(FPCore (re im) :precision binary64 (* (* 0.5 (sin re)) (+ (exp (- 0.0 im)) (exp im))))
(FPCore (re im) :precision binary64 (* (sin re) (fma 0.5 (exp im) (log (pow E (/ 0.5 (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 sin(re) * fma(0.5, exp(im), log(pow(((double) M_E), (0.5 / 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(sin(re) * fma(0.5, exp(im), log((exp(1) ^ Float64(0.5 / 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[Sin[re], $MachinePrecision] * N[(0.5 * N[Exp[im], $MachinePrecision] + N[Log[N[Power[E, N[(0.5 / N[Exp[im], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\left(0.5 \cdot \sin re\right) \cdot \left(e^{0 - im} + e^{im}\right)
\sin re \cdot \mathsf{fma}\left(0.5, e^{im}, \log \left({e}^{\left(\frac{0.5}{e^{im}}\right)}\right)\right)



Bits error versus re



Bits error versus im
Initial program 0.0
Simplified0.0
Applied egg-rr0.2
Applied egg-rr0.2
Final simplification0.2
herbie shell --seed 2022145
(FPCore (re im)
:name "math.sin on complex, real part"
:precision binary64
(* (* 0.5 (sin re)) (+ (exp (- 0.0 im)) (exp im))))