Numeric.SpecFunctions:$slogFactorial from math-functions-0.1.5.2, B

Percentage Accurate: 93.5% → 99.3%
Time: 14.9s
Alternatives: 19
Speedup: 1.0×

Specification

?
\[\begin{array}{l} \\ \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (+
  (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467)
  (/
   (+
    (* (- (* (+ y 0.0007936500793651) z) 0.0027777777777778) z)
    0.083333333333333)
   x)))
double code(double x, double y, double z) {
	return ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = ((((x - 0.5d0) * log(x)) - x) + 0.91893853320467d0) + ((((((y + 0.0007936500793651d0) * z) - 0.0027777777777778d0) * z) + 0.083333333333333d0) / x)
end function
public static double code(double x, double y, double z) {
	return ((((x - 0.5) * Math.log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
}
def code(x, y, z):
	return ((((x - 0.5) * math.log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x)
function code(x, y, z)
	return Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) - x) + 0.91893853320467) + Float64(Float64(Float64(Float64(Float64(Float64(y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x))
end
function tmp = code(x, y, z)
	tmp = ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
end
code[x_, y_, z_] := N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(N[(N[(N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision] + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x}
\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 19 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: 93.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (+
  (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467)
  (/
   (+
    (* (- (* (+ y 0.0007936500793651) z) 0.0027777777777778) z)
    0.083333333333333)
   x)))
double code(double x, double y, double z) {
	return ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = ((((x - 0.5d0) * log(x)) - x) + 0.91893853320467d0) + ((((((y + 0.0007936500793651d0) * z) - 0.0027777777777778d0) * z) + 0.083333333333333d0) / x)
end function
public static double code(double x, double y, double z) {
	return ((((x - 0.5) * Math.log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
}
def code(x, y, z):
	return ((((x - 0.5) * math.log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x)
function code(x, y, z)
	return Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) - x) + 0.91893853320467) + Float64(Float64(Float64(Float64(Float64(Float64(y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x))
end
function tmp = code(x, y, z)
	tmp = ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
end
code[x_, y_, z_] := N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(N[(N[(N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision] + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x}
\end{array}

Alternative 1: 99.3% accurate, 0.6× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 2 \cdot 10^{+66}:\\ \;\;\;\;\left(\mathsf{fma}\left(\log x - 1, x, -0.5 \cdot \log x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x}\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{0.0007936500793651}{x}\right) \cdot z - \frac{0.0027777777777778}{x}, z, \frac{0.083333333333333}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<= x 2e+66)
   (+
    (+ (fma (- (log x) 1.0) x (* -0.5 (log x))) 0.91893853320467)
    (/
     (+
      (* (- (* (+ y 0.0007936500793651) z) 0.0027777777777778) z)
      0.083333333333333)
     x))
   (+
    (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467)
    (fma
     (- (* (+ (/ y x) (/ 0.0007936500793651 x)) z) (/ 0.0027777777777778 x))
     z
     (/ 0.083333333333333 x)))))
double code(double x, double y, double z) {
	double tmp;
	if (x <= 2e+66) {
		tmp = (fma((log(x) - 1.0), x, (-0.5 * log(x))) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
	} else {
		tmp = ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + fma(((((y / x) + (0.0007936500793651 / x)) * z) - (0.0027777777777778 / x)), z, (0.083333333333333 / x));
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (x <= 2e+66)
		tmp = Float64(Float64(fma(Float64(log(x) - 1.0), x, Float64(-0.5 * log(x))) + 0.91893853320467) + Float64(Float64(Float64(Float64(Float64(Float64(y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x));
	else
		tmp = Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) - x) + 0.91893853320467) + fma(Float64(Float64(Float64(Float64(y / x) + Float64(0.0007936500793651 / x)) * z) - Float64(0.0027777777777778 / x)), z, Float64(0.083333333333333 / x)));
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[x, 2e+66], N[(N[(N[(N[(N[Log[x], $MachinePrecision] - 1.0), $MachinePrecision] * x + N[(-0.5 * N[Log[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(N[(N[(N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision] + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision], N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(N[(N[(N[(N[(y / x), $MachinePrecision] + N[(0.0007936500793651 / x), $MachinePrecision]), $MachinePrecision] * z), $MachinePrecision] - N[(0.0027777777777778 / x), $MachinePrecision]), $MachinePrecision] * z + N[(0.083333333333333 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 2 \cdot 10^{+66}:\\
\;\;\;\;\left(\mathsf{fma}\left(\log x - 1, x, -0.5 \cdot \log x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x}\\

\mathbf{else}:\\
\;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{0.0007936500793651}{x}\right) \cdot z - \frac{0.0027777777777778}{x}, z, \frac{0.083333333333333}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < 1.99999999999999989e66

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around 0

      \[\leadsto \left(\color{blue}{\left(\frac{-1}{2} \cdot \log x + x \cdot \left(\log x - 1\right)\right)} + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
    4. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \left(\left(x \cdot \left(\log x - 1\right) + \color{blue}{\frac{-1}{2} \cdot \log x}\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      2. *-commutativeN/A

        \[\leadsto \left(\left(\left(\log x - 1\right) \cdot x + \color{blue}{\frac{-1}{2}} \cdot \log x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      3. lower-fma.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\log x - 1, \color{blue}{x}, \frac{-1}{2} \cdot \log x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      4. lower--.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\log x - 1, x, \frac{-1}{2} \cdot \log x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\log x - 1, x, \frac{-1}{2} \cdot \log x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      6. lower-*.f64N/A

        \[\leadsto \left(\mathsf{fma}\left(\log x - 1, x, \frac{-1}{2} \cdot \log x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      7. lift-log.f6499.7

        \[\leadsto \left(\mathsf{fma}\left(\log x - 1, x, -0.5 \cdot \log x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    5. Applied rewrites99.7%

      \[\leadsto \left(\color{blue}{\mathsf{fma}\left(\log x - 1, x, -0.5 \cdot \log x\right)} + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]

    if 1.99999999999999989e66 < x

    1. Initial program 81.3%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around 0

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}\right) + \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\left(z \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}\right) \cdot z + \color{blue}{\frac{83333333333333}{1000000000000000}} \cdot \frac{1}{x}\right) \]
      2. lower-fma.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(z \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, \color{blue}{z}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      3. lower--.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(z \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      4. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      5. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      6. +-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{7936500793651}{10000000000000000} \cdot \frac{1}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      7. lower-+.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{7936500793651}{10000000000000000} \cdot \frac{1}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      8. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{7936500793651}{10000000000000000} \cdot \frac{1}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      9. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000} \cdot 1}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      10. metadata-evalN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      11. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      12. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{\frac{13888888888889}{5000000000000000} \cdot 1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      13. metadata-evalN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{\frac{13888888888889}{5000000000000000}}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      14. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{\frac{13888888888889}{5000000000000000}}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      15. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{\frac{13888888888889}{5000000000000000}}{x}, z, \frac{\frac{83333333333333}{1000000000000000} \cdot 1}{x}\right) \]
    5. Applied rewrites99.6%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(\left(\frac{y}{x} + \frac{0.0007936500793651}{x}\right) \cdot z - \frac{0.0027777777777778}{x}, z, \frac{0.083333333333333}{x}\right)} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 2: 99.5% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 10^{-34}:\\ \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{0.0007936500793651}{x}\right) \cdot z - \frac{0.0027777777777778}{x}, z, \frac{0.083333333333333}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<= x 1e-34)
   (/
    (fma
     (- (* (+ 0.0007936500793651 y) z) 0.0027777777777778)
     z
     0.083333333333333)
    x)
   (+
    (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467)
    (fma
     (- (* (+ (/ y x) (/ 0.0007936500793651 x)) z) (/ 0.0027777777777778 x))
     z
     (/ 0.083333333333333 x)))))
double code(double x, double y, double z) {
	double tmp;
	if (x <= 1e-34) {
		tmp = fma((((0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x;
	} else {
		tmp = ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + fma(((((y / x) + (0.0007936500793651 / x)) * z) - (0.0027777777777778 / x)), z, (0.083333333333333 / x));
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (x <= 1e-34)
		tmp = Float64(fma(Float64(Float64(Float64(0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x);
	else
		tmp = Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) - x) + 0.91893853320467) + fma(Float64(Float64(Float64(Float64(y / x) + Float64(0.0007936500793651 / x)) * z) - Float64(0.0027777777777778 / x)), z, Float64(0.083333333333333 / x)));
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[x, 1e-34], N[(N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(N[(N[(N[(N[(y / x), $MachinePrecision] + N[(0.0007936500793651 / x), $MachinePrecision]), $MachinePrecision] * z), $MachinePrecision] - N[(0.0027777777777778 / x), $MachinePrecision]), $MachinePrecision] * z + N[(0.083333333333333 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 10^{-34}:\\
\;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\

\mathbf{else}:\\
\;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{0.0007936500793651}{x}\right) \cdot z - \frac{0.0027777777777778}{x}, z, \frac{0.083333333333333}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < 9.99999999999999928e-35

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      3. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      4. +-commutativeN/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{\color{blue}{x}} \]
      6. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      7. lift-*.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      8. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      9. lift--.f6499.7

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      11. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      12. lower-+.f6499.7

        \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
    5. Applied rewrites99.7%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]

    if 9.99999999999999928e-35 < x

    1. Initial program 86.1%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around 0

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}\right) + \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\left(z \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}\right) \cdot z + \color{blue}{\frac{83333333333333}{1000000000000000}} \cdot \frac{1}{x}\right) \]
      2. lower-fma.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(z \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, \color{blue}{z}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      3. lower--.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(z \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      4. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      5. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      6. +-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{7936500793651}{10000000000000000} \cdot \frac{1}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      7. lower-+.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{7936500793651}{10000000000000000} \cdot \frac{1}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      8. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{7936500793651}{10000000000000000} \cdot \frac{1}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      9. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000} \cdot 1}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      10. metadata-evalN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      11. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{13888888888889}{5000000000000000} \cdot \frac{1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      12. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{\frac{13888888888889}{5000000000000000} \cdot 1}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      13. metadata-evalN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{\frac{13888888888889}{5000000000000000}}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      14. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{\frac{13888888888889}{5000000000000000}}{x}, z, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right) \]
      15. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \mathsf{fma}\left(\left(\frac{y}{x} + \frac{\frac{7936500793651}{10000000000000000}}{x}\right) \cdot z - \frac{\frac{13888888888889}{5000000000000000}}{x}, z, \frac{\frac{83333333333333}{1000000000000000} \cdot 1}{x}\right) \]
    5. Applied rewrites99.6%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(\left(\frac{y}{x} + \frac{0.0007936500793651}{x}\right) \cdot z - \frac{0.0027777777777778}{x}, z, \frac{0.083333333333333}{x}\right)} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 3: 52.3% accurate, 0.8× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \leq 5 \cdot 10^{+307}:\\ \;\;\;\;\frac{\mathsf{fma}\left(z \cdot y, z, 0.083333333333333\right)}{x}\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(z \cdot \frac{z}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<=
      (+
       (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467)
       (/
        (+
         (* (- (* (+ y 0.0007936500793651) z) 0.0027777777777778) z)
         0.083333333333333)
        x))
      5e+307)
   (/ (fma (* z y) z 0.083333333333333) x)
   (* y (* z (/ z x)))))
double code(double x, double y, double z) {
	double tmp;
	if ((((((x - 0.5) * log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x)) <= 5e+307) {
		tmp = fma((z * y), z, 0.083333333333333) / x;
	} else {
		tmp = y * (z * (z / x));
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) - x) + 0.91893853320467) + Float64(Float64(Float64(Float64(Float64(Float64(y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x)) <= 5e+307)
		tmp = Float64(fma(Float64(z * y), z, 0.083333333333333) / x);
	else
		tmp = Float64(y * Float64(z * Float64(z / x)));
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(N[(N[(N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision] + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision], 5e+307], N[(N[(N[(z * y), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], N[(y * N[(z * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \leq 5 \cdot 10^{+307}:\\
\;\;\;\;\frac{\mathsf{fma}\left(z \cdot y, z, 0.083333333333333\right)}{x}\\

\mathbf{else}:\\
\;\;\;\;y \cdot \left(z \cdot \frac{z}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 x #s(literal 1/2 binary64)) (log.f64 x)) x) #s(literal 91893853320467/100000000000000 binary64)) (/.f64 (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64)) x)) < 5e307

