Math FPCore C Julia Wolfram TeX \[\left(\left(\left(\left(x \cdot \log y + z\right) + t\right) + a\right) + \left(b - 0.5\right) \cdot \log c\right) + y \cdot i
\]
↓
\[\begin{array}{l}
t_1 := \left(\left(\left(\left(x \cdot \log y + z\right) + t\right) + a\right) + \log c \cdot b\right) + y \cdot i\\
\mathbf{if}\;x \leq -1.3 \cdot 10^{+66}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 10^{-84}:\\
\;\;\;\;\mathsf{fma}\left(i, y, \left(b - 0.5\right) \cdot \log c + \left(a + \left(t + z\right)\right)\right)\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
(FPCore (x y z t a b c i)
:precision binary64
(+ (+ (+ (+ (+ (* x (log y)) z) t) a) (* (- b 0.5) (log c))) (* y i))) ↓
(FPCore (x y z t a b c i)
:precision binary64
(let* ((t_1 (+ (+ (+ (+ (+ (* x (log y)) z) t) a) (* (log c) b)) (* y i))))
(if (<= x -1.3e+66)
t_1
(if (<= x 1e-84) (fma i y (+ (* (- b 0.5) (log c)) (+ a (+ t z)))) t_1)))) double code(double x, double y, double z, double t, double a, double b, double c, double i) {
return (((((x * log(y)) + z) + t) + a) + ((b - 0.5) * log(c))) + (y * i);
}
↓
double code(double x, double y, double z, double t, double a, double b, double c, double i) {
double t_1 = (((((x * log(y)) + z) + t) + a) + (log(c) * b)) + (y * i);
double tmp;
if (x <= -1.3e+66) {
tmp = t_1;
} else if (x <= 1e-84) {
tmp = fma(i, y, (((b - 0.5) * log(c)) + (a + (t + z))));
} else {
tmp = t_1;
}
return tmp;
}
function code(x, y, z, t, a, b, c, i)
return Float64(Float64(Float64(Float64(Float64(Float64(x * log(y)) + z) + t) + a) + Float64(Float64(b - 0.5) * log(c))) + Float64(y * i))
end
↓
function code(x, y, z, t, a, b, c, i)
t_1 = Float64(Float64(Float64(Float64(Float64(Float64(x * log(y)) + z) + t) + a) + Float64(log(c) * b)) + Float64(y * i))
tmp = 0.0
if (x <= -1.3e+66)
tmp = t_1;
elseif (x <= 1e-84)
tmp = fma(i, y, Float64(Float64(Float64(b - 0.5) * log(c)) + Float64(a + Float64(t + z))));
else
tmp = t_1;
end
return tmp
end
code[x_, y_, z_, t_, a_, b_, c_, i_] := N[(N[(N[(N[(N[(N[(x * N[Log[y], $MachinePrecision]), $MachinePrecision] + z), $MachinePrecision] + t), $MachinePrecision] + a), $MachinePrecision] + N[(N[(b - 0.5), $MachinePrecision] * N[Log[c], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y * i), $MachinePrecision]), $MachinePrecision]
↓
code[x_, y_, z_, t_, a_, b_, c_, i_] := Block[{t$95$1 = N[(N[(N[(N[(N[(N[(x * N[Log[y], $MachinePrecision]), $MachinePrecision] + z), $MachinePrecision] + t), $MachinePrecision] + a), $MachinePrecision] + N[(N[Log[c], $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision] + N[(y * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.3e+66], t$95$1, If[LessEqual[x, 1e-84], N[(i * y + N[(N[(N[(b - 0.5), $MachinePrecision] * N[Log[c], $MachinePrecision]), $MachinePrecision] + N[(a + N[(t + z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]
\left(\left(\left(\left(x \cdot \log y + z\right) + t\right) + a\right) + \left(b - 0.5\right) \cdot \log c\right) + y \cdot i
↓
\begin{array}{l}
t_1 := \left(\left(\left(\left(x \cdot \log y + z\right) + t\right) + a\right) + \log c \cdot b\right) + y \cdot i\\
