Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[x + \left(\left(y - x\right) \cdot 6\right) \cdot \left(\frac{2}{3} - z\right)
\]
↓
\[4 \cdot \left(y - x\right) + \left(x + -6 \cdot \left(\left(y - x\right) \cdot z\right)\right)
\]
(FPCore (x y z)
:precision binary64
(+ x (* (* (- y x) 6.0) (- (/ 2.0 3.0) z)))) ↓
(FPCore (x y z)
:precision binary64
(+ (* 4.0 (- y x)) (+ x (* -6.0 (* (- y x) z))))) double code(double x, double y, double z) {
return x + (((y - x) * 6.0) * ((2.0 / 3.0) - z));
}
↓
double code(double x, double y, double z) {
return (4.0 * (y - x)) + (x + (-6.0 * ((y - x) * z)));
}
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 - x) * 6.0d0) * ((2.0d0 / 3.0d0) - z))
end function
↓
real(8) function code(x, y, z)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
code = (4.0d0 * (y - x)) + (x + ((-6.0d0) * ((y - x) * z)))
end function
public static double code(double x, double y, double z) {
return x + (((y - x) * 6.0) * ((2.0 / 3.0) - z));
}
↓
public static double code(double x, double y, double z) {
return (4.0 * (y - x)) + (x + (-6.0 * ((y - x) * z)));
}
def code(x, y, z):
return x + (((y - x) * 6.0) * ((2.0 / 3.0) - z))
↓
def code(x, y, z):
return (4.0 * (y - x)) + (x + (-6.0 * ((y - x) * z)))
function code(x, y, z)
return Float64(x + Float64(Float64(Float64(y - x) * 6.0) * Float64(Float64(2.0 / 3.0) - z)))
end
↓
function code(x, y, z)
return Float64(Float64(4.0 * Float64(y - x)) + Float64(x + Float64(-6.0 * Float64(Float64(y - x) * z))))
end
function tmp = code(x, y, z)
tmp = x + (((y - x) * 6.0) * ((2.0 / 3.0) - z));
end
↓
function tmp = code(x, y, z)
tmp = (4.0 * (y - x)) + (x + (-6.0 * ((y - x) * z)));
end
code[x_, y_, z_] := N[(x + N[(N[(N[(y - x), $MachinePrecision] * 6.0), $MachinePrecision] * N[(N[(2.0 / 3.0), $MachinePrecision] - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_] := N[(N[(4.0 * N[(y - x), $MachinePrecision]), $MachinePrecision] + N[(x + N[(-6.0 * N[(N[(y - x), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
x + \left(\left(y - x\right) \cdot 6\right) \cdot \left(\frac{2}{3} - z\right)
↓
4 \cdot \left(y - x\right) + \left(x + -6 \cdot \left(\left(y - x\right) \cdot z\right)\right)
Alternatives Alternative 1 Accuracy 99.8% Cost 960
\[4 \cdot \left(y - x\right) + \left(x + -6 \cdot \left(\left(y - x\right) \cdot z\right)\right)
\]
Alternative 2 Accuracy 50.5% Cost 2037
\[\begin{array}{l}
t_0 := -6 \cdot \left(y \cdot z\right)\\
t_1 := x \cdot \left(z \cdot 6\right)\\
\mathbf{if}\;z \leq -9.5 \cdot 10^{+266}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -1.8 \cdot 10^{+173}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq -1.4 \cdot 10^{+94}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -2.4 \cdot 10^{+39}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq -3.4 \cdot 10^{-11}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -5.5 \cdot 10^{-175}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq -6.5 \cdot 10^{-231}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 4.5 \cdot 10^{-301}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 6 \cdot 10^{-129}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 3.1 \cdot 10^{-107}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 0.5:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 6.9 \cdot 10^{+168} \lor \neg \left(z \leq 9.5 \cdot 10^{+208}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 3 Accuracy 50.3% Cost 2037
\[\begin{array}{l}
t_0 := -6 \cdot \left(y \cdot z\right)\\
t_1 := x \cdot \left(z \cdot 6\right)\\
\mathbf{if}\;z \leq -5.2 \cdot 10^{+266}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -4.8 \cdot 10^{+171}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq -1.45 \cdot 10^{+88}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -3.5 \cdot 10^{+39}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq -3.4 \cdot 10^{-11}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -2.65 \cdot 10^{-179}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq -5.8 \cdot 10^{-232}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 4 \cdot 10^{-301}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 8.8 \cdot 10^{-131}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 1.6 \cdot 10^{-106}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 0.5:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 6.9 \cdot 10^{+168} \lor \neg \left(z \leq 2.45 \cdot 10^{+208}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;z \cdot \left(y \cdot -6\right)\\
\end{array}
\]
Alternative 4 Accuracy 50.4% Cost 2037
\[\begin{array}{l}
t_0 := -6 \cdot \left(y \cdot z\right)\\
t_1 := x \cdot \left(z \cdot 6\right)\\
\mathbf{if}\;z \leq -8.4 \cdot 10^{+266}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -4.5 \cdot 10^{+172}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq -9.5 \cdot 10^{+95}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -1.4 \cdot 10^{+38}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq -3.4 \cdot 10^{-11}:\\
