Disney BSSRDF, PDF of scattering profile

Percentage Accurate: 99.5% → 99.6%
Time: 11.9s
Alternatives: 12
Speedup: 1.1×

Specification

?
\[\left(0 \leq s \land s \leq 256\right) \land \left(10^{-6} < r \land r < 1000000\right)\]
\[\begin{array}{l} \\ \frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* 0.25 (exp (/ (- r) s))) (* (* (* 2.0 PI) s) r))
  (/ (* 0.75 (exp (/ (- r) (* 3.0 s)))) (* (* (* 6.0 PI) s) r))))
float code(float s, float r) {
	return ((0.25f * expf((-r / s))) / (((2.0f * ((float) M_PI)) * s) * r)) + ((0.75f * expf((-r / (3.0f * s)))) / (((6.0f * ((float) M_PI)) * s) * r));
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.25) * exp(Float32(Float32(-r) / s))) / Float32(Float32(Float32(Float32(2.0) * Float32(pi)) * s) * r)) + Float32(Float32(Float32(0.75) * exp(Float32(Float32(-r) / Float32(Float32(3.0) * s)))) / Float32(Float32(Float32(Float32(6.0) * Float32(pi)) * s) * r)))
end
function tmp = code(s, r)
	tmp = ((single(0.25) * exp((-r / s))) / (((single(2.0) * single(pi)) * s) * r)) + ((single(0.75) * exp((-r / (single(3.0) * s)))) / (((single(6.0) * single(pi)) * s) * r));
end
\begin{array}{l}

\\
\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r}
\end{array}

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Accuracy vs Speed?

Herbie found 12 alternatives:

AlternativeAccuracySpeedup
The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Initial Program: 99.5% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* 0.25 (exp (/ (- r) s))) (* (* (* 2.0 PI) s) r))
  (/ (* 0.75 (exp (/ (- r) (* 3.0 s)))) (* (* (* 6.0 PI) s) r))))
float code(float s, float r) {
	return ((0.25f * expf((-r / s))) / (((2.0f * ((float) M_PI)) * s) * r)) + ((0.75f * expf((-r / (3.0f * s)))) / (((6.0f * ((float) M_PI)) * s) * r));
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.25) * exp(Float32(Float32(-r) / s))) / Float32(Float32(Float32(Float32(2.0) * Float32(pi)) * s) * r)) + Float32(Float32(Float32(0.75) * exp(Float32(Float32(-r) / Float32(Float32(3.0) * s)))) / Float32(Float32(Float32(Float32(6.0) * Float32(pi)) * s) * r)))
end
function tmp = code(s, r)
	tmp = ((single(0.25) * exp((-r / s))) / (((single(2.0) * single(pi)) * s) * r)) + ((single(0.75) * exp((-r / (single(3.0) * s)))) / (((single(6.0) * single(pi)) * s) * r));
end
\begin{array}{l}

\\
\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r}
\end{array}

Alternative 1: 99.6% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (* 0.125 (exp (/ (- r) s))) (* (* PI s) r))
  (/ (* 0.75 (exp (/ r (* -3.0 s)))) (* (* (* 6.0 PI) s) r))))
float code(float s, float r) {
	return ((0.125f * expf((-r / s))) / ((((float) M_PI) * s) * r)) + ((0.75f * expf((r / (-3.0f * s)))) / (((6.0f * ((float) M_PI)) * s) * r));
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.125) * exp(Float32(Float32(-r) / s))) / Float32(Float32(Float32(pi) * s) * r)) + Float32(Float32(Float32(0.75) * exp(Float32(r / Float32(Float32(-3.0) * s)))) / Float32(Float32(Float32(Float32(6.0) * Float32(pi)) * s) * r)))
end
function tmp = code(s, r)
	tmp = ((single(0.125) * exp((-r / s))) / ((single(pi) * s) * r)) + ((single(0.75) * exp((r / (single(-3.0) * s)))) / (((single(6.0) * single(pi)) * s) * r));
end
\begin{array}{l}

