7. Simplified71.0%

    \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{x}{y + -1}}\right) \]
  8. Add Preprocessing

Alternative 6: 62.6% accurate, 1.1× speedup?

\[\begin{array}{l} \\ 1 - \mathsf{log1p}\left(0 - x\right) \end{array} \]
(FPCore (x y) :precision binary64 (- 1.0 (log1p (- 0.0 x))))
double code(double x, double y) {
	return 1.0 - log1p((0.0 - x));
}
public static double code(double x, double y) {
	return 1.0 - Math.log1p((0.0 - x));
}
def code(x, y):
	return 1.0 - math.log1p((0.0 - x))
function code(x, y)
	return Float64(1.0 - log1p(Float64(0.0 - x)))
end
code[x_, y_] := N[(1.0 - N[Log[1 + N[(0.0 - x), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
1 - \mathsf{log1p}\left(0 - x\right)
\end{array}
Derivation
  1. Initial program 68.9%

    \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
  2. Step-by-step derivation
    1. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    3. log1p-defineN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    4. log1p-lowering-log1p.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    5. distribute-neg-frac2N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
    6. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
    7. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
    8. neg-sub0N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
    9. associate--r-N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
    10. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
    11. +-commutativeN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
    12. +-lowering-+.f6469.0%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
  3. Simplified69.0%

    \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
  4. Add Preprocessing
  5. Step-by-step derivation
    1. div-invN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\left(x - y\right) \cdot \frac{1}{y + -1}\right)\right)\right) \]
    2. flip--N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x \cdot x - y \cdot y}{x + y} \cdot \frac{1}{y + -1}\right)\right)\right) \]
    3. associate-*l/N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{\left(x \cdot x - y \cdot y\right) \cdot \frac{1}{y + -1}}{x + y}\right)\right)\right) \]
    4. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(\left(x \cdot x - y \cdot y\right) \cdot \frac{1}{y + -1}\right), \left(x + y\right)\right)\right)\right) \]
    5. un-div-invN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(\frac{x \cdot x - y \cdot y}{y + -1}\right), \left(x + y\right)\right)\right)\right) \]
    6. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\left(x \cdot x - y \cdot y\right), \left(y + -1\right)\right), \left(x + y\right)\right)\right)\right) \]
    7. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\left(x \cdot x\right), \left(y \cdot y\right)\right), \left(y + -1\right)\right), \left(x + y\right)\right)\right)\right) \]
    8. *-lowering-*.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\mathsf{*.f64}\left(x, x\right), \left(y \cdot y\right)\right), \left(y + -1\right)\right), \left(x + y\right)\right)\right)\right) \]
    9. *-lowering-*.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{*.f64}\left(y, y\right)\right), \left(y + -1\right)\right), \left(x + y\right)\right)\right)\right) \]
    10. +-lowering-+.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{*.f64}\left(y, y\right)\right), \mathsf{+.f64}\left(y, -1\right)\right), \left(x + y\right)\right)\right)\right) \]
    11. +-lowering-+.f6453.9%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(\mathsf{*.f64}\left(x, x\right), \mathsf{*.f64}\left(y, y\right)\right), \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{+.f64}\left(x, y\right)\right)\right)\right) \]
  6. Applied egg-rr53.9%

    \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{\frac{x \cdot x - y \cdot y}{y + -1}}{x + y}}\right) \]
  7. Taylor expanded in x around inf

    \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(x \cdot \left(-1 \cdot \frac{y}{x \cdot \left(y - 1\right)} + \frac{1}{y - 1}\right)\right)}\right)\right) \]
  8. Step-by-step derivation
    1. *-lowering-*.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \left(-1 \cdot \frac{y}{x \cdot \left(y - 1\right)} + \frac{1}{y - 1}\right)\right)\right)\right) \]
    2. +-commutativeN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \left(\frac{1}{y - 1} + -1 \cdot \frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right) \]
    3. mul-1-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \left(\frac{1}{y - 1} + \left(\mathsf{neg}\left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right)\right) \]
    4. unsub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \left(\frac{1}{y - 1} - \frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right) \]
    5. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\left(\frac{1}{y - 1}\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
    6. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \left(y - 1\right)\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
    7. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
    8. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \left(y + -1\right)\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
    9. +-lowering-+.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \left(\frac{y}{x \cdot \left(y - 1\right)}\right)\right)\right)\right)\right) \]
    10. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \left(x \cdot \left(y - 1\right)\right)\right)\right)\right)\right)\right) \]
    11. *-lowering-*.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \mathsf{*.f64}\left(x, \left(y - 1\right)\right)\right)\right)\right)\right)\right) \]
    12. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \mathsf{*.f64}\left(x, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right)\right)\right)\right)\right)\right) \]
    13. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \mathsf{*.f64}\left(x, \left(y + -1\right)\right)\right)\right)\right)\right)\right) \]
    14. +-lowering-+.f6469.9%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{/.f64}\left(y, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right)\right)\right)\right)\right) \]
  9. Simplified69.9%

