Math FPCore C Fortran Java Python Julia MATLAB Wolfram TeX \[\left(0.5 \cdot \cos re\right) \cdot \left(e^{0 - im} - e^{im}\right)
\]
↓
\[\begin{array}{l}
t_0 := e^{-im} - e^{im}\\
\mathbf{if}\;t_0 \leq -5 \lor \neg \left(t_0 \leq 5 \cdot 10^{-11}\right):\\
\;\;\;\;\left(0.5 \cdot \cos re\right) \cdot t_0\\
\mathbf{else}:\\
\;\;\;\;\cos re \cdot \left(\left(\left(-0.16666666666666666 \cdot {im}^{3} + -0.0001984126984126984 \cdot {im}^{7}\right) + -0.008333333333333333 \cdot {im}^{5}\right) - im\right)\\
\end{array}
\]
(FPCore (re im)
:precision binary64
(* (* 0.5 (cos re)) (- (exp (- 0.0 im)) (exp im)))) ↓
(FPCore (re im)
:precision binary64
(let* ((t_0 (- (exp (- im)) (exp im))))
(if (or (<= t_0 -5.0) (not (<= t_0 5e-11)))
(* (* 0.5 (cos re)) t_0)
(*
(cos re)
(-
(+
(+
(* -0.16666666666666666 (pow im 3.0))
(* -0.0001984126984126984 (pow im 7.0)))
(* -0.008333333333333333 (pow im 5.0)))
im))))) double code(double re, double im) {
return (0.5 * cos(re)) * (exp((0.0 - im)) - exp(im));
}
↓
double code(double re, double im) {
double t_0 = exp(-im) - exp(im);
double tmp;
if ((t_0 <= -5.0) || !(t_0 <= 5e-11)) {
tmp = (0.5 * cos(re)) * t_0;
} else {
tmp = cos(re) * ((((-0.16666666666666666 * pow(im, 3.0)) + (-0.0001984126984126984 * pow(im, 7.0))) + (-0.008333333333333333 * pow(im, 5.0))) - im);
}
return tmp;
}
real(8) function code(re, im)
real(8), intent (in) :: re
real(8), intent (in) :: im
code = (0.5d0 * cos(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
real(8) :: t_0
real(8) :: tmp
t_0 = exp(-im) - exp(im)
if ((t_0 <= (-5.0d0)) .or. (.not. (t_0 <= 5d-11))) then
tmp = (0.5d0 * cos(re)) * t_0
else
tmp = cos(re) * (((((-0.16666666666666666d0) * (im ** 3.0d0)) + ((-0.0001984126984126984d0) * (im ** 7.0d0))) + ((-0.008333333333333333d0) * (im ** 5.0d0))) - im)
end if
code = tmp
end function
public static double code(double re, double im) {
return (0.5 * Math.cos(re)) * (Math.exp((0.0 - im)) - Math.exp(im));
}
↓
public static double code(double re, double im) {
double t_0 = Math.exp(-im) - Math.exp(im);
double tmp;
if ((t_0 <= -5.0) || !(t_0 <= 5e-11)) {
tmp = (0.5 * Math.cos(re)) * t_0;
} else {
tmp = Math.cos(re) * ((((-0.16666666666666666 * Math.pow(im, 3.0)) + (-0.0001984126984126984 * Math.pow(im, 7.0))) + (-0.008333333333333333 * Math.pow(im, 5.0))) - im);
}
return tmp;
}
def code(re, im):
return (0.5 * math.cos(re)) * (math.exp((0.0 - im)) - math.exp(im))
↓
def code(re, im):
t_0 = math.exp(-im) - math.exp(im)
tmp = 0
if (t_0 <= -5.0) or not (t_0 <= 5e-11):
tmp = (0.5 * math.cos(re)) * t_0
else:
tmp = math.cos(re) * ((((-0.16666666666666666 * math.pow(im, 3.0)) + (-0.0001984126984126984 * math.pow(im, 7.0))) + (-0.008333333333333333 * math.pow(im, 5.0))) - im)
return tmp
function code(re, im)
return Float64(Float64(0.5 * cos(re)) * Float64(exp(Float64(0.0 - im)) - exp(im)))
end
↓
function code(re, im)
t_0 = Float64(exp(Float64(-im)) - exp(im))
tmp = 0.0
if ((t_0 <= -5.0) || !(t_0 <= 5e-11))
tmp = Float64(Float64(0.5 * cos(re)) * t_0);
else
tmp = Float64(cos(re) * Float64(Float64(Float64(Float64(-0.16666666666666666 * (im ^ 3.0)) + Float64(-0.0001984126984126984 * (im ^ 7.0))) + Float64(-0.008333333333333333 * (im ^ 5.0))) - im));
end
return tmp
end
function tmp = code(re, im)
tmp = (0.5 * cos(re)) * (exp((0.0 - im)) - exp(im));
end
↓
function tmp_2 = code(re, im)
t_0 = exp(-im) - exp(im);
tmp = 0.0;
if ((t_0 <= -5.0) || ~((t_0 <= 5e-11)))
