Average Error: 43.2 → 0.7
Time: 32.1s
Precision: 64
\[\left(0.5 \cdot \sin re\right) \cdot \left(e^{-im} - e^{im}\right)\]
\[\left(0.5 \cdot \sin re\right) \cdot \left(\frac{-1}{3} \cdot {im}^{3}\right) + \left(0.5 \cdot \sin re\right) \cdot \mathsf{fma}\left(im, -2, {im}^{5} \cdot \frac{-1}{60}\right)\]
\left(0.5 \cdot \sin re\right) \cdot \left(e^{-im} - e^{im}\right)
\left(0.5 \cdot \sin re\right) \cdot \left(\frac{-1}{3} \cdot {im}^{3}\right) + \left(0.5 \cdot \sin re\right) \cdot \mathsf{fma}\left(im, -2, {im}^{5} \cdot \frac{-1}{60}\right)
double f(double re, double im) {
        double r224120 = 0.5;
        double r224121 = re;
        double r224122 = sin(r224121);
        double r224123 = r224120 * r224122;
        double r224124 = im;
        double r224125 = -r224124;
        double r224126 = exp(r224125);
        double r224127 = exp(r224124);
        double r224128 = r224126 - r224127;
        double r224129 = r224123 * r224128;
        return r224129;
}

double f(double re, double im) {
        double r224130 = 0.5;
        double r224131 = re;
        double r224132 = sin(r224131);
        double r224133 = r224130 * r224132;
        double r224134 = -0.3333333333333333;
        double r224135 = im;
        double r224136 = 3.0;
        double r224137 = pow(r224135, r224136);
        double r224138 = r224134 * r224137;
        double r224139 = r224133 * r224138;
        double r224140 = -2.0;
        double r224141 = 5.0;
        double r224142 = pow(r224135, r224141);
        double r224143 = -0.016666666666666666;
        double r224144 = r224142 * r224143;
        double r224145 = fma(r224135, r224140, r224144);
        double r224146 = r224133 * r224145;
        double r224147 = r224139 + r224146;
        return r224147;
}

Error

Bits error versus re

Bits error versus im

Target

Original43.2
Target0.3
Herbie0.7
\[\begin{array}{l} \mathbf{if}\;\left|im\right| \lt 1:\\ \;\;\;\;-\sin re \cdot \left(\left(im + \left(\left(0.1666666666666666574148081281236954964697 \cdot im\right) \cdot im\right) \cdot im\right) + \left(\left(\left(\left(0.008333333333333333217685101601546193705872 \cdot im\right) \cdot im\right) \cdot im\right) \cdot im\right) \cdot im\right)\\ \mathbf{else}:\\ \;\;\;\;\left(0.5 \cdot \sin re\right) \cdot \left(e^{-im} - e^{im}\right)\\ \end{array}\]

Derivation

  1. Initial program 43.2

    \[\left(0.5 \cdot \sin re\right) \cdot \left(e^{-im} - e^{im}\right)\]
  2. Taylor expanded around 0 0.7

    \[\leadsto \left(0.5 \cdot \sin re\right) \cdot \color{blue}{\left(-\left(\frac{1}{3} \cdot {im}^{3} + \left(\frac{1}{60} \cdot {im}^{5} + 2 \cdot im\right)\right)\right)}\]
  3. Simplified0.7

    \[\leadsto \left(0.5 \cdot \sin re\right) \cdot \color{blue}{\mathsf{fma}\left(\frac{-1}{3}, {im}^{3}, \mathsf{fma}\left(im, -2, {im}^{5} \cdot \frac{-1}{60}\right)\right)}\]
  4. Using strategy rm
  5. Applied fma-udef0.7

    \[\leadsto \left(0.5 \cdot \sin re\right) \cdot \color{blue}{\left(\frac{-1}{3} \cdot {im}^{3} + \mathsf{fma}\left(im, -2, {im}^{5} \cdot \frac{-1}{60}\right)\right)}\]
  6. Applied distribute-lft-in0.7

    \[\leadsto \color{blue}{\left(0.5 \cdot \sin re\right) \cdot \left(\frac{-1}{3} \cdot {im}^{3}\right) + \left(0.5 \cdot \sin re\right) \cdot \mathsf{fma}\left(im, -2, {im}^{5} \cdot \frac{-1}{60}\right)}\]
  7. Final simplification0.7

    \[\leadsto \left(0.5 \cdot \sin re\right) \cdot \left(\frac{-1}{3} \cdot {im}^{3}\right) + \left(0.5 \cdot \sin re\right) \cdot \mathsf{fma}\left(im, -2, {im}^{5} \cdot \frac{-1}{60}\right)\]

Reproduce

herbie shell --seed 2019323 +o rules:numerics
(FPCore (re im)
  :name "math.cos on complex, imaginary part"
  :precision binary64

  :herbie-target
  (if (< (fabs im) 1) (- (* (sin re) (+ (+ im (* (* (* 0.16666666666666666 im) im) im)) (* (* (* (* (* 0.008333333333333333 im) im) im) im) im)))) (* (* 0.5 (sin re)) (- (exp (- im)) (exp im))))

  (* (* 0.5 (sin re)) (- (exp (- im)) (exp im))))