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



Bits error versus re



Bits error versus im
Initial program 0.0
Simplified0.0
Applied egg-rr0.0
Applied egg-rr0.0
Final simplification0.0
herbie shell --seed 2022162
(FPCore (re im)
:name "math.sin on complex, real part"
:precision binary64
(* (* 0.5 (sin re)) (+ (exp (- 0.0 im)) (exp im))))