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

Percentage Accurate: 68.9% → 98.6%
Time: 9.3s
Alternatives: 13
Speedup: 2.5×

Specification

?
\[\begin{array}{l} \\ x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (+
  x
  (/
   (*
    y
    (+
     (* (+ (* z 0.0692910599291889) 0.4917317610505968) z)
     0.279195317918525))
   (+ (* (+ z 6.012459259764103) z) 3.350343815022304))))
double code(double x, double y, double z) {
	return x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304));
}
real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x + ((y * ((((z * 0.0692910599291889d0) + 0.4917317610505968d0) * z) + 0.279195317918525d0)) / (((z + 6.012459259764103d0) * z) + 3.350343815022304d0))
end function
public static double code(double x, double y, double z) {
	return x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304));
}
def code(x, y, z):
	return x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304))
function code(x, y, z)
	return Float64(x + Float64(Float64(y * Float64(Float64(Float64(Float64(z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / Float64(Float64(Float64(z + 6.012459259764103) * z) + 3.350343815022304)))
end
function tmp = code(x, y, z)
	tmp = x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304));
end
code[x_, y_, z_] := N[(x + N[(N[(y * N[(N[(N[(N[(z * 0.0692910599291889), $MachinePrecision] + 0.4917317610505968), $MachinePrecision] * z), $MachinePrecision] + 0.279195317918525), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(z + 6.012459259764103), $MachinePrecision] * z), $MachinePrecision] + 3.350343815022304), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}
\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 13 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: 68.9% accurate, 1.0× speedup?

\[\begin{array}{l} \\ x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (+
  x
  (/
   (*
    y
    (+
     (* (+ (* z 0.0692910599291889) 0.4917317610505968) z)
     0.279195317918525))
   (+ (* (+ z 6.012459259764103) z) 3.350343815022304))))
double code(double x, double y, double z) {
	return x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304));
}
real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x + ((y * ((((z * 0.0692910599291889d0) + 0.4917317610505968d0) * z) + 0.279195317918525d0)) / (((z + 6.012459259764103d0) * z) + 3.350343815022304d0))
end function
public static double code(double x, double y, double z) {
	return x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304));
}
def code(x, y, z):
	return x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304))
function code(x, y, z)
	return Float64(x + Float64(Float64(y * Float64(Float64(Float64(Float64(z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / Float64(Float64(Float64(z + 6.012459259764103) * z) + 3.350343815022304)))
end
function tmp = code(x, y, z)
	tmp = x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304));
end
code[x_, y_, z_] := N[(x + N[(N[(y * N[(N[(N[(N[(z * 0.0692910599291889), $MachinePrecision] + 0.4917317610505968), $MachinePrecision] * z), $MachinePrecision] + 0.279195317918525), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(z + 6.012459259764103), $MachinePrecision] * z), $MachinePrecision] + 3.350343815022304), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}
\end{array}

Alternative 1: 98.6% accurate, 0.5× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \leq 10^{+271}:\\ \;\;\;\;\mathsf{fma}\left(\frac{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y}{14.431876219268936}\\ \end{array} \end{array} \]
(FPCore (x y z)
 :precision binary64
 (if (<=
      (/
       (*
        y
        (+
         (* (+ (* z 0.0692910599291889) 0.4917317610505968) z)
         0.279195317918525))
       (+ (* (+ z 6.012459259764103) z) 3.350343815022304))
      1e+271)
   (fma
    (/
     (fma (fma 0.0692910599291889 z 0.4917317610505968) z 0.279195317918525)
     (fma (+ 6.012459259764103 z) z 3.350343815022304))
    y
    x)
   (+ x (/ y 14.431876219268936))))
double code(double x, double y, double z) {
	double tmp;
	if (((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304)) <= 1e+271) {
		tmp = fma((fma(fma(0.0692910599291889, z, 0.4917317610505968), z, 0.279195317918525) / fma((6.012459259764103 + z), z, 3.350343815022304)), y, x);
	} else {
		tmp = x + (y / 14.431876219268936);
	}
	return tmp;
}
function code(x, y, z)
	tmp = 0.0
	if (Float64(Float64(y * Float64(Float64(Float64(Float64(z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / Float64(Float64(Float64(z + 6.012459259764103) * z) + 3.350343815022304)) <= 1e+271)
		tmp = fma(Float64(fma(fma(0.0692910599291889, z, 0.4917317610505968), z, 0.279195317918525) / fma(Float64(6.012459259764103 + z), z, 3.350343815022304)), y, x);
	else
		tmp = Float64(x + Float64(y / 14.431876219268936));
	end
	return tmp
end
code[x_, y_, z_] := If[LessEqual[N[(N[(y * N[(N[(N[(N[(z * 0.0692910599291889), $MachinePrecision] + 0.4917317610505968), $MachinePrecision] * z), $MachinePrecision] + 0.279195317918525), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(z + 6.012459259764103), $MachinePrecision] * z), $MachinePrecision] + 3.350343815022304), $MachinePrecision]), $MachinePrecision], 1e+271], N[(N[(N[(N[(0.0692910599291889 * z + 0.4917317610505968), $MachinePrecision] * z + 0.279195317918525), $MachinePrecision] / N[(N[(6.012459259764103 + z), $MachinePrecision] * z + 3.350343815022304), $MachinePrecision]), $MachinePrecision] * y + x), $MachinePrecision], N[(x + N[(y / 14.431876219268936), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;\frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \leq 10^{+271}:\\
\;\;\;\;\mathsf{fma}\left(\frac{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}, y, x\right)\\

\mathbf{else}:\\
\;\;\;\;x + \frac{y}{14.431876219268936}\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if (/.f64 (*.f64 y (+.f64 (*.f64 (+.f64 (*.f64 z #s(literal 692910599291889/10000000000000000 binary64)) #s(literal 307332350656623/625000000000000 binary64)) z) #s(literal 11167812716741/40000000000000 binary64))) (+.f64 (*.f64 (+.f64 z #s(literal 6012459259764103/1000000000000000 binary64)) z) #s(literal 104698244219447/31250000000000 binary64))) < 9.99999999999999953e270

    1. Initial program 96.6%

      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-+.f64N/A

        \[\leadsto \color{blue}{x + \frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
      2. +-commutativeN/A

        \[\leadsto \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} + x} \]
      3. lift-/.f64N/A

        \[\leadsto \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} + x \]
      4. lift-*.f64N/A

        \[\leadsto \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} + x \]
      5. associate-/l*N/A

        \[\leadsto \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} + x \]
      6. *-commutativeN/A

        \[\leadsto \color{blue}{\frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \cdot y} + x \]
      7. lower-fma.f64N/A

        \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}, y, x\right)} \]
    4. Applied rewrites99.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\frac{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}, y, x\right)} \]

    if 9.99999999999999953e270 < (/.f64 (*.f64 y (+.f64 (*.f64 (+.f64 (*.f64 z #s(literal 692910599291889/10000000000000000 binary64)) #s(literal 307332350656623/625000000000000 binary64)) z) #s(literal 11167812716741/40000000000000 binary64))) (+.f64 (*.f64 (+.f64 z #s(literal 6012459259764103/1000000000000000 binary64)) z) #s(literal 104698244219447/31250000000000 binary64)))

    1. Initial program 0.6%

      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
    2. Add Preprocessing
    3. Step-by-step derivation
      1. lift-/.f64N/A

        \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
      2. lift-*.f64N/A

        \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
      3. associate-/l*N/A

        \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
      4. clear-numN/A

        \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
      5. un-div-invN/A

        \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
      6. lower-/.f64N/A

        \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
      7. lower-/.f6411.4

        \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
      8. lift-+.f64N/A

        \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
      9. lift-*.f64N/A

        \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
      10. lower-fma.f6411.4

        \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
      11. lift-+.f64N/A

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
      12. +-commutativeN/A

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
      13. lower-+.f6411.4

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
      14. lift-+.f64N/A

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
      15. lift-*.f64N/A

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
      16. lower-fma.f6411.4

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
      17. lift-+.f64N/A

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
      18. lift-*.f64N/A

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
      19. *-commutativeN/A

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
      20. lower-fma.f6411.4

        \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
    4. Applied rewrites11.4%

      \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
    5. Taylor expanded in z around inf

      \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889}}} \]
    6. Step-by-step derivation
      1. Applied rewrites99.8%

        \[\leadsto x + \frac{y}{\color{blue}{14.431876219268936}} \]
    7. Recombined 2 regimes into one program.
    8. Add Preprocessing

    Alternative 2: 83.6% accurate, 0.2× speedup?

    \[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}\\ \mathbf{if}\;t\_0 \leq -\infty \lor \neg \left(t\_0 \leq -1 \cdot 10^{+64} \lor \neg \left(t\_0 \leq 2 \cdot 10^{+159} \lor \neg \left(t\_0 \leq 10^{+271}\right)\right)\right):\\ \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;0.08333333333333323 \cdot y\\ \end{array} \end{array} \]
    (FPCore (x y z)
     :precision binary64
     (let* ((t_0
             (/
              (*
               y
               (+
                (* (+ (* z 0.0692910599291889) 0.4917317610505968) z)
                0.279195317918525))
              (+ (* (+ z 6.012459259764103) z) 3.350343815022304))))
       (if (or (<= t_0 (- INFINITY))
               (not
                (or (<= t_0 -1e+64)
                    (not (or (<= t_0 2e+159) (not (<= t_0 1e+271)))))))
         (fma 0.0692910599291889 y x)
         (* 0.08333333333333323 y))))
    double code(double x, double y, double z) {
    	double t_0 = (y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304);
    	double tmp;
    	if ((t_0 <= -((double) INFINITY)) || !((t_0 <= -1e+64) || !((t_0 <= 2e+159) || !(t_0 <= 1e+271)))) {
    		tmp = fma(0.0692910599291889, y, x);
    	} else {
    		tmp = 0.08333333333333323 * y;
    	}
    	return tmp;
    }
    
    function code(x, y, z)
    	t_0 = Float64(Float64(y * Float64(Float64(Float64(Float64(z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / Float64(Float64(Float64(z + 6.012459259764103) * z) + 3.350343815022304))
    	tmp = 0.0
    	if ((t_0 <= Float64(-Inf)) || !((t_0 <= -1e+64) || !((t_0 <= 2e+159) || !(t_0 <= 1e+271))))
    		tmp = fma(0.0692910599291889, y, x);
    	else
    		tmp = Float64(0.08333333333333323 * y);
    	end
    	return tmp
    end
    
    code[x_, y_, z_] := Block[{t$95$0 = N[(N[(y * N[(N[(N[(N[(z * 0.0692910599291889), $MachinePrecision] + 0.4917317610505968), $MachinePrecision] * z), $MachinePrecision] + 0.279195317918525), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(z + 6.012459259764103), $MachinePrecision] * z), $MachinePrecision] + 3.350343815022304), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[t$95$0, (-Infinity)], N[Not[Or[LessEqual[t$95$0, -1e+64], N[Not[Or[LessEqual[t$95$0, 2e+159], N[Not[LessEqual[t$95$0, 1e+271]], $MachinePrecision]]], $MachinePrecision]]], $MachinePrecision]], N[(0.0692910599291889 * y + x), $MachinePrecision], N[(0.08333333333333323 * y), $MachinePrecision]]]
    
    \begin{array}{l}
    
    \\
    \begin{array}{l}
    t_0 := \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}\\
    \mathbf{if}\;t\_0 \leq -\infty \lor \neg \left(t\_0 \leq -1 \cdot 10^{+64} \lor \neg \left(t\_0 \leq 2 \cdot 10^{+159} \lor \neg \left(t\_0 \leq 10^{+271}\right)\right)\right):\\
    \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\
    
