Math FPCore C Julia Wolfram TeX \[\frac{60 \cdot \left(x - y\right)}{z - t} + a \cdot 120
\]
↓
\[\mathsf{fma}\left(a, 120, \frac{60}{z - t} \cdot \left(x - y\right)\right)
\]
(FPCore (x y z t a)
:precision binary64
(+ (/ (* 60.0 (- x y)) (- z t)) (* a 120.0))) ↓
(FPCore (x y z t a)
:precision binary64
(fma a 120.0 (* (/ 60.0 (- z t)) (- x y)))) double code(double x, double y, double z, double t, double a) {
return ((60.0 * (x - y)) / (z - t)) + (a * 120.0);
}
↓
double code(double x, double y, double z, double t, double a) {
return fma(a, 120.0, ((60.0 / (z - t)) * (x - y)));
}
function code(x, y, z, t, a)
return Float64(Float64(Float64(60.0 * Float64(x - y)) / Float64(z - t)) + Float64(a * 120.0))
end
↓
function code(x, y, z, t, a)
return fma(a, 120.0, Float64(Float64(60.0 / Float64(z - t)) * Float64(x - y)))
end
code[x_, y_, z_, t_, a_] := N[(N[(N[(60.0 * N[(x - y), $MachinePrecision]), $MachinePrecision] / N[(z - t), $MachinePrecision]), $MachinePrecision] + N[(a * 120.0), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_, a_] := N[(a * 120.0 + N[(N[(60.0 / N[(z - t), $MachinePrecision]), $MachinePrecision] * N[(x - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{60 \cdot \left(x - y\right)}{z - t} + a \cdot 120
↓
\mathsf{fma}\left(a, 120, \frac{60}{z - t} \cdot \left(x - y\right)\right)
Alternatives Alternative 1 Accuracy 76.5% Cost 1225
\[\begin{array}{l}
\mathbf{if}\;a \cdot 120 \leq -1 \cdot 10^{-144} \lor \neg \left(a \cdot 120 \leq 10^{-67}\right):\\
\;\;\;\;\frac{-60}{\frac{z - t}{y}} + a \cdot 120\\
\mathbf{else}:\\
\;\;\;\;60 \cdot \frac{x - y}{z - t}\\
\end{array}
\]
Alternative 2 Accuracy 56.3% Cost 1108
\[\begin{array}{l}
t_1 := 60 \cdot \frac{x}{z - t}\\
t_2 := -60 \cdot \frac{y}{z - t}\\
\mathbf{if}\;a \leq -5.5 \cdot 10^{-147}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \leq -2.5 \cdot 10^{-298}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;a \leq 2.35 \cdot 10^{-247}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq 3.1 \cdot 10^{-128}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;a \leq 7.8 \cdot 10^{-81}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 3 Accuracy 56.3% Cost 1108
\[\begin{array}{l}
t_1 := 60 \cdot \frac{x}{z - t}\\
\mathbf{if}\;a \leq -3.3 \cdot 10^{-147}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \leq -3.6 \cdot 10^{-298}:\\
\;\;\;\;y \cdot \frac{-60}{z - t}\\
\mathbf{elif}\;a \leq 2.3 \cdot 10^{-247}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq 1.75 \cdot 10^{-131}:\\
\;\;\;\;-60 \cdot \frac{y}{z - t}\\
\mathbf{elif}\;a \leq 9 \cdot 10^{-83}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 4 Accuracy 56.2% Cost 1108
\[\begin{array}{l}
\mathbf{if}\;a \leq -8.8 \cdot 10^{-147}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \leq -5.5 \cdot 10^{-298}:\\
\;\;\;\;y \cdot \frac{-60}{z - t}\\
\mathbf{elif}\;a \leq 6.2 \cdot 10^{-248}:\\
\;\;\;\;60 \cdot \frac{x}{z - t}\\
\mathbf{elif}\;a \leq 7.5 \cdot 10^{-129}:\\
