Average Error: 0.2 → 0.2
Time: 9.4s
Precision: binary32
\[\left(10^{-5} \leq u \land u \leq 1\right) \land \left(0 \leq v \land v \leq 109.746574\right)\]
\[1 + v \cdot \log \left(u + \left(1 - u\right) \cdot e^{\frac{-2}{v}}\right) \]
\[\mathsf{fma}\left(v, 0.3333333333333333 \cdot \left(3 \cdot \log \left(\mathsf{fma}\left(1 - u, e^{\frac{-2}{v}}, u\right)\right)\right), 1\right) \]
1 + v \cdot \log \left(u + \left(1 - u\right) \cdot e^{\frac{-2}{v}}\right)
\mathsf{fma}\left(v, 0.3333333333333333 \cdot \left(3 \cdot \log \left(\mathsf{fma}\left(1 - u, e^{\frac{-2}{v}}, u\right)\right)\right), 1\right)
(FPCore (u v)
 :precision binary32
 (+ 1.0 (* v (log (+ u (* (- 1.0 u) (exp (/ -2.0 v))))))))
(FPCore (u v)
 :precision binary32
 (fma
  v
  (* 0.3333333333333333 (* 3.0 (log (fma (- 1.0 u) (exp (/ -2.0 v)) u))))
  1.0))
float code(float u, float v) {
	return 1.0f + (v * logf(u + ((1.0f - u) * expf(-2.0f / v))));
}
float code(float u, float v) {
	return fmaf(v, (0.3333333333333333f * (3.0f * logf(fmaf((1.0f - u), expf(-2.0f / v), u)))), 1.0f);
}

Error

Bits error versus u

Bits error versus v

Derivation

  1. Initial program 0.2

    \[1 + v \cdot \log \left(u + \left(1 - u\right) \cdot e^{\frac{-2}{v}}\right) \]
  2. Simplified0.2

    \[\leadsto \color{blue}{\mathsf{fma}\left(v, \log \left(\mathsf{fma}\left(1 - u, e^{\frac{-2}{v}}, u\right)\right), 1\right)} \]
  3. Applied egg0.2

    \[\leadsto \color{blue}{\mathsf{log1p}\left(\mathsf{expm1}\left(\mathsf{fma}\left(v, \log \left(\mathsf{fma}\left(1 - u, e^{\frac{-2}{v}}, u\right)\right), 1\right)\right)\right)} \]
  4. Applied egg0.2

    \[\leadsto \color{blue}{0 + \mathsf{fma}\left(v, \log \left(\mathsf{fma}\left(1 - u, e^{\frac{-2}{v}}, u\right)\right), 1\right)} \]
  5. Applied egg0.2

    \[\leadsto 0 + \mathsf{fma}\left(v, \color{blue}{0.3333333333333333 \cdot \left(3 \cdot \log \left(\mathsf{fma}\left(1 - u, e^{\frac{-2}{v}}, u\right)\right)\right)}, 1\right) \]
  6. Final simplification0.2

    \[\leadsto \mathsf{fma}\left(v, 0.3333333333333333 \cdot \left(3 \cdot \log \left(\mathsf{fma}\left(1 - u, e^{\frac{-2}{v}}, u\right)\right)\right), 1\right) \]

Reproduce

herbie shell --seed 2022125 
(FPCore (u v)
  :name "HairBSDF, sample_f, cosTheta"
  :precision binary32
  :pre (and (and (<= 1e-5 u) (<= u 1.0)) (and (<= 0.0 v) (<= v 109.746574)))
  (+ 1.0 (* v (log (+ u (* (- 1.0 u) (exp (/ -2.0 v))))))))