    \mathbf{else}:\\
    \;\;\;\;0.08333333333333323 \cdot y\\
    
    
    \end{array}
    \end{array}
    
    Derivation
    1. Split input into 2 regimes
    2. if (/.f64 (*.f64 y (+.f64 (*.f64 (+.f64 (*.f64 z #s(literal 692910599291889/10000000000000000 binary64)) #s(literal 307332350656623/625000000000000 binary64)) z) #s(literal 11167812716741/40000000000000 binary64))) (+.f64 (*.f64 (+.f64 z #s(literal 6012459259764103/1000000000000000 binary64)) z) #s(literal 104698244219447/31250000000000 binary64))) < -inf.0 or -1.00000000000000002e64 < (/.f64 (*.f64 y (+.f64 (*.f64 (+.f64 (*.f64 z #s(literal 692910599291889/10000000000000000 binary64)) #s(literal 307332350656623/625000000000000 binary64)) z) #s(literal 11167812716741/40000000000000 binary64))) (+.f64 (*.f64 (+.f64 z #s(literal 6012459259764103/1000000000000000 binary64)) z) #s(literal 104698244219447/31250000000000 binary64))) < 1.9999999999999999e159 or 9.99999999999999953e270 < (/.f64 (*.f64 y (+.f64 (*.f64 (+.f64 (*.f64 z #s(literal 692910599291889/10000000000000000 binary64)) #s(literal 307332350656623/625000000000000 binary64)) z) #s(literal 11167812716741/40000000000000 binary64))) (+.f64 (*.f64 (+.f64 z #s(literal 6012459259764103/1000000000000000 binary64)) z) #s(literal 104698244219447/31250000000000 binary64)))

      1. Initial program 61.9%

        \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
      2. Add Preprocessing
      3. Taylor expanded in z around inf

        \[\leadsto \color{blue}{x + \frac{692910599291889}{10000000000000000} \cdot y} \]
      4. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \color{blue}{\frac{692910599291889}{10000000000000000} \cdot y + x} \]
        2. lower-fma.f6489.9

          \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]
      5. Applied rewrites89.9%

        \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]

      if -inf.0 < (/.f64 (*.f64 y (+.f64 (*.f64 (+.f64 (*.f64 z #s(literal 692910599291889/10000000000000000 binary64)) #s(literal 307332350656623/625000000000000 binary64)) z) #s(literal 11167812716741/40000000000000 binary64))) (+.f64 (*.f64 (+.f64 z #s(literal 6012459259764103/1000000000000000 binary64)) z) #s(literal 104698244219447/31250000000000 binary64))) < -1.00000000000000002e64 or 1.9999999999999999e159 < (/.f64 (*.f64 y (+.f64 (*.f64 (+.f64 (*.f64 z #s(literal 692910599291889/10000000000000000 binary64)) #s(literal 307332350656623/625000000000000 binary64)) z) #s(literal 11167812716741/40000000000000 binary64))) (+.f64 (*.f64 (+.f64 z #s(literal 6012459259764103/1000000000000000 binary64)) z) #s(literal 104698244219447/31250000000000 binary64))) < 9.99999999999999953e270

      1. Initial program 99.4%

        \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
      2. Add Preprocessing
      3. Taylor expanded in z around 0

        \[\leadsto \color{blue}{x + \frac{279195317918525}{3350343815022304} \cdot y} \]
      4. Step-by-step derivation
        1. +-commutativeN/A

          \[\leadsto \color{blue}{\frac{279195317918525}{3350343815022304} \cdot y + x} \]
        2. lower-fma.f6489.7

          \[\leadsto \color{blue}{\mathsf{fma}\left(0.08333333333333323, y, x\right)} \]
      5. Applied rewrites89.7%

        \[\leadsto \color{blue}{\mathsf{fma}\left(0.08333333333333323, y, x\right)} \]
      6. Taylor expanded in x around 0

        \[\leadsto \frac{279195317918525}{3350343815022304} \cdot \color{blue}{y} \]
      7. Step-by-step derivation
        1. Applied rewrites79.2%

          \[\leadsto 0.08333333333333323 \cdot \color{blue}{y} \]
      8. Recombined 2 regimes into one program.
      9. Final simplification87.5%

        \[\leadsto \begin{array}{l} \mathbf{if}\;\frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \leq -\infty \lor \neg \left(\frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \leq -1 \cdot 10^{+64} \lor \neg \left(\frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \leq 2 \cdot 10^{+159} \lor \neg \left(\frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \leq 10^{+271}\right)\right)\right):\\ \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;0.08333333333333323 \cdot y\\ \end{array} \]
      10. Add Preprocessing

      Alternative 3: 99.5% accurate, 1.0× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -4 \lor \neg \left(z \leq 3.75\right):\\ \;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.07852944389170011, z, -0.10095235035524991\right), z, 0.39999999996247915\right), z, 12.000000000000014\right)}\\ \end{array} \end{array} \]
      (FPCore (x y z)
       :precision binary64
       (if (or (<= z -4.0) (not (<= z 3.75)))
         (+ x (/ y (- 14.431876219268936 (/ 15.646356830292042 z))))
         (+
          x
          (/
           y
           (fma
            (fma
             (fma 0.07852944389170011 z -0.10095235035524991)
             z
             0.39999999996247915)
            z
            12.000000000000014)))))
      double code(double x, double y, double z) {
      	double tmp;
      	if ((z <= -4.0) || !(z <= 3.75)) {
      		tmp = x + (y / (14.431876219268936 - (15.646356830292042 / z)));
      	} else {
      		tmp = x + (y / fma(fma(fma(0.07852944389170011, z, -0.10095235035524991), z, 0.39999999996247915), z, 12.000000000000014));
      	}
      	return tmp;
      }
      
      function code(x, y, z)
      	tmp = 0.0
      	if ((z <= -4.0) || !(z <= 3.75))
      		tmp = Float64(x + Float64(y / Float64(14.431876219268936 - Float64(15.646356830292042 / z))));
      	else
      		tmp = Float64(x + Float64(y / fma(fma(fma(0.07852944389170011, z, -0.10095235035524991), z, 0.39999999996247915), z, 12.000000000000014)));
      	end
      	return tmp
      end
      
      code[x_, y_, z_] := If[Or[LessEqual[z, -4.0], N[Not[LessEqual[z, 3.75]], $MachinePrecision]], N[(x + N[(y / N[(14.431876219268936 - N[(15.646356830292042 / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(y / N[(N[(N[(0.07852944389170011 * z + -0.10095235035524991), $MachinePrecision] * z + 0.39999999996247915), $MachinePrecision] * z + 12.000000000000014), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;z \leq -4 \lor \neg \left(z \leq 3.75\right):\\
      \;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\
      
      \mathbf{else}:\\
      \;\;\;\;x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.07852944389170011, z, -0.10095235035524991\right), z, 0.39999999996247915\right), z, 12.000000000000014\right)}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if z < -4 or 3.75 < z

        1. Initial program 41.1%

          \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          2. lift-*.f64N/A

            \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
          3. associate-/l*N/A

            \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          4. clear-numN/A

            \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          5. un-div-invN/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          6. lower-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          7. lower-/.f6451.4

            \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
          8. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          9. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          10. lower-fma.f6451.4

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          11. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          12. +-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          13. lower-+.f6451.4

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          14. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          15. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
          16. lower-fma.f6451.4

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
          17. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          18. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          19. *-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          20. lower-fma.f6451.4

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
        4. Applied rewrites51.4%

          \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
        5. Taylor expanded in z around inf

          \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889} - \frac{2504069538682520235663395798110}{160041699537014921582740396107} \cdot \frac{1}{z}}} \]
        6. Step-by-step derivation
          1. lower--.f64N/A

            \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889} - \frac{2504069538682520235663395798110}{160041699537014921582740396107} \cdot \frac{1}{z}}} \]
          2. associate-*r/N/A

            \[\leadsto x + \frac{y}{\frac{10000000000000000}{692910599291889} - \color{blue}{\frac{\frac{2504069538682520235663395798110}{160041699537014921582740396107} \cdot 1}{z}}} \]
          3. metadata-evalN/A

            \[\leadsto x + \frac{y}{\frac{10000000000000000}{692910599291889} - \frac{\color{blue}{\frac{2504069538682520235663395798110}{160041699537014921582740396107}}}{z}} \]
          4. lower-/.f6499.3

            \[\leadsto x + \frac{y}{14.431876219268936 - \color{blue}{\frac{15.646356830292042}{z}}} \]
        7. Applied rewrites99.3%

          \[\leadsto x + \frac{y}{\color{blue}{14.431876219268936 - \frac{15.646356830292042}{z}}} \]

        if -4 < z < 3.75

        1. Initial program 99.7%

          \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          2. lift-*.f64N/A

            \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
          3. associate-/l*N/A

            \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          4. clear-numN/A

            \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          5. un-div-invN/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          6. lower-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          7. lower-/.f6499.2

            \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
          8. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          9. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          10. lower-fma.f6499.2

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          11. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          12. +-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          13. lower-+.f6499.2

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          14. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          15. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
          16. lower-fma.f6499.2

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
          17. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          18. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          19. *-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          20. lower-fma.f6499.2

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
        4. Applied rewrites99.2%

          \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
        5. Taylor expanded in z around 0

          \[\leadsto x + \frac{y}{\color{blue}{\frac{3350343815022304}{279195317918525} + z \cdot \left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + z \cdot \left(\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z - \frac{54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}\right)\right)}} \]
        6. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto x + \frac{y}{\color{blue}{z \cdot \left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + z \cdot \left(\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z - \frac{54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}\right)\right) + \frac{3350343815022304}{279195317918525}}} \]
          2. *-commutativeN/A

            \[\leadsto x + \frac{y}{\color{blue}{\left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + z \cdot \left(\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z - \frac{54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}\right)\right) \cdot z} + \frac{3350343815022304}{279195317918525}} \]
          3. lower-fma.f64N/A

            \[\leadsto x + \frac{y}{\color{blue}{\mathsf{fma}\left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + z \cdot \left(\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z - \frac{54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}\right), z, \frac{3350343815022304}{279195317918525}\right)}} \]
          4. +-commutativeN/A

            \[\leadsto x + \frac{y}{\mathsf{fma}\left(\color{blue}{z \cdot \left(\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z - \frac{54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}\right) + \frac{155900051080628738716045985239}{389750127738131234692690878125}}, z, \frac{3350343815022304}{279195317918525}\right)} \]
          5. *-commutativeN/A

            \[\leadsto x + \frac{y}{\mathsf{fma}\left(\color{blue}{\left(\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z - \frac{54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}\right) \cdot z} + \frac{155900051080628738716045985239}{389750127738131234692690878125}, z, \frac{3350343815022304}{279195317918525}\right)} \]
          6. lower-fma.f64N/A

            \[\leadsto x + \frac{y}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z - \frac{54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}, z, \frac{155900051080628738716045985239}{389750127738131234692690878125}\right)}, z, \frac{3350343815022304}{279195317918525}\right)} \]
          7. sub-negN/A

            \[\leadsto x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z + \left(\mathsf{neg}\left(\frac{54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}\right)\right)}, z, \frac{155900051080628738716045985239}{389750127738131234692690878125}\right), z, \frac{3350343815022304}{279195317918525}\right)} \]
          8. metadata-evalN/A

            \[\leadsto x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(\frac{119290279017840661005388637518195067609906756376454090785993}{1519051620718896144731238710708768455317203651375836035156250} \cdot z + \color{blue}{\frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125}}, z, \frac{155900051080628738716045985239}{389750127738131234692690878125}\right), z, \frac{3350343815022304}{279195317918525}\right)} \]
          9. lower-fma.f6499.6

            \[\leadsto x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.07852944389170011, z, -0.10095235035524991\right)}, z, 0.39999999996247915\right), z, 12.000000000000014\right)} \]
        7. Applied rewrites99.6%

          \[\leadsto x + \frac{y}{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.07852944389170011, z, -0.10095235035524991\right), z, 0.39999999996247915\right), z, 12.000000000000014\right)}} \]
      3. Recombined 2 regimes into one program.
      4. Final simplification99.4%

