Math FPCore C Julia Wolfram TeX \[x - \frac{y - z}{\frac{\left(t - z\right) + 1}{a}}
\]
↓
\[\mathsf{fma}\left(a, \frac{z - y}{\left(t - z\right) + 1}, x\right)
\]
(FPCore (x y z t a)
:precision binary64
(- x (/ (- y z) (/ (+ (- t z) 1.0) a)))) ↓
(FPCore (x y z t a) :precision binary64 (fma a (/ (- z y) (+ (- t z) 1.0)) x)) double code(double x, double y, double z, double t, double a) {
return x - ((y - z) / (((t - z) + 1.0) / a));
}
↓
double code(double x, double y, double z, double t, double a) {
return fma(a, ((z - y) / ((t - z) + 1.0)), x);
}
function code(x, y, z, t, a)
return Float64(x - Float64(Float64(y - z) / Float64(Float64(Float64(t - z) + 1.0) / a)))
end
↓
function code(x, y, z, t, a)
return fma(a, Float64(Float64(z - y) / Float64(Float64(t - z) + 1.0)), x)
end
code[x_, y_, z_, t_, a_] := N[(x - N[(N[(y - z), $MachinePrecision] / N[(N[(N[(t - z), $MachinePrecision] + 1.0), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_, a_] := N[(a * N[(N[(z - y), $MachinePrecision] / N[(N[(t - z), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision] + x), $MachinePrecision]
x - \frac{y - z}{\frac{\left(t - z\right) + 1}{a}}
↓
\mathsf{fma}\left(a, \frac{z - y}{\left(t - z\right) + 1}, x\right)
Alternatives Alternative 1 Accuracy 68.7% Cost 1240
\[\begin{array}{l}
t_1 := x - a \cdot y\\
t_2 := x + z \cdot \frac{a}{t}\\
\mathbf{if}\;t \leq -1.5 \cdot 10^{+170}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;t \leq -5.6 \cdot 10^{-208}:\\
\;\;\;\;x - a\\
\mathbf{elif}\;t \leq 6.4 \cdot 10^{-267}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq 1.05 \cdot 10^{-174}:\\
\;\;\;\;x - a\\
\mathbf{elif}\;t \leq 7.6 \cdot 10^{-52}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq 6.7 \cdot 10^{+136}:\\
\;\;\;\;x - a\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 2 Accuracy 74.7% Cost 1104
\[\begin{array}{l}
t_1 := x + z \cdot \frac{a}{1 - z}\\
t_2 := x - \frac{a}{\frac{t}{y}}\\
\mathbf{if}\;t \leq -7.5 \cdot 10^{+117}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;t \leq 3.8 \cdot 10^{-163}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq 7.8 \cdot 10^{-48}:\\
\;\;\;\;x - a \cdot y\\
\mathbf{elif}\;t \leq 6.8 \cdot 10^{+103}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 3 Accuracy 77.9% Cost 1104
\[\begin{array}{l}
t_1 := x + z \cdot \frac{a}{1 - z}\\
t_2 := x + \frac{a}{t} \cdot \left(z - y\right)\\
\mathbf{if}\;t \leq -1.35 \cdot 10^{+28}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;t \leq 8.8 \cdot 10^{-172}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq 1.26 \cdot 10^{-51}:\\
\;\;\;\;x - a \cdot y\\
\mathbf{elif}\;t \leq 8 \cdot 10^{+86}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 4 Accuracy 71.3% Cost 976
\[\begin{array}{l}
t_1 := x - \frac{a}{\frac{t}{y}}\\
\mathbf{if}\;t \leq -2.4 \cdot 10^{+126}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq 4 \cdot 10^{-165}:\\
\;\;\;\;x - a\\
\mathbf{elif}\;t \leq 3.5 \cdot 10^{-34}:\\
\;\;\;\;x - a \cdot y\\
\mathbf{elif}\;t \leq 2.05 \cdot 10^{-7}:\\
\;\;\;\;x + \frac{a}{\frac{z}{y}}\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 5 Accuracy 71.3% Cost 976
\[\begin{array}{l}
t_1 := x - \frac{a}{\frac{t}{y}}\\
\mathbf{if}\;t \leq -2.1 \cdot 10^{+126}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;t \leq 2.4 \cdot 10^{-165}:\\
\;\;\;\;x - a\\
\mathbf{elif}\;t \leq 3.5 \cdot 10^{-34}:\\
\;\;\;\;x - a \cdot y\\
\mathbf{elif}\;t \leq 2.9 \cdot 10^{-5}:\\
\;\;\;\;x + a \cdot \frac{y}{z}\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 6 Accuracy 89.7% Cost 969
\[\begin{array}{l}
\mathbf{if}\;z \leq -5.2 \cdot 10^{-40} \lor \neg \left(z \leq 185000000\right):\\
\;\;\;\;x + a \cdot \frac{z}{\left(t - z\right) + 1}\\
\mathbf{else}:\\
\;\;\;\;x - a \cdot \frac{y}{t + 1}\\
\end{array}
\]
Alternative 7 Accuracy 70.8% Cost 844
\[\begin{array}{l}
\mathbf{if}\;z \leq -3.3 \cdot 10^{+26}:\\
\;\;\;\;x - a\\
\mathbf{elif}\;z \leq -3.1 \cdot 10^{-222}:\\
\;\;\;\;x + z \cdot \frac{a}{t}\\
\mathbf{elif}\;z \leq 2.6 \cdot 10^{+85}:\\
\;\;\;\;x - \frac{a}{\frac{t}{y}}\\
\mathbf{else}:\\
\;\;\;\;x - a\\
\end{array}
\]
Alternative 8 Accuracy 84.9% Cost 841
\[\begin{array}{l}
\mathbf{if}\;z \leq -9.5 \cdot 10^{+89} \lor \neg \left(z \leq 3.2 \cdot 10^{+85}\right):\\
\;\;\;\;x - a\\
\mathbf{else}:\\
\;\;\;\;x - a \cdot \frac{y}{t + 1}\\
\end{array}
\]
Alternative 9 Accuracy 87.7% Cost 841
\[\begin{array}{l}
\mathbf{if}\;z \leq -3.8 \cdot 10^{+87} \lor \neg \left(z \leq 1.6 \cdot 10^{+32}\right):\\
\;\;\;\;x + \left(y \cdot \frac{a}{z} - a\right)\\
\mathbf{else}:\\
\;\;\;\;x - a \cdot \frac{y}{t + 1}\\
\end{array}
\]
Alternative 10 Accuracy 99.6% Cost 832
\[x + a \cdot \frac{z - y}{\left(t - z\right) + 1}
\]
Alternative 11 Accuracy 70.2% Cost 456
\[\begin{array}{l}
\mathbf{if}\;z \leq -5.9 \cdot 10^{+29}:\\
\;\;\;\;x - a\\
\mathbf{elif}\;z \leq 9.5 \cdot 10^{+28}:\\
\;\;\;\;x\\
\mathbf{else}:\\
\;\;\;\;x - a\\
\end{array}
\]
Alternative 12 Accuracy 57.0% Cost 64
\[x
\]