\;\;\;\;-60 \cdot \frac{y}{z - t}\\
\mathbf{elif}\;a \leq 7.2 \cdot 10^{-87}:\\
\;\;\;\;\frac{60}{\frac{z - t}{x}}\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 5 Accuracy 69.7% Cost 1096
\[\begin{array}{l}
\mathbf{if}\;a \cdot 120 \leq -1 \cdot 10^{+23}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \cdot 120 \leq 10^{-67}:\\
\;\;\;\;60 \cdot \frac{x - y}{z - t}\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 6 Accuracy 55.4% Cost 976
\[\begin{array}{l}
t_1 := -60 \cdot \frac{y}{z - t}\\
\mathbf{if}\;a \leq -1.95 \cdot 10^{-147}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \leq 1.52 \cdot 10^{-301}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq 2 \cdot 10^{-265}:\\
\;\;\;\;-60 \cdot \frac{x}{t}\\
\mathbf{elif}\;a \leq 9.5 \cdot 10^{-129}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 7 Accuracy 81.5% Cost 969
\[\begin{array}{l}
\mathbf{if}\;y \leq -2.6 \cdot 10^{+115} \lor \neg \left(y \leq 2.1 \cdot 10^{+70}\right):\\
\;\;\;\;\frac{-60}{\frac{z - t}{y}} + a \cdot 120\\
\mathbf{else}:\\
\;\;\;\;\frac{x}{\frac{z - t}{60}} + a \cdot 120\\
\end{array}
\]
Alternative 8 Accuracy 81.4% Cost 969
\[\begin{array}{l}
\mathbf{if}\;y \leq -3.3 \cdot 10^{+115} \lor \neg \left(y \leq 1.15 \cdot 10^{+69}\right):\\
\;\;\;\;\frac{-60}{\frac{z - t}{y}} + a \cdot 120\\
\mathbf{else}:\\
\;\;\;\;\frac{60 \cdot x}{z - t} + a \cdot 120\\
\end{array}
\]
Alternative 9 Accuracy 50.0% Cost 848
\[\begin{array}{l}
t_1 := 60 \cdot \frac{x}{z}\\
\mathbf{if}\;a \leq -1.55 \cdot 10^{-214}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \leq 5.7 \cdot 10^{-297}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq 3.4 \cdot 10^{-118}:\\
\;\;\;\;-60 \cdot \frac{x}{t}\\
\mathbf{elif}\;a \leq 1.1 \cdot 10^{-87}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 10 Accuracy 50.0% Cost 848
\[\begin{array}{l}
t_1 := 60 \cdot \frac{x}{z}\\
\mathbf{if}\;a \leq -3.9 \cdot 10^{-215}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \leq 8.2 \cdot 10^{-300}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq 1.55 \cdot 10^{-115}:\\
\;\;\;\;\frac{x \cdot -60}{t}\\
\mathbf{elif}\;a \leq 1.45 \cdot 10^{-87}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 11 Accuracy 91.2% Cost 832
\[\frac{60}{z - t} \cdot \left(x - y\right) + a \cdot 120
\]
Alternative 12 Accuracy 50.4% Cost 716
\[\begin{array}{l}
\mathbf{if}\;a \leq -6.2 \cdot 10^{-198}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \leq -4.4 \cdot 10^{-304}:\\
\;\;\;\;-60 \cdot \frac{y}{z}\\
\mathbf{elif}\;a \leq 1.9 \cdot 10^{-111}:\\
\;\;\;\;-60 \cdot \frac{x}{t}\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 13 Accuracy 50.5% Cost 584
\[\begin{array}{l}
\mathbf{if}\;a \leq -1.62 \cdot 10^{-177}:\\
\;\;\;\;a \cdot 120\\
\mathbf{elif}\;a \leq 1.9 \cdot 10^{-111}:\\
\;\;\;\;-60 \cdot \frac{x}{t}\\
\mathbf{else}:\\
\;\;\;\;a \cdot 120\\
\end{array}
\]
Alternative 14 Accuracy 49.9% Cost 192
\[a \cdot 120
\]