        \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -4 \lor \neg \left(z \leq 3.75\right):\\ \;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(\mathsf{fma}\left(0.07852944389170011, z, -0.10095235035524991\right), z, 0.39999999996247915\right), z, 12.000000000000014\right)}\\ \end{array} \]
      5. Add Preprocessing

      Alternative 4: 99.5% accurate, 1.1× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5.2\right):\\ \;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right), z, 12.000000000000014\right)}\\ \end{array} \end{array} \]
      (FPCore (x y z)
       :precision binary64
       (if (or (<= z -5.4) (not (<= z 5.2)))
         (+ x (/ y (- 14.431876219268936 (/ 15.646356830292042 z))))
         (+
          x
          (/
           y
           (fma
            (fma -0.10095235035524991 z 0.39999999996247915)
            z
            12.000000000000014)))))
      double code(double x, double y, double z) {
      	double tmp;
      	if ((z <= -5.4) || !(z <= 5.2)) {
      		tmp = x + (y / (14.431876219268936 - (15.646356830292042 / z)));
      	} else {
      		tmp = x + (y / fma(fma(-0.10095235035524991, z, 0.39999999996247915), z, 12.000000000000014));
      	}
      	return tmp;
      }
      
      function code(x, y, z)
      	tmp = 0.0
      	if ((z <= -5.4) || !(z <= 5.2))
      		tmp = Float64(x + Float64(y / Float64(14.431876219268936 - Float64(15.646356830292042 / z))));
      	else
      		tmp = Float64(x + Float64(y / fma(fma(-0.10095235035524991, z, 0.39999999996247915), z, 12.000000000000014)));
      	end
      	return tmp
      end
      
      code[x_, y_, z_] := If[Or[LessEqual[z, -5.4], N[Not[LessEqual[z, 5.2]], $MachinePrecision]], N[(x + N[(y / N[(14.431876219268936 - N[(15.646356830292042 / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(y / N[(N[(-0.10095235035524991 * z + 0.39999999996247915), $MachinePrecision] * z + 12.000000000000014), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5.2\right):\\
      \;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\
      
      \mathbf{else}:\\
      \;\;\;\;x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right), z, 12.000000000000014\right)}\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 2 regimes
      2. if z < -5.4000000000000004 or 5.20000000000000018 < z

        1. Initial program 41.1%

          \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          2. lift-*.f64N/A

            \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
          3. associate-/l*N/A

            \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          4. clear-numN/A

            \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          5. un-div-invN/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          6. lower-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          7. lower-/.f6451.4

            \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
          8. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          9. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          10. lower-fma.f6451.4

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          11. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          12. +-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          13. lower-+.f6451.4

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          14. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          15. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
          16. lower-fma.f6451.4

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
          17. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          18. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          19. *-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          20. lower-fma.f6451.4

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
        4. Applied rewrites51.4%

          \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
        5. Taylor expanded in z around inf

          \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889} - \frac{2504069538682520235663395798110}{160041699537014921582740396107} \cdot \frac{1}{z}}} \]
        6. Step-by-step derivation
          1. lower--.f64N/A

            \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889} - \frac{2504069538682520235663395798110}{160041699537014921582740396107} \cdot \frac{1}{z}}} \]
          2. associate-*r/N/A

            \[\leadsto x + \frac{y}{\frac{10000000000000000}{692910599291889} - \color{blue}{\frac{\frac{2504069538682520235663395798110}{160041699537014921582740396107} \cdot 1}{z}}} \]
          3. metadata-evalN/A

            \[\leadsto x + \frac{y}{\frac{10000000000000000}{692910599291889} - \frac{\color{blue}{\frac{2504069538682520235663395798110}{160041699537014921582740396107}}}{z}} \]
          4. lower-/.f6499.3

            \[\leadsto x + \frac{y}{14.431876219268936 - \color{blue}{\frac{15.646356830292042}{z}}} \]
        7. Applied rewrites99.3%

          \[\leadsto x + \frac{y}{\color{blue}{14.431876219268936 - \frac{15.646356830292042}{z}}} \]

        if -5.4000000000000004 < z < 5.20000000000000018

        1. Initial program 99.7%

          \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          2. lift-*.f64N/A

            \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
          3. associate-/l*N/A

            \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          4. clear-numN/A

            \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          5. un-div-invN/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          6. lower-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          7. lower-/.f6499.2

            \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
          8. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          9. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          10. lower-fma.f6499.2

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          11. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          12. +-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          13. lower-+.f6499.2

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          14. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          15. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
          16. lower-fma.f6499.2

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
          17. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          18. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          19. *-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          20. lower-fma.f6499.2

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
        4. Applied rewrites99.2%

          \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
        5. Taylor expanded in z around 0

          \[\leadsto x + \frac{y}{\color{blue}{\frac{3350343815022304}{279195317918525} + z \cdot \left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + \frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z\right)}} \]
        6. Step-by-step derivation
          1. +-commutativeN/A

            \[\leadsto x + \frac{y}{\color{blue}{z \cdot \left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + \frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z\right) + \frac{3350343815022304}{279195317918525}}} \]
          2. *-commutativeN/A

            \[\leadsto x + \frac{y}{\color{blue}{\left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + \frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z\right) \cdot z} + \frac{3350343815022304}{279195317918525}} \]
          3. lower-fma.f64N/A

            \[\leadsto x + \frac{y}{\color{blue}{\mathsf{fma}\left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + \frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z, z, \frac{3350343815022304}{279195317918525}\right)}} \]
          4. +-commutativeN/A

            \[\leadsto x + \frac{y}{\mathsf{fma}\left(\color{blue}{\frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z + \frac{155900051080628738716045985239}{389750127738131234692690878125}}, z, \frac{3350343815022304}{279195317918525}\right)} \]
          5. lower-fma.f6499.5

            \[\leadsto x + \frac{y}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right)}, z, 12.000000000000014\right)} \]
        7. Applied rewrites99.5%

          \[\leadsto x + \frac{y}{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right), z, 12.000000000000014\right)}} \]
      3. Recombined 2 regimes into one program.
      4. Final simplification99.4%

        \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5.2\right):\\ \;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right), z, 12.000000000000014\right)}\\ \end{array} \]
      5. Add Preprocessing

      Alternative 5: 99.4% accurate, 1.2× speedup?

      \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.4:\\ \;\;\;\;x + \frac{y}{14.431876219268936}\\ \mathbf{elif}\;z \leq 4.6:\\ \;\;\;\;x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right), z, 12.000000000000014\right)}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(y, 0.0692910599291889 - \frac{-0.07512208616047561}{z}, x\right)\\ \end{array} \end{array} \]
      (FPCore (x y z)
       :precision binary64
       (if (<= z -5.4)
         (+ x (/ y 14.431876219268936))
         (if (<= z 4.6)
           (+
            x
            (/
             y
             (fma
              (fma -0.10095235035524991 z 0.39999999996247915)
              z
              12.000000000000014)))
           (fma y (- 0.0692910599291889 (/ -0.07512208616047561 z)) x))))
      double code(double x, double y, double z) {
      	double tmp;
      	if (z <= -5.4) {
      		tmp = x + (y / 14.431876219268936);
      	} else if (z <= 4.6) {
      		tmp = x + (y / fma(fma(-0.10095235035524991, z, 0.39999999996247915), z, 12.000000000000014));
      	} else {
      		tmp = fma(y, (0.0692910599291889 - (-0.07512208616047561 / z)), x);
      	}
      	return tmp;
      }
      
      function code(x, y, z)
      	tmp = 0.0
      	if (z <= -5.4)
      		tmp = Float64(x + Float64(y / 14.431876219268936));
      	elseif (z <= 4.6)
      		tmp = Float64(x + Float64(y / fma(fma(-0.10095235035524991, z, 0.39999999996247915), z, 12.000000000000014)));
      	else
      		tmp = fma(y, Float64(0.0692910599291889 - Float64(-0.07512208616047561 / z)), x);
      	end
      	return tmp
      end
      
      code[x_, y_, z_] := If[LessEqual[z, -5.4], N[(x + N[(y / 14.431876219268936), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.6], N[(x + N[(y / N[(N[(-0.10095235035524991 * z + 0.39999999996247915), $MachinePrecision] * z + 12.000000000000014), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y * N[(0.0692910599291889 - N[(-0.07512208616047561 / z), $MachinePrecision]), $MachinePrecision] + x), $MachinePrecision]]]
      
      \begin{array}{l}
      
      \\
      \begin{array}{l}
      \mathbf{if}\;z \leq -5.4:\\
      \;\;\;\;x + \frac{y}{14.431876219268936}\\
      
      \mathbf{elif}\;z \leq 4.6:\\
      \;\;\;\;x + \frac{y}{\mathsf{fma}\left(\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right), z, 12.000000000000014\right)}\\
      
      \mathbf{else}:\\
      \;\;\;\;\mathsf{fma}\left(y, 0.0692910599291889 - \frac{-0.07512208616047561}{z}, x\right)\\
      
      
      \end{array}
      \end{array}
      
      Derivation
      1. Split input into 3 regimes
      2. if z < -5.4000000000000004

        1. Initial program 45.1%

          \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
        2. Add Preprocessing
        3. Step-by-step derivation
          1. lift-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          2. lift-*.f64N/A

            \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
          3. associate-/l*N/A

            \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
          4. clear-numN/A

            \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          5. un-div-invN/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          6. lower-/.f64N/A

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          7. lower-/.f6455.3

            \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
          8. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          9. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          10. lower-fma.f6455.3

            \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          11. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          12. +-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
          13. lower-+.f6455.3

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
          14. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
          15. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
          16. lower-fma.f6455.3

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
          17. lift-+.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          18. lift-*.f64N/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          19. *-commutativeN/A

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
          20. lower-fma.f6455.3

            \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
        4. Applied rewrites55.3%

          \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
        5. Taylor expanded in z around inf

          \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889}}} \]
        6. Step-by-step derivation
          1. Applied rewrites98.4%

            \[\leadsto x + \frac{y}{\color{blue}{14.431876219268936}} \]

          if -5.4000000000000004 < z < 4.5999999999999996

          1. Initial program 99.7%

            \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-/.f64N/A

              \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
            2. lift-*.f64N/A