tmp = (0.5 * cos(re)) * t_0;
else
tmp = cos(re) * ((((-0.16666666666666666 * (im ^ 3.0)) + (-0.0001984126984126984 * (im ^ 7.0))) + (-0.008333333333333333 * (im ^ 5.0))) - im);
end
tmp_2 = tmp;
end
code[re_, im_] := N[(N[(0.5 * N[Cos[re], $MachinePrecision]), $MachinePrecision] * N[(N[Exp[N[(0.0 - im), $MachinePrecision]], $MachinePrecision] - N[Exp[im], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
↓
code[re_, im_] := Block[{t$95$0 = N[(N[Exp[(-im)], $MachinePrecision] - N[Exp[im], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[t$95$0, -5.0], N[Not[LessEqual[t$95$0, 5e-11]], $MachinePrecision]], N[(N[(0.5 * N[Cos[re], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision], N[(N[Cos[re], $MachinePrecision] * N[(N[(N[(N[(-0.16666666666666666 * N[Power[im, 3.0], $MachinePrecision]), $MachinePrecision] + N[(-0.0001984126984126984 * N[Power[im, 7.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-0.008333333333333333 * N[Power[im, 5.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - im), $MachinePrecision]), $MachinePrecision]]]
\left(0.5 \cdot \cos re\right) \cdot \left(e^{0 - im} - e^{im}\right)
↓
\begin{array}{l}
t_0 := e^{-im} - e^{im}\\
\mathbf{if}\;t_0 \leq -5 \lor \neg \left(t_0 \leq 5 \cdot 10^{-11}\right):\\
\;\;\;\;\left(0.5 \cdot \cos re\right) \cdot t_0\\
\mathbf{else}:\\
\;\;\;\;\cos re \cdot \left(\left(\left(-0.16666666666666666 \cdot {im}^{3} + -0.0001984126984126984 \cdot {im}^{7}\right) + -0.008333333333333333 \cdot {im}^{5}\right) - im\right)\\
\end{array}
Alternatives Alternative 1 Accuracy 99.7% Cost 53001
\[\begin{array}{l}
t_0 := e^{-im} - e^{im}\\
\mathbf{if}\;t_0 \leq -5 \lor \neg \left(t_0 \leq 5 \cdot 10^{-11}\right):\\
\;\;\;\;\left(0.5 \cdot \cos re\right) \cdot t_0\\
\mathbf{else}:\\
\;\;\;\;\cos re \cdot \left(\left(-0.0001984126984126984 \cdot {im}^{7} + -0.008333333333333333 \cdot {im}^{5}\right) + \left(-0.16666666666666666 \cdot {im}^{3} - im\right)\right)\\
\end{array}
\]
Alternative 2 Accuracy 99.7% Cost 45961
\[\begin{array}{l}
t_0 := e^{-im} - e^{im}\\
\mathbf{if}\;t_0 \leq -0.02 \lor \neg \left(t_0 \leq 5 \cdot 10^{-11}\right):\\
\;\;\;\;\left(0.5 \cdot \cos re\right) \cdot t_0\\
\mathbf{else}:\\
\;\;\;\;\cos re \cdot \left(-0.16666666666666666 \cdot {im}^{3} - im\right)\\
\end{array}
\]
Alternative 3 Accuracy 94.7% Cost 13842
\[\begin{array}{l}
\mathbf{if}\;im \leq -4 \cdot 10^{+132} \lor \neg \left(im \leq -0.55 \lor \neg \left(im \leq 2.3\right) \land im \leq 5.7 \cdot 10^{+102}\right):\\
\;\;\;\;\cos re \cdot \left(-0.16666666666666666 \cdot {im}^{3} - im\right)\\
\mathbf{else}:\\
\;\;\;\;0.5 \cdot \left(e^{-im} - e^{im}\right)\\
\end{array}
\]
Alternative 4 Accuracy 38.6% Cost 13640
\[\begin{array}{l}
\mathbf{if}\;\cos re \leq -0.05:\\
\;\;\;\;re \cdot \left(re \cdot \left(im \cdot 0.5\right)\right) - im\\
\mathbf{elif}\;\cos re \leq 0.94:\\
\;\;\;\;-3 \cdot \left(0.5 + re \cdot \left(re \cdot -0.25\right)\right)\\
\mathbf{else}:\\
\;\;\;\;-im\\
\end{array}
\]
Alternative 5 Accuracy 86.8% Cost 13580
\[\begin{array}{l}
t_0 := 0.5 \cdot \left(e^{-im} - e^{im}\right)\\
t_1 := -0.16666666666666666 \cdot {im}^{3} - im\\
\mathbf{if}\;im \leq -0.55:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq 0.0155:\\
\;\;\;\;im \cdot \left(-\cos re\right)\\
\mathbf{elif}\;im \leq 10^{+106}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq 1.35 \cdot 10^{+193}:\\