    1. Initial program 97.6%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
      2. lift-+.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
      3. lift-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
      4. lift--.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lift-+.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      6. lift-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      7. div-addN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
      8. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      9. +-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      10. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      11. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      12. metadata-evalN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
      13. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
      14. lower-fma.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
    4. Applied rewrites97.0%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
    5. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    6. Step-by-step derivation
      1. div-subN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      3. div-subN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      4. associate-/l*N/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z} \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      5. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      6. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      7. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      8. div-addN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}}{x} \]
      9. lower-/.f64N/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{\color{blue}{x}} \]
    7. Applied rewrites58.0%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]
    8. Taylor expanded in y around inf

      \[\leadsto \frac{\mathsf{fma}\left(y \cdot z, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
    9. Step-by-step derivation
      1. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(y \cdot z, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(z \cdot y, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      3. lower-*.f6452.6

        \[\leadsto \frac{\mathsf{fma}\left(z \cdot y, z, 0.083333333333333\right)}{x} \]
    10. Applied rewrites52.6%

      \[\leadsto \frac{\mathsf{fma}\left(z \cdot y, z, 0.083333333333333\right)}{x} \]

    if 5e307 < (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 x #s(literal 1/2 binary64)) (log.f64 x)) x) #s(literal 91893853320467/100000000000000 binary64)) (/.f64 (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64)) x))

    1. Initial program 78.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{\frac{y \cdot {z}^{2}}{x}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \frac{y \cdot {z}^{2}}{\color{blue}{x}} \]
      2. *-commutativeN/A

        \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
      3. lower-*.f64N/A

        \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
      4. unpow2N/A

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
      5. lower-*.f6453.7

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
    5. Applied rewrites53.7%

      \[\leadsto \color{blue}{\frac{\left(z \cdot z\right) \cdot y}{x}} \]
    6. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{\color{blue}{x}} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
      3. lift-*.f64N/A

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
      4. pow2N/A

        \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
      5. *-commutativeN/A

        \[\leadsto \frac{y \cdot {z}^{2}}{x} \]
      6. associate-/l*N/A

        \[\leadsto y \cdot \color{blue}{\frac{{z}^{2}}{x}} \]
      7. lower-*.f64N/A

        \[\leadsto y \cdot \color{blue}{\frac{{z}^{2}}{x}} \]
      8. lower-/.f64N/A

        \[\leadsto y \cdot \frac{{z}^{2}}{\color{blue}{x}} \]
      9. pow2N/A

        \[\leadsto y \cdot \frac{z \cdot z}{x} \]
      10. lift-*.f6458.9

        \[\leadsto y \cdot \frac{z \cdot z}{x} \]
    7. Applied rewrites58.9%

      \[\leadsto y \cdot \color{blue}{\frac{z \cdot z}{x}} \]
    8. Step-by-step derivation
      1. lift-*.f64N/A

        \[\leadsto y \cdot \frac{z \cdot z}{x} \]
      2. lift-/.f64N/A

        \[\leadsto y \cdot \frac{z \cdot z}{\color{blue}{x}} \]
      3. associate-/l*N/A

        \[\leadsto y \cdot \left(z \cdot \color{blue}{\frac{z}{x}}\right) \]
      4. lower-*.f64N/A

        \[\leadsto y \cdot \left(z \cdot \color{blue}{\frac{z}{x}}\right) \]
      5. lower-/.f6461.7

        \[\leadsto y \cdot \left(z \cdot \frac{z}{\color{blue}{x}}\right) \]
    9. Applied rewrites61.7%

      \[\leadsto y \cdot \left(z \cdot \color{blue}{\frac{z}{x}}\right) \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 4: 97.7% accurate, 0.9× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 3.4 \cdot 10^{+218}:\\ \;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)\\ \mathbf{else}:\\ \;\;\;\;\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<= x 3.4e+218)
   (+
    (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467)
    (fma
     z
     (/ (- (* (+ 0.0007936500793651 y) z) 0.0027777777777778) x)
     (/ 0.083333333333333 x)))
   (+ (- (* (log x) (- x 0.5)) (- x 0.91893853320467)) (* z (* y (/ z x))))))
double code(double x, double y, double z) {
	double tmp;
	if (x <= 3.4e+218) {
		tmp = ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + fma(z, ((((0.0007936500793651 + y) * z) - 0.0027777777777778) / x), (0.083333333333333 / x));
	} else {
		tmp = ((log(x) * (x - 0.5)) - (x - 0.91893853320467)) + (z * (y * (z / x)));
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (x <= 3.4e+218)
		tmp = Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) - x) + 0.91893853320467) + fma(z, Float64(Float64(Float64(Float64(0.0007936500793651 + y) * z) - 0.0027777777777778) / x), Float64(0.083333333333333 / x)));
	else
		tmp = Float64(Float64(Float64(log(x) * Float64(x - 0.5)) - Float64(x - 0.91893853320467)) + Float64(z * Float64(y * Float64(z / x))));
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[x, 3.4e+218], N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(z * N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] / x), $MachinePrecision] + N[(0.083333333333333 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(N[Log[x], $MachinePrecision] * N[(x - 0.5), $MachinePrecision]), $MachinePrecision] - N[(x - 0.91893853320467), $MachinePrecision]), $MachinePrecision] + N[(z * N[(y * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 3.4 \cdot 10^{+218}:\\
\;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)\\

\mathbf{else}:\\
\;\;\;\;\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < 3.40000000000000009e218

    1. Initial program 95.9%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
      2. lift-+.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
      3. lift-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
      4. lift--.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lift-+.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      6. lift-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      7. div-addN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
      8. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      9. +-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      10. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      11. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      12. metadata-evalN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
      13. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
      14. lower-fma.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
    4. Applied rewrites98.3%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]

    if 3.40000000000000009e218 < x

    1. Initial program 74.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6484.5

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites84.5%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6484.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites87.0%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
    8. Taylor expanded in y around inf

      \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{y \cdot z}{\color{blue}{x}} \]
    9. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      2. lower-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      3. lower-/.f6499.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right) \]
    10. Applied rewrites99.5%

      \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \color{blue}{\frac{z}{x}}\right) \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 5: 98.6% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \log x \cdot \left(x - 0.5\right)\\ \mathbf{if}\;x \leq 1300000:\\ \;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x}\\ \mathbf{elif}\;x \leq 3.4 \cdot 10^{+218}:\\ \;\;\;\;t\_0 - \left(\left(x - 0.91893853320467\right) - \frac{\left(0.0007936500793651 + y\right) \cdot z}{x} \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;\left(t\_0 - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (* (log x) (- x 0.5))))
   (if (<= x 1300000.0)
     (+
      (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467)
      (/
       (+
        (* (- (* (+ y 0.0007936500793651) z) 0.0027777777777778) z)
        0.083333333333333)
       x))
     (if (<= x 3.4e+218)
       (-
        t_0
        (- (- x 0.91893853320467) (* (/ (* (+ 0.0007936500793651 y) z) x) z)))
       (+ (- t_0 (- x 0.91893853320467)) (* z (* y (/ z x))))))))
double code(double x, double y, double z) {
	double t_0 = log(x) * (x - 0.5);
	double tmp;
	if (x <= 1300000.0) {
		tmp = ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
	} else if (x <= 3.4e+218) {
		tmp = t_0 - ((x - 0.91893853320467) - ((((0.0007936500793651 + y) * z) / x) * z));
	} else {
		tmp = (t_0 - (x - 0.91893853320467)) + (z * (y * (z / x)));
	}
	return tmp;
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: t_0
    real(8) :: tmp
    t_0 = log(x) * (x - 0.5d0)
    if (x <= 1300000.0d0) then
        tmp = ((((x - 0.5d0) * log(x)) - x) + 0.91893853320467d0) + ((((((y + 0.0007936500793651d0) * z) - 0.0027777777777778d0) * z) + 0.083333333333333d0) / x)
    else if (x <= 3.4d+218) then
        tmp = t_0 - ((x - 0.91893853320467d0) - ((((0.0007936500793651d0 + y) * z) / x) * z))
    else
        tmp = (t_0 - (x - 0.91893853320467d0)) + (z * (y * (z / x)))
    end if
    code = tmp
end function
public static double code(double x, double y, double z) {
	double t_0 = Math.log(x) * (x - 0.5);
	double tmp;
	if (x <= 1300000.0) {
		tmp = ((((x - 0.5) * Math.log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
	} else if (x <= 3.4e+218) {
		tmp = t_0 - ((x - 0.91893853320467) - ((((0.0007936500793651 + y) * z) / x) * z));
	} else {
		tmp = (t_0 - (x - 0.91893853320467)) + (z * (y * (z / x)));
	}
	return tmp;
}
def code(x, y, z):
	t_0 = math.log(x) * (x - 0.5)
	tmp = 0
	if x <= 1300000.0:
		tmp = ((((x - 0.5) * math.log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x)
	elif x <= 3.4e+218:
		tmp = t_0 - ((x - 0.91893853320467) - ((((0.0007936500793651 + y) * z) / x) * z))
	else:
		tmp = (t_0 - (x - 0.91893853320467)) + (z * (y * (z / x)))
	return tmp
function code(x, y, z)
	t_0 = Float64(log(x) * Float64(x - 0.5))
	tmp = 0.0
	if (x <= 1300000.0)
		tmp = Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) - x) + 0.91893853320467) + Float64(Float64(Float64(Float64(Float64(Float64(y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x));
	elseif (x <= 3.4e+218)
		tmp = Float64(t_0 - Float64(Float64(x - 0.91893853320467) - Float64(Float64(Float64(Float64(0.0007936500793651 + y) * z) / x) * z)));
	else
		tmp = Float64(Float64(t_0 - Float64(x - 0.91893853320467)) + Float64(z * Float64(y * Float64(z / x))));
	end
	return tmp
end
function tmp_2 = code(x, y, z)
	t_0 = log(x) * (x - 0.5);
	tmp = 0.0;
	if (x <= 1300000.0)
		tmp = ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + ((((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333) / x);
	elseif (x <= 3.4e+218)
		tmp = t_0 - ((x - 0.91893853320467) - ((((0.0007936500793651 + y) * z) / x) * z));
	else
		tmp = (t_0 - (x - 0.91893853320467)) + (z * (y * (z / x)));
	end
	tmp_2 = tmp;
end
code[x_, y_, z_] := Block[{t$95$0 = N[(N[Log[x], $MachinePrecision] * N[(x - 0.5), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, 1300000.0], N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(N[(N[(N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision] + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 3.4e+218], N[(t$95$0 - N[(N[(x - 0.91893853320467), $MachinePrecision] - N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] / x), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(t$95$0 - N[(x - 0.91893853320467), $MachinePrecision]), $MachinePrecision] + N[(z * N[(y * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \log x \cdot \left(x - 0.5\right)\\
\mathbf{if}\;x \leq 1300000:\\
\;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x}\\

\mathbf{elif}\;x \leq 3.4 \cdot 10^{+218}:\\
\;\;\;\;t\_0 - \left(\left(x - 0.91893853320467\right) - \frac{\left(0.0007936500793651 + y\right) \cdot z}{x} \cdot z\right)\\

\mathbf{else}:\\
\;\;\;\;\left(t\_0 - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if x < 1.3e6

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing

    if 1.3e6 < x < 3.40000000000000009e218

    1. Initial program 89.4%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6494.0

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites94.0%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6494.0

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites99.6%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
    8. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}} \]
      2. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \color{blue}{\left(x - \frac{91893853320467}{100000000000000}\right)}\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      3. lift--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      4. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      5. lift-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      6. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      7. associate-+l-N/A

        \[\leadsto \color{blue}{\log x \cdot \left(x - \frac{1}{2}\right) - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right)} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\log x \cdot \left(x - \frac{1}{2}\right) - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right)} \]
      9. lift-log.f64N/A

        \[\leadsto \color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right) \]
      10. lift-*.f64N/A

        \[\leadsto \color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right) \]
      11. lift--.f64N/A

        \[\leadsto \log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right) \]
      12. lower--.f64N/A

        \[\leadsto \log x \cdot \left(x - \frac{1}{2}\right) - \color{blue}{\left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right)} \]
    9. Applied rewrites99.6%

      \[\leadsto \color{blue}{\log x \cdot \left(x - 0.5\right) - \left(\left(x - 0.91893853320467\right) - \frac{\left(0.0007936500793651 + y\right) \cdot z}{x} \cdot z\right)} \]

    if 3.40000000000000009e218 < x

    1. Initial program 74.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6484.5

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites84.5%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6484.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites87.0%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
    8. Taylor expanded in y around inf

      \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{y \cdot z}{\color{blue}{x}} \]
    9. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      2. lower-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      3. lower-/.f6499.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right) \]
    10. Applied rewrites99.5%

      \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \color{blue}{\frac{z}{x}}\right) \]
  3. Recombined 3 regimes into one program.
  4. Add Preprocessing

