Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\left(0.5 \cdot \sin re\right) \cdot \left(e^{0 - im} + e^{im}\right)
\]
↓
\[\left(0.5 \cdot \sin re\right) \cdot \left(e^{-im} + e^{im}\right)
\]
(FPCore (re im)
:precision binary64
(* (* 0.5 (sin re)) (+ (exp (- 0.0 im)) (exp im)))) ↓
(FPCore (re im)
:precision binary64
(* (* 0.5 (sin re)) (+ (exp (- im)) (exp im)))) double code(double re, double im) {
return (0.5 * sin(re)) * (exp((0.0 - im)) + exp(im));
}
↓
double code(double re, double im) {
return (0.5 * sin(re)) * (exp(-im) + exp(im));
}
real(8) function code(re, im)
real(8), intent (in) :: re
real(8), intent (in) :: im
code = (0.5d0 * sin(re)) * (exp((0.0d0 - im)) + exp(im))
end function
↓
real(8) function code(re, im)
real(8), intent (in) :: re
real(8), intent (in) :: im
code = (0.5d0 * sin(re)) * (exp(-im) + exp(im))
end function
public static double code(double re, double im) {
return (0.5 * Math.sin(re)) * (Math.exp((0.0 - im)) + Math.exp(im));
}
↓
public static double code(double re, double im) {
return (0.5 * Math.sin(re)) * (Math.exp(-im) + Math.exp(im));
}
def code(re, im):
return (0.5 * math.sin(re)) * (math.exp((0.0 - im)) + math.exp(im))
↓
def code(re, im):
return (0.5 * math.sin(re)) * (math.exp(-im) + math.exp(im))
function code(re, im)
return Float64(Float64(0.5 * sin(re)) * Float64(exp(Float64(0.0 - im)) + exp(im)))
end
↓
function code(re, im)
return Float64(Float64(0.5 * sin(re)) * Float64(exp(Float64(-im)) + exp(im)))
end
function tmp = code(re, im)
tmp = (0.5 * sin(re)) * (exp((0.0 - im)) + exp(im));
end
↓
function tmp = code(re, im)
tmp = (0.5 * sin(re)) * (exp(-im) + exp(im));
end
code[re_, im_] := N[(N[(0.5 * N[Sin[re], $MachinePrecision]), $MachinePrecision] * N[(N[Exp[N[(0.0 - im), $MachinePrecision]], $MachinePrecision] + N[Exp[im], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[re_, im_] := N[(N[(0.5 * N[Sin[re], $MachinePrecision]), $MachinePrecision] * N[(N[Exp[(-im)], $MachinePrecision] + N[Exp[im], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\left(0.5 \cdot \sin re\right) \cdot \left(e^{0 - im} + e^{im}\right)
↓
\left(0.5 \cdot \sin re\right) \cdot \left(e^{-im} + e^{im}\right)
Alternatives Alternative 1 Accuracy 96.2% Cost 14092
\[\begin{array}{l}
t_0 := re \cdot \mathsf{log1p}\left(\mathsf{expm1}\left(0.5 \cdot \left(im \cdot im\right)\right)\right)\\
t_1 := 0.041666666666666664 \cdot \left(\sin re \cdot {im}^{4}\right)\\
\mathbf{if}\;im \leq -1.35 \cdot 10^{+83}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;im \leq -650:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq 580:\\
\;\;\;\;\left(0.5 \cdot \sin re\right) \cdot \left(2 + \left(im \cdot im + {im}^{4} \cdot 0.08333333333333333\right)\right)\\
\mathbf{elif}\;im \leq 4.9 \cdot 10^{+73}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 2 Accuracy 96.1% Cost 13776
\[\begin{array}{l}
t_0 := re \cdot \mathsf{log1p}\left(\mathsf{expm1}\left(0.5 \cdot \left(im \cdot im\right)\right)\right)\\
t_1 := 0.041666666666666664 \cdot \left(\sin re \cdot {im}^{4}\right)\\
\mathbf{if}\;im \leq -1.35 \cdot 10^{+83}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;im \leq -600:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq 580:\\
\;\;\;\;\left(0.5 \cdot \sin re\right) \cdot \left(im \cdot im + 2\right)\\
\mathbf{elif}\;im \leq 4.9 \cdot 10^{+73}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 3 Accuracy 96.1% Cost 13776
\[\begin{array}{l}
t_0 := re \cdot \mathsf{log1p}\left(\mathsf{expm1}\left(0.5 \cdot \left(im \cdot im\right)\right)\right)\\
t_1 := 0.041666666666666664 \cdot \left(\sin re \cdot {im}^{4}\right)\\
\mathbf{if}\;im \leq -1.35 \cdot 10^{+83}:\\
\;\;\;\;t_1\\
\mathbf{elif}\;im \leq -550:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq 620:\\
\;\;\;\;\sin re + 0.5 \cdot \left(\sin re \cdot \left(im \cdot im\right)\right)\\
\mathbf{elif}\;im \leq 4.9 \cdot 10^{+73}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 4 Accuracy 88.9% Cost 13712
\[\begin{array}{l}