              \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
            3. associate-/l*N/A

              \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
            4. clear-numN/A

              \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
            5. un-div-invN/A

              \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
            6. lower-/.f64N/A

              \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
            7. lower-/.f6499.2

              \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
            8. lift-+.f64N/A

              \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
            9. lift-*.f64N/A

              \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
            10. lower-fma.f6499.2

              \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
            11. lift-+.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
            12. +-commutativeN/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
            13. lower-+.f6499.2

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
            14. lift-+.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
            15. lift-*.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
            16. lower-fma.f6499.2

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
            17. lift-+.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
            18. lift-*.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
            19. *-commutativeN/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
            20. lower-fma.f6499.2

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
          4. Applied rewrites99.2%

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
          5. Taylor expanded in z around 0

            \[\leadsto x + \frac{y}{\color{blue}{\frac{3350343815022304}{279195317918525} + z \cdot \left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + \frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z\right)}} \]
          6. Step-by-step derivation
            1. +-commutativeN/A

              \[\leadsto x + \frac{y}{\color{blue}{z \cdot \left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + \frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z\right) + \frac{3350343815022304}{279195317918525}}} \]
            2. *-commutativeN/A

              \[\leadsto x + \frac{y}{\color{blue}{\left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + \frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z\right) \cdot z} + \frac{3350343815022304}{279195317918525}} \]
            3. lower-fma.f64N/A

              \[\leadsto x + \frac{y}{\color{blue}{\mathsf{fma}\left(\frac{155900051080628738716045985239}{389750127738131234692690878125} + \frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z, z, \frac{3350343815022304}{279195317918525}\right)}} \]
            4. +-commutativeN/A

              \[\leadsto x + \frac{y}{\mathsf{fma}\left(\color{blue}{\frac{-54926362148836417054593262229306108478309176}{544082054113166395691471098236108147273828125} \cdot z + \frac{155900051080628738716045985239}{389750127738131234692690878125}}, z, \frac{3350343815022304}{279195317918525}\right)} \]
            5. lower-fma.f6499.5

              \[\leadsto x + \frac{y}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right)}, z, 12.000000000000014\right)} \]
          7. Applied rewrites99.5%

            \[\leadsto x + \frac{y}{\color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(-0.10095235035524991, z, 0.39999999996247915\right), z, 12.000000000000014\right)}} \]

          if 4.5999999999999996 < z

          1. Initial program 38.2%

            \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
          2. Add Preprocessing
          3. Taylor expanded in z around inf

            \[\leadsto \color{blue}{\left(x + \left(\frac{692910599291889}{10000000000000000} \cdot y + \frac{307332350656623}{625000000000000} \cdot \frac{y}{z}\right)\right) - \frac{4166096748901211929300981260567}{10000000000000000000000000000000} \cdot \frac{y}{z}} \]
          4. Step-by-step derivation
            1. associate-+r+N/A

              \[\leadsto \color{blue}{\left(\left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{307332350656623}{625000000000000} \cdot \frac{y}{z}\right)} - \frac{4166096748901211929300981260567}{10000000000000000000000000000000} \cdot \frac{y}{z} \]
            2. associate--l+N/A

              \[\leadsto \color{blue}{\left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \left(\frac{307332350656623}{625000000000000} \cdot \frac{y}{z} - \frac{4166096748901211929300981260567}{10000000000000000000000000000000} \cdot \frac{y}{z}\right)} \]
            3. distribute-rgt-out--N/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \color{blue}{\frac{y}{z} \cdot \left(\frac{307332350656623}{625000000000000} - \frac{4166096748901211929300981260567}{10000000000000000000000000000000}\right)} \]
            4. metadata-evalN/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{y}{z} \cdot \color{blue}{\frac{751220861604756070699018739433}{10000000000000000000000000000000}} \]
            5. metadata-evalN/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{y}{z} \cdot \color{blue}{\frac{\frac{-751220861604756070699018739433}{10000000000000000000000000000000}}{-1}} \]
            6. metadata-evalN/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{y}{z} \cdot \frac{\color{blue}{\frac{-307332350656623}{625000000000000} - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000}}}{-1} \]
            7. times-fracN/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \color{blue}{\frac{y \cdot \left(\frac{-307332350656623}{625000000000000} - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000}\right)}{z \cdot -1}} \]
            8. distribute-rgt-out--N/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{\color{blue}{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}}{z \cdot -1} \]
            9. *-commutativeN/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{\color{blue}{-1 \cdot z}} \]
            10. mul-1-negN/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{\color{blue}{\mathsf{neg}\left(z\right)}} \]
            11. distribute-neg-frac2N/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \color{blue}{\left(\mathsf{neg}\left(\frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z}\right)\right)} \]
            12. mul-1-negN/A

              \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \color{blue}{-1 \cdot \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z}} \]
            13. associate-+r+N/A

              \[\leadsto \color{blue}{x + \left(\frac{692910599291889}{10000000000000000} \cdot y + -1 \cdot \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z}\right)} \]
            14. +-commutativeN/A

              \[\leadsto x + \color{blue}{\left(-1 \cdot \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z} + \frac{692910599291889}{10000000000000000} \cdot y\right)} \]
            15. +-commutativeN/A

              \[\leadsto \color{blue}{\left(-1 \cdot \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z} + \frac{692910599291889}{10000000000000000} \cdot y\right) + x} \]
          5. Applied rewrites99.6%

            \[\leadsto \color{blue}{\mathsf{fma}\left(y, 0.0692910599291889 - \frac{-0.07512208616047561}{z}, x\right)} \]
        7. Recombined 3 regimes into one program.
        8. Add Preprocessing

        Alternative 6: 99.3% accurate, 1.4× speedup?

        \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.4:\\ \;\;\;\;x + \frac{y}{14.431876219268936}\\ \mathbf{elif}\;z \leq 4.9:\\ \;\;\;\;\mathsf{fma}\left(-0.00277777777751721 \cdot y, z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(y, 0.0692910599291889 - \frac{-0.07512208616047561}{z}, x\right)\\ \end{array} \end{array} \]
        (FPCore (x y z)
         :precision binary64
         (if (<= z -5.4)
           (+ x (/ y 14.431876219268936))
           (if (<= z 4.9)
             (fma (* -0.00277777777751721 y) z (fma 0.08333333333333323 y x))
             (fma y (- 0.0692910599291889 (/ -0.07512208616047561 z)) x))))
        double code(double x, double y, double z) {
        	double tmp;
        	if (z <= -5.4) {
        		tmp = x + (y / 14.431876219268936);
        	} else if (z <= 4.9) {
        		tmp = fma((-0.00277777777751721 * y), z, fma(0.08333333333333323, y, x));
        	} else {
        		tmp = fma(y, (0.0692910599291889 - (-0.07512208616047561 / z)), x);
        	}
        	return tmp;
        }
        
        function code(x, y, z)
        	tmp = 0.0
        	if (z <= -5.4)
        		tmp = Float64(x + Float64(y / 14.431876219268936));
        	elseif (z <= 4.9)
        		tmp = fma(Float64(-0.00277777777751721 * y), z, fma(0.08333333333333323, y, x));
        	else
        		tmp = fma(y, Float64(0.0692910599291889 - Float64(-0.07512208616047561 / z)), x);
        	end
        	return tmp
        end
        
        code[x_, y_, z_] := If[LessEqual[z, -5.4], N[(x + N[(y / 14.431876219268936), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.9], N[(N[(-0.00277777777751721 * y), $MachinePrecision] * z + N[(0.08333333333333323 * y + x), $MachinePrecision]), $MachinePrecision], N[(y * N[(0.0692910599291889 - N[(-0.07512208616047561 / z), $MachinePrecision]), $MachinePrecision] + x), $MachinePrecision]]]
        
        \begin{array}{l}
        
        \\
        \begin{array}{l}
        \mathbf{if}\;z \leq -5.4:\\
        \;\;\;\;x + \frac{y}{14.431876219268936}\\
        
        \mathbf{elif}\;z \leq 4.9:\\
        \;\;\;\;\mathsf{fma}\left(-0.00277777777751721 \cdot y, z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right)\\
        
        \mathbf{else}:\\
        \;\;\;\;\mathsf{fma}\left(y, 0.0692910599291889 - \frac{-0.07512208616047561}{z}, x\right)\\
        
        
        \end{array}
        \end{array}
        
        Derivation
        1. Split input into 3 regimes
        2. if z < -5.4000000000000004

          1. Initial program 45.1%

            \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
          2. Add Preprocessing
          3. Step-by-step derivation
            1. lift-/.f64N/A

              \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
            2. lift-*.f64N/A

              \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
            3. associate-/l*N/A

              \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
            4. clear-numN/A

              \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
            5. un-div-invN/A

              \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
            6. lower-/.f64N/A

              \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
            7. lower-/.f6455.3

              \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
            8. lift-+.f64N/A

              \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
            9. lift-*.f64N/A

              \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
            10. lower-fma.f6455.3

              \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
            11. lift-+.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
            12. +-commutativeN/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
            13. lower-+.f6455.3

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
            14. lift-+.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
            15. lift-*.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
            16. lower-fma.f6455.3

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
            17. lift-+.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
            18. lift-*.f64N/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
            19. *-commutativeN/A

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
            20. lower-fma.f6455.3

              \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
          4. Applied rewrites55.3%

            \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
          5. Taylor expanded in z around inf

            \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889}}} \]
          6. Step-by-step derivation
            1. Applied rewrites98.4%

              \[\leadsto x + \frac{y}{\color{blue}{14.431876219268936}} \]

            if -5.4000000000000004 < z < 4.9000000000000004

            1. Initial program 99.7%

              \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
            2. Add Preprocessing
            3. Taylor expanded in z around 0

              \[\leadsto \color{blue}{x + \left(\frac{279195317918525}{3350343815022304} \cdot y + z \cdot \left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)} \]
            4. Step-by-step derivation
              1. associate-+r+N/A

                \[\leadsto \color{blue}{\left(x + \frac{279195317918525}{3350343815022304} \cdot y\right) + z \cdot \left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)} \]
              2. +-commutativeN/A

                \[\leadsto \color{blue}{z \cdot \left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right) + \left(x + \frac{279195317918525}{3350343815022304} \cdot y\right)} \]
              3. *-commutativeN/A

                \[\leadsto \color{blue}{\left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right) \cdot z} + \left(x + \frac{279195317918525}{3350343815022304} \cdot y\right) \]
              4. lower-fma.f64N/A

                \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y, z, x + \frac{279195317918525}{3350343815022304} \cdot y\right)} \]
            5. Applied rewrites99.4%