Alternative 6: 97.8% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \log x \cdot \left(x - 0.5\right)\\ t_1 := \left(0.0007936500793651 + y\right) \cdot z\\ \mathbf{if}\;x \leq 0.082:\\ \;\;\;\;\frac{\mathsf{fma}\left(t\_1 - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\ \mathbf{elif}\;x \leq 3.4 \cdot 10^{+218}:\\ \;\;\;\;t\_0 - \left(\left(x - 0.91893853320467\right) - \frac{t\_1}{x} \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;\left(t\_0 - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (* (log x) (- x 0.5))) (t_1 (* (+ 0.0007936500793651 y) z)))
   (if (<= x 0.082)
     (/ (fma (- t_1 0.0027777777777778) z 0.083333333333333) x)
     (if (<= x 3.4e+218)
       (- t_0 (- (- x 0.91893853320467) (* (/ t_1 x) z)))
       (+ (- t_0 (- x 0.91893853320467)) (* z (* y (/ z x))))))))
double code(double x, double y, double z) {
	double t_0 = log(x) * (x - 0.5);
	double t_1 = (0.0007936500793651 + y) * z;
	double tmp;
	if (x <= 0.082) {
		tmp = fma((t_1 - 0.0027777777777778), z, 0.083333333333333) / x;
	} else if (x <= 3.4e+218) {
		tmp = t_0 - ((x - 0.91893853320467) - ((t_1 / x) * z));
	} else {
		tmp = (t_0 - (x - 0.91893853320467)) + (z * (y * (z / x)));
	}
	return tmp;
}
function code(x, y, z)
	t_0 = Float64(log(x) * Float64(x - 0.5))
	t_1 = Float64(Float64(0.0007936500793651 + y) * z)
	tmp = 0.0
	if (x <= 0.082)
		tmp = Float64(fma(Float64(t_1 - 0.0027777777777778), z, 0.083333333333333) / x);
	elseif (x <= 3.4e+218)
		tmp = Float64(t_0 - Float64(Float64(x - 0.91893853320467) - Float64(Float64(t_1 / x) * z)));
	else
		tmp = Float64(Float64(t_0 - Float64(x - 0.91893853320467)) + Float64(z * Float64(y * Float64(z / x))));
	end
	return tmp
end
code[x_, y_, z_] := Block[{t$95$0 = N[(N[Log[x], $MachinePrecision] * N[(x - 0.5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision]}, If[LessEqual[x, 0.082], N[(N[(N[(t$95$1 - 0.0027777777777778), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], If[LessEqual[x, 3.4e+218], N[(t$95$0 - N[(N[(x - 0.91893853320467), $MachinePrecision] - N[(N[(t$95$1 / x), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(t$95$0 - N[(x - 0.91893853320467), $MachinePrecision]), $MachinePrecision] + N[(z * N[(y * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \log x \cdot \left(x - 0.5\right)\\
t_1 := \left(0.0007936500793651 + y\right) \cdot z\\
\mathbf{if}\;x \leq 0.082:\\
\;\;\;\;\frac{\mathsf{fma}\left(t\_1 - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\

\mathbf{elif}\;x \leq 3.4 \cdot 10^{+218}:\\
\;\;\;\;t\_0 - \left(\left(x - 0.91893853320467\right) - \frac{t\_1}{x} \cdot z\right)\\

\mathbf{else}:\\
\;\;\;\;\left(t\_0 - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if x < 0.0820000000000000034

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      3. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      4. +-commutativeN/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{\color{blue}{x}} \]
      6. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      7. lift-*.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      8. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      9. lift--.f6498.2

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      11. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      12. lower-+.f6498.2

        \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
    5. Applied rewrites98.2%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]

    if 0.0820000000000000034 < x < 3.40000000000000009e218

    1. Initial program 89.9%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6493.2

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites93.2%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6493.2

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites98.5%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
    8. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}} \]
      2. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \color{blue}{\left(x - \frac{91893853320467}{100000000000000}\right)}\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      3. lift--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      4. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      5. lift-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      6. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x} \]
      7. associate-+l-N/A

        \[\leadsto \color{blue}{\log x \cdot \left(x - \frac{1}{2}\right) - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right)} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\log x \cdot \left(x - \frac{1}{2}\right) - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right)} \]
      9. lift-log.f64N/A

        \[\leadsto \color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right) \]
      10. lift-*.f64N/A

        \[\leadsto \color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right) \]
      11. lift--.f64N/A

        \[\leadsto \log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right) \]
      12. lower--.f64N/A

        \[\leadsto \log x \cdot \left(x - \frac{1}{2}\right) - \color{blue}{\left(\left(x - \frac{91893853320467}{100000000000000}\right) - z \cdot \frac{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z}{x}\right)} \]
    9. Applied rewrites98.5%

      \[\leadsto \color{blue}{\log x \cdot \left(x - 0.5\right) - \left(\left(x - 0.91893853320467\right) - \frac{\left(0.0007936500793651 + y\right) \cdot z}{x} \cdot z\right)} \]

    if 3.40000000000000009e218 < x

    1. Initial program 74.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6484.5

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites84.5%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6484.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites87.0%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
    8. Taylor expanded in y around inf

      \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{y \cdot z}{\color{blue}{x}} \]
    9. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      2. lower-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      3. lower-/.f6499.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right) \]
    10. Applied rewrites99.5%

      \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \color{blue}{\frac{z}{x}}\right) \]
  3. Recombined 3 regimes into one program.
  4. Add Preprocessing

Alternative 7: 97.8% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\\ \mathbf{if}\;x \leq 0.082:\\ \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\ \mathbf{elif}\;x \leq 3.4 \cdot 10^{+218}:\\ \;\;\;\;t\_0 + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}\\ \mathbf{else}:\\ \;\;\;\;t\_0 + z \cdot \left(y \cdot \frac{z}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (let* ((t_0 (- (* (log x) (- x 0.5)) (- x 0.91893853320467))))
   (if (<= x 0.082)
     (/
      (fma
       (- (* (+ 0.0007936500793651 y) z) 0.0027777777777778)
       z
       0.083333333333333)
      x)
     (if (<= x 3.4e+218)
       (+ t_0 (* z (/ (* (+ y 0.0007936500793651) z) x)))
       (+ t_0 (* z (* y (/ z x))))))))
double code(double x, double y, double z) {
	double t_0 = (log(x) * (x - 0.5)) - (x - 0.91893853320467);
	double tmp;
	if (x <= 0.082) {
		tmp = fma((((0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x;
	} else if (x <= 3.4e+218) {
		tmp = t_0 + (z * (((y + 0.0007936500793651) * z) / x));
	} else {
		tmp = t_0 + (z * (y * (z / x)));
	}
	return tmp;
}
function code(x, y, z)
	t_0 = Float64(Float64(log(x) * Float64(x - 0.5)) - Float64(x - 0.91893853320467))
	tmp = 0.0
	if (x <= 0.082)
		tmp = Float64(fma(Float64(Float64(Float64(0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x);
	elseif (x <= 3.4e+218)
		tmp = Float64(t_0 + Float64(z * Float64(Float64(Float64(y + 0.0007936500793651) * z) / x)));
	else
		tmp = Float64(t_0 + Float64(z * Float64(y * Float64(z / x))));
	end
	return tmp
end
code[x_, y_, z_] := Block[{t$95$0 = N[(N[(N[Log[x], $MachinePrecision] * N[(x - 0.5), $MachinePrecision]), $MachinePrecision] - N[(x - 0.91893853320467), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, 0.082], N[(N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], If[LessEqual[x, 3.4e+218], N[(t$95$0 + N[(z * N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t$95$0 + N[(z * N[(y * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\\
\mathbf{if}\;x \leq 0.082:\\
\;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\

\mathbf{elif}\;x \leq 3.4 \cdot 10^{+218}:\\
\;\;\;\;t\_0 + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}\\

\mathbf{else}:\\
\;\;\;\;t\_0 + z \cdot \left(y \cdot \frac{z}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if x < 0.0820000000000000034

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      3. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      4. +-commutativeN/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{\color{blue}{x}} \]
      6. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      7. lift-*.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      8. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      9. lift--.f6498.2

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      11. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      12. lower-+.f6498.2

        \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
    5. Applied rewrites98.2%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]

    if 0.0820000000000000034 < x < 3.40000000000000009e218

    1. Initial program 89.9%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6493.2

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites93.2%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6493.2

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites98.5%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]

    if 3.40000000000000009e218 < x

    1. Initial program 74.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6484.5

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites84.5%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6484.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites87.0%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
    8. Taylor expanded in y around inf

      \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{y \cdot z}{\color{blue}{x}} \]
    9. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      2. lower-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      3. lower-/.f6499.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right) \]
    10. Applied rewrites99.5%

      \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \color{blue}{\frac{z}{x}}\right) \]
  3. Recombined 3 regimes into one program.
  4. Add Preprocessing

Alternative 8: 96.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 0.082:\\ \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\ \mathbf{elif}\;x \leq 7 \cdot 10^{+163}:\\ \;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}\\ \mathbf{else}:\\ \;\;\;\;\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<= x 0.082)
   (/
    (fma
     (- (* (+ 0.0007936500793651 y) z) 0.0027777777777778)
     z
     0.083333333333333)
    x)
   (if (<= x 7e+163)
     (+
      (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467)
      (* (* z z) (/ (+ 0.0007936500793651 y) x)))
     (+
      (- (* (log x) (- x 0.5)) (- x 0.91893853320467))
      (* z (* y (/ z x)))))))
double code(double x, double y, double z) {
	double tmp;
	if (x <= 0.082) {
		tmp = fma((((0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x;
	} else if (x <= 7e+163) {
		tmp = ((((x - 0.5) * log(x)) - x) + 0.91893853320467) + ((z * z) * ((0.0007936500793651 + y) / x));
	} else {
		tmp = ((log(x) * (x - 0.5)) - (x - 0.91893853320467)) + (z * (y * (z / x)));
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (x <= 0.082)
		tmp = Float64(fma(Float64(Float64(Float64(0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x);
	elseif (x <= 7e+163)
		tmp = Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) - x) + 0.91893853320467) + Float64(Float64(z * z) * Float64(Float64(0.0007936500793651 + y) / x)));
	else
		tmp = Float64(Float64(Float64(log(x) * Float64(x - 0.5)) - Float64(x - 0.91893853320467)) + Float64(z * Float64(y * Float64(z / x))));
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[x, 0.082], N[(N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], If[LessEqual[x, 7e+163], N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision] + 0.91893853320467), $MachinePrecision] + N[(N[(z * z), $MachinePrecision] * N[(N[(0.0007936500793651 + y), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(N[Log[x], $MachinePrecision] * N[(x - 0.5), $MachinePrecision]), $MachinePrecision] - N[(x - 0.91893853320467), $MachinePrecision]), $MachinePrecision] + N[(z * N[(y * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 0.082:\\
\;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\

\mathbf{elif}\;x \leq 7 \cdot 10^{+163}:\\
\;\;\;\;\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}\\

\mathbf{else}:\\
\;\;\;\;\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if x < 0.0820000000000000034

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      3. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      4. +-commutativeN/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{\color{blue}{x}} \]
      6. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      7. lift-*.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      8. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      9. lift--.f6498.2

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      11. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      12. lower-+.f6498.2

        \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
    5. Applied rewrites98.2%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]

    if 0.0820000000000000034 < x < 7.0000000000000005e163

    1. Initial program 92.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6494.1

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites94.1%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]

    if 7.0000000000000005e163 < x

    1. Initial program 76.5%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6486.4

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites86.4%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6486.4

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites91.3%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
    8. Taylor expanded in y around inf

      \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{y \cdot z}{\color{blue}{x}} \]
    9. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      2. lower-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      3. lower-/.f6497.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right) \]
    10. Applied rewrites97.5%

      \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \color{blue}{\frac{z}{x}}\right) \]
  3. Recombined 3 regimes into one program.
  4. Add Preprocessing