    \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{x \cdot \left(\frac{1}{y + -1} - \frac{y}{x \cdot \left(y + -1\right)}\right)}\right) \]
  10. Step-by-step derivation
    1. clear-numN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \left(\frac{1}{\frac{x \cdot \left(y + -1\right)}{y}}\right)\right)\right)\right)\right) \]
    2. associate-/r/N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \left(\frac{1}{x \cdot \left(y + -1\right)} \cdot y\right)\right)\right)\right)\right) \]
    3. *-lowering-*.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{*.f64}\left(\left(\frac{1}{x \cdot \left(y + -1\right)}\right), y\right)\right)\right)\right)\right) \]
    4. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \left(x \cdot \left(y + -1\right)\right)\right), y\right)\right)\right)\right)\right) \]
    5. *-lowering-*.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{*.f64}\left(x, \left(y + -1\right)\right)\right), y\right)\right)\right)\right)\right) \]
    6. +-lowering-+.f6470.2%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{*.f64}\left(x, \mathsf{\_.f64}\left(\mathsf{/.f64}\left(1, \mathsf{+.f64}\left(y, -1\right)\right), \mathsf{*.f64}\left(\mathsf{/.f64}\left(1, \mathsf{*.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right), y\right)\right)\right)\right)\right) \]
  11. Applied egg-rr70.2%

    \[\leadsto 1 - \mathsf{log1p}\left(x \cdot \left(\frac{1}{y + -1} - \color{blue}{\frac{1}{x \cdot \left(y + -1\right)} \cdot y}\right)\right) \]
  12. Taylor expanded in y around 0

    \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(-1 \cdot x\right)}\right)\right) \]
  13. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(x\right)\right)\right)\right) \]
    2. neg-lowering-neg.f6460.2%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{neg.f64}\left(x\right)\right)\right) \]
  14. Simplified60.2%

    \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{-x}\right) \]
  15. Final simplification60.2%

    \[\leadsto 1 - \mathsf{log1p}\left(0 - x\right) \]
  16. Add Preprocessing

Alternative 7: 45.0% accurate, 15.9× speedup?

\[\begin{array}{l} \\ 1 - \frac{x}{y + -1} \end{array} \]
(FPCore (x y) :precision binary64 (- 1.0 (/ x (+ y -1.0))))
double code(double x, double y) {
	return 1.0 - (x / (y + -1.0));
}
real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = 1.0d0 - (x / (y + (-1.0d0)))
end function
public static double code(double x, double y) {
	return 1.0 - (x / (y + -1.0));
}
def code(x, y):
	return 1.0 - (x / (y + -1.0))
function code(x, y)
	return Float64(1.0 - Float64(x / Float64(y + -1.0)))
end
function tmp = code(x, y)
	tmp = 1.0 - (x / (y + -1.0));
end
code[x_, y_] := N[(1.0 - N[(x / N[(y + -1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
1 - \frac{x}{y + -1}
\end{array}
Derivation
  1. Initial program 68.9%

    \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
  2. Step-by-step derivation
    1. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    3. log1p-defineN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    4. log1p-lowering-log1p.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    5. distribute-neg-frac2N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
    6. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
    7. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
    8. neg-sub0N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
    9. associate--r-N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
    10. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
    11. +-commutativeN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
    12. +-lowering-+.f6469.0%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
  3. Simplified69.0%

    \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
  4. Add Preprocessing
  5. Taylor expanded in x around inf

    \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(\frac{x}{y - 1}\right)}\right)\right) \]
  6. Step-by-step derivation
    1. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y - 1\right)\right)\right)\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right)\right)\right) \]
    3. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + -1\right)\right)\right)\right) \]
    4. +-lowering-+.f6471.0%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
  7. Simplified71.0%

