Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\frac{x \cdot x}{y \cdot y} + \frac{z \cdot z}{t \cdot t}
\]
↓
\[\frac{\frac{x}{y}}{\frac{y}{x}} + \frac{\frac{z}{t}}{\frac{t}{z}}
\]
(FPCore (x y z t)
:precision binary64
(+ (/ (* x x) (* y y)) (/ (* z z) (* t t)))) ↓
(FPCore (x y z t)
:precision binary64
(+ (/ (/ x y) (/ y x)) (/ (/ z t) (/ t z)))) double code(double x, double y, double z, double t) {
return ((x * x) / (y * y)) + ((z * z) / (t * t));
}
↓
double code(double x, double y, double z, double t) {
return ((x / y) / (y / x)) + ((z / t) / (t / z));
}
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x * x) / (y * y)) + ((z * z) / (t * t))
end function
↓
real(8) function code(x, y, z, t)
real(8), intent (in) :: x
real(8), intent (in) :: y
real(8), intent (in) :: z
real(8), intent (in) :: t
code = ((x / y) / (y / x)) + ((z / t) / (t / z))
end function
public static double code(double x, double y, double z, double t) {
return ((x * x) / (y * y)) + ((z * z) / (t * t));
}
↓
public static double code(double x, double y, double z, double t) {
return ((x / y) / (y / x)) + ((z / t) / (t / z));
}
def code(x, y, z, t):
return ((x * x) / (y * y)) + ((z * z) / (t * t))
↓
def code(x, y, z, t):
return ((x / y) / (y / x)) + ((z / t) / (t / z))
function code(x, y, z, t)
return Float64(Float64(Float64(x * x) / Float64(y * y)) + Float64(Float64(z * z) / Float64(t * t)))
end
↓
function code(x, y, z, t)
return Float64(Float64(Float64(x / y) / Float64(y / x)) + Float64(Float64(z / t) / Float64(t / z)))
end
function tmp = code(x, y, z, t)
tmp = ((x * x) / (y * y)) + ((z * z) / (t * t));
end
↓
function tmp = code(x, y, z, t)
tmp = ((x / y) / (y / x)) + ((z / t) / (t / z));
end
code[x_, y_, z_, t_] := N[(N[(N[(x * x), $MachinePrecision] / N[(y * y), $MachinePrecision]), $MachinePrecision] + N[(N[(z * z), $MachinePrecision] / N[(t * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_] := N[(N[(N[(x / y), $MachinePrecision] / N[(y / x), $MachinePrecision]), $MachinePrecision] + N[(N[(z / t), $MachinePrecision] / N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{x \cdot x}{y \cdot y} + \frac{z \cdot z}{t \cdot t}
↓
\frac{\frac{x}{y}}{\frac{y}{x}} + \frac{\frac{z}{t}}{\frac{t}{z}}
Alternatives Alternative 1 Accuracy 80.6% Cost 1996
\[\begin{array}{l}
t_1 := \frac{x \cdot x}{y \cdot y}\\
t_2 := \frac{z}{t} \cdot \frac{z}{t}\\
\mathbf{if}\;t_1 \leq 0:\\
\;\;\;\;t_2\\
\mathbf{elif}\;t_1 \leq 2 \cdot 10^{-77}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t_1 \leq 5 \cdot 10^{-60}:\\
\;\;\;\;t_2\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{y} \cdot \frac{x}{y}\\
\end{array}
\]
Alternative 2 Accuracy 81.1% Cost 1996
\[\begin{array}{l}
t_1 := \frac{z \cdot z}{t \cdot t}\\
t_2 := \frac{x}{y} \cdot \frac{x}{y}\\
\mathbf{if}\;t_1 \leq 4 \cdot 10^{-246}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;t_1 \leq 5 \cdot 10^{-54}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t_1 \leq 200000000000:\\
\;\;\;\;t_2\\
\mathbf{else}:\\
\;\;\;\;\frac{z}{t} \cdot \frac{z}{t}\\
\end{array}
\]
Alternative 3 Accuracy 81.1% Cost 1996
\[\begin{array}{l}
t_1 := \frac{z \cdot z}{t \cdot t}\\
t_2 := \frac{\frac{x}{y}}{\frac{y}{x}}\\
\mathbf{if}\;t_1 \leq 4 \cdot 10^{-246}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;t_1 \leq 5 \cdot 10^{-54}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t_1 \leq 200000000000:\\
\;\;\;\;t_2\\
\mathbf{else}:\\
\;\;\;\;\frac{z}{t} \cdot \frac{z}{t}\\
\end{array}
\]
Alternative 4 Accuracy 85.3% Cost 1992
\[\begin{array}{l}
t_1 := \frac{z \cdot z}{t \cdot t}\\
\mathbf{if}\;t_1 \leq 5 \cdot 10^{-288}:\\
\;\;\;\;\frac{\frac{x}{y}}{\frac{y}{x}}\\
\mathbf{elif}\;t_1 \leq 10^{+261}:\\
\;\;\;\;z \cdot \frac{\frac{z}{t}}{t} + x \cdot \frac{x}{y \cdot y}\\
\mathbf{else}:\\
\;\;\;\;\frac{z}{t} \cdot \frac{z}{t}\\
\end{array}
\]
Alternative 5 Accuracy 67.5% Cost 1505
\[\begin{array}{l}
t_1 := \frac{z}{t} \cdot \frac{z}{t}\\
t_2 := \frac{x}{y} \cdot \frac{x}{y}\\
t_3 := x \cdot \frac{x}{y \cdot y}\\
\mathbf{if}\;y \leq -1.22 \cdot 10^{+44}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq -7.5 \cdot 10^{-76}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;y \leq -8 \cdot 10^{-152}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 2.4 \cdot 10^{-150}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;y \leq 9.5 \cdot 10^{-89}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;y \leq 1.1 \cdot 10^{+31}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;y \leq 3.1 \cdot 10^{+47} \lor \neg \left(y \leq 2.5 \cdot 10^{+138}\right):\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 6 Accuracy 99.3% Cost 960
\[\frac{z}{t} \cdot \frac{z}{t} + \frac{x}{y} \cdot \frac{x}{y}
\]
Alternative 7 Accuracy 99.4% Cost 960
\[\frac{\frac{z}{t}}{\frac{t}{z}} + \frac{x}{y} \cdot \frac{x}{y}
\]
Alternative 8 Accuracy 99.4% Cost 960
\[\frac{\frac{x}{y}}{\frac{y}{x}} + \frac{z}{t} \cdot \frac{z}{t}
\]
Alternative 9 Accuracy 58.5% Cost 448
\[\frac{x}{y} \cdot \frac{x}{y}
\]