Alternative 9: 96.3% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 1:\\ \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\ \mathbf{elif}\;x \leq 7 \cdot 10^{+163}:\\ \;\;\;\;\left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}\\ \mathbf{else}:\\ \;\;\;\;\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<= x 1.0)
   (/
    (fma
     (- (* (+ 0.0007936500793651 y) z) 0.0027777777777778)
     z
     0.083333333333333)
    x)
   (if (<= x 7e+163)
     (+ (* (- (log x) 1.0) x) (* (* z z) (/ (+ 0.0007936500793651 y) x)))
     (+
      (- (* (log x) (- x 0.5)) (- x 0.91893853320467))
      (* z (* y (/ z x)))))))
double code(double x, double y, double z) {
	double tmp;
	if (x <= 1.0) {
		tmp = fma((((0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x;
	} else if (x <= 7e+163) {
		tmp = ((log(x) - 1.0) * x) + ((z * z) * ((0.0007936500793651 + y) / x));
	} else {
		tmp = ((log(x) * (x - 0.5)) - (x - 0.91893853320467)) + (z * (y * (z / x)));
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (x <= 1.0)
		tmp = Float64(fma(Float64(Float64(Float64(0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x);
	elseif (x <= 7e+163)
		tmp = Float64(Float64(Float64(log(x) - 1.0) * x) + Float64(Float64(z * z) * Float64(Float64(0.0007936500793651 + y) / x)));
	else
		tmp = Float64(Float64(Float64(log(x) * Float64(x - 0.5)) - Float64(x - 0.91893853320467)) + Float64(z * Float64(y * Float64(z / x))));
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[x, 1.0], N[(N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], If[LessEqual[x, 7e+163], N[(N[(N[(N[Log[x], $MachinePrecision] - 1.0), $MachinePrecision] * x), $MachinePrecision] + N[(N[(z * z), $MachinePrecision] * N[(N[(0.0007936500793651 + y), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(N[Log[x], $MachinePrecision] * N[(x - 0.5), $MachinePrecision]), $MachinePrecision] - N[(x - 0.91893853320467), $MachinePrecision]), $MachinePrecision] + N[(z * N[(y * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 1:\\
\;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\

\mathbf{elif}\;x \leq 7 \cdot 10^{+163}:\\
\;\;\;\;\left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}\\

\mathbf{else}:\\
\;\;\;\;\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if x < 1

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      3. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      4. +-commutativeN/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{\color{blue}{x}} \]
      6. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      7. lift-*.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      8. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      9. lift--.f6497.6

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      11. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      12. lower-+.f6497.6

        \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
    5. Applied rewrites97.6%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]

    if 1 < x < 7.0000000000000005e163

    1. Initial program 92.6%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6495.2

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites95.2%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(-1 \cdot \log \left(\frac{1}{x}\right) - 1\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
    7. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(-1 \cdot \log \left(\frac{1}{x}\right) - 1\right) \cdot \color{blue}{x} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. log-pow-revN/A

        \[\leadsto \left(\log \left({\left(\frac{1}{x}\right)}^{-1}\right) - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. inv-powN/A

        \[\leadsto \left(\log \left({\left({x}^{-1}\right)}^{-1}\right) - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. pow-powN/A

        \[\leadsto \left(\log \left({x}^{\left(-1 \cdot -1\right)}\right) - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. metadata-evalN/A

        \[\leadsto \left(\log \left({x}^{1}\right) - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. unpow1N/A

        \[\leadsto \left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. lower-*.f64N/A

        \[\leadsto \left(\log x - 1\right) \cdot \color{blue}{x} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lift-log.f64N/A

        \[\leadsto \left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lift--.f6494.1

        \[\leadsto \left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    8. Applied rewrites94.1%

      \[\leadsto \color{blue}{\left(\log x - 1\right) \cdot x} + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]

    if 7.0000000000000005e163 < x

    1. Initial program 76.5%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6486.4

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites86.4%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{\left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. lift--.f64N/A

        \[\leadsto \left(\color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right)} + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. lift--.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right)} \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. lift-*.f64N/A

        \[\leadsto \left(\left(\color{blue}{\left(x - \frac{1}{2}\right) \cdot \log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. lift-log.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \color{blue}{\log x} - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. associate-+l-N/A

        \[\leadsto \color{blue}{\left(\left(x - \frac{1}{2}\right) \cdot \log x - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. *-commutativeN/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lower--.f64N/A

        \[\leadsto \color{blue}{\left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lower-*.f64N/A

        \[\leadsto \left(\color{blue}{\log x \cdot \left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      10. lift-log.f64N/A

        \[\leadsto \left(\color{blue}{\log x} \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      11. lift--.f64N/A

        \[\leadsto \left(\log x \cdot \color{blue}{\left(x - \frac{1}{2}\right)} - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      12. lower--.f6486.4

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \color{blue}{\left(x - 0.91893853320467\right)}\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
      13. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      14. lift-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      15. lift-+.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      16. lift-/.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      17. associate-*l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \color{blue}{\left(z \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x}\right)} \]
    7. Applied rewrites91.3%

      \[\leadsto \color{blue}{\left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
    8. Taylor expanded in y around inf

      \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \frac{y \cdot z}{\color{blue}{x}} \]
    9. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      2. lower-*.f64N/A

        \[\leadsto \left(\log x \cdot \left(x - \frac{1}{2}\right) - \left(x - \frac{91893853320467}{100000000000000}\right)\right) + z \cdot \left(y \cdot \frac{z}{\color{blue}{x}}\right) \]
      3. lower-/.f6497.5

        \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \frac{z}{x}\right) \]
    10. Applied rewrites97.5%

      \[\leadsto \left(\log x \cdot \left(x - 0.5\right) - \left(x - 0.91893853320467\right)\right) + z \cdot \left(y \cdot \color{blue}{\frac{z}{x}}\right) \]
  3. Recombined 3 regimes into one program.
  4. Add Preprocessing

Alternative 10: 94.6% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 1:\\ \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\ \mathbf{else}:\\ \;\;\;\;\left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<= x 1.0)
   (/
    (fma
     (- (* (+ 0.0007936500793651 y) z) 0.0027777777777778)
     z
     0.083333333333333)
    x)
   (+ (* (- (log x) 1.0) x) (* (* z z) (/ (+ 0.0007936500793651 y) x)))))
double code(double x, double y, double z) {
	double tmp;
	if (x <= 1.0) {
		tmp = fma((((0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x;
	} else {
		tmp = ((log(x) - 1.0) * x) + ((z * z) * ((0.0007936500793651 + y) / x));
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (x <= 1.0)
		tmp = Float64(fma(Float64(Float64(Float64(0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x);
	else
		tmp = Float64(Float64(Float64(log(x) - 1.0) * x) + Float64(Float64(z * z) * Float64(Float64(0.0007936500793651 + y) / x)));
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[x, 1.0], N[(N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], N[(N[(N[(N[Log[x], $MachinePrecision] - 1.0), $MachinePrecision] * x), $MachinePrecision] + N[(N[(z * z), $MachinePrecision] * N[(N[(0.0007936500793651 + y), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 1:\\
\;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\

\mathbf{else}:\\
\;\;\;\;\left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}\\


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

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      3. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      4. +-commutativeN/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{\color{blue}{x}} \]
      6. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      7. lift-*.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      8. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      9. lift--.f6497.6

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      11. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      12. lower-+.f6497.6

        \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
    5. Applied rewrites97.6%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]

    if 1 < x

    1. Initial program 85.2%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in z around inf

      \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)}{x}} \]
    4. Step-by-step derivation
      1. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      2. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + {z}^{2} \cdot \color{blue}{\frac{\frac{7936500793651}{10000000000000000} + y}{x}} \]
      3. unpow2N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      4. lower-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\color{blue}{\frac{7936500793651}{10000000000000000} + y}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{\color{blue}{x}} \]
      6. lower-+.f6491.1

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    5. Applied rewrites91.1%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x}} \]
    6. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(-1 \cdot \log \left(\frac{1}{x}\right) - 1\right)} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
    7. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(-1 \cdot \log \left(\frac{1}{x}\right) - 1\right) \cdot \color{blue}{x} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      2. log-pow-revN/A

        \[\leadsto \left(\log \left({\left(\frac{1}{x}\right)}^{-1}\right) - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      3. inv-powN/A

        \[\leadsto \left(\log \left({\left({x}^{-1}\right)}^{-1}\right) - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      4. pow-powN/A

        \[\leadsto \left(\log \left({x}^{\left(-1 \cdot -1\right)}\right) - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      5. metadata-evalN/A

        \[\leadsto \left(\log \left({x}^{1}\right) - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      6. unpow1N/A

        \[\leadsto \left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      7. lower-*.f64N/A

        \[\leadsto \left(\log x - 1\right) \cdot \color{blue}{x} + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      8. lift-log.f64N/A

        \[\leadsto \left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{\frac{7936500793651}{10000000000000000} + y}{x} \]
      9. lift--.f6490.7

        \[\leadsto \left(\log x - 1\right) \cdot x + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
    8. Applied rewrites90.7%

      \[\leadsto \color{blue}{\left(\log x - 1\right) \cdot x} + \left(z \cdot z\right) \cdot \frac{0.0007936500793651 + y}{x} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 11: 84.4% accurate, 1.3× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 4.2 \cdot 10^{+42}:\\ \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\ \mathbf{else}:\\ \;\;\;\;\left(\log x - 1\right) \cdot x\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<= x 4.2e+42)
   (/
    (fma
     (- (* (+ 0.0007936500793651 y) z) 0.0027777777777778)
     z
     0.083333333333333)
    x)
   (* (- (log x) 1.0) x)))
double code(double x, double y, double z) {
	double tmp;
	if (x <= 4.2e+42) {
		tmp = fma((((0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x;
	} else {
		tmp = (log(x) - 1.0) * x;
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (x <= 4.2e+42)
		tmp = Float64(fma(Float64(Float64(Float64(0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x);
	else
		tmp = Float64(Float64(log(x) - 1.0) * x);
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[x, 4.2e+42], N[(N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], N[(N[(N[Log[x], $MachinePrecision] - 1.0), $MachinePrecision] * x), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq 4.2 \cdot 10^{+42}:\\
\;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\

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


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < 4.19999999999999991e42

    1. Initial program 99.7%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      3. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
      4. +-commutativeN/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lower-/.f64N/A

        \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{\color{blue}{x}} \]
      6. lower-fma.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      7. lift-*.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      8. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      9. lift--.f6494.1

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      10. lift-+.f64N/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      11. +-commutativeN/A

        \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
      12. lower-+.f6494.1

        \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
    5. Applied rewrites94.1%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]

    if 4.19999999999999991e42 < x

    1. Initial program 83.0%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in x around inf

      \[\leadsto \color{blue}{x \cdot \left(-1 \cdot \log \left(\frac{1}{x}\right) - 1\right)} \]
    4. Step-by-step derivation
      1. *-commutativeN/A

        \[\leadsto \left(-1 \cdot \log \left(\frac{1}{x}\right) - 1\right) \cdot \color{blue}{x} \]
      2. log-pow-revN/A

        \[\leadsto \left(\log \left({\left(\frac{1}{x}\right)}^{-1}\right) - 1\right) \cdot x \]
      3. inv-powN/A

        \[\leadsto \left(\log \left({\left({x}^{-1}\right)}^{-1}\right) - 1\right) \cdot x \]
      4. pow-powN/A

        \[\leadsto \left(\log \left({x}^{\left(-1 \cdot -1\right)}\right) - 1\right) \cdot x \]
      5. metadata-evalN/A

        \[\leadsto \left(\log \left({x}^{1}\right) - 1\right) \cdot x \]
      6. unpow1N/A

        \[\leadsto \left(\log x - 1\right) \cdot x \]
      7. lower-*.f64N/A

        \[\leadsto \left(\log x - 1\right) \cdot \color{blue}{x} \]
      8. lower--.f64N/A

        \[\leadsto \left(\log x - 1\right) \cdot x \]
      9. lift-log.f6477.9

        \[\leadsto \left(\log x - 1\right) \cdot x \]
    5. Applied rewrites77.9%

      \[\leadsto \color{blue}{\left(\log x - 1\right) \cdot x} \]
  3. Recombined 2 regimes into one program.
  4. Add Preprocessing