\\
\frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\color{blue}{\frac{1}{4} \cdot e^{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    3. lift-exp.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot \color{blue}{e^{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    4. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\color{blue}{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    5. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\color{blue}{\mathsf{neg}\left(r\right)}}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    7. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(2 \cdot \pi\right) \cdot s}}{r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  3. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r}} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  4. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{\color{blue}{3 \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    2. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\color{blue}{\frac{-r}{3 \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    3. associate-/r*N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\color{blue}{\frac{\frac{-r}{3}}{s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    4. frac-2negN/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{\color{blue}{\frac{\mathsf{neg}\left(\left(-r\right)\right)}{\mathsf{neg}\left(3\right)}}}{s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    5. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{\frac{\mathsf{neg}\left(\color{blue}{\left(\mathsf{neg}\left(r\right)\right)}\right)}{\mathsf{neg}\left(3\right)}}{s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    6. remove-double-negN/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{\frac{\color{blue}{r}}{\mathsf{neg}\left(3\right)}}{s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    7. associate-/l/N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\color{blue}{\frac{r}{\left(\mathsf{neg}\left(3\right)\right) \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    8. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\color{blue}{\frac{r}{\left(\mathsf{neg}\left(3\right)\right) \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    9. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{\color{blue}{\left(\mathsf{neg}\left(3\right)\right) \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    10. metadata-eval99.5

      \[\leadsto \frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{r}{\color{blue}{-3} \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  5. Applied rewrites99.5%

    \[\leadsto \frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\color{blue}{\frac{r}{-3 \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  6. Add Preprocessing

Alternative 2: 99.5% accurate, 1.1× speedup?

\[\begin{array}{l} \\ \frac{\frac{0.125}{s \cdot e^{\frac{r}{s}}}}{\pi \cdot r} + \frac{0.75 \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \end{array} \]
(FPCore (s r)
 :precision binary32
 (+
  (/ (/ 0.125 (* s (exp (/ r s)))) (* PI r))
  (/ (* 0.75 (exp (/ r (* -3.0 s)))) (* (* (* 6.0 PI) s) r))))
float code(float s, float r) {
	return ((0.125f / (s * expf((r / s)))) / (((float) M_PI) * r)) + ((0.75f * expf((r / (-3.0f * s)))) / (((6.0f * ((float) M_PI)) * s) * r));
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.125) / Float32(s * exp(Float32(r / s)))) / Float32(Float32(pi) * r)) + Float32(Float32(Float32(0.75) * exp(Float32(r / Float32(Float32(-3.0) * s)))) / Float32(Float32(Float32(Float32(6.0) * Float32(pi)) * s) * r)))
end
function tmp = code(s, r)
	tmp = ((single(0.125) / (s * exp((r / s)))) / (single(pi) * r)) + ((single(0.75) * exp((r / (single(-3.0) * s)))) / (((single(6.0) * single(pi)) * s) * r));
end
\begin{array}{l}

\\
\frac{\frac{0.125}{s \cdot e^{\frac{r}{s}}}}{\pi \cdot r} + \frac{0.75 \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\color{blue}{\frac{1}{4} \cdot e^{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    3. lift-exp.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot \color{blue}{e^{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    4. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\color{blue}{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    5. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\color{blue}{\mathsf{neg}\left(r\right)}}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    7. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(2 \cdot \pi\right) \cdot s}}{r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  3. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r}} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  4. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{\color{blue}{3 \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    2. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\color{blue}{\frac{-r}{3 \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    3. associate-/r*N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\color{blue}{\frac{\frac{-r}{3}}{s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    4. frac-2negN/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{\color{blue}{\frac{\mathsf{neg}\left(\left(-r\right)\right)}{\mathsf{neg}\left(3\right)}}}{s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    5. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{\frac{\mathsf{neg}\left(\color{blue}{\left(\mathsf{neg}\left(r\right)\right)}\right)}{\mathsf{neg}\left(3\right)}}{s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    6. remove-double-negN/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{\frac{\color{blue}{r}}{\mathsf{neg}\left(3\right)}}{s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    7. associate-/l/N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\color{blue}{\frac{r}{\left(\mathsf{neg}\left(3\right)\right) \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    8. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\color{blue}{\frac{r}{\left(\mathsf{neg}\left(3\right)\right) \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    9. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{\color{blue}{\left(\mathsf{neg}\left(3\right)\right) \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    10. metadata-eval99.5

