Average Error: 0.0 → 0.0
Time: 3.9s
Precision: binary64
Cost: 12992
\[e^{re} \cdot \sin im\]
↓
\[e^{re} \cdot \sin im\]
e^{re} \cdot \sin im
↓
e^{re} \cdot \sin im
(FPCore (re im) :precision binary64 (* (exp re) (sin im)))
↓
(FPCore (re im) :precision binary64 (* (exp re) (sin im)))
double code(double re, double im) {
	return exp(re) * sin(im);
}
↓
double code(double re, double im) {
	return exp(re) * sin(im);
}

Error

Bits error versus re

Bits error versus im

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Alternatives

Alternative 1
Error20.2
Cost25792
\[\log \left(e^{e^{re} \cdot \sin im}\right)\]
Alternative 2
Error36.3
Cost19520
\[\log \left(e^{\sin im \cdot \left(re + 1\right)}\right)\]
Alternative 3
Error21.0
Cost7104
\[\sin im \cdot \left(re + \left(1 + 0.5 \cdot \left(re \cdot re\right)\right)\right)\]
Alternative 4
Error20.8
Cost6720
\[\sin im \cdot \left(re + 1\right)\]
Alternative 5
Error21.1
Cost6592
\[e^{re} \cdot im\]
Alternative 6
Error20.9
Cost6464
\[\sin im\]
Alternative 7
Error41.5
Cost6464
\[\log 1\]
Alternative 8
Error60.1
Cost64
\[1\]
Alternative 9
Error41.5
Cost64
\[0\]
Alternative 10
Error60.1
Cost64
\[-1\]

Error

Derivation

  1. Initial program 0.0

    \[e^{re} \cdot \sin im\]

  2. Simplified0.0

    \[\leadsto \color{blue}{e^{re} \cdot \sin im}\]

  3. Final simplification0.0

    \[\leadsto e^{re} \cdot \sin im\]

Reproduce

herbie shell --seed 2021022 
(FPCore (re im)
  :name "math.exp on complex, imaginary part"
  :precision binary64
  (* (exp re) (sin im)))