Alternative 12: 52.2% accurate, 2.1× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333\\ \mathbf{if}\;t\_0 \leq -2000000000000:\\ \;\;\;\;y \cdot \frac{z \cdot z}{x}\\ \mathbf{elif}\;t\_0 \leq 5 \cdot 10^{+35}:\\ \;\;\;\;\frac{0.083333333333333}{x}\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(z \cdot \frac{z}{x}\right)\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (let* ((t_0
         (+
          (* (- (* (+ y 0.0007936500793651) z) 0.0027777777777778) z)
          0.083333333333333)))
   (if (<= t_0 -2000000000000.0)
     (* y (/ (* z z) x))
     (if (<= t_0 5e+35) (/ 0.083333333333333 x) (* y (* z (/ z x)))))))
double code(double x, double y, double z) {
	double t_0 = ((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333;
	double tmp;
	if (t_0 <= -2000000000000.0) {
		tmp = y * ((z * z) / x);
	} else if (t_0 <= 5e+35) {
		tmp = 0.083333333333333 / x;
	} else {
		tmp = y * (z * (z / x));
	}
	return tmp;
}
module fmin_fmax_functions
    implicit none
    private
    public fmax
    public fmin

    interface fmax
        module procedure fmax88
        module procedure fmax44
        module procedure fmax84
        module procedure fmax48
    end interface
    interface fmin
        module procedure fmin88
        module procedure fmin44
        module procedure fmin84
        module procedure fmin48
    end interface
contains
    real(8) function fmax88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(4) function fmax44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, max(x, y), y /= y), x /= x)
    end function
    real(8) function fmax84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmax48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
    end function
    real(8) function fmin88(x, y) result (res)
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(4) function fmin44(x, y) result (res)
        real(4), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(y, merge(x, min(x, y), y /= y), x /= x)
    end function
    real(8) function fmin84(x, y) result(res)
        real(8), intent (in) :: x
        real(4), intent (in) :: y
        res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
    end function
    real(8) function fmin48(x, y) result(res)
        real(4), intent (in) :: x
        real(8), intent (in) :: y
        res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
    end function
end module

real(8) function code(x, y, z)
use fmin_fmax_functions
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: t_0
    real(8) :: tmp
    t_0 = ((((y + 0.0007936500793651d0) * z) - 0.0027777777777778d0) * z) + 0.083333333333333d0
    if (t_0 <= (-2000000000000.0d0)) then
        tmp = y * ((z * z) / x)
    else if (t_0 <= 5d+35) then
        tmp = 0.083333333333333d0 / x
    else
        tmp = y * (z * (z / x))
    end if
    code = tmp
end function
public static double code(double x, double y, double z) {
	double t_0 = ((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333;
	double tmp;
	if (t_0 <= -2000000000000.0) {
		tmp = y * ((z * z) / x);
	} else if (t_0 <= 5e+35) {
		tmp = 0.083333333333333 / x;
	} else {
		tmp = y * (z * (z / x));
	}
	return tmp;
}
def code(x, y, z):
	t_0 = ((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333
	tmp = 0
	if t_0 <= -2000000000000.0:
		tmp = y * ((z * z) / x)
	elif t_0 <= 5e+35:
		tmp = 0.083333333333333 / x
	else:
		tmp = y * (z * (z / x))
	return tmp
function code(x, y, z)
	t_0 = Float64(Float64(Float64(Float64(Float64(y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333)
	tmp = 0.0
	if (t_0 <= -2000000000000.0)
		tmp = Float64(y * Float64(Float64(z * z) / x));
	elseif (t_0 <= 5e+35)
		tmp = Float64(0.083333333333333 / x);
	else
		tmp = Float64(y * Float64(z * Float64(z / x)));
	end
	return tmp
end
function tmp_2 = code(x, y, z)
	t_0 = ((((y + 0.0007936500793651) * z) - 0.0027777777777778) * z) + 0.083333333333333;
	tmp = 0.0;
	if (t_0 <= -2000000000000.0)
		tmp = y * ((z * z) / x);
	elseif (t_0 <= 5e+35)
		tmp = 0.083333333333333 / x;
	else
		tmp = y * (z * (z / x));
	end
	tmp_2 = tmp;
end
code[x_, y_, z_] := Block[{t$95$0 = N[(N[(N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision] + 0.083333333333333), $MachinePrecision]}, If[LessEqual[t$95$0, -2000000000000.0], N[(y * N[(N[(z * z), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$0, 5e+35], N[(0.083333333333333 / x), $MachinePrecision], N[(y * N[(z * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333\\
\mathbf{if}\;t\_0 \leq -2000000000000:\\
\;\;\;\;y \cdot \frac{z \cdot z}{x}\\

\mathbf{elif}\;t\_0 \leq 5 \cdot 10^{+35}:\\
\;\;\;\;\frac{0.083333333333333}{x}\\

\mathbf{else}:\\
\;\;\;\;y \cdot \left(z \cdot \frac{z}{x}\right)\\


\end{array}
\end{array}
Derivation
  1. Split input into 3 regimes
  2. if (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64)) < -2e12

    1. Initial program 91.2%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Taylor expanded in y around inf

      \[\leadsto \color{blue}{\frac{y \cdot {z}^{2}}{x}} \]
    4. Step-by-step derivation
      1. lower-/.f64N/A

        \[\leadsto \frac{y \cdot {z}^{2}}{\color{blue}{x}} \]
      2. *-commutativeN/A

        \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
      3. lower-*.f64N/A

        \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
      4. unpow2N/A

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
      5. lower-*.f6477.3

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
    5. Applied rewrites77.3%

      \[\leadsto \color{blue}{\frac{\left(z \cdot z\right) \cdot y}{x}} \]
    6. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{\color{blue}{x}} \]
      2. lift-*.f64N/A

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
      3. lift-*.f64N/A

        \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
      4. pow2N/A

        \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
      5. *-commutativeN/A

        \[\leadsto \frac{y \cdot {z}^{2}}{x} \]
      6. associate-/l*N/A

        \[\leadsto y \cdot \color{blue}{\frac{{z}^{2}}{x}} \]
      7. lower-*.f64N/A

        \[\leadsto y \cdot \color{blue}{\frac{{z}^{2}}{x}} \]
      8. lower-/.f64N/A

        \[\leadsto y \cdot \frac{{z}^{2}}{\color{blue}{x}} \]
      9. pow2N/A

        \[\leadsto y \cdot \frac{z \cdot z}{x} \]
      10. lift-*.f6483.6

        \[\leadsto y \cdot \frac{z \cdot z}{x} \]
    7. Applied rewrites83.6%

      \[\leadsto y \cdot \color{blue}{\frac{z \cdot z}{x}} \]

    if -2e12 < (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64)) < 5.00000000000000021e35

    1. Initial program 99.4%

      \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
      2. lift-+.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
      3. lift-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
      4. lift--.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      5. lift-+.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      6. lift-*.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
      7. div-addN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
      8. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      9. +-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      10. *-commutativeN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      11. associate-/l*N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
      12. metadata-evalN/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
      13. associate-*r/N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
      14. lower-fma.f64N/A

        \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
    4. Applied rewrites97.8%

      \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
    5. Taylor expanded in x around 0

      \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
    6. Step-by-step derivation
      1. div-subN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      2. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      3. div-subN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      4. associate-/l*N/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z} \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      5. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      6. +-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      7. *-commutativeN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
      8. div-addN/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}}{x} \]
      9. lower-/.f64N/A

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{\color{blue}{x}} \]
    7. Applied rewrites52.4%

      \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]
    8. Taylor expanded in z around 0

      \[\leadsto \frac{\frac{83333333333333}{1000000000000000}}{x} \]
    9. Step-by-step derivation
      1. Applied rewrites49.5%

        \[\leadsto \frac{0.083333333333333}{x} \]

      if 5.00000000000000021e35 < (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64))

      1. Initial program 84.4%

        \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
      2. Add Preprocessing
      3. Taylor expanded in y around inf

        \[\leadsto \color{blue}{\frac{y \cdot {z}^{2}}{x}} \]
      4. Step-by-step derivation
        1. lower-/.f64N/A

          \[\leadsto \frac{y \cdot {z}^{2}}{\color{blue}{x}} \]
        2. *-commutativeN/A

          \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
        3. lower-*.f64N/A

          \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
        4. unpow2N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
        5. lower-*.f6444.5

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
      5. Applied rewrites44.5%

        \[\leadsto \color{blue}{\frac{\left(z \cdot z\right) \cdot y}{x}} \]
      6. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{\color{blue}{x}} \]
        2. lift-*.f64N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
        3. lift-*.f64N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
        4. pow2N/A

          \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
        5. *-commutativeN/A

          \[\leadsto \frac{y \cdot {z}^{2}}{x} \]
        6. associate-/l*N/A

          \[\leadsto y \cdot \color{blue}{\frac{{z}^{2}}{x}} \]
        7. lower-*.f64N/A

          \[\leadsto y \cdot \color{blue}{\frac{{z}^{2}}{x}} \]
        8. lower-/.f64N/A

          \[\leadsto y \cdot \frac{{z}^{2}}{\color{blue}{x}} \]
        9. pow2N/A

          \[\leadsto y \cdot \frac{z \cdot z}{x} \]
        10. lift-*.f6448.2

          \[\leadsto y \cdot \frac{z \cdot z}{x} \]
      7. Applied rewrites48.2%

        \[\leadsto y \cdot \color{blue}{\frac{z \cdot z}{x}} \]
      8. Step-by-step derivation
        1. lift-*.f64N/A

          \[\leadsto y \cdot \frac{z \cdot z}{x} \]
        2. lift-/.f64N/A

          \[\leadsto y \cdot \frac{z \cdot z}{\color{blue}{x}} \]
        3. associate-/l*N/A

          \[\leadsto y \cdot \left(z \cdot \color{blue}{\frac{z}{x}}\right) \]
        4. lower-*.f64N/A

          \[\leadsto y \cdot \left(z \cdot \color{blue}{\frac{z}{x}}\right) \]
        5. lower-/.f6450.2

          \[\leadsto y \cdot \left(z \cdot \frac{z}{\color{blue}{x}}\right) \]
      9. Applied rewrites50.2%

        \[\leadsto y \cdot \left(z \cdot \color{blue}{\frac{z}{x}}\right) \]
    10. Recombined 3 regimes into one program.
    11. Add Preprocessing

    Alternative 13: 52.5% accurate, 2.2× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z\\ \mathbf{if}\;t\_0 \leq -2000000000000 \lor \neg \left(t\_0 \leq 5 \cdot 10^{+35}\right):\\ \;\;\;\;y \cdot \left(z \cdot \frac{z}{x}\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{0.083333333333333}{x}\\ \end{array} \end{array} \]
    (FPCore (x y z)
     :precision binary64
     (let* ((t_0 (* (- (* (+ y 0.0007936500793651) z) 0.0027777777777778) z)))
       (if (or (<= t_0 -2000000000000.0) (not (<= t_0 5e+35)))
         (* y (* z (/ z x)))
         (/ 0.083333333333333 x))))
    double code(double x, double y, double z) {
    	double t_0 = (((y + 0.0007936500793651) * z) - 0.0027777777777778) * z;
    	double tmp;
    	if ((t_0 <= -2000000000000.0) || !(t_0 <= 5e+35)) {
    		tmp = y * (z * (z / x));
    	} else {
    		tmp = 0.083333333333333 / x;
    	}
    	return tmp;
    }
    
    module fmin_fmax_functions
        implicit none
        private
        public fmax
        public fmin
    
        interface fmax
            module procedure fmax88
            module procedure fmax44
            module procedure fmax84
            module procedure fmax48
        end interface
        interface fmin
            module procedure fmin88
            module procedure fmin44
            module procedure fmin84
            module procedure fmin48
        end interface
    contains
        real(8) function fmax88(x, y) result (res)
            real(8), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
        end function
        real(4) function fmax44(x, y) result (res)
            real(4), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(y, merge(x, max(x, y), y /= y), x /= x)
        end function
        real(8) function fmax84(x, y) result(res)
            real(8), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
        end function
        real(8) function fmax48(x, y) result(res)
            real(4), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
        end function
        real(8) function fmin88(x, y) result (res)
            real(8), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
        end function
        real(4) function fmin44(x, y) result (res)
            real(4), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(y, merge(x, min(x, y), y /= y), x /= x)
        end function
        real(8) function fmin84(x, y) result(res)
            real(8), intent (in) :: x
            real(4), intent (in) :: y
            res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
        end function
        real(8) function fmin48(x, y) result(res)
            real(4), intent (in) :: x
            real(8), intent (in) :: y
            res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
        end function
    end module
    
    real(8) function code(x, y, z)
    use fmin_fmax_functions
        real(8), intent (in) :: x
        real(8), intent (in) :: y
        real(8), intent (in) :: z
        real(8) :: t_0
        real(8) :: tmp
        t_0 = (((y + 0.0007936500793651d0) * z) - 0.0027777777777778d0) * z
        if ((t_0 <= (-2000000000000.0d0)) .or. (.not. (t_0 <= 5d+35))) then
            tmp = y * (z * (z / x))
        else
            tmp = 0.083333333333333d0 / x
        end if
        code = tmp
    end function
    
    public static double code(double x, double y, double z) {
    	double t_0 = (((y + 0.0007936500793651) * z) - 0.0027777777777778) * z;
    	double tmp;
    	if ((t_0 <= -2000000000000.0) || !(t_0 <= 5e+35)) {
    		tmp = y * (z * (z / x));
    	} else {
    		tmp = 0.083333333333333 / x;
    	}
    	return tmp;
    }
    
    def code(x, y, z):
    	t_0 = (((y + 0.0007936500793651) * z) - 0.0027777777777778) * z
    	tmp = 0
    	if (t_0 <= -2000000000000.0) or not (t_0 <= 5e+35):
    		tmp = y * (z * (z / x))
    	else:
    		tmp = 0.083333333333333 / x
    	return tmp
    
    function code(x, y, z)
    	t_0 = Float64(Float64(Float64(Float64(y + 0.0007936500793651) * z) - 0.0027777777777778) * z)
    	tmp = 0.0
    	if ((t_0 <= -2000000000000.0) || !(t_0 <= 5e+35))
    		tmp = Float64(y * Float64(z * Float64(z / x)));
    	else
    		tmp = Float64(0.083333333333333 / x);
    	end
    	return tmp
    end
    
    function tmp_2 = code(x, y, z)
    	t_0 = (((y + 0.0007936500793651) * z) - 0.0027777777777778) * z;
    	tmp = 0.0;
    	if ((t_0 <= -2000000000000.0) || ~((t_0 <= 5e+35)))
    		tmp = y * (z * (z / x));
    	else
    		tmp = 0.083333333333333 / x;
    	end
    	tmp_2 = tmp;
    end
    
    code[x_, y_, z_] := Block[{t$95$0 = N[(N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision]}, If[Or[LessEqual[t$95$0, -2000000000000.0], N[Not[LessEqual[t$95$0, 5e+35]], $MachinePrecision]], N[(y * N[(z * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(0.083333333333333 / x), $MachinePrecision]]]
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z\\
    \mathbf{if}\;t\_0 \leq -2000000000000 \lor \neg \left(t\_0 \leq 5 \cdot 10^{+35}\right):\\
    \;\;\;\;y \cdot \left(z \cdot \frac{z}{x}\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;\frac{0.083333333333333}{x}\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) < -2e12 or 5.00000000000000021e35 < (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z)

