Average Error: 0.1 → 0.1
Time: 5.0s
Precision: binary64
\[\]
↓
\[\]
↓
double code(double re, double im) {
	return ((double) (((double) (0.5 * ((double) sin(re)))) * ((double) (((double) exp(((double) (0.0 - im)))) + ((double) exp(im))))));
}

↓
double code(double re, double im) {
	return ((double) (((double) (0.5 * ((double) (((double) sin(re)) / ((double) exp(im)))))) + ((double) (0.5 * ((double) (((double) sin(re)) * ((double) exp(im))))))));
}

Error
Bits error versus re
Bits error versus im
Try it out
Your Program's Arguments
Results
Enter valid numbers for all inputs
Derivation
  1. Initial program 0.1
    \[\]
  2. Using strategy rm
  3. Applied distribute-lft-in0.1
    \[\leadsto \]
  4. Simplified0.1
    \[\leadsto \]
  5. Simplified0.1
    \[\leadsto \]
  6. Taylor expanded around inf 0.1
    \[\leadsto \]
  7. Simplified0.1
    \[\leadsto \]
  8. Final simplification0.1
    \[\leadsto \]
Reproduce
herbie shell --seed 2020181 
(FPCore (re im)
  :name "math.sin on complex, real part"
  :precision binary64
  (* (* 0.5 (sin re)) (+ (exp (- 0.0 im)) (exp im))))