              \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(-0.00277777777751721, y, \left(y \cdot 0.0007936505811533442\right) \cdot z\right), z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right)} \]
            6. Taylor expanded in z around 0

              \[\leadsto \mathsf{fma}\left(\frac{-155900051080628738716045985239}{56124018394291031809500087342080} \cdot y, z, \mathsf{fma}\left(\frac{279195317918525}{3350343815022304}, y, x\right)\right) \]
            7. Step-by-step derivation
              1. Applied rewrites99.4%

                \[\leadsto \mathsf{fma}\left(-0.00277777777751721 \cdot y, z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right) \]

              if 4.9000000000000004 < z

              1. Initial program 38.2%

                \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
              2. Add Preprocessing
              3. Taylor expanded in z around inf

                \[\leadsto \color{blue}{\left(x + \left(\frac{692910599291889}{10000000000000000} \cdot y + \frac{307332350656623}{625000000000000} \cdot \frac{y}{z}\right)\right) - \frac{4166096748901211929300981260567}{10000000000000000000000000000000} \cdot \frac{y}{z}} \]
              4. Step-by-step derivation
                1. associate-+r+N/A

                  \[\leadsto \color{blue}{\left(\left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{307332350656623}{625000000000000} \cdot \frac{y}{z}\right)} - \frac{4166096748901211929300981260567}{10000000000000000000000000000000} \cdot \frac{y}{z} \]
                2. associate--l+N/A

                  \[\leadsto \color{blue}{\left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \left(\frac{307332350656623}{625000000000000} \cdot \frac{y}{z} - \frac{4166096748901211929300981260567}{10000000000000000000000000000000} \cdot \frac{y}{z}\right)} \]
                3. distribute-rgt-out--N/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \color{blue}{\frac{y}{z} \cdot \left(\frac{307332350656623}{625000000000000} - \frac{4166096748901211929300981260567}{10000000000000000000000000000000}\right)} \]
                4. metadata-evalN/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{y}{z} \cdot \color{blue}{\frac{751220861604756070699018739433}{10000000000000000000000000000000}} \]
                5. metadata-evalN/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{y}{z} \cdot \color{blue}{\frac{\frac{-751220861604756070699018739433}{10000000000000000000000000000000}}{-1}} \]
                6. metadata-evalN/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{y}{z} \cdot \frac{\color{blue}{\frac{-307332350656623}{625000000000000} - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000}}}{-1} \]
                7. times-fracN/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \color{blue}{\frac{y \cdot \left(\frac{-307332350656623}{625000000000000} - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000}\right)}{z \cdot -1}} \]
                8. distribute-rgt-out--N/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{\color{blue}{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}}{z \cdot -1} \]
                9. *-commutativeN/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{\color{blue}{-1 \cdot z}} \]
                10. mul-1-negN/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{\color{blue}{\mathsf{neg}\left(z\right)}} \]
                11. distribute-neg-frac2N/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \color{blue}{\left(\mathsf{neg}\left(\frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z}\right)\right)} \]
                12. mul-1-negN/A

                  \[\leadsto \left(x + \frac{692910599291889}{10000000000000000} \cdot y\right) + \color{blue}{-1 \cdot \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z}} \]
                13. associate-+r+N/A

                  \[\leadsto \color{blue}{x + \left(\frac{692910599291889}{10000000000000000} \cdot y + -1 \cdot \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z}\right)} \]
                14. +-commutativeN/A

                  \[\leadsto x + \color{blue}{\left(-1 \cdot \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z} + \frac{692910599291889}{10000000000000000} \cdot y\right)} \]
                15. +-commutativeN/A

                  \[\leadsto \color{blue}{\left(-1 \cdot \frac{\frac{-307332350656623}{625000000000000} \cdot y - \frac{-4166096748901211929300981260567}{10000000000000000000000000000000} \cdot y}{z} + \frac{692910599291889}{10000000000000000} \cdot y\right) + x} \]
              5. Applied rewrites99.6%

                \[\leadsto \color{blue}{\mathsf{fma}\left(y, 0.0692910599291889 - \frac{-0.07512208616047561}{z}, x\right)} \]
            8. Recombined 3 regimes into one program.
            9. Add Preprocessing

            Alternative 7: 99.2% accurate, 1.6× speedup?

            \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\ \;\;\;\;x + \frac{y}{14.431876219268936}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-0.00277777777751721 \cdot y, z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right)\\ \end{array} \end{array} \]
            (FPCore (x y z)
             :precision binary64
             (if (or (<= z -5.4) (not (<= z 5.0)))
               (+ x (/ y 14.431876219268936))
               (fma (* -0.00277777777751721 y) z (fma 0.08333333333333323 y x))))
            double code(double x, double y, double z) {
            	double tmp;
            	if ((z <= -5.4) || !(z <= 5.0)) {
            		tmp = x + (y / 14.431876219268936);
            	} else {
            		tmp = fma((-0.00277777777751721 * y), z, fma(0.08333333333333323, y, x));
            	}
            	return tmp;
            }
            
            function code(x, y, z)
            	tmp = 0.0
            	if ((z <= -5.4) || !(z <= 5.0))
            		tmp = Float64(x + Float64(y / 14.431876219268936));
            	else
            		tmp = fma(Float64(-0.00277777777751721 * y), z, fma(0.08333333333333323, y, x));
            	end
            	return tmp
            end
            
            code[x_, y_, z_] := If[Or[LessEqual[z, -5.4], N[Not[LessEqual[z, 5.0]], $MachinePrecision]], N[(x + N[(y / 14.431876219268936), $MachinePrecision]), $MachinePrecision], N[(N[(-0.00277777777751721 * y), $MachinePrecision] * z + N[(0.08333333333333323 * y + x), $MachinePrecision]), $MachinePrecision]]
            
            \begin{array}{l}
            
            \\
            \begin{array}{l}
            \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\
            \;\;\;\;x + \frac{y}{14.431876219268936}\\
            
            \mathbf{else}:\\
            \;\;\;\;\mathsf{fma}\left(-0.00277777777751721 \cdot y, z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right)\\
            
            
            \end{array}
            \end{array}
            
            Derivation
            1. Split input into 2 regimes
            2. if z < -5.4000000000000004 or 5 < z

              1. Initial program 41.1%

                \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
              2. Add Preprocessing
              3. Step-by-step derivation
                1. lift-/.f64N/A

                  \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
                2. lift-*.f64N/A

                  \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
                3. associate-/l*N/A

                  \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
                4. clear-numN/A

                  \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
                5. un-div-invN/A

                  \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
                6. lower-/.f64N/A

                  \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
                7. lower-/.f6451.4

                  \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
                8. lift-+.f64N/A

                  \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
                9. lift-*.f64N/A

                  \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
                10. lower-fma.f6451.4

                  \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
                11. lift-+.f64N/A

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
                12. +-commutativeN/A

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
                13. lower-+.f6451.4

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
                14. lift-+.f64N/A

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
                15. lift-*.f64N/A

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
                16. lower-fma.f6451.4

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
                17. lift-+.f64N/A

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
                18. lift-*.f64N/A

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
                19. *-commutativeN/A

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
                20. lower-fma.f6451.4

                  \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
              4. Applied rewrites51.4%

                \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
              5. Taylor expanded in z around inf

                \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889}}} \]
              6. Step-by-step derivation
                1. Applied rewrites99.1%

                  \[\leadsto x + \frac{y}{\color{blue}{14.431876219268936}} \]

                if -5.4000000000000004 < z < 5

                1. Initial program 99.7%

                  \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                2. Add Preprocessing
                3. Taylor expanded in z around 0

                  \[\leadsto \color{blue}{x + \left(\frac{279195317918525}{3350343815022304} \cdot y + z \cdot \left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)} \]
                4. Step-by-step derivation
                  1. associate-+r+N/A

                    \[\leadsto \color{blue}{\left(x + \frac{279195317918525}{3350343815022304} \cdot y\right) + z \cdot \left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)} \]
                  2. +-commutativeN/A

                    \[\leadsto \color{blue}{z \cdot \left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right) + \left(x + \frac{279195317918525}{3350343815022304} \cdot y\right)} \]
                  3. *-commutativeN/A

                    \[\leadsto \color{blue}{\left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right) \cdot z} + \left(x + \frac{279195317918525}{3350343815022304} \cdot y\right) \]
                  4. lower-fma.f64N/A

                    \[\leadsto \color{blue}{\mathsf{fma}\left(\left(\frac{307332350656623}{2093964884388940} \cdot y + z \cdot \left(\frac{692910599291889}{33503438150223040} \cdot y - \left(\frac{272651677654809570312500000}{10961722342634967150292985809} \cdot y + \frac{6012459259764103}{3350343815022304} \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)\right)\right) - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y, z, x + \frac{279195317918525}{3350343815022304} \cdot y\right)} \]
                5. Applied rewrites99.4%

                  \[\leadsto \color{blue}{\mathsf{fma}\left(\mathsf{fma}\left(-0.00277777777751721, y, \left(y \cdot 0.0007936505811533442\right) \cdot z\right), z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right)} \]
                6. Taylor expanded in z around 0

                  \[\leadsto \mathsf{fma}\left(\frac{-155900051080628738716045985239}{56124018394291031809500087342080} \cdot y, z, \mathsf{fma}\left(\frac{279195317918525}{3350343815022304}, y, x\right)\right) \]
                7. Step-by-step derivation
                  1. Applied rewrites99.4%

                    \[\leadsto \mathsf{fma}\left(-0.00277777777751721 \cdot y, z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right) \]
                8. Recombined 2 regimes into one program.
                9. Final simplification99.2%

                  \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\ \;\;\;\;x + \frac{y}{14.431876219268936}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(-0.00277777777751721 \cdot y, z, \mathsf{fma}\left(0.08333333333333323, y, x\right)\right)\\ \end{array} \]
                10. Add Preprocessing

                Alternative 8: 99.2% accurate, 1.7× speedup?

                \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\ \;\;\;\;x + \frac{y}{14.431876219268936}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(y, \mathsf{fma}\left(-0.00277777777751721, z, 0.08333333333333323\right), x\right)\\ \end{array} \end{array} \]
                (FPCore (x y z)
                 :precision binary64
                 (if (or (<= z -5.4) (not (<= z 5.0)))
                   (+ x (/ y 14.431876219268936))
                   (fma y (fma -0.00277777777751721 z 0.08333333333333323) x)))
                double code(double x, double y, double z) {
                	double tmp;
                	if ((z <= -5.4) || !(z <= 5.0)) {
                		tmp = x + (y / 14.431876219268936);
                	} else {
                		tmp = fma(y, fma(-0.00277777777751721, z, 0.08333333333333323), x);
                	}
                	return tmp;
                }
                
                function code(x, y, z)
                	tmp = 0.0
                	if ((z <= -5.4) || !(z <= 5.0))
                		tmp = Float64(x + Float64(y / 14.431876219268936));
                	else
                		tmp = fma(y, fma(-0.00277777777751721, z, 0.08333333333333323), x);
                	end
                	return tmp
                end
                
                code[x_, y_, z_] := If[Or[LessEqual[z, -5.4], N[Not[LessEqual[z, 5.0]], $MachinePrecision]], N[(x + N[(y / 14.431876219268936), $MachinePrecision]), $MachinePrecision], N[(y * N[(-0.00277777777751721 * z + 0.08333333333333323), $MachinePrecision] + x), $MachinePrecision]]
                
                \begin{array}{l}
                
                \\
                \begin{array}{l}
                \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\
                \;\;\;\;x + \frac{y}{14.431876219268936}\\
                
                \mathbf{else}:\\
                \;\;\;\;\mathsf{fma}\left(y, \mathsf{fma}\left(-0.00277777777751721, z, 0.08333333333333323\right), x\right)\\
                
                
                \end{array}
                \end{array}
                
                Derivation
                1. Split input into 2 regimes
                2. if z < -5.4000000000000004 or 5 < z