    \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{x}{y + -1}}\right) \]
  8. Taylor expanded in x around 0

    \[\leadsto \color{blue}{1 + -1 \cdot \frac{x}{y - 1}} \]
  9. Step-by-step derivation
    1. mul-1-negN/A

      \[\leadsto 1 + \left(\mathsf{neg}\left(\frac{x}{y - 1}\right)\right) \]
    2. unsub-negN/A

      \[\leadsto 1 - \color{blue}{\frac{x}{y - 1}} \]
    3. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\left(\frac{x}{y - 1}\right)}\right) \]
    4. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{/.f64}\left(x, \color{blue}{\left(y - 1\right)}\right)\right) \]
    5. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{/.f64}\left(x, \left(y + \color{blue}{\left(\mathsf{neg}\left(1\right)\right)}\right)\right)\right) \]
    6. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{/.f64}\left(x, \left(y + -1\right)\right)\right) \]
    7. +-lowering-+.f6444.9%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{/.f64}\left(x, \mathsf{+.f64}\left(y, \color{blue}{-1}\right)\right)\right) \]
  10. Simplified44.9%

    \[\leadsto \color{blue}{1 - \frac{x}{y + -1}} \]
  11. Add Preprocessing

Alternative 8: 43.3% accurate, 111.0× speedup?

\[\begin{array}{l} \\ 1 \end{array} \]
(FPCore (x y) :precision binary64 1.0)
double code(double x, double y) {
	return 1.0;
}
real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = 1.0d0
end function
public static double code(double x, double y) {
	return 1.0;
}
def code(x, y):
	return 1.0
function code(x, y)
	return 1.0
end
function tmp = code(x, y)
	tmp = 1.0;
end
code[x_, y_] := 1.0
\begin{array}{l}

\\
1
\end{array}
Derivation
  1. Initial program 68.9%

    \[1 - \log \left(1 - \frac{x - y}{1 - y}\right) \]
  2. Step-by-step derivation
    1. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \color{blue}{\log \left(1 - \frac{x - y}{1 - y}\right)}\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \log \left(1 + \left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    3. log1p-defineN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \left(\mathsf{log1p}\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    4. log1p-lowering-log1p.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\mathsf{neg}\left(\frac{x - y}{1 - y}\right)\right)\right)\right) \]
    5. distribute-neg-frac2N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\left(\frac{x - y}{\mathsf{neg}\left(\left(1 - y\right)\right)}\right)\right)\right) \]
    6. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\left(x - y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
    7. --lowering--.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\mathsf{neg}\left(\left(1 - y\right)\right)\right)\right)\right)\right) \]
    8. neg-sub0N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(0 - \left(1 - y\right)\right)\right)\right)\right) \]
    9. associate--r-N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(\left(0 - 1\right) + y\right)\right)\right)\right) \]
    10. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(-1 + y\right)\right)\right)\right) \]
    11. +-commutativeN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \left(y + -1\right)\right)\right)\right) \]
    12. +-lowering-+.f6469.0%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(\mathsf{\_.f64}\left(x, y\right), \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
  3. Simplified69.0%

    \[\leadsto \color{blue}{1 - \mathsf{log1p}\left(\frac{x - y}{y + -1}\right)} \]
  4. Add Preprocessing
  5. Taylor expanded in x around inf

    \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\color{blue}{\left(\frac{x}{y - 1}\right)}\right)\right) \]
  6. Step-by-step derivation
    1. /-lowering-/.f64N/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y - 1\right)\right)\right)\right) \]
    2. sub-negN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + \left(\mathsf{neg}\left(1\right)\right)\right)\right)\right)\right) \]
    3. metadata-evalN/A

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \left(y + -1\right)\right)\right)\right) \]
    4. +-lowering-+.f6471.0%

      \[\leadsto \mathsf{\_.f64}\left(1, \mathsf{log1p.f64}\left(\mathsf{/.f64}\left(x, \mathsf{+.f64}\left(y, -1\right)\right)\right)\right) \]
  7. Simplified71.0%

    \[\leadsto 1 - \mathsf{log1p}\left(\color{blue}{\frac{x}{y + -1}}\right) \]
  8. Taylor expanded in x around 0

    \[\leadsto \color{blue}{1} \]
  9. Step-by-step derivation
    1. Simplified43.3%

      \[\leadsto \color{blue}{1} \]
    2. Add Preprocessing

    Developer Target 1: 99.8% accurate, 0.5× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := 1 - \log \left(\frac{x}{y \cdot y} - \left(\frac{1}{y} - \frac{x}{y}\right)\right)\\ \mathbf{if}\;y < -81284752.61947241:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;y < 3.0094271212461764 \cdot 10^{+25}:\\ \;\;\;\;\log \left(\frac{e^{1}}{1 - \frac{x - y}{1 - y}}\right)\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
    (FPCore (x y)
     :precision binary64
     (let* ((t_0 (- 1.0 (log (- (/ x (* y y)) (- (/ 1.0 y) (/ x y)))))))
       (if (< y -81284752.61947241)
         t_0
         (if (< y 3.0094271212461764e+25)
           (log (/ (exp 1.0) (- 1.0 (/ (- x y) (- 1.0 y)))))
           t_0))))
    double code(double x, double y) {
    	double t_0 = 1.0 - log(((x / (y * y)) - ((1.0 / y) - (x / y))));
    	double tmp;
    	if (y < -81284752.61947241) {
    		tmp = t_0;
    	} else if (y < 3.0094271212461764e+25) {
    		tmp = log((exp(1.0) / (1.0 - ((x - y) / (1.0 - y)))));
    	} else {
    		tmp = t_0;
    	}
    	return tmp;
    }
    