      1. Initial program 86.6%

        \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
      2. Add Preprocessing
      3. Taylor expanded in y around inf

        \[\leadsto \color{blue}{\frac{y \cdot {z}^{2}}{x}} \]
      4. Step-by-step derivation
        1. lower-/.f64N/A

          \[\leadsto \frac{y \cdot {z}^{2}}{\color{blue}{x}} \]
        2. *-commutativeN/A

          \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
        3. lower-*.f64N/A

          \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
        4. unpow2N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
        5. lower-*.f6455.2

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
      5. Applied rewrites55.2%

        \[\leadsto \color{blue}{\frac{\left(z \cdot z\right) \cdot y}{x}} \]
      6. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{\color{blue}{x}} \]
        2. lift-*.f64N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
        3. lift-*.f64N/A

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y}{x} \]
        4. pow2N/A

          \[\leadsto \frac{{z}^{2} \cdot y}{x} \]
        5. *-commutativeN/A

          \[\leadsto \frac{y \cdot {z}^{2}}{x} \]
        6. associate-/l*N/A

          \[\leadsto y \cdot \color{blue}{\frac{{z}^{2}}{x}} \]
        7. lower-*.f64N/A

          \[\leadsto y \cdot \color{blue}{\frac{{z}^{2}}{x}} \]
        8. lower-/.f64N/A

          \[\leadsto y \cdot \frac{{z}^{2}}{\color{blue}{x}} \]
        9. pow2N/A

          \[\leadsto y \cdot \frac{z \cdot z}{x} \]
        10. lift-*.f6459.7

          \[\leadsto y \cdot \frac{z \cdot z}{x} \]
      7. Applied rewrites59.7%

        \[\leadsto y \cdot \color{blue}{\frac{z \cdot z}{x}} \]
      8. Step-by-step derivation
        1. lift-*.f64N/A

          \[\leadsto y \cdot \frac{z \cdot z}{x} \]
        2. lift-/.f64N/A

          \[\leadsto y \cdot \frac{z \cdot z}{\color{blue}{x}} \]
        3. associate-/l*N/A

          \[\leadsto y \cdot \left(z \cdot \color{blue}{\frac{z}{x}}\right) \]
        4. lower-*.f64N/A

          \[\leadsto y \cdot \left(z \cdot \color{blue}{\frac{z}{x}}\right) \]
        5. lower-/.f6461.1

          \[\leadsto y \cdot \left(z \cdot \frac{z}{\color{blue}{x}}\right) \]
      9. Applied rewrites61.1%

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

      if -2e12 < (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) < 5.00000000000000021e35

      1. Initial program 99.4%

        \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
        2. lift-+.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
        3. lift-*.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
        4. lift--.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        5. lift-+.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        6. lift-*.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        7. div-addN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
        8. *-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        9. +-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        10. *-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        11. associate-/l*N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        12. metadata-evalN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
        13. associate-*r/N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
        14. lower-fma.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
      4. Applied rewrites97.8%

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
      5. Taylor expanded in x around 0

        \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
      6. Step-by-step derivation
        1. div-subN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        2. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        3. div-subN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        4. associate-/l*N/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z} \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        5. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        6. +-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        7. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        8. div-addN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}}{x} \]
        9. lower-/.f64N/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{\color{blue}{x}} \]
      7. Applied rewrites52.4%

        \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]
      8. Taylor expanded in z around 0

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000}}{x} \]
      9. Step-by-step derivation
        1. Applied rewrites49.5%

          \[\leadsto \frac{0.083333333333333}{x} \]
      10. Recombined 2 regimes into one program.
      11. Final simplification55.5%

        \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z \leq -2000000000000 \lor \neg \left(\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z \leq 5 \cdot 10^{+35}\right):\\ \;\;\;\;y \cdot \left(z \cdot \frac{z}{x}\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{0.083333333333333}{x}\\ \end{array} \]
      12. Add Preprocessing

      Alternative 14: 63.1% accurate, 3.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(y + 0.0007936500793651\right) \cdot z\\ \mathbf{if}\;\left(t\_0 - 0.0027777777777778\right) \cdot z + 0.083333333333333 \leq 0.1:\\ \;\;\;\;\frac{\left(z \cdot z\right) \cdot y + 0.083333333333333}{x}\\ \mathbf{else}:\\ \;\;\;\;z \cdot \frac{t\_0}{x}\\ \end{array} \end{array} \]
      (FPCore (x y z)
       :precision binary64
       (let* ((t_0 (* (+ y 0.0007936500793651) z)))
         (if (<= (+ (* (- t_0 0.0027777777777778) z) 0.083333333333333) 0.1)
           (/ (+ (* (* z z) y) 0.083333333333333) x)
           (* z (/ t_0 x)))))
      double code(double x, double y, double z) {
      	double t_0 = (y + 0.0007936500793651) * z;
      	double tmp;
      	if ((((t_0 - 0.0027777777777778) * z) + 0.083333333333333) <= 0.1) {
      		tmp = (((z * z) * y) + 0.083333333333333) / x;
      	} else {
      		tmp = z * (t_0 / x);
      	}
      	return tmp;
      }
      
      module fmin_fmax_functions
          implicit none
          private
          public fmax
          public fmin
      
          interface fmax
              module procedure fmax88
              module procedure fmax44
              module procedure fmax84
              module procedure fmax48
          end interface
          interface fmin
              module procedure fmin88
              module procedure fmin44
              module procedure fmin84
              module procedure fmin48
          end interface
      contains
          real(8) function fmax88(x, y) result (res)
              real(8), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(x, max(x, y), y /= y), x /= x)
          end function
          real(4) function fmax44(x, y) result (res)
              real(4), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(y, merge(x, max(x, y), y /= y), x /= x)
          end function
          real(8) function fmax84(x, y) result(res)
              real(8), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
          end function
          real(8) function fmax48(x, y) result(res)
              real(4), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
          end function
          real(8) function fmin88(x, y) result (res)
              real(8), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(x, min(x, y), y /= y), x /= x)
          end function
          real(4) function fmin44(x, y) result (res)
              real(4), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(y, merge(x, min(x, y), y /= y), x /= x)
          end function
          real(8) function fmin84(x, y) result(res)
              real(8), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
          end function
          real(8) function fmin48(x, y) result(res)
              real(4), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
          end function
      end module
      
      real(8) function code(x, y, z)
      use fmin_fmax_functions
          real(8), intent (in) :: x
          real(8), intent (in) :: y
          real(8), intent (in) :: z
          real(8) :: t_0
          real(8) :: tmp
          t_0 = (y + 0.0007936500793651d0) * z
          if ((((t_0 - 0.0027777777777778d0) * z) + 0.083333333333333d0) <= 0.1d0) then
              tmp = (((z * z) * y) + 0.083333333333333d0) / x
          else
              tmp = z * (t_0 / x)
          end if
          code = tmp
      end function
      
      public static double code(double x, double y, double z) {
      	double t_0 = (y + 0.0007936500793651) * z;
      	double tmp;
      	if ((((t_0 - 0.0027777777777778) * z) + 0.083333333333333) <= 0.1) {
      		tmp = (((z * z) * y) + 0.083333333333333) / x;
      	} else {
      		tmp = z * (t_0 / x);
      	}
      	return tmp;
      }
      
      def code(x, y, z):
      	t_0 = (y + 0.0007936500793651) * z
      	tmp = 0
      	if (((t_0 - 0.0027777777777778) * z) + 0.083333333333333) <= 0.1:
      		tmp = (((z * z) * y) + 0.083333333333333) / x
      	else:
      		tmp = z * (t_0 / x)
      	return tmp
      
      function code(x, y, z)
      	t_0 = Float64(Float64(y + 0.0007936500793651) * z)
      	tmp = 0.0
      	if (Float64(Float64(Float64(t_0 - 0.0027777777777778) * z) + 0.083333333333333) <= 0.1)
      		tmp = Float64(Float64(Float64(Float64(z * z) * y) + 0.083333333333333) / x);
      	else
      		tmp = Float64(z * Float64(t_0 / x));
      	end
      	return tmp
      end
      
      function tmp_2 = code(x, y, z)
      	t_0 = (y + 0.0007936500793651) * z;
      	tmp = 0.0;
      	if ((((t_0 - 0.0027777777777778) * z) + 0.083333333333333) <= 0.1)
      		tmp = (((z * z) * y) + 0.083333333333333) / x;
      	else
      		tmp = z * (t_0 / x);
      	end
      	tmp_2 = tmp;
      end
      
      code[x_, y_, z_] := Block[{t$95$0 = N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision]}, If[LessEqual[N[(N[(N[(t$95$0 - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision] + 0.083333333333333), $MachinePrecision], 0.1], N[(N[(N[(N[(z * z), $MachinePrecision] * y), $MachinePrecision] + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], N[(z * N[(t$95$0 / x), $MachinePrecision]), $MachinePrecision]]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := \left(y + 0.0007936500793651\right) \cdot z\\
      \mathbf{if}\;\left(t\_0 - 0.0027777777777778\right) \cdot z + 0.083333333333333 \leq 0.1:\\
      \;\;\;\;\frac{\left(z \cdot z\right) \cdot y + 0.083333333333333}{x}\\
      
      \mathbf{else}:\\
      \;\;\;\;z \cdot \frac{t\_0}{x}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64)) < 0.10000000000000001

        1. Initial program 97.2%

          \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
        2. Add Preprocessing
        3. Taylor expanded in x around 0

          \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + \left(x \cdot \left(\frac{91893853320467}{100000000000000} + \left(\frac{-1}{2} \cdot \log x + x \cdot \left(\log x - 1\right)\right)\right) + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)\right)}{x}} \]
        4. Step-by-step derivation
          1. lower-/.f64N/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(x \cdot \left(\frac{91893853320467}{100000000000000} + \left(\frac{-1}{2} \cdot \log x + x \cdot \left(\log x - 1\right)\right)\right) + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)\right)}{\color{blue}{x}} \]
        5. Applied rewrites81.1%

          \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, \left(\mathsf{fma}\left(\log x - 1, x, -0.5 \cdot \log x\right) + 0.91893853320467\right) \cdot x\right) + 0.083333333333333}{x}} \]
        6. Taylor expanded in y around inf

          \[\leadsto \frac{y \cdot {z}^{2} + \frac{83333333333333}{1000000000000000}}{x} \]
        7. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \frac{{z}^{2} \cdot y + \frac{83333333333333}{1000000000000000}}{x} \]
          2. pow2N/A

            \[\leadsto \frac{\left(z \cdot z\right) \cdot y + \frac{83333333333333}{1000000000000000}}{x} \]
          3. lift-*.f64N/A

            \[\leadsto \frac{\left(z \cdot z\right) \cdot y + \frac{83333333333333}{1000000000000000}}{x} \]
          4. lift-*.f6459.1

            \[\leadsto \frac{\left(z \cdot z\right) \cdot y + 0.083333333333333}{x} \]
        8. Applied rewrites59.1%

          \[\leadsto \frac{\left(z \cdot z\right) \cdot y + 0.083333333333333}{x} \]

        if 0.10000000000000001 < (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64))

        1. Initial program 85.3%

          \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
          2. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
          3. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
          4. lift--.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          5. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          6. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          7. div-addN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
          8. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          9. +-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          10. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          11. associate-/l*N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          12. metadata-evalN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
          13. associate-*r/N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
          14. lower-fma.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
        4. Applied rewrites96.9%