                  1. Initial program 41.1%

                    \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                  2. Add Preprocessing
                  3. Step-by-step derivation
                    1. lift-/.f64N/A

                      \[\leadsto x + \color{blue}{\frac{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
                    2. lift-*.f64N/A

                      \[\leadsto x + \frac{\color{blue}{y \cdot \left(\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}\right)}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}} \]
                    3. associate-/l*N/A

                      \[\leadsto x + \color{blue}{y \cdot \frac{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}} \]
                    4. clear-numN/A

                      \[\leadsto x + y \cdot \color{blue}{\frac{1}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
                    5. un-div-invN/A

                      \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
                    6. lower-/.f64N/A

                      \[\leadsto x + \color{blue}{\frac{y}{\frac{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
                    7. lower-/.f6451.4

                      \[\leadsto x + \frac{y}{\color{blue}{\frac{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}}} \]
                    8. lift-+.f64N/A

                      \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z + \frac{104698244219447}{31250000000000}}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
                    9. lift-*.f64N/A

                      \[\leadsto x + \frac{y}{\frac{\color{blue}{\left(z + \frac{6012459259764103}{1000000000000000}\right) \cdot z} + \frac{104698244219447}{31250000000000}}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
                    10. lower-fma.f6451.4

                      \[\leadsto x + \frac{y}{\frac{\color{blue}{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
                    11. lift-+.f64N/A

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{z + \frac{6012459259764103}{1000000000000000}}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
                    12. +-commutativeN/A

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{\frac{6012459259764103}{1000000000000000} + z}, z, \frac{104698244219447}{31250000000000}\right)}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}} \]
                    13. lower-+.f6451.4

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\color{blue}{6.012459259764103 + z}, z, 3.350343815022304\right)}{\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525}} \]
                    14. lift-+.f64N/A

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z + \frac{11167812716741}{40000000000000}}}} \]
                    15. lift-*.f64N/A

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\color{blue}{\left(z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}\right) \cdot z} + \frac{11167812716741}{40000000000000}}} \]
                    16. lower-fma.f6451.4

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\color{blue}{\mathsf{fma}\left(z \cdot 0.0692910599291889 + 0.4917317610505968, z, 0.279195317918525\right)}}} \]
                    17. lift-+.f64N/A

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000} + \frac{307332350656623}{625000000000000}}, z, \frac{11167812716741}{40000000000000}\right)}} \]
                    18. lift-*.f64N/A

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{z \cdot \frac{692910599291889}{10000000000000000}} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
                    19. *-commutativeN/A

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(\frac{6012459259764103}{1000000000000000} + z, z, \frac{104698244219447}{31250000000000}\right)}{\mathsf{fma}\left(\color{blue}{\frac{692910599291889}{10000000000000000} \cdot z} + \frac{307332350656623}{625000000000000}, z, \frac{11167812716741}{40000000000000}\right)}} \]
                    20. lower-fma.f6451.4

                      \[\leadsto x + \frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\color{blue}{\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right)}, z, 0.279195317918525\right)}} \]
                  4. Applied rewrites51.4%

                    \[\leadsto x + \color{blue}{\frac{y}{\frac{\mathsf{fma}\left(6.012459259764103 + z, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(0.0692910599291889, z, 0.4917317610505968\right), z, 0.279195317918525\right)}}} \]
                  5. Taylor expanded in z around inf

                    \[\leadsto x + \frac{y}{\color{blue}{\frac{10000000000000000}{692910599291889}}} \]
                  6. Step-by-step derivation
                    1. Applied rewrites99.1%

                      \[\leadsto x + \frac{y}{\color{blue}{14.431876219268936}} \]

                    if -5.4000000000000004 < z < 5

                    1. Initial program 99.7%

                      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                    2. Add Preprocessing
                    3. Taylor expanded in z around 0

                      \[\leadsto \color{blue}{x + \left(\frac{279195317918525}{3350343815022304} \cdot y + z \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)} \]
                    4. Step-by-step derivation
                      1. +-commutativeN/A

                        \[\leadsto \color{blue}{\left(\frac{279195317918525}{3350343815022304} \cdot y + z \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right) + x} \]
                      2. +-commutativeN/A

                        \[\leadsto \color{blue}{\left(z \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right) + \frac{279195317918525}{3350343815022304} \cdot y\right)} + x \]
                      3. *-commutativeN/A

                        \[\leadsto \left(\color{blue}{\left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right) \cdot z} + \frac{279195317918525}{3350343815022304} \cdot y\right) + x \]
                      4. distribute-rgt-out--N/A

                        \[\leadsto \left(\color{blue}{\left(y \cdot \left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right)\right)} \cdot z + \frac{279195317918525}{3350343815022304} \cdot y\right) + x \]
                      5. associate-*l*N/A

                        \[\leadsto \left(\color{blue}{y \cdot \left(\left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right) \cdot z\right)} + \frac{279195317918525}{3350343815022304} \cdot y\right) + x \]
                      6. *-commutativeN/A

                        \[\leadsto \left(y \cdot \left(\left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right) \cdot z\right) + \color{blue}{y \cdot \frac{279195317918525}{3350343815022304}}\right) + x \]
                      7. distribute-lft-outN/A

                        \[\leadsto \color{blue}{y \cdot \left(\left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right) \cdot z + \frac{279195317918525}{3350343815022304}\right)} + x \]
                      8. lower-fma.f64N/A

                        \[\leadsto \color{blue}{\mathsf{fma}\left(y, \left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right) \cdot z + \frac{279195317918525}{3350343815022304}, x\right)} \]
                      9. lower-fma.f64N/A

                        \[\leadsto \mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}, z, \frac{279195317918525}{3350343815022304}\right)}, x\right) \]
                      10. metadata-eval99.3

                        \[\leadsto \mathsf{fma}\left(y, \mathsf{fma}\left(\color{blue}{-0.00277777777751721}, z, 0.08333333333333323\right), x\right) \]
                    5. Applied rewrites99.3%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(y, \mathsf{fma}\left(-0.00277777777751721, z, 0.08333333333333323\right), x\right)} \]
                  7. Recombined 2 regimes into one program.
                  8. Final simplification99.2%

                    \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\ \;\;\;\;x + \frac{y}{14.431876219268936}\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(y, \mathsf{fma}\left(-0.00277777777751721, z, 0.08333333333333323\right), x\right)\\ \end{array} \]
                  9. Add Preprocessing

                  Alternative 9: 99.1% accurate, 1.9× speedup?

                  \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\ \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(y, \mathsf{fma}\left(-0.00277777777751721, z, 0.08333333333333323\right), x\right)\\ \end{array} \end{array} \]
                  (FPCore (x y z)
                   :precision binary64
                   (if (or (<= z -5.4) (not (<= z 5.0)))
                     (fma 0.0692910599291889 y x)
                     (fma y (fma -0.00277777777751721 z 0.08333333333333323) x)))
                  double code(double x, double y, double z) {
                  	double tmp;
                  	if ((z <= -5.4) || !(z <= 5.0)) {
                  		tmp = fma(0.0692910599291889, y, x);
                  	} else {
                  		tmp = fma(y, fma(-0.00277777777751721, z, 0.08333333333333323), x);
                  	}
                  	return tmp;
                  }
                  
                  function code(x, y, z)
                  	tmp = 0.0
                  	if ((z <= -5.4) || !(z <= 5.0))
                  		tmp = fma(0.0692910599291889, y, x);
                  	else
                  		tmp = fma(y, fma(-0.00277777777751721, z, 0.08333333333333323), x);
                  	end
                  	return tmp
                  end
                  
                  code[x_, y_, z_] := If[Or[LessEqual[z, -5.4], N[Not[LessEqual[z, 5.0]], $MachinePrecision]], N[(0.0692910599291889 * y + x), $MachinePrecision], N[(y * N[(-0.00277777777751721 * z + 0.08333333333333323), $MachinePrecision] + x), $MachinePrecision]]
                  
                  \begin{array}{l}
                  
                  \\
                  \begin{array}{l}
                  \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\
                  \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\
                  
                  \mathbf{else}:\\
                  \;\;\;\;\mathsf{fma}\left(y, \mathsf{fma}\left(-0.00277777777751721, z, 0.08333333333333323\right), x\right)\\
                  
                  
                  \end{array}
                  \end{array}
                  
                  Derivation
                  1. Split input into 2 regimes
                  2. if z < -5.4000000000000004 or 5 < z

                    1. Initial program 41.1%

                      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                    2. Add Preprocessing
                    3. Taylor expanded in z around inf

                      \[\leadsto \color{blue}{x + \frac{692910599291889}{10000000000000000} \cdot y} \]
                    4. Step-by-step derivation
                      1. +-commutativeN/A

                        \[\leadsto \color{blue}{\frac{692910599291889}{10000000000000000} \cdot y + x} \]
                      2. lower-fma.f6498.9

                        \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]
                    5. Applied rewrites98.9%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]

                    if -5.4000000000000004 < z < 5

                    1. Initial program 99.7%

                      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                    2. Add Preprocessing
                    3. Taylor expanded in z around 0

                      \[\leadsto \color{blue}{x + \left(\frac{279195317918525}{3350343815022304} \cdot y + z \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right)} \]
                    4. Step-by-step derivation
                      1. +-commutativeN/A

                        \[\leadsto \color{blue}{\left(\frac{279195317918525}{3350343815022304} \cdot y + z \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right)\right) + x} \]
                      2. +-commutativeN/A

                        \[\leadsto \color{blue}{\left(z \cdot \left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right) + \frac{279195317918525}{3350343815022304} \cdot y\right)} + x \]
                      3. *-commutativeN/A

                        \[\leadsto \left(\color{blue}{\left(\frac{307332350656623}{2093964884388940} \cdot y - \frac{1678650474502018223880473708075}{11224803678858206361900017468416} \cdot y\right) \cdot z} + \frac{279195317918525}{3350343815022304} \cdot y\right) + x \]
                      4. distribute-rgt-out--N/A

                        \[\leadsto \left(\color{blue}{\left(y \cdot \left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right)\right)} \cdot z + \frac{279195317918525}{3350343815022304} \cdot y\right) + x \]
                      5. associate-*l*N/A

                        \[\leadsto \left(\color{blue}{y \cdot \left(\left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right) \cdot z\right)} + \frac{279195317918525}{3350343815022304} \cdot y\right) + x \]
                      6. *-commutativeN/A

                        \[\leadsto \left(y \cdot \left(\left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right) \cdot z\right) + \color{blue}{y \cdot \frac{279195317918525}{3350343815022304}}\right) + x \]
                      7. distribute-lft-outN/A

                        \[\leadsto \color{blue}{y \cdot \left(\left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right) \cdot z + \frac{279195317918525}{3350343815022304}\right)} + x \]
                      8. lower-fma.f64N/A

                        \[\leadsto \color{blue}{\mathsf{fma}\left(y, \left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}\right) \cdot z + \frac{279195317918525}{3350343815022304}, x\right)} \]
                      9. lower-fma.f64N/A

                        \[\leadsto \mathsf{fma}\left(y, \color{blue}{\mathsf{fma}\left(\frac{307332350656623}{2093964884388940} - \frac{1678650474502018223880473708075}{11224803678858206361900017468416}, z, \frac{279195317918525}{3350343815022304}\right)}, x\right) \]
                      10. metadata-eval99.3

                        \[\leadsto \mathsf{fma}\left(y, \mathsf{fma}\left(\color{blue}{-0.00277777777751721}, z, 0.08333333333333323\right), x\right) \]
                    5. Applied rewrites99.3%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(y, \mathsf{fma}\left(-0.00277777777751721, z, 0.08333333333333323\right), x\right)} \]
                  3. Recombined 2 regimes into one program.
                  4. Final simplification99.1%

                    \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 5\right):\\ \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(y, \mathsf{fma}\left(-0.00277777777751721, z, 0.08333333333333323\right), x\right)\\ \end{array} \]
                  5. Add Preprocessing

                  Alternative 10: 98.8% accurate, 2.2× speedup?

