Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[x + \frac{y \cdot \left(\left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) \cdot z + 0.279195317918525\right)}{\left(z + 6.012459259764103\right) \cdot z + 3.350343815022304}
\]
↓
\[\begin{array}{l}
\mathbf{if}\;z \leq -1300000000000 \lor \neg \left(z \leq 5.8 \cdot 10^{-9}\right):\\
\;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y}{z \cdot 0.39999999996247915 + 12.000000000000014}\\
\end{array}
\]
(FPCore (x y z)
:precision binary64
(+
x
(/
(*
y
(+
(* (+ (* z 0.0692910599291889) 0.4917317610505968) z)
0.279195317918525))
(+ (* (+ z 6.012459259764103) z) 3.350343815022304)))) ↓
(FPCore (x y z)
:precision binary64
(if (or (<= z -1300000000000.0) (not (<= z 5.8e-9)))
(+ x (/ y (- 14.431876219268936 (/ 15.646356830292042 z))))
(+ x (/ y (+ (* z 0.39999999996247915) 12.000000000000014))))) 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));
}
↓
double code(double x, double y, double z) {
double tmp;
if ((z <= -1300000000000.0) || !(z <= 5.8e-9)) {
tmp = x + (y / (14.431876219268936 - (15.646356830292042 / z)));
} else {
tmp = x + (y / ((z * 0.39999999996247915) + 12.000000000000014));
}
return tmp;
}
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
↓
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 <= (-1300000000000.0d0)) .or. (.not. (z <= 5.8d-9))) then
tmp = x + (y / (14.431876219268936d0 - (15.646356830292042d0 / z)))
else
tmp = x + (y / ((z * 0.39999999996247915d0) + 12.000000000000014d0))
end if
code = tmp
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));
}
↓
public static double code(double x, double y, double z) {
double tmp;
if ((z <= -1300000000000.0) || !(z <= 5.8e-9)) {
tmp = x + (y / (14.431876219268936 - (15.646356830292042 / z)));
} else {
tmp = x + (y / ((z * 0.39999999996247915) + 12.000000000000014));
}
return tmp;
}
def code(x, y, z):
return x + ((y * ((((z * 0.0692910599291889) + 0.4917317610505968) * z) + 0.279195317918525)) / (((z + 6.012459259764103) * z) + 3.350343815022304))
↓
def code(x, y, z):
tmp = 0
if (z <= -1300000000000.0) or not (z <= 5.8e-9):
tmp = x + (y / (14.431876219268936 - (15.646356830292042 / z)))
else:
tmp = x + (y / ((z * 0.39999999996247915) + 12.000000000000014))
return tmp
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 code(x, y, z)
tmp = 0.0
if ((z <= -1300000000000.0) || !(z <= 5.8e-9))
tmp = Float64(x + Float64(y / Float64(14.431876219268936 - Float64(15.646356830292042 / z))));
else
tmp = Float64(x + Float64(y / Float64(Float64(z * 0.39999999996247915) + 12.000000000000014)));
end
return tmp
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
↓
function tmp_2 = code(x, y, z)
tmp = 0.0;
if ((z <= -1300000000000.0) || ~((z <= 5.8e-9)))
tmp = x + (y / (14.431876219268936 - (15.646356830292042 / z)));
else
tmp = x + (y / ((z * 0.39999999996247915) + 12.000000000000014));
end
tmp_2 = tmp;
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]
↓
code[x_, y_, z_] := If[Or[LessEqual[z, -1300000000000.0], N[Not[LessEqual[z, 5.8e-9]], $MachinePrecision]], N[(x + N[(y / N[(14.431876219268936 - N[(15.646356830292042 / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(y / N[(N[(z * 0.39999999996247915), $MachinePrecision] + 12.000000000000014), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
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}
↓
\begin{array}{l}
\mathbf{if}\;z \leq -1300000000000 \lor \neg \left(z \leq 5.8 \cdot 10^{-9}\right):\\
\;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y}{z \cdot 0.39999999996247915 + 12.000000000000014}\\
\end{array}
Alternatives Alternative 1 Accuracy 99.0% Cost 841