          \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
        5. Taylor expanded in z around inf

          \[\leadsto \color{blue}{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right)} \]
        6. Applied rewrites72.3%

          \[\leadsto \color{blue}{z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 15: 63.1% accurate, 3.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(y + 0.0007936500793651\right) \cdot z\\ \mathbf{if}\;\left(t\_0 - 0.0027777777777778\right) \cdot z + 0.083333333333333 \leq 0.1:\\ \;\;\;\;\frac{\mathsf{fma}\left(z \cdot y, z, 0.083333333333333\right)}{x}\\ \mathbf{else}:\\ \;\;\;\;z \cdot \frac{t\_0}{x}\\ \end{array} \end{array} \]
      (FPCore (x y z)
       :precision binary64
       (let* ((t_0 (* (+ y 0.0007936500793651) z)))
         (if (<= (+ (* (- t_0 0.0027777777777778) z) 0.083333333333333) 0.1)
           (/ (fma (* z y) z 0.083333333333333) x)
           (* z (/ t_0 x)))))
      double code(double x, double y, double z) {
      	double t_0 = (y + 0.0007936500793651) * z;
      	double tmp;
      	if ((((t_0 - 0.0027777777777778) * z) + 0.083333333333333) <= 0.1) {
      		tmp = fma((z * y), z, 0.083333333333333) / x;
      	} else {
      		tmp = z * (t_0 / x);
      	}
      	return tmp;
      }
      
      function code(x, y, z)
      	t_0 = Float64(Float64(y + 0.0007936500793651) * z)
      	tmp = 0.0
      	if (Float64(Float64(Float64(t_0 - 0.0027777777777778) * z) + 0.083333333333333) <= 0.1)
      		tmp = Float64(fma(Float64(z * y), z, 0.083333333333333) / x);
      	else
      		tmp = Float64(z * Float64(t_0 / x));
      	end
      	return tmp
      end
      
      code[x_, y_, z_] := Block[{t$95$0 = N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision]}, If[LessEqual[N[(N[(N[(t$95$0 - 0.0027777777777778), $MachinePrecision] * z), $MachinePrecision] + 0.083333333333333), $MachinePrecision], 0.1], N[(N[(N[(z * y), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], N[(z * N[(t$95$0 / x), $MachinePrecision]), $MachinePrecision]]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      t_0 := \left(y + 0.0007936500793651\right) \cdot z\\
      \mathbf{if}\;\left(t\_0 - 0.0027777777777778\right) \cdot z + 0.083333333333333 \leq 0.1:\\
      \;\;\;\;\frac{\mathsf{fma}\left(z \cdot y, z, 0.083333333333333\right)}{x}\\
      
      \mathbf{else}:\\
      \;\;\;\;z \cdot \frac{t\_0}{x}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64)) < 0.10000000000000001

        1. Initial program 97.2%

          \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
          2. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
          3. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
          4. lift--.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          5. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          6. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          7. div-addN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
          8. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          9. +-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          10. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          11. associate-/l*N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          12. metadata-evalN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
          13. associate-*r/N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
          14. lower-fma.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
        4. Applied rewrites96.6%

          \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
        5. Taylor expanded in x around 0

          \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
        6. Step-by-step derivation
          1. div-subN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          2. *-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          3. div-subN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          4. associate-/l*N/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z} \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          5. *-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          6. +-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          7. *-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          8. div-addN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}}{x} \]
          9. lower-/.f64N/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{\color{blue}{x}} \]
        7. Applied rewrites59.1%

          \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]
        8. Taylor expanded in y around inf

          \[\leadsto \frac{\mathsf{fma}\left(y \cdot z, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
        9. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \frac{\mathsf{fma}\left(y \cdot z, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          2. *-commutativeN/A

            \[\leadsto \frac{\mathsf{fma}\left(z \cdot y, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          3. lower-*.f6459.1

            \[\leadsto \frac{\mathsf{fma}\left(z \cdot y, z, 0.083333333333333\right)}{x} \]
        10. Applied rewrites59.1%

          \[\leadsto \frac{\mathsf{fma}\left(z \cdot y, z, 0.083333333333333\right)}{x} \]

        if 0.10000000000000001 < (+.f64 (*.f64 (-.f64 (*.f64 (+.f64 y #s(literal 7936500793651/10000000000000000 binary64)) z) #s(literal 13888888888889/5000000000000000 binary64)) z) #s(literal 83333333333333/1000000000000000 binary64))

        1. Initial program 85.3%

          \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
          2. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
          3. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
          4. lift--.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          5. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          6. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          7. div-addN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
          8. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          9. +-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          10. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          11. associate-/l*N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          12. metadata-evalN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
          13. associate-*r/N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
          14. lower-fma.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
        4. Applied rewrites96.9%

          \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
        5. Taylor expanded in z around inf

          \[\leadsto \color{blue}{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right)} \]
        6. Applied rewrites72.3%

          \[\leadsto \color{blue}{z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 16: 64.2% accurate, 4.2× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 3.7 \cdot 10^{+66}:\\ \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\ \mathbf{else}:\\ \;\;\;\;z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}\\ \end{array} \end{array} \]
      (FPCore (x y z)
       :precision binary64
       (if (<= x 3.7e+66)
         (/
          (fma
           (- (* (+ 0.0007936500793651 y) z) 0.0027777777777778)
           z
           0.083333333333333)
          x)
         (* z (/ (* (+ y 0.0007936500793651) z) x))))
      double code(double x, double y, double z) {
      	double tmp;
      	if (x <= 3.7e+66) {
      		tmp = fma((((0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x;
      	} else {
      		tmp = z * (((y + 0.0007936500793651) * z) / x);
      	}
      	return tmp;
      }
      
      function code(x, y, z)
      	tmp = 0.0
      	if (x <= 3.7e+66)
      		tmp = Float64(fma(Float64(Float64(Float64(0.0007936500793651 + y) * z) - 0.0027777777777778), z, 0.083333333333333) / x);
      	else
      		tmp = Float64(z * Float64(Float64(Float64(y + 0.0007936500793651) * z) / x));
      	end
      	return tmp
      end
      
      code[x_, y_, z_] := If[LessEqual[x, 3.7e+66], N[(N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] - 0.0027777777777778), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], N[(z * N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;x \leq 3.7 \cdot 10^{+66}:\\
      \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}\\
      
      \mathbf{else}:\\
      \;\;\;\;z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if x < 3.7e66

        1. Initial program 99.7%

          \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
        2. Add Preprocessing
        3. Taylor expanded in x around 0

          \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
        4. Step-by-step derivation
          1. *-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
          2. *-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
          3. +-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} \]
          4. +-commutativeN/A

            \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          5. lower-/.f64N/A

            \[\leadsto \frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{\color{blue}{x}} \]
          6. lower-fma.f64N/A

            \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          7. lift-*.f64N/A

            \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          8. lift-+.f64N/A

            \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          9. lift--.f6489.2

            \[\leadsto \frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
          10. lift-+.f64N/A

            \[\leadsto \frac{\mathsf{fma}\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          11. +-commutativeN/A

            \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z - \frac{13888888888889}{5000000000000000}, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          12. lower-+.f6489.2

            \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x} \]
        5. Applied rewrites89.2%

          \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]

        if 3.7e66 < x

        1. Initial program 81.3%

          \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
          2. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
          3. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
          4. lift--.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          5. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          6. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          7. div-addN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
          8. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          9. +-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          10. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          11. associate-/l*N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          12. metadata-evalN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
          13. associate-*r/N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
          14. lower-fma.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
        4. Applied rewrites94.7%

          \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
        5. Taylor expanded in z around inf

          \[\leadsto \color{blue}{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right)} \]
        6. Applied rewrites24.0%

          \[\leadsto \color{blue}{z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 17: 63.7% accurate, 4.6× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq 3.7 \cdot 10^{+66}:\\ \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z, z, 0.083333333333333\right)}{x}\\ \mathbf{else}:\\ \;\;\;\;z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}\\ \end{array} \end{array} \]
      (FPCore (x y z)
       :precision binary64
       (if (<= x 3.7e+66)
         (/ (fma (* (+ 0.0007936500793651 y) z) z 0.083333333333333) x)
         (* z (/ (* (+ y 0.0007936500793651) z) x))))
      double code(double x, double y, double z) {
      	double tmp;
      	if (x <= 3.7e+66) {
      		tmp = fma(((0.0007936500793651 + y) * z), z, 0.083333333333333) / x;
      	} else {
      		tmp = z * (((y + 0.0007936500793651) * z) / x);
      	}
      	return tmp;
      }
      
      function code(x, y, z)
      	tmp = 0.0
      	if (x <= 3.7e+66)
      		tmp = Float64(fma(Float64(Float64(0.0007936500793651 + y) * z), z, 0.083333333333333) / x);
      	else
      		tmp = Float64(z * Float64(Float64(Float64(y + 0.0007936500793651) * z) / x));
      	end
      	return tmp
      end
      
      code[x_, y_, z_] := If[LessEqual[x, 3.7e+66], N[(N[(N[(N[(0.0007936500793651 + y), $MachinePrecision] * z), $MachinePrecision] * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision], N[(z * N[(N[(N[(y + 0.0007936500793651), $MachinePrecision] * z), $MachinePrecision] / x), $MachinePrecision]), $MachinePrecision]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;x \leq 3.7 \cdot 10^{+66}:\\
      \;\;\;\;\frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z, z, 0.083333333333333\right)}{x}\\
      
      \mathbf{else}:\\
      \;\;\;\;z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if x < 3.7e66

        1. Initial program 99.7%

          \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
          2. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
          3. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
          4. lift--.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          5. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          6. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          7. div-addN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
          8. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          9. +-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          10. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          11. associate-/l*N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          12. metadata-evalN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
          13. associate-*r/N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
          14. lower-fma.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
        4. Applied rewrites97.8%

          \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
        5. Taylor expanded in x around 0

          \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
        6. Step-by-step derivation
          1. div-subN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          2. *-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          3. div-subN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          4. associate-/l*N/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z} \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          5. *-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          6. +-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          7. *-commutativeN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
          8. div-addN/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}}{x} \]
          9. lower-/.f64N/A

            \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{\color{blue}{x}} \]
        7. Applied rewrites89.2%

          \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]
        8. Taylor expanded in z around inf

          \[\leadsto \frac{\mathsf{fma}\left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right), z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
        9. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto \frac{\mathsf{fma}\left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right), z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          2. *-commutativeN/A

            \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          3. lower-*.f64N/A

            \[\leadsto \frac{\mathsf{fma}\left(\left(\frac{7936500793651}{10000000000000000} + y\right) \cdot z, z, \frac{83333333333333}{1000000000000000}\right)}{x} \]
          4. lower-+.f6488.9

            \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z, z, 0.083333333333333\right)}{x} \]
        10. Applied rewrites88.9%

          \[\leadsto \frac{\mathsf{fma}\left(\left(0.0007936500793651 + y\right) \cdot z, z, 0.083333333333333\right)}{x} \]

        if 3.7e66 < x

        1. Initial program 81.3%

          \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
          2. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
          3. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
          4. lift--.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          5. lift-+.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          6. lift-*.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
          7. div-addN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
          8. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          9. +-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          10. *-commutativeN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          11. associate-/l*N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
          12. metadata-evalN/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
          13. associate-*r/N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
          14. lower-fma.f64N/A

            \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
        4. Applied rewrites94.7%

          \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
        5. Taylor expanded in z around inf

          \[\leadsto \color{blue}{{z}^{2} \cdot \left(\frac{7936500793651}{10000000000000000} \cdot \frac{1}{x} + \frac{y}{x}\right)} \]
        6. Applied rewrites24.0%

          \[\leadsto \color{blue}{z \cdot \frac{\left(y + 0.0007936500793651\right) \cdot z}{x}} \]
      3. Recombined 2 regimes into one program.
      4. Add Preprocessing

      Alternative 18: 28.7% accurate, 8.2× speedup?

      \[\begin{array}{l} \\ \frac{\mathsf{fma}\left(-0.0027777777777778, z, 0.083333333333333\right)}{x} \end{array} \]
      (FPCore (x y z)
       :precision binary64
       (/ (fma -0.0027777777777778 z 0.083333333333333) x))
      double code(double x, double y, double z) {
      	return fma(-0.0027777777777778, z, 0.083333333333333) / x;
      }
      
      function code(x, y, z)
      	return Float64(fma(-0.0027777777777778, z, 0.083333333333333) / x)
      end
      
      code[x_, y_, z_] := N[(N[(-0.0027777777777778 * z + 0.083333333333333), $MachinePrecision] / x), $MachinePrecision]
      
      \begin{array}{l}
      
      \\
      \frac{\mathsf{fma}\left(-0.0027777777777778, z, 0.083333333333333\right)}{x}
      \end{array}
      