                  \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 6\right):\\ \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;x + 0.08333333333333323 \cdot y\\ \end{array} \end{array} \]
                  (FPCore (x y z)
                   :precision binary64
                   (if (or (<= z -5.4) (not (<= z 6.0)))
                     (fma 0.0692910599291889 y x)
                     (+ x (* 0.08333333333333323 y))))
                  double code(double x, double y, double z) {
                  	double tmp;
                  	if ((z <= -5.4) || !(z <= 6.0)) {
                  		tmp = fma(0.0692910599291889, y, x);
                  	} else {
                  		tmp = x + (0.08333333333333323 * y);
                  	}
                  	return tmp;
                  }
                  
                  function code(x, y, z)
                  	tmp = 0.0
                  	if ((z <= -5.4) || !(z <= 6.0))
                  		tmp = fma(0.0692910599291889, y, x);
                  	else
                  		tmp = Float64(x + Float64(0.08333333333333323 * y));
                  	end
                  	return tmp
                  end
                  
                  code[x_, y_, z_] := If[Or[LessEqual[z, -5.4], N[Not[LessEqual[z, 6.0]], $MachinePrecision]], N[(0.0692910599291889 * y + x), $MachinePrecision], N[(x + N[(0.08333333333333323 * y), $MachinePrecision]), $MachinePrecision]]
                  
                  \begin{array}{l}
                  
                  \\
                  \begin{array}{l}
                  \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 6\right):\\
                  \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\
                  
                  \mathbf{else}:\\
                  \;\;\;\;x + 0.08333333333333323 \cdot y\\
                  
                  
                  \end{array}
                  \end{array}
                  
                  Derivation
                  1. Split input into 2 regimes
                  2. if z < -5.4000000000000004 or 6 < z

                    1. Initial program 41.1%

                      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                    2. Add Preprocessing
                    3. Taylor expanded in z around inf

                      \[\leadsto \color{blue}{x + \frac{692910599291889}{10000000000000000} \cdot y} \]
                    4. Step-by-step derivation
                      1. +-commutativeN/A

                        \[\leadsto \color{blue}{\frac{692910599291889}{10000000000000000} \cdot y + x} \]
                      2. lower-fma.f6498.9

                        \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]
                    5. Applied rewrites98.9%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]

                    if -5.4000000000000004 < z < 6

                    1. Initial program 99.7%

                      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                    2. Add Preprocessing
                    3. Taylor expanded in z around 0

                      \[\leadsto x + \color{blue}{\frac{279195317918525}{3350343815022304} \cdot y} \]
                    4. Step-by-step derivation
                      1. lower-*.f6498.9

                        \[\leadsto x + \color{blue}{0.08333333333333323 \cdot y} \]
                    5. Applied rewrites98.9%

                      \[\leadsto x + \color{blue}{0.08333333333333323 \cdot y} \]
                  3. Recombined 2 regimes into one program.
                  4. Final simplification98.9%

                    \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 6\right):\\ \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;x + 0.08333333333333323 \cdot y\\ \end{array} \]
                  5. Add Preprocessing

                  Alternative 11: 98.8% accurate, 2.5× speedup?

                  \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 6\right):\\ \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(0.08333333333333323, y, x\right)\\ \end{array} \end{array} \]
                  (FPCore (x y z)
                   :precision binary64
                   (if (or (<= z -5.4) (not (<= z 6.0)))
                     (fma 0.0692910599291889 y x)
                     (fma 0.08333333333333323 y x)))
                  double code(double x, double y, double z) {
                  	double tmp;
                  	if ((z <= -5.4) || !(z <= 6.0)) {
                  		tmp = fma(0.0692910599291889, y, x);
                  	} else {
                  		tmp = fma(0.08333333333333323, y, x);
                  	}
                  	return tmp;
                  }
                  
                  function code(x, y, z)
                  	tmp = 0.0
                  	if ((z <= -5.4) || !(z <= 6.0))
                  		tmp = fma(0.0692910599291889, y, x);
                  	else
                  		tmp = fma(0.08333333333333323, y, x);
                  	end
                  	return tmp
                  end
                  
                  code[x_, y_, z_] := If[Or[LessEqual[z, -5.4], N[Not[LessEqual[z, 6.0]], $MachinePrecision]], N[(0.0692910599291889 * y + x), $MachinePrecision], N[(0.08333333333333323 * y + x), $MachinePrecision]]
                  
                  \begin{array}{l}
                  
                  \\
                  \begin{array}{l}
                  \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 6\right):\\
                  \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\
                  
                  \mathbf{else}:\\
                  \;\;\;\;\mathsf{fma}\left(0.08333333333333323, y, x\right)\\
                  
                  
                  \end{array}
                  \end{array}
                  
                  Derivation
                  1. Split input into 2 regimes
                  2. if z < -5.4000000000000004 or 6 < z

                    1. Initial program 41.1%

                      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                    2. Add Preprocessing
                    3. Taylor expanded in z around inf

                      \[\leadsto \color{blue}{x + \frac{692910599291889}{10000000000000000} \cdot y} \]
                    4. Step-by-step derivation
                      1. +-commutativeN/A

                        \[\leadsto \color{blue}{\frac{692910599291889}{10000000000000000} \cdot y + x} \]
                      2. lower-fma.f6498.9

                        \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]
                    5. Applied rewrites98.9%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]

                    if -5.4000000000000004 < z < 6

                    1. Initial program 99.7%

                      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                    2. Add Preprocessing
                    3. Taylor expanded in z around 0

                      \[\leadsto \color{blue}{x + \frac{279195317918525}{3350343815022304} \cdot y} \]
                    4. Step-by-step derivation
                      1. +-commutativeN/A

                        \[\leadsto \color{blue}{\frac{279195317918525}{3350343815022304} \cdot y + x} \]
                      2. lower-fma.f6498.9

                        \[\leadsto \color{blue}{\mathsf{fma}\left(0.08333333333333323, y, x\right)} \]
                    5. Applied rewrites98.9%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(0.08333333333333323, y, x\right)} \]
                  3. Recombined 2 regimes into one program.
                  4. Final simplification98.9%

                    \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -5.4 \lor \neg \left(z \leq 6\right):\\ \;\;\;\;\mathsf{fma}\left(0.0692910599291889, y, x\right)\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(0.08333333333333323, y, x\right)\\ \end{array} \]
                  5. Add Preprocessing

                  Alternative 12: 49.7% accurate, 2.6× speedup?

                  \[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -6.5 \lor \neg \left(z \leq 6\right):\\ \;\;\;\;0.0692910599291889 \cdot y\\ \mathbf{else}:\\ \;\;\;\;0.08333333333333323 \cdot y\\ \end{array} \end{array} \]
                  (FPCore (x y z)
                   :precision binary64
                   (if (or (<= z -6.5) (not (<= z 6.0)))
                     (* 0.0692910599291889 y)
                     (* 0.08333333333333323 y)))
                  double code(double x, double y, double z) {
                  	double tmp;
                  	if ((z <= -6.5) || !(z <= 6.0)) {
                  		tmp = 0.0692910599291889 * y;
                  	} else {
                  		tmp = 0.08333333333333323 * y;
                  	}
                  	return tmp;
                  }
                  
                  real(8) function code(x, y, z)
                      real(8), intent (in) :: x
                      real(8), intent (in) :: y
                      real(8), intent (in) :: z
                      real(8) :: tmp
                      if ((z <= (-6.5d0)) .or. (.not. (z <= 6.0d0))) then
                          tmp = 0.0692910599291889d0 * y
                      else
                          tmp = 0.08333333333333323d0 * y
                      end if
                      code = tmp
                  end function
                  
                  public static double code(double x, double y, double z) {
                  	double tmp;
                  	if ((z <= -6.5) || !(z <= 6.0)) {
                  		tmp = 0.0692910599291889 * y;
                  	} else {
                  		tmp = 0.08333333333333323 * y;
                  	}
                  	return tmp;
                  }
                  
                  def code(x, y, z):
                  	tmp = 0
                  	if (z <= -6.5) or not (z <= 6.0):
                  		tmp = 0.0692910599291889 * y
                  	else:
                  		tmp = 0.08333333333333323 * y
                  	return tmp
                  
                  function code(x, y, z)
                  	tmp = 0.0
                  	if ((z <= -6.5) || !(z <= 6.0))
                  		tmp = Float64(0.0692910599291889 * y);
                  	else
                  		tmp = Float64(0.08333333333333323 * y);
                  	end
                  	return tmp
                  end
                  
                  function tmp_2 = code(x, y, z)
                  	tmp = 0.0;
                  	if ((z <= -6.5) || ~((z <= 6.0)))
                  		tmp = 0.0692910599291889 * y;
                  	else
                  		tmp = 0.08333333333333323 * y;
                  	end
                  	tmp_2 = tmp;
                  end
                  
                  code[x_, y_, z_] := If[Or[LessEqual[z, -6.5], N[Not[LessEqual[z, 6.0]], $MachinePrecision]], N[(0.0692910599291889 * y), $MachinePrecision], N[(0.08333333333333323 * y), $MachinePrecision]]
                  
                  \begin{array}{l}
                  
                  \\
                  \begin{array}{l}
                  \mathbf{if}\;z \leq -6.5 \lor \neg \left(z \leq 6\right):\\
                  \;\;\;\;0.0692910599291889 \cdot y\\
                  
                  \mathbf{else}:\\
                  \;\;\;\;0.08333333333333323 \cdot y\\
                  
                  
                  \end{array}
                  \end{array}
                  
                  Derivation
                  1. Split input into 2 regimes
                  2. if z < -6.5 or 6 < z

                    1. Initial program 41.1%

                      \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                    2. Add Preprocessing
                    3. Taylor expanded in z around inf

                      \[\leadsto \color{blue}{x + \frac{692910599291889}{10000000000000000} \cdot y} \]
                    4. Step-by-step derivation
                      1. +-commutativeN/A

                        \[\leadsto \color{blue}{\frac{692910599291889}{10000000000000000} \cdot y + x} \]
                      2. lower-fma.f6498.9

                        \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]
                    5. Applied rewrites98.9%

                      \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]
                    6. Taylor expanded in x around 0

                      \[\leadsto \frac{692910599291889}{10000000000000000} \cdot \color{blue}{y} \]
                    7. Step-by-step derivation
                      1. Applied rewrites47.7%

                        \[\leadsto 0.0692910599291889 \cdot \color{blue}{y} \]

                      if -6.5 < z < 6

                      1. Initial program 99.7%

                        \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                      2. Add Preprocessing
                      3. Taylor expanded in z around 0

