Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[x + \left(\left(y - x\right) \cdot 6\right) \cdot z
\]
↓
\[x + \left(6 \cdot y + x \cdot -6\right) \cdot z
\]
(FPCore (x y z) :precision binary64 (+ x (* (* (- y x) 6.0) z))) ↓
(FPCore (x y z) :precision binary64 (+ x (* (+ (* 6.0 y) (* x -6.0)) z))) double code(double x, double y, double z) {
return x + (((y - x) * 6.0) * z);
}
↓
double code(double x, double y, double z) {
return x + (((6.0 * y) + (x * -6.0)) * 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) * 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 = x + (((6.0d0 * y) + (x * (-6.0d0))) * z)
end function
public static double code(double x, double y, double z) {
return x + (((y - x) * 6.0) * z);
}
↓
public static double code(double x, double y, double z) {
return x + (((6.0 * y) + (x * -6.0)) * z);
}
def code(x, y, z):
return x + (((y - x) * 6.0) * z)
↓
def code(x, y, z):
return x + (((6.0 * y) + (x * -6.0)) * z)
function code(x, y, z)
return Float64(x + Float64(Float64(Float64(y - x) * 6.0) * z))
end
↓
function code(x, y, z)
return Float64(x + Float64(Float64(Float64(6.0 * y) + Float64(x * -6.0)) * z))
end
function tmp = code(x, y, z)
tmp = x + (((y - x) * 6.0) * z);
end
↓
function tmp = code(x, y, z)
tmp = x + (((6.0 * y) + (x * -6.0)) * z);
end
code[x_, y_, z_] := N[(x + N[(N[(N[(y - x), $MachinePrecision] * 6.0), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_] := N[(x + N[(N[(N[(6.0 * y), $MachinePrecision] + N[(x * -6.0), $MachinePrecision]), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]
x + \left(\left(y - x\right) \cdot 6\right) \cdot z
↓
x + \left(6 \cdot y + x \cdot -6\right) \cdot z
Alternatives Alternative 1 Accuracy 60.9% Cost 716
\[\begin{array}{l}
\mathbf{if}\;z \leq -2.3 \cdot 10^{-77}:\\
\;\;\;\;\left(6 \cdot y\right) \cdot z\\
\mathbf{elif}\;z \leq 1.8 \cdot 10^{-38}:\\
\;\;\;\;x\\
\mathbf{elif}\;z \leq 8.4 \cdot 10^{+104}:\\
\;\;\;\;y \cdot \left(6 \cdot z\right)\\
\mathbf{else}:\\
\;\;\;\;\left(x \cdot -6\right) \cdot z\\
\end{array}
\]
Alternative 2 Accuracy 61.0% Cost 716
\[\begin{array}{l}
\mathbf{if}\;z \leq -6.6 \cdot 10^{-77}:\\
\;\;\;\;\left(6 \cdot y\right) \cdot z\\
\mathbf{elif}\;z \leq 1.65 \cdot 10^{-38}:\\
\;\;\;\;x\\
\mathbf{elif}\;z \leq 6 \cdot 10^{+104}:\\
\;\;\;\;y \cdot \left(6 \cdot z\right)\\
\mathbf{else}:\\
\;\;\;\;x \cdot \left(-6 \cdot z\right)\\
\end{array}
\]
Alternative 3 Accuracy 83.9% Cost 713
\[\begin{array}{l}
\mathbf{if}\;z \leq -1.16 \cdot 10^{-76} \lor \neg \left(z \leq 1.65 \cdot 10^{-38}\right):\\
\;\;\;\;\left(y - x\right) \cdot \left(6 \cdot z\right)\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
Alternative 4 Accuracy 98.7% Cost 713
\[\begin{array}{l}
\mathbf{if}\;z \leq -0.165 \lor \neg \left(z \leq 0.17\right):\\
\;\;\;\;\left(y - x\right) \cdot \left(6 \cdot z\right)\\
\mathbf{else}:\\
\;\;\;\;x + y \cdot \left(6 \cdot z\right)\\
\end{array}
\]
Alternative 5 Accuracy 61.2% Cost 585
\[\begin{array}{l}
\mathbf{if}\;z \leq -3.15 \cdot 10^{-77} \lor \neg \left(z \leq 1.85 \cdot 10^{-38}\right):\\
\;\;\;\;6 \cdot \left(y \cdot z\right)\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
Alternative 6 Accuracy 61.2% Cost 584
\[\begin{array}{l}
\mathbf{if}\;z \leq -9.2 \cdot 10^{-82}:\\
\;\;\;\;6 \cdot \left(y \cdot z\right)\\
\mathbf{elif}\;z \leq 1.65 \cdot 10^{-38}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;y \cdot \left(6 \cdot z\right)\\
\end{array}
\]
Alternative 7 Accuracy 61.1% Cost 584
\[\begin{array}{l}
\mathbf{if}\;z \leq -1.25 \cdot 10^{-86}:\\
\;\;\;\;\left(6 \cdot y\right) \cdot z\\
\mathbf{elif}\;z \leq 1.7 \cdot 10^{-38}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;y \cdot \left(6 \cdot z\right)\\
\end{array}
\]
Alternative 8 Accuracy 99.7% Cost 576
\[x + z \cdot \left(6 \cdot \left(y - x\right)\right)
\]
Alternative 9 Accuracy 36.8% Cost 64
\[x
\]