\[\begin{array}{l}
\mathbf{if}\;z \leq -1300000000000 \lor \neg \left(z \leq 5.8 \cdot 10^{-9}\right):\\
\;\;\;\;x + \frac{y}{14.431876219268936 - \frac{15.646356830292042}{z}}\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y}{z \cdot 0.39999999996247915 + 12.000000000000014}\\
\end{array}
\]
Alternative 2 Accuracy 98.7% Cost 27716
\[\begin{array}{l}
\mathbf{if}\;\frac{y \cdot \left(z \cdot \left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) + 0.279195317918525\right)}{z \cdot \left(z + 6.012459259764103\right) + 3.350343815022304} \leq 5 \cdot 10^{+267}:\\
\;\;\;\;\mathsf{fma}\left(y, \frac{\mathsf{fma}\left(z, \mathsf{fma}\left(z, 0.0692910599291889, 0.4917317610505968\right), 0.279195317918525\right)}{\mathsf{fma}\left(z, z + 6.012459259764103, 3.350343815022304\right)}, x\right)\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y}{14.431876219268936}\\
\end{array}
\]
Alternative 3 Accuracy 98.5% Cost 21444
\[\begin{array}{l}
\mathbf{if}\;\frac{y \cdot \left(z \cdot \left(z \cdot 0.0692910599291889 + 0.4917317610505968\right) + 0.279195317918525\right)}{z \cdot \left(z + 6.012459259764103\right) + 3.350343815022304} \leq 5 \cdot 10^{+267}:\\
\;\;\;\;x + \frac{y}{\frac{\mathsf{fma}\left(z + 6.012459259764103, z, 3.350343815022304\right)}{\mathsf{fma}\left(\mathsf{fma}\left(z, 0.0692910599291889, 0.4917317610505968\right), z, 0.279195317918525\right)}}\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y}{14.431876219268936}\\
\end{array}
\]
Alternative 4 Accuracy 98.4% Cost 3268
\[\begin{array}{l}
t_0 := z \cdot \left(z + 6.012459259764103\right) + 3.350343815022304\\
t_1 := z \cdot \left(z \cdot 0.0692910599291889 + 0.4917317610505968\right)\\
\mathbf{if}\;\frac{y \cdot \left(t_1 + 0.279195317918525\right)}{t_0} \leq 5 \cdot 10^{+267}:\\
\;\;\;\;x + y \cdot \left(\frac{t_1}{t_0} + 0.279195317918525 \cdot \frac{1}{t_0}\right)\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y}{14.431876219268936}\\
\end{array}
\]
Alternative 5 Accuracy 98.9% Cost 841
\[\begin{array}{l}
\mathbf{if}\;z \leq -1300000000000 \lor \neg \left(z \leq 5.8 \cdot 10^{-9}\right):\\
\;\;\;\;x + \frac{y}{14.431876219268936}\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y}{z \cdot 0.39999999996247915 + 12.000000000000014}\\
\end{array}
\]
Alternative 6 Accuracy 60.8% Cost 588
\[\begin{array}{l}
\mathbf{if}\;x \leq -9.5 \cdot 10^{-35}:\\
\;\;\;\;x\\
\mathbf{elif}\;x \leq 3.7 \cdot 10^{-235}:\\
\;\;\;\;y \cdot 0.0692910599291889\\
\mathbf{elif}\;x \leq 2.65 \cdot 10^{-51}:\\
\;\;\;\;y \cdot 0.08333333333333323\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
Alternative 7 Accuracy 60.8% Cost 588
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.05 \cdot 10^{-34}:\\
\;\;\;\;x\\
\mathbf{elif}\;x \leq 3.6 \cdot 10^{-235}:\\
\;\;\;\;y \cdot 0.0692910599291889\\
\mathbf{elif}\;x \leq 7.2 \cdot 10^{-51}:\\
\;\;\;\;\frac{y}{12.000000000000014}\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
Alternative 8 Accuracy 98.9% Cost 585
\[\begin{array}{l}
\mathbf{if}\;z \leq -1300000000000 \lor \neg \left(z \leq 5.8 \cdot 10^{-9}\right):\\
\;\;\;\;x + \frac{y}{14.431876219268936}\\
\mathbf{else}:\\
\;\;\;\;x + \frac{y}{12.000000000000014}\\
\end{array}
\]
Alternative 9 Accuracy 59.9% Cost 456
\[\begin{array}{l}
\mathbf{if}\;x \leq -3.3 \cdot 10^{-34}:\\
\;\;\;\;x\\
\mathbf{elif}\;x \leq 7.5 \cdot 10^{-146}:\\
\;\;\;\;y \cdot 0.0692910599291889\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
Alternative 10 Accuracy 79.4% Cost 320
\[x + \frac{y}{12.000000000000014}
\]
Alternative 11 Accuracy 49.8% Cost 64
\[x
\]