\;\;\;\;y \cdot \left(-6 \cdot z\right)\\
\mathbf{elif}\;z \leq -1.48 \cdot 10^{-182}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq -2.45 \cdot 10^{-230}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 4.4 \cdot 10^{-301}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 9.6 \cdot 10^{-129}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 1.9 \cdot 10^{-108}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 0.5:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 7 \cdot 10^{+168} \lor \neg \left(z \leq 1.75 \cdot 10^{+208}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;z \cdot \left(y \cdot -6\right)\\
\end{array}
\]
Alternative 5 Accuracy 73.5% Cost 1372
\[\begin{array}{l}
t_0 := -6 \cdot \left(\left(y - x\right) \cdot z\right)\\
\mathbf{if}\;z \leq -3.4 \cdot 10^{-11}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -1.7 \cdot 10^{-181}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq -3.5 \cdot 10^{-232}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 3.1 \cdot 10^{-301}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 2.15 \cdot 10^{-128}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 3.8 \cdot 10^{-106}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 0.5:\\
\;\;\;\;x \cdot -3\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 6 Accuracy 73.7% Cost 1372
\[\begin{array}{l}
t_0 := x \cdot \left(-3 + z \cdot 6\right)\\
t_1 := -6 \cdot \left(\left(y - x\right) \cdot z\right)\\
\mathbf{if}\;z \leq -3.4 \cdot 10^{-11}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq -4.3 \cdot 10^{-179}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq -2.55 \cdot 10^{-232}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq 3.05 \cdot 10^{-301}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 3.5 \cdot 10^{-130}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 5 \cdot 10^{-109}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 2700000000000:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 7 Accuracy 73.8% Cost 1372
\[\begin{array}{l}
t_0 := x \cdot \left(-3 + z \cdot 6\right)\\
\mathbf{if}\;z \leq -3.4 \cdot 10^{-11}:\\
\;\;\;\;-6 \cdot \left(\left(y - x\right) \cdot z\right)\\
\mathbf{elif}\;z \leq -1.75 \cdot 10^{-178}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq -5.6 \cdot 10^{-231}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq 3.65 \cdot 10^{-301}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 1.35 \cdot 10^{-129}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 1.62 \cdot 10^{-108}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 2700000000000:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;z \cdot \left(\left(y - x\right) \cdot -6\right)\\
\end{array}
\]
Alternative 8 Accuracy 49.9% Cost 1244
\[\begin{array}{l}
t_0 := -6 \cdot \left(y \cdot z\right)\\
\mathbf{if}\;z \leq -3.4 \cdot 10^{-11}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;z \leq -8.2 \cdot 10^{-179}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq -5.7 \cdot 10^{-232}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 4.2 \cdot 10^{-301}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 1.5 \cdot 10^{-127}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;z \leq 1.2 \cdot 10^{-106}:\\
\;\;\;\;4 \cdot y\\
\mathbf{elif}\;z \leq 0.52:\\
\;\;\;\;x \cdot -3\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 9 Accuracy 74.8% Cost 978
\[\begin{array}{l}
\mathbf{if}\;x \leq -4.1 \cdot 10^{+29} \lor \neg \left(x \leq -1.28 \cdot 10^{-20} \lor \neg \left(x \leq -1.56 \cdot 10^{-83}\right) \land x \leq 5.5 \cdot 10^{-21}\right):\\
\;\;\;\;x \cdot \left(-3 + z \cdot 6\right)\\
\mathbf{else}:\\
\;\;\;\;\left(0.6666666666666666 - z\right) \cdot \left(y \cdot 6\right)\\
\end{array}
\]
Alternative 10 Accuracy 74.9% Cost 978
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.12 \cdot 10^{+28} \lor \neg \left(x \leq -4.7 \cdot 10^{-18} \lor \neg \left(x \leq -1.8 \cdot 10^{-83}\right) \land x \leq 1.4 \cdot 10^{-19}\right):\\
\;\;\;\;x \cdot \left(-3 + z \cdot 6\right)\\
\mathbf{else}:\\
\;\;\;\;y \cdot \left(4 + -6 \cdot z\right)\\
\end{array}
\]
Alternative 11 Accuracy 97.8% Cost 712
\[\begin{array}{l}
\mathbf{if}\;z \leq -0.55:\\
\;\;\;\;-6 \cdot \left(\left(y - x\right) \cdot z\right)\\
\mathbf{elif}\;z \leq 0.58:\\
\;\;\;\;4 \cdot y + x \cdot -3\\
\mathbf{else}:\\
\;\;\;\;z \cdot \left(\left(y - x\right) \cdot -6\right)\\
\end{array}
\]
Alternative 12 Accuracy 99.5% Cost 704
\[x + \left(0.6666666666666666 - z\right) \cdot \left(\left(y - x\right) \cdot 6\right)
\]
Alternative 13 Accuracy 99.7% Cost 704
\[x + \left(y - x\right) \cdot \left(6 \cdot \left(0.6666666666666666 - z\right)\right)
\]
Alternative 14 Accuracy 36.4% Cost 456
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.8 \cdot 10^{-83}:\\
\;\;\;\;x \cdot -3\\
\mathbf{elif}\;x \leq 1.45 \cdot 10^{-78}:\\
\;\;\;\;4 \cdot y\\
\mathbf{else}:\\
\;\;\;\;x \cdot -3\\
\end{array}
\]
Alternative 15 Accuracy 26.2% Cost 192
\[x \cdot -3
\]
Alternative 16 Accuracy 2.6% Cost 64
\[x
\]