      Derivation
      1. Initial program 92.8%

        \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
        2. lift-+.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
        3. lift-*.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
        4. lift--.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        5. lift-+.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        6. lift-*.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        7. div-addN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
        8. *-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        9. +-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        10. *-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        11. associate-/l*N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        12. metadata-evalN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
        13. associate-*r/N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
        14. lower-fma.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
      4. Applied rewrites96.7%

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
      5. Taylor expanded in x around 0

        \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
      6. Step-by-step derivation
        1. div-subN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        2. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        3. div-subN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        4. associate-/l*N/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z} \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        5. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        6. +-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        7. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        8. div-addN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}}{x} \]
        9. lower-/.f64N/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{\color{blue}{x}} \]
      7. Applied rewrites62.5%

        \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]
      8. Taylor expanded in z around 0

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \frac{-13888888888889}{5000000000000000} \cdot z}{x} \]
      9. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \frac{\frac{-13888888888889}{5000000000000000} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        2. lower-fma.f6432.9

          \[\leadsto \frac{\mathsf{fma}\left(-0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      10. Applied rewrites32.9%

        \[\leadsto \frac{\mathsf{fma}\left(-0.0027777777777778, z, 0.083333333333333\right)}{x} \]
      11. Add Preprocessing

      Alternative 19: 23.3% accurate, 12.3× speedup?

      \[\begin{array}{l} \\ \frac{0.083333333333333}{x} \end{array} \]
      (FPCore (x y z) :precision binary64 (/ 0.083333333333333 x))
      double code(double x, double y, double z) {
      	return 0.083333333333333 / x;
      }
      
      module fmin_fmax_functions
          implicit none
          private
          public fmax
          public fmin
      
          interface fmax
              module procedure fmax88
              module procedure fmax44
              module procedure fmax84
              module procedure fmax48
          end interface
          interface fmin
              module procedure fmin88
              module procedure fmin44
              module procedure fmin84
              module procedure fmin48
          end interface
      contains
          real(8) function fmax88(x, y) result (res)
              real(8), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(x, max(x, y), y /= y), x /= x)
          end function
          real(4) function fmax44(x, y) result (res)
              real(4), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(y, merge(x, max(x, y), y /= y), x /= x)
          end function
          real(8) function fmax84(x, y) result(res)
              real(8), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
          end function
          real(8) function fmax48(x, y) result(res)
              real(4), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
          end function
          real(8) function fmin88(x, y) result (res)
              real(8), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(x, min(x, y), y /= y), x /= x)
          end function
          real(4) function fmin44(x, y) result (res)
              real(4), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(y, merge(x, min(x, y), y /= y), x /= x)
          end function
          real(8) function fmin84(x, y) result(res)
              real(8), intent (in) :: x
              real(4), intent (in) :: y
              res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
          end function
          real(8) function fmin48(x, y) result(res)
              real(4), intent (in) :: x
              real(8), intent (in) :: y
              res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
          end function
      end module
      
      real(8) function code(x, y, z)
      use fmin_fmax_functions
          real(8), intent (in) :: x
          real(8), intent (in) :: y
          real(8), intent (in) :: z
          code = 0.083333333333333d0 / x
      end function
      
      public static double code(double x, double y, double z) {
      	return 0.083333333333333 / x;
      }
      
      def code(x, y, z):
      	return 0.083333333333333 / x
      
      function code(x, y, z)
      	return Float64(0.083333333333333 / x)
      end
      
      function tmp = code(x, y, z)
      	tmp = 0.083333333333333 / x;
      end
      
      code[x_, y_, z_] := N[(0.083333333333333 / x), $MachinePrecision]
      
      \begin{array}{l}
      
      \\
      \frac{0.083333333333333}{x}
      \end{array}
      
      Derivation
      1. Initial program 92.8%

        \[\left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \frac{\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778\right) \cdot z + 0.083333333333333}{x} \]
      2. Add Preprocessing
      3. Step-by-step derivation
        1. lift-/.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x}} \]
        2. lift-+.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}}{x} \]
        3. lift-*.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z} + \frac{83333333333333}{1000000000000000}}{x} \]
        4. lift--.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\color{blue}{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)} \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        5. lift-+.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        6. lift-*.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \frac{\left(\color{blue}{\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z} - \frac{13888888888889}{5000000000000000}\right) \cdot z + \frac{83333333333333}{1000000000000000}}{x} \]
        7. div-addN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\left(\frac{\left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right) \cdot z}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right)} \]
        8. *-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{\color{blue}{z \cdot \left(\left(y + \frac{7936500793651}{10000000000000000}\right) \cdot z - \frac{13888888888889}{5000000000000000}\right)}}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        9. +-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{\left(\frac{7936500793651}{10000000000000000} + y\right)} \cdot z - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        10. *-commutativeN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\frac{z \cdot \left(\color{blue}{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right)} - \frac{13888888888889}{5000000000000000}\right)}{x} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        11. associate-/l*N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(\color{blue}{z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}} + \frac{\frac{83333333333333}{1000000000000000}}{x}\right) \]
        12. metadata-evalN/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \frac{\color{blue}{\frac{83333333333333}{1000000000000000} \cdot 1}}{x}\right) \]
        13. associate-*r/N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \left(z \cdot \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x} + \color{blue}{\frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}}\right) \]
        14. lower-fma.f64N/A

          \[\leadsto \left(\left(\left(x - \frac{1}{2}\right) \cdot \log x - x\right) + \frac{91893853320467}{100000000000000}\right) + \color{blue}{\mathsf{fma}\left(z, \frac{z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}}{x}, \frac{83333333333333}{1000000000000000} \cdot \frac{1}{x}\right)} \]
      4. Applied rewrites96.7%

        \[\leadsto \left(\left(\left(x - 0.5\right) \cdot \log x - x\right) + 0.91893853320467\right) + \color{blue}{\mathsf{fma}\left(z, \frac{\left(0.0007936500793651 + y\right) \cdot z - 0.0027777777777778}{x}, \frac{0.083333333333333}{x}\right)} \]
      5. Taylor expanded in x around 0

        \[\leadsto \color{blue}{\frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x}} \]
      6. Step-by-step derivation
        1. div-subN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        2. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        3. div-subN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        4. associate-/l*N/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z} \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        5. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        6. +-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        7. *-commutativeN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{x} \]
        8. div-addN/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + \color{blue}{z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}}{x} \]
        9. lower-/.f64N/A

          \[\leadsto \frac{\frac{83333333333333}{1000000000000000} + z \cdot \left(z \cdot \left(\frac{7936500793651}{10000000000000000} + y\right) - \frac{13888888888889}{5000000000000000}\right)}{\color{blue}{x}} \]
      7. Applied rewrites62.5%

        \[\leadsto \color{blue}{\frac{\mathsf{fma}\left(\left(y + 0.0007936500793651\right) \cdot z - 0.0027777777777778, z, 0.083333333333333\right)}{x}} \]
      8. Taylor expanded in z around 0

        \[\leadsto \frac{\frac{83333333333333}{1000000000000000}}{x} \]
      9. Step-by-step derivation
        1. Applied rewrites25.6%

          \[\leadsto \frac{0.083333333333333}{x} \]
        2. Add Preprocessing

        Developer Target 1: 98.5% accurate, 0.9× speedup?

        \[\begin{array}{l} \\ \left(\left(\left(x - 0.5\right) \cdot \log x + \left(0.91893853320467 - x\right)\right) + \frac{0.083333333333333}{x}\right) + \frac{z}{x} \cdot \left(z \cdot \left(y + 0.0007936500793651\right) - 0.0027777777777778\right) \end{array} \]
        (FPCore (x y z)
         :precision binary64
         (+
          (+ (+ (* (- x 0.5) (log x)) (- 0.91893853320467 x)) (/ 0.083333333333333 x))
          (* (/ z x) (- (* z (+ y 0.0007936500793651)) 0.0027777777777778))))
        double code(double x, double y, double z) {
        	return ((((x - 0.5) * log(x)) + (0.91893853320467 - x)) + (0.083333333333333 / x)) + ((z / x) * ((z * (y + 0.0007936500793651)) - 0.0027777777777778));
        }
        
        module fmin_fmax_functions
            implicit none
            private
            public fmax
            public fmin
        
            interface fmax
                module procedure fmax88
                module procedure fmax44
                module procedure fmax84
                module procedure fmax48
            end interface
            interface fmin
                module procedure fmin88
                module procedure fmin44
                module procedure fmin84
                module procedure fmin48
            end interface
        contains
            real(8) function fmax88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(4) function fmax44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, max(x, y), y /= y), x /= x)
            end function
            real(8) function fmax84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, max(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmax48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), max(dble(x), y), y /= y), x /= x)
            end function
            real(8) function fmin88(x, y) result (res)
                real(8), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(4) function fmin44(x, y) result (res)
                real(4), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(y, merge(x, min(x, y), y /= y), x /= x)
            end function
            real(8) function fmin84(x, y) result(res)
                real(8), intent (in) :: x
                real(4), intent (in) :: y
                res = merge(dble(y), merge(x, min(x, dble(y)), y /= y), x /= x)
            end function
            real(8) function fmin48(x, y) result(res)
                real(4), intent (in) :: x
                real(8), intent (in) :: y
                res = merge(y, merge(dble(x), min(dble(x), y), y /= y), x /= x)
            end function
        end module
        
        real(8) function code(x, y, z)
        use fmin_fmax_functions
            real(8), intent (in) :: x
            real(8), intent (in) :: y
            real(8), intent (in) :: z
            code = ((((x - 0.5d0) * log(x)) + (0.91893853320467d0 - x)) + (0.083333333333333d0 / x)) + ((z / x) * ((z * (y + 0.0007936500793651d0)) - 0.0027777777777778d0))
        end function
        
        public static double code(double x, double y, double z) {
        	return ((((x - 0.5) * Math.log(x)) + (0.91893853320467 - x)) + (0.083333333333333 / x)) + ((z / x) * ((z * (y + 0.0007936500793651)) - 0.0027777777777778));
        }
        
        def code(x, y, z):
        	return ((((x - 0.5) * math.log(x)) + (0.91893853320467 - x)) + (0.083333333333333 / x)) + ((z / x) * ((z * (y + 0.0007936500793651)) - 0.0027777777777778))
        
        function code(x, y, z)
        	return Float64(Float64(Float64(Float64(Float64(x - 0.5) * log(x)) + Float64(0.91893853320467 - x)) + Float64(0.083333333333333 / x)) + Float64(Float64(z / x) * Float64(Float64(z * Float64(y + 0.0007936500793651)) - 0.0027777777777778)))
        end
        
        function tmp = code(x, y, z)
        	tmp = ((((x - 0.5) * log(x)) + (0.91893853320467 - x)) + (0.083333333333333 / x)) + ((z / x) * ((z * (y + 0.0007936500793651)) - 0.0027777777777778));
        end
        
        code[x_, y_, z_] := N[(N[(N[(N[(N[(x - 0.5), $MachinePrecision] * N[Log[x], $MachinePrecision]), $MachinePrecision] + N[(0.91893853320467 - x), $MachinePrecision]), $MachinePrecision] + N[(0.083333333333333 / x), $MachinePrecision]), $MachinePrecision] + N[(N[(z / x), $MachinePrecision] * N[(N[(z * N[(y + 0.0007936500793651), $MachinePrecision]), $MachinePrecision] - 0.0027777777777778), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
        
        \begin{array}{l}
        
        \\
        \left(\left(\left(x - 0.5\right) \cdot \log x + \left(0.91893853320467 - x\right)\right) + \frac{0.083333333333333}{x}\right) + \frac{z}{x} \cdot \left(z \cdot \left(y + 0.0007936500793651\right) - 0.0027777777777778\right)
        \end{array}
        

        Reproduce

        ?
        herbie shell --seed 2025043 
        (FPCore (x y z)
          :name "Numeric.SpecFunctions:$slogFactorial from math-functions-0.1.5.2, B"
          :precision binary64
        
          :alt
          (! :herbie-platform default (+ (+ (+ (* (- x 1/2) (log x)) (- 91893853320467/100000000000000 x)) (/ 83333333333333/1000000000000000 x)) (* (/ z x) (- (* z (+ y 7936500793651/10000000000000000)) 13888888888889/5000000000000000))))
        
          (+ (+ (- (* (- x 0.5) (log x)) x) 0.91893853320467) (/ (+ (* (- (* (+ y 0.0007936500793651) z) 0.0027777777777778) z) 0.083333333333333) x)))