\mathbf{if}\;x \leq -1.3 \cdot 10^{+66}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;x \leq 10^{-84}:\\
\;\;\;\;\mathsf{fma}\left(i, y, \left(b - 0.5\right) \cdot \log c + \left(a + \left(t + z\right)\right)\right)\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
Alternatives Alternative 1 Error 0.1 Cost 32832
\[\mathsf{fma}\left(i, y, \mathsf{fma}\left(\log c, b + -0.5, \mathsf{fma}\left(\log y, x, z + t\right) + a\right)\right)
\]
Alternative 2 Error 0.1 Cost 14016
\[\left(\left(\left(\left(x \cdot \log y + z\right) + t\right) + a\right) + \left(b - 0.5\right) \cdot \log c\right) + y \cdot i
\]
Alternative 3 Error 11.0 Cost 13632
\[\mathsf{fma}\left(i, y, \left(b - 0.5\right) \cdot \log c + \left(a + \left(t + z\right)\right)\right)
\]
Alternative 4 Error 37.4 Cost 7772
\[\begin{array}{l}
t_1 := \log c \cdot b + i \cdot y\\
t_2 := a + y \cdot i\\
t_3 := z + y \cdot i\\
\mathbf{if}\;a \leq -2.6 \cdot 10^{+142}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;a \leq -1.5 \cdot 10^{-51}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq -3.1 \cdot 10^{-233}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;a \leq -5.8 \cdot 10^{-292}:\\
\;\;\;\;t + y \cdot i\\
\mathbf{elif}\;a \leq 1.2 \cdot 10^{-239}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq 1.38 \cdot 10^{-16}:\\
\;\;\;\;t_3\\
\mathbf{elif}\;a \leq 7.5 \cdot 10^{+55}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq 2.65 \cdot 10^{+88}:\\
\;\;\;\;t_3\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 5 Error 11.0 Cost 7360
\[\left(\left(b - 0.5\right) \cdot \log c + \left(a + \left(t + z\right)\right)\right) + y \cdot i
\]
Alternative 6 Error 37.9 Cost 848
\[\begin{array}{l}
t_1 := a + y \cdot i\\
t_2 := z + y \cdot i\\
\mathbf{if}\;z \leq -7.6 \cdot 10^{+132}:\\
\;\;\;\;t_2\\
\mathbf{elif}\;z \leq 9.5 \cdot 10^{-247}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;z \leq 2.15 \cdot 10^{-139}:\\
\;\;\;\;t + y \cdot i\\
\mathbf{elif}\;z \leq 2.9 \cdot 10^{+139}:\\
\;\;\;\;t_1\\
\mathbf{else}:\\
\;\;\;\;t_2\\
\end{array}
\]
Alternative 7 Error 46.8 Cost 720
\[\begin{array}{l}
\mathbf{if}\;a \leq -1.4 \cdot 10^{+163}:\\
\;\;\;\;a\\
\mathbf{elif}\;a \leq 2 \cdot 10^{-219}:\\
\;\;\;\;y \cdot i\\
\mathbf{elif}\;a \leq 7.5 \cdot 10^{-18}:\\
\;\;\;\;t\\
\mathbf{elif}\;a \leq 7.5 \cdot 10^{+90}:\\
\;\;\;\;y \cdot i\\
\mathbf{else}:\\
\;\;\;\;a\\
\end{array}
\]
Alternative 8 Error 38.7 Cost 584
\[\begin{array}{l}
\mathbf{if}\;t \leq -8.8 \cdot 10^{+224}:\\
\;\;\;\;t\\
\mathbf{elif}\;t \leq 3.9 \cdot 10^{+179}:\\
\;\;\;\;a + y \cdot i\\
\mathbf{else}:\\
\;\;\;\;t\\
\end{array}
\]
Alternative 9 Error 37.3 Cost 584
\[\begin{array}{l}
t_1 := a + y \cdot i\\
\mathbf{if}\;a \leq -1.15 \cdot 10^{+124}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;a \leq 5.2 \cdot 10^{+79}:\\
\;\;\;\;t + y \cdot i\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 10 Error 44.7 Cost 328
\[\begin{array}{l}
\mathbf{if}\;a \leq -1.4 \cdot 10^{+114}:\\
\;\;\;\;a\\
\mathbf{elif}\;a \leq 9.5 \cdot 10^{+73}:\\
\;\;\;\;t\\
\mathbf{else}:\\
\;\;\;\;a\\
\end{array}
\]
Alternative 11 Error 52.1 Cost 64
\[a
\]