                        \[\leadsto \color{blue}{x + \frac{279195317918525}{3350343815022304} \cdot y} \]
                      4. Step-by-step derivation
                        1. +-commutativeN/A

                          \[\leadsto \color{blue}{\frac{279195317918525}{3350343815022304} \cdot y + x} \]
                        2. lower-fma.f6498.9

                          \[\leadsto \color{blue}{\mathsf{fma}\left(0.08333333333333323, y, x\right)} \]
                      5. Applied rewrites98.9%

                        \[\leadsto \color{blue}{\mathsf{fma}\left(0.08333333333333323, y, x\right)} \]
                      6. Taylor expanded in x around 0

                        \[\leadsto \frac{279195317918525}{3350343815022304} \cdot \color{blue}{y} \]
                      7. Step-by-step derivation
                        1. Applied rewrites53.1%

                          \[\leadsto 0.08333333333333323 \cdot \color{blue}{y} \]
                      8. Recombined 2 regimes into one program.
                      9. Final simplification50.4%

                        \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -6.5 \lor \neg \left(z \leq 6\right):\\ \;\;\;\;0.0692910599291889 \cdot y\\ \mathbf{else}:\\ \;\;\;\;0.08333333333333323 \cdot y\\ \end{array} \]
                      10. Add Preprocessing

                      Alternative 13: 30.8% accurate, 7.8× speedup?

                      \[\begin{array}{l} \\ 0.0692910599291889 \cdot y \end{array} \]
                      (FPCore (x y z) :precision binary64 (* 0.0692910599291889 y))
                      double code(double x, double y, double z) {
                      	return 0.0692910599291889 * y;
                      }
                      
                      real(8) function code(x, y, z)
                          real(8), intent (in) :: x
                          real(8), intent (in) :: y
                          real(8), intent (in) :: z
                          code = 0.0692910599291889d0 * y
                      end function
                      
                      public static double code(double x, double y, double z) {
                      	return 0.0692910599291889 * y;
                      }
                      
                      def code(x, y, z):
                      	return 0.0692910599291889 * y
                      
                      function code(x, y, z)
                      	return Float64(0.0692910599291889 * y)
                      end
                      
                      function tmp = code(x, y, z)
                      	tmp = 0.0692910599291889 * y;
                      end
                      
                      code[x_, y_, z_] := N[(0.0692910599291889 * y), $MachinePrecision]
                      
                      \begin{array}{l}
                      
                      \\
                      0.0692910599291889 \cdot y
                      \end{array}
                      
                      Derivation
                      1. Initial program 70.4%

                        \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304} \]
                      2. Add Preprocessing
                      3. Taylor expanded in z around inf

                        \[\leadsto \color{blue}{x + \frac{692910599291889}{10000000000000000} \cdot y} \]
                      4. Step-by-step derivation
                        1. +-commutativeN/A

                          \[\leadsto \color{blue}{\frac{692910599291889}{10000000000000000} \cdot y + x} \]
                        2. lower-fma.f6477.7

                          \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]
                      5. Applied rewrites77.7%

                        \[\leadsto \color{blue}{\mathsf{fma}\left(0.0692910599291889, y, x\right)} \]
                      6. Taylor expanded in x around 0

                        \[\leadsto \frac{692910599291889}{10000000000000000} \cdot \color{blue}{y} \]
                      7. Step-by-step derivation
                        1. Applied rewrites30.5%

                          \[\leadsto 0.0692910599291889 \cdot \color{blue}{y} \]
                        2. Add Preprocessing

                        Developer Target 1: 99.4% accurate, 0.7× speedup?

                        \[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\frac{0.07512208616047561}{z} + 0.0692910599291889\right) \cdot y - \left(\frac{0.40462203869992125 \cdot y}{z \cdot z} - x\right)\\ \mathbf{if}\;z < -8120153.652456675:\\ \;\;\;\;t\_0\\ \mathbf{elif}\;z < 6.576118972787377 \cdot 10^{+20}:\\ \;\;\;\;x + \left(y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)\right) \cdot \frac{1}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}\\ \mathbf{else}:\\ \;\;\;\;t\_0\\ \end{array} \end{array} \]
                        (FPCore (x y z)
                         :precision binary64
                         (let* ((t_0
                                 (-
                                  (* (+ (/ 0.07512208616047561 z) 0.0692910599291889) y)
                                  (- (/ (* 0.40462203869992125 y) (* z z)) x))))
                           (if (< z -8120153.652456675)
                             t_0
                             (if (< z 6.576118972787377e+20)
                               (+
                                x
                                (*
                                 (*
                                  y
                                  (+
                                   (* (+ (* z 0.0692910599291889) 0.4917317610505968) z)
                                   0.279195317918525))
                                 (/ 1.0 (+ (* (+ z 6.012459259764103) z) 3.350343815022304))))
                               t_0))))
                        double code(double x, double y, double z) {
                        	double t_0 = (((0.07512208616047561 / z) + 0.0692910599291889) * y) - (((0.40462203869992125 * y) / (z * z)) - x);
                        	double tmp;
                        	if (z < -8120153.652456675) {
                        		tmp = t_0;
                        	} else if (z < 6.576118972787377e+20) {
                        		tmp = x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) * (1.0 / (((z + 6.012459259764103) * z) + 3.350343815022304)));
                        	} else {
                        		tmp = t_0;
                        	}
                        	return tmp;
                        }
                        
                        real(8) function code(x, y, z)
                            real(8), intent (in) :: x
                            real(8), intent (in) :: y
                            real(8), intent (in) :: z
                            real(8) :: t_0
                            real(8) :: tmp
                            t_0 = (((0.07512208616047561d0 / z) + 0.0692910599291889d0) * y) - (((0.40462203869992125d0 * y) / (z * z)) - x)
                            if (z < (-8120153.652456675d0)) then
                                tmp = t_0
                            else if (z < 6.576118972787377d+20) then
                                tmp = x + ((y * ((((z * 0.0692910599291889d0) + 0.4917317610505968d0) * z) + 0.279195317918525d0)) * (1.0d0 / (((z + 6.012459259764103d0) * z) + 3.350343815022304d0)))
                            else
                                tmp = t_0
                            end if
                            code = tmp
                        end function
                        
                        public static double code(double x, double y, double z) {
                        	double t_0 = (((0.07512208616047561 / z) + 0.0692910599291889) * y) - (((0.40462203869992125 * y) / (z * z)) - x);
                        	double tmp;
                        	if (z < -8120153.652456675) {
                        		tmp = t_0;
                        	} else if (z < 6.576118972787377e+20) {
                        		tmp = x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) * (1.0 / (((z + 6.012459259764103) * z) + 3.350343815022304)));
                        	} else {
                        		tmp = t_0;
                        	}
                        	return tmp;
                        }
                        
                        def code(x, y, z):
                        	t_0 = (((0.07512208616047561 / z) + 0.0692910599291889) * y) - (((0.40462203869992125 * y) / (z * z)) - x)
                        	tmp = 0
                        	if z < -8120153.652456675:
                        		tmp = t_0
                        	elif z < 6.576118972787377e+20:
                        		tmp = x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) * (1.0 / (((z + 6.012459259764103) * z) + 3.350343815022304)))
                        	else:
                        		tmp = t_0
                        	return tmp
                        
                        function code(x, y, z)
                        	t_0 = Float64(Float64(Float64(Float64(0.07512208616047561 / z) + 0.0692910599291889) * y) - Float64(Float64(Float64(0.40462203869992125 * y) / Float64(z * z)) - x))
                        	tmp = 0.0
                        	if (z < -8120153.652456675)
                        		tmp = t_0;
                        	elseif (z < 6.576118972787377e+20)
                        		tmp = Float64(x + Float64(Float64(y * Float64(Float64(Float64(Float64(z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) * Float64(1.0 / Float64(Float64(Float64(z + 6.012459259764103) * z) + 3.350343815022304))));
                        	else
                        		tmp = t_0;
                        	end
                        	return tmp
                        end
                        
                        function tmp_2 = code(x, y, z)
                        	t_0 = (((0.07512208616047561 / z) + 0.0692910599291889) * y) - (((0.40462203869992125 * y) / (z * z)) - x);
                        	tmp = 0.0;
                        	if (z < -8120153.652456675)
                        		tmp = t_0;
                        	elseif (z < 6.576118972787377e+20)
                        		tmp = x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) * (1.0 / (((z + 6.012459259764103) * z) + 3.350343815022304)));
                        	else
                        		tmp = t_0;
                        	end
                        	tmp_2 = tmp;
                        end
                        
                        code[x_, y_, z_] := Block[{t$95$0 = N[(N[(N[(N[(0.07512208616047561 / z), $MachinePrecision] + 0.0692910599291889), $MachinePrecision] * y), $MachinePrecision] - N[(N[(N[(0.40462203869992125 * y), $MachinePrecision] / N[(z * z), $MachinePrecision]), $MachinePrecision] - x), $MachinePrecision]), $MachinePrecision]}, If[Less[z, -8120153.652456675], t$95$0, If[Less[z, 6.576118972787377e+20], N[(x + N[(N[(y * N[(N[(N[(N[(z * 0.0692910599291889), $MachinePrecision] + 0.4917317610505968), $MachinePrecision] * z), $MachinePrecision] + 0.279195317918525), $MachinePrecision]), $MachinePrecision] * N[(1.0 / N[(N[(N[(z + 6.012459259764103), $MachinePrecision] * z), $MachinePrecision] + 3.350343815022304), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$0]]]
                        
                        \begin{array}{l}
                        
                        \\
                        \begin{array}{l}
                        t_0 := \left(\frac{0.07512208616047561}{z} + 0.0692910599291889\right) \cdot y - \left(\frac{0.40462203869992125 \cdot y}{z \cdot z} - x\right)\\
                        \mathbf{if}\;z < -8120153.652456675:\\
                        \;\;\;\;t\_0\\
                        
                        \mathbf{elif}\;z < 6.576118972787377 \cdot 10^{+20}:\\
                        \;\;\;\;x + \left(y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)\right) \cdot \frac{1}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}\\
                        
                        \mathbf{else}:\\
                        \;\;\;\;t\_0\\
                        
                        
                        \end{array}
                        \end{array}
                        

                        Reproduce

                        ?
                        herbie shell --seed 2024318 
                        (FPCore (x y z)
                          :name "Numeric.SpecFunctions:logGamma from math-functions-0.1.5.2, B"
                          :precision binary64
                        
                          :alt
                          (! :herbie-platform default (if (< z -324806146098267/40000000) (- (* (+ (/ 7512208616047561/100000000000000000 z) 692910599291889/10000000000000000) y) (- (/ (* 323697630959937/800000000000000 y) (* z z)) x)) (if (< z 657611897278737700000) (+ x (* (* y (+ (* (+ (* z 692910599291889/10000000000000000) 307332350656623/625000000000000) z) 11167812716741/40000000000000)) (/ 1 (+ (* (+ z 6012459259764103/1000000000000000) z) 104698244219447/31250000000000)))) (- (* (+ (/ 7512208616047561/100000000000000000 z) 692910599291889/10000000000000000) y) (- (/ (* 323697630959937/800000000000000 y) (* z z)) x)))))
                        
                          (+ x (/ (* y (+ (* (+ (* z 0.0692910599291889) 0.4917317610505968) z) 0.279195317918525)) (+ (* (+ z 6.012459259764103) z) 3.350343815022304))))