t_0 := 0.041666666666666664 \cdot \left(\sin re \cdot {im}^{4}\right)\\
\mathbf{if}\;im \leq -1.3 \cdot 10^{+62}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq -54000:\\
\;\;\;\;re \cdot \left(0.041666666666666664 \cdot {im}^{4}\right)\\
\mathbf{elif}\;im \leq 14000:\\
\;\;\;\;\left(0.5 \cdot \sin re\right) \cdot \left(im \cdot im + 2\right)\\
\mathbf{elif}\;im \leq 1.1 \cdot 10^{+76}:\\
\;\;\;\;\left(im \cdot im\right) \cdot \left(0.5 \cdot re + -0.08333333333333333 \cdot {re}^{3}\right)\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 5 Accuracy 86.6% Cost 7696
\[\begin{array}{l}
t_0 := \left(im \cdot im\right) \cdot \left(\left(im \cdot im\right) \cdot \left(\sin re \cdot 0.041666666666666664\right)\right)\\
\mathbf{if}\;im \leq -1.15 \cdot 10^{+101}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq -290:\\
\;\;\;\;re \cdot \left(0.041666666666666664 \cdot {im}^{4}\right)\\
\mathbf{elif}\;im \leq 13500:\\
\;\;\;\;\left(0.5 \cdot \sin re\right) \cdot \left(im \cdot im + 2\right)\\
\mathbf{elif}\;im \leq 1.7 \cdot 10^{+77}:\\
\;\;\;\;\left(im \cdot im\right) \cdot \left(0.5 \cdot re + -0.08333333333333333 \cdot {re}^{3}\right)\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 6 Accuracy 85.8% Cost 7500
\[\begin{array}{l}
t_0 := \left(im \cdot im\right) \cdot \left(\left(im \cdot im\right) \cdot \left(\sin re \cdot 0.041666666666666664\right)\right)\\
\mathbf{if}\;im \leq -2.7 \cdot 10^{+98}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq -190000:\\
\;\;\;\;re \cdot \left(0.041666666666666664 \cdot {im}^{4}\right)\\
\mathbf{elif}\;im \leq 3.7:\\
\;\;\;\;\left(0.5 \cdot \sin re\right) \cdot \left(im \cdot im + 2\right)\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 7 Accuracy 82.1% Cost 7308
\[\begin{array}{l}
t_0 := re \cdot \left(1 + 0.041666666666666664 \cdot {im}^{4}\right)\\
\mathbf{if}\;im \leq -1.46 \cdot 10^{-7}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq 4.1 \cdot 10^{+21}:\\
\;\;\;\;\sin re\\
\mathbf{elif}\;im \leq 3.9 \cdot 10^{+151}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;\sin re \cdot \left(0.5 \cdot \left(im \cdot im\right)\right)\\
\end{array}
\]
Alternative 8 Accuracy 82.6% Cost 7308
\[\begin{array}{l}
t_0 := 0.041666666666666664 \cdot {im}^{4}\\
\mathbf{if}\;im \leq -12500:\\
\;\;\;\;re \cdot t_0\\
\mathbf{elif}\;im \leq 1.35 \cdot 10^{+21}:\\
\;\;\;\;\left(0.5 \cdot \sin re\right) \cdot \left(im \cdot im + 2\right)\\
\mathbf{elif}\;im \leq 3.9 \cdot 10^{+151}:\\
\;\;\;\;re \cdot \left(1 + t_0\right)\\
\mathbf{else}:\\
\;\;\;\;\sin re \cdot \left(0.5 \cdot \left(im \cdot im\right)\right)\\
\end{array}
\]
Alternative 9 Accuracy 82.3% Cost 7244
\[\begin{array}{l}
t_0 := re \cdot \left(0.041666666666666664 \cdot {im}^{4}\right)\\
\mathbf{if}\;im \leq -120000:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq 2.2 \cdot 10^{+21}:\\
\;\;\;\;\sin re\\
\mathbf{elif}\;im \leq 3.9 \cdot 10^{+151}:\\
\;\;\;\;t_0\\
\mathbf{else}:\\
\;\;\;\;\sin re \cdot \left(0.5 \cdot \left(im \cdot im\right)\right)\\
\end{array}
\]
Alternative 10 Accuracy 79.6% Cost 7049
\[\begin{array}{l}
\mathbf{if}\;im \leq -290 \lor \neg \left(im \leq 4.1 \cdot 10^{+21}\right):\\
\;\;\;\;re \cdot \left(0.041666666666666664 \cdot {im}^{4}\right)\\
\mathbf{else}:\\
\;\;\;\;\sin re\\
\end{array}
\]
Alternative 11 Accuracy 72.4% Cost 6728
\[\begin{array}{l}
t_0 := re \cdot \left(0.5 \cdot \left(im \cdot im\right)\right)\\
\mathbf{if}\;im \leq -1.46 \cdot 10^{-7}:\\
\;\;\;\;re + t_0\\
\mathbf{elif}\;im \leq 1.2 \cdot 10^{+21}:\\
\;\;\;\;\sin re\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 12 Accuracy 47.9% Cost 713
\[\begin{array}{l}
\mathbf{if}\;im \leq -1.4 \lor \neg \left(im \leq 1.65 \cdot 10^{-11}\right):\\
\;\;\;\;re \cdot \left(0.5 \cdot \left(im \cdot im\right)\right)\\
\mathbf{else}:\\
\;\;\;\;re\\
\end{array}
\]
Alternative 13 Accuracy 48.3% Cost 576
\[re + re \cdot \left(0.5 \cdot \left(im \cdot im\right)\right)
\]
Alternative 14 Accuracy 26.9% Cost 64
\[re
\]