    real(8) function code(x, y)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        real(8) :: t_0
        real(8) :: tmp
        t_0 = 1.0d0 - log(((x / (y * y)) - ((1.0d0 / y) - (x / y))))
        if (y < (-81284752.61947241d0)) then
            tmp = t_0
        else if (y < 3.0094271212461764d+25) then
            tmp = log((exp(1.0d0) / (1.0d0 - ((x - y) / (1.0d0 - y)))))
        else
            tmp = t_0
        end if
        code = tmp
    end function
    
    public static double code(double x, double y) {
    	double t_0 = 1.0 - Math.log(((x / (y * y)) - ((1.0 / y) - (x / y))));
    	double tmp;
    	if (y < -81284752.61947241) {
    		tmp = t_0;
    	} else if (y < 3.0094271212461764e+25) {
    		tmp = Math.log((Math.exp(1.0) / (1.0 - ((x - y) / (1.0 - y)))));
    	} else {
    		tmp = t_0;
    	}
    	return tmp;
    }
    
    def code(x, y):
    	t_0 = 1.0 - math.log(((x / (y * y)) - ((1.0 / y) - (x / y))))
    	tmp = 0
    	if y < -81284752.61947241:
    		tmp = t_0
    	elif y < 3.0094271212461764e+25:
    		tmp = math.log((math.exp(1.0) / (1.0 - ((x - y) / (1.0 - y)))))
    	else:
    		tmp = t_0
    	return tmp
    
    function code(x, y)
    	t_0 = Float64(1.0 - log(Float64(Float64(x / Float64(y * y)) - Float64(Float64(1.0 / y) - Float64(x / y)))))
    	tmp = 0.0
    	if (y < -81284752.61947241)
    		tmp = t_0;
    	elseif (y < 3.0094271212461764e+25)
    		tmp = log(Float64(exp(1.0) / Float64(1.0 - Float64(Float64(x - y) / Float64(1.0 - y)))));
    	else
    		tmp = t_0;
    	end
    	return tmp
    end
    
    function tmp_2 = code(x, y)
    	t_0 = 1.0 - log(((x / (y * y)) - ((1.0 / y) - (x / y))));
    	tmp = 0.0;
    	if (y < -81284752.61947241)
    		tmp = t_0;
    	elseif (y < 3.0094271212461764e+25)
    		tmp = log((exp(1.0) / (1.0 - ((x - y) / (1.0 - y)))));
    	else
    		tmp = t_0;
    	end
    	tmp_2 = tmp;
    end
    
    code[x_, y_] := Block[{t$95$0 = N[(1.0 - N[Log[N[(N[(x / N[(y * y), $MachinePrecision]), $MachinePrecision] - N[(N[(1.0 / y), $MachinePrecision] - N[(x / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, If[Less[y, -81284752.61947241], t$95$0, If[Less[y, 3.0094271212461764e+25], N[Log[N[(N[Exp[1.0], $MachinePrecision] / N[(1.0 - N[(N[(x - y), $MachinePrecision] / N[(1.0 - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], t$95$0]]]
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := 1 - \log \left(\frac{x}{y \cdot y} - \left(\frac{1}{y} - \frac{x}{y}\right)\right)\\
    \mathbf{if}\;y < -81284752.61947241:\\
    \;\;\;\;t\_0\\
    
    \mathbf{elif}\;y < 3.0094271212461764 \cdot 10^{+25}:\\
    \;\;\;\;\log \left(\frac{e^{1}}{1 - \frac{x - y}{1 - y}}\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;t\_0\\
    
    
    \end{array}
    \end{array}
    

    Reproduce

    ?
    herbie shell --seed 2024138 
    (FPCore (x y)
      :name "Numeric.SpecFunctions:invIncompleteGamma from math-functions-0.1.5.2, B"
      :precision binary64
    
      :alt
      (! :herbie-platform default (if (< y -8128475261947241/100000000) (- 1 (log (- (/ x (* y y)) (- (/ 1 y) (/ x y))))) (if (< y 30094271212461764000000000) (log (/ (exp 1) (- 1 (/ (- x y) (- 1 y))))) (- 1 (log (- (/ x (* y y)) (- (/ 1 y) (/ x y))))))))
    
      (- 1.0 (log (- 1.0 (/ (- x y) (- 1.0 y))))))