Average Error: 0.0 → 0.0

Time: 4.6s

Precision: 64

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

↓

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

e^{re} \cdot \sin im

↓

e^{re} \cdot \sin im

double f(double re, double im) {
        double r263 = re;
        double r264 = exp(r263);
        double r265 = im;
        double r266 = sin(r265);
        double r267 = r264 * r266;
        return r267;
}

↓

double f(double re, double im) {
        double r268 = re;
        double r269 = exp(r268);
        double r270 = im;
        double r271 = sin(r270);
        double r272 = r269 * r271;
        return r272;
}

Error

The X axis uses an exponential scale — Bits error versus `re`

Try it out

In
Out

Enter valid numbers for all inputs

Derivation

Initial program 0.0
\[e^{re} \cdot \sin im\]
Final simplification0.0
\[\leadsto e^{re} \cdot \sin im\]

Reproduce

herbie shell --seed 2020025 
(FPCore (re im)
  :name "math.exp on complex, imaginary part"
  :precision binary64
  (* (exp re) (sin im)))