\;\;\;\;t_1 \cdot \left(-0.5 \cdot \left(re \cdot re\right) + 1\right)\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 6 Accuracy 77.6% Cost 7824
\[\begin{array}{l}
t_0 := -0.16666666666666666 \cdot {im}^{3}\\
t_1 := t_0 - im\\
t_2 := t_1 \cdot \left(-0.5 \cdot \left(re \cdot re\right) + 1\right)\\
\mathbf{if}\;im \leq -1.45 \cdot 10^{+84}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq -1.15:\\
\;\;\;\;t_2\\
\mathbf{elif}\;im \leq 4.1 \cdot 10^{+14}:\\
\;\;\;\;im \cdot \left(-\cos re\right)\\
\mathbf{elif}\;im \leq 5 \cdot 10^{+193}:\\
\;\;\;\;t_2\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 7 Accuracy 76.0% Cost 7432
\[\begin{array}{l}
t_0 := -0.16666666666666666 \cdot {im}^{3}\\
t_1 := t_0 - im\\
\mathbf{if}\;im \leq -1.45 \cdot 10^{+84}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq -2400:\\
\;\;\;\;t_1 \cdot \left(-0.5 \cdot \left(re \cdot re\right)\right)\\
\mathbf{elif}\;im \leq 8.5 \cdot 10^{-8}:\\
\;\;\;\;im \cdot \left(-\cos re\right)\\
\mathbf{else}:\\
\;\;\;\;t_1\\
\end{array}
\]
Alternative 8 Accuracy 54.0% Cost 7184
\[\begin{array}{l}
t_0 := -0.16666666666666666 \cdot {im}^{3}\\
\mathbf{if}\;im \leq -1.45 \cdot 10^{+84}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq -2.1 \cdot 10^{-14}:\\
\;\;\;\;re \cdot \left(re \cdot \left(im \cdot 0.5\right)\right) - im\\
\mathbf{elif}\;im \leq 15500:\\
\;\;\;\;-im\\
\mathbf{elif}\;im \leq 9 \cdot 10^{+73}:\\
\;\;\;\;\left(re \cdot re\right) \cdot -6.75\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 9 Accuracy 75.9% Cost 7180
\[\begin{array}{l}
t_0 := -0.16666666666666666 \cdot {im}^{3}\\
\mathbf{if}\;im \leq -1.45 \cdot 10^{+84}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq -7400:\\
\;\;\;\;re \cdot \left(re \cdot \left(im \cdot 0.5\right)\right) - im\\
\mathbf{elif}\;im \leq 8.5 \cdot 10^{-8}:\\
\;\;\;\;im \cdot \left(-\cos re\right)\\
\mathbf{else}:\\
\;\;\;\;t_0 - im\\
\end{array}
\]
Alternative 10 Accuracy 76.0% Cost 7052
\[\begin{array}{l}
t_0 := -0.16666666666666666 \cdot {im}^{3}\\
\mathbf{if}\;im \leq -1.45 \cdot 10^{+84}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;im \leq -780:\\
\;\;\;\;re \cdot \left(re \cdot \left(im \cdot 0.5\right)\right) - im\\
\mathbf{elif}\;im \leq 2.2:\\
\;\;\;\;im \cdot \left(-\cos re\right)\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 11 Accuracy 33.4% Cost 972
\[\begin{array}{l}
t_0 := -3 \cdot \left(0.5 + re \cdot \left(re \cdot -0.25\right)\right)\\
\mathbf{if}\;re \leq -1.5 \cdot 10^{+153}:\\
\;\;\;\;t_0\\
\mathbf{elif}\;re \leq 3.8 \cdot 10^{+153}:\\
\;\;\;\;-im\\
\mathbf{elif}\;re \leq 1.35 \cdot 10^{+212}:\\
\;\;\;\;\left(re \cdot re\right) \cdot -6.75\\
\mathbf{else}:\\
\;\;\;\;t_0\\
\end{array}
\]
Alternative 12 Accuracy 33.7% Cost 585
\[\begin{array}{l}
\mathbf{if}\;im \leq -780 \lor \neg \left(im \leq 5300\right):\\
\;\;\;\;\left(re \cdot re\right) \cdot -6.75\\
\mathbf{else}:\\
\;\;\;\;-im\\
\end{array}
\]
Alternative 13 Accuracy 33.9% Cost 584
\[\begin{array}{l}
\mathbf{if}\;im \leq -1.15:\\
\;\;\;\;1.5 + \left(re \cdot re\right) \cdot -0.75\\
\mathbf{elif}\;im \leq 3600:\\
\;\;\;\;-im\\
\mathbf{else}:\\
\;\;\;\;\left(re \cdot re\right) \cdot -6.75\\
\end{array}
\]
Alternative 14 Accuracy 28.8% Cost 128
\[-im
\]
Alternative 15 Accuracy 2.9% Cost 64
\[-3
\]
Alternative 16 Accuracy 2.9% Cost 64
\[-2
\]
Alternative 17 Accuracy 2.9% Cost 64
\[-0.25
\]
Alternative 18 Accuracy 2.9% Cost 64
\[-0.015625
\]
Alternative 19 Accuracy 3.5% Cost 64
\[0
\]