Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\left(x + \cos y\right) - z \cdot \sin y
\]
↓
\[\left(x + \cos y\right) - \left(\left(1 + \sin y \cdot z\right) + -1\right)
\]
(FPCore (x y z) :precision binary64 (- (+ x (cos y)) (* z (sin y)))) ↓
(FPCore (x y z)
:precision binary64
(- (+ x (cos y)) (+ (+ 1.0 (* (sin y) z)) -1.0))) double code(double x, double y, double z) {
return (x + cos(y)) - (z * sin(y));
}
↓
double code(double x, double y, double z) {
return (x + cos(y)) - ((1.0 + (sin(y) * z)) + -1.0);
}
real(8) function code(x, y, z)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
code = (x + cos(y)) - (z * sin(y))
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 + cos(y)) - ((1.0d0 + (sin(y) * z)) + (-1.0d0))
end function
public static double code(double x, double y, double z) {
return (x + Math.cos(y)) - (z * Math.sin(y));
}
↓
public static double code(double x, double y, double z) {
return (x + Math.cos(y)) - ((1.0 + (Math.sin(y) * z)) + -1.0);
}
def code(x, y, z):
return (x + math.cos(y)) - (z * math.sin(y))
↓
def code(x, y, z):
return (x + math.cos(y)) - ((1.0 + (math.sin(y) * z)) + -1.0)
function code(x, y, z)
return Float64(Float64(x + cos(y)) - Float64(z * sin(y)))
end
↓
function code(x, y, z)
return Float64(Float64(x + cos(y)) - Float64(Float64(1.0 + Float64(sin(y) * z)) + -1.0))
end
function tmp = code(x, y, z)
tmp = (x + cos(y)) - (z * sin(y));
end
↓
function tmp = code(x, y, z)
tmp = (x + cos(y)) - ((1.0 + (sin(y) * z)) + -1.0);
end
code[x_, y_, z_] := N[(N[(x + N[Cos[y], $MachinePrecision]), $MachinePrecision] - N[(z * N[Sin[y], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_] := N[(N[(x + N[Cos[y], $MachinePrecision]), $MachinePrecision] - N[(N[(1.0 + N[(N[Sin[y], $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]), $MachinePrecision]
\left(x + \cos y\right) - z \cdot \sin y
↓
\left(x + \cos y\right) - \left(\left(1 + \sin y \cdot z\right) + -1\right)
Alternatives Alternative 1 Error 10.1% Cost 13384
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.02 \cdot 10^{-10}:\\
\;\;\;\;x + \cos y\\
\mathbf{elif}\;x \leq 4.5 \cdot 10^{+39}:\\
\;\;\;\;\cos y - \sin y \cdot z\\
\mathbf{else}:\\
\;\;\;\;x + 1\\
\end{array}
\]
Alternative 2 Error 0.08% Cost 13248
\[\left(x + \cos y\right) - \sin y \cdot z
\]
Alternative 3 Error 17.72% Cost 6921
\[\begin{array}{l}
\mathbf{if}\;z \leq -3.1 \cdot 10^{+177} \lor \neg \left(z \leq 5.2 \cdot 10^{+183}\right):\\
\;\;\;\;\sin y \cdot \left(-z\right)\\
\mathbf{else}:\\
\;\;\;\;x + \cos y\\
\end{array}
\]
Alternative 4 Error 18.44% Cost 6857
\[\begin{array}{l}
\mathbf{if}\;y \leq -0.0056 \lor \neg \left(y \leq 2.4\right):\\
\;\;\;\;x + \cos y\\
\mathbf{else}:\\
\;\;\;\;1 + \left(x - y \cdot z\right)\\
\end{array}
\]
Alternative 5 Error 29.61% Cost 968
\[\begin{array}{l}
\mathbf{if}\;y \leq -100000:\\
\;\;\;\;x + 1\\
\mathbf{elif}\;y \leq 1.1 \cdot 10^{+49}:\\
\;\;\;\;\left(x + 1\right) + y \cdot \left(y \cdot -0.5 - z\right)\\
\mathbf{else}:\\
\;\;\;\;x + 1\\
\end{array}
\]
Alternative 6 Error 29.39% Cost 712
\[\begin{array}{l}
\mathbf{if}\;y \leq -16500:\\
\;\;\;\;x + 1\\
\mathbf{elif}\;y \leq 1.65 \cdot 10^{+27}:\\
\;\;\;\;1 + \left(x - y \cdot z\right)\\
\mathbf{else}:\\
\;\;\;\;x + 1\\
\end{array}
\]
Alternative 7 Error 32.4% Cost 584
\[\begin{array}{l}
\mathbf{if}\;x \leq -1.95 \cdot 10^{-13}:\\
\;\;\;\;x + 1\\
\mathbf{elif}\;x \leq 3.3 \cdot 10^{-13}:\\
\;\;\;\;1 - y \cdot z\\
\mathbf{else}:\\
\;\;\;\;x + 1\\
\end{array}
\]
Alternative 8 Error 37.87% Cost 388
\[\begin{array}{l}
\mathbf{if}\;z \leq -1.5 \cdot 10^{+262}:\\
\;\;\;\;y \cdot \left(-z\right)\\
\mathbf{else}:\\
\;\;\;\;x + 1\\
\end{array}
\]
Alternative 9 Error 38.7% Cost 328
\[\begin{array}{l}
\mathbf{if}\;x \leq -0.0033:\\
\;\;\;\;x\\
\mathbf{elif}\;x \leq 0.245:\\
\;\;\;\;1\\
\mathbf{else}:\\
\;\;\;\;x\\
\end{array}
\]
Alternative 10 Error 37.95% Cost 192
\[x + 1
\]
Alternative 11 Error 78.64% Cost 64
\[1
\]