      \[\leadsto \frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{r}{\color{blue}{-3} \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  5. Applied rewrites99.5%

    \[\leadsto \frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\color{blue}{\frac{r}{-3 \cdot s}}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  6. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{8} \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\color{blue}{\frac{1}{8} \cdot e^{\frac{-r}{s}}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    3. lift-exp.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot \color{blue}{e^{\frac{-r}{s}}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    4. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\color{blue}{\frac{-r}{s}}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    5. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{\color{blue}{\mathsf{neg}\left(r\right)}}{s}}}{\left(\pi \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{\left(\pi \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    7. lift-PI.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(\color{blue}{\mathsf{PI}\left(\right)} \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    8. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{8} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot s\right)} \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    9. times-fracN/A

      \[\leadsto \color{blue}{\frac{\frac{1}{8}}{\mathsf{PI}\left(\right) \cdot s} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r}} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    10. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{8}}{\color{blue}{s \cdot \mathsf{PI}\left(\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    11. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{8}}{s}}{\mathsf{PI}\left(\right)}} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    12. metadata-evalN/A

      \[\leadsto \frac{\frac{\color{blue}{\frac{1}{8} \cdot 1}}{s}}{\mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    13. associate-*r/N/A

      \[\leadsto \frac{\color{blue}{\frac{1}{8} \cdot \frac{1}{s}}}{\mathsf{PI}\left(\right)} \cdot \frac{e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    14. frac-timesN/A

      \[\leadsto \color{blue}{\frac{\left(\frac{1}{8} \cdot \frac{1}{s}\right) \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\mathsf{PI}\left(\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    15. *-commutativeN/A

      \[\leadsto \frac{\left(\frac{1}{8} \cdot \frac{1}{s}\right) \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{r \cdot \mathsf{PI}\left(\right)}} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    16. lower-/.f32N/A

      \[\leadsto \color{blue}{\frac{\left(\frac{1}{8} \cdot \frac{1}{s}\right) \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{r \cdot \mathsf{PI}\left(\right)}} + \frac{\frac{3}{4} \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  7. Applied rewrites99.6%

    \[\leadsto \color{blue}{\frac{\frac{0.125}{s \cdot e^{\frac{r}{s}}}}{\pi \cdot r}} + \frac{0.75 \cdot e^{\frac{r}{-3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  8. Add Preprocessing

Alternative 3: 99.5% accurate, 1.3× speedup?

\[\begin{array}{l} \\ \frac{0.125}{\pi \cdot s} \cdot \left(\frac{e^{-0.3333333333333333 \cdot \frac{r}{s}}}{r} + \frac{e^{\frac{-r}{s}}}{r}\right) \end{array} \]
(FPCore (s r)
 :precision binary32
 (*
  (/ 0.125 (* PI s))
  (+ (/ (exp (* -0.3333333333333333 (/ r s))) r) (/ (exp (/ (- r) s)) r))))
float code(float s, float r) {
	return (0.125f / (((float) M_PI) * s)) * ((expf((-0.3333333333333333f * (r / s))) / r) + (expf((-r / s)) / r));
}
function code(s, r)
	return Float32(Float32(Float32(0.125) / Float32(Float32(pi) * s)) * Float32(Float32(exp(Float32(Float32(-0.3333333333333333) * Float32(r / s))) / r) + Float32(exp(Float32(Float32(-r) / s)) / r)))
end
function tmp = code(s, r)
	tmp = (single(0.125) / (single(pi) * s)) * ((exp((single(-0.3333333333333333) * (r / s))) / r) + (exp((-r / s)) / r));
end
\begin{array}{l}

\\
\frac{0.125}{\pi \cdot s} \cdot \left(\frac{e^{-0.3333333333333333 \cdot \frac{r}{s}}}{r} + \frac{e^{\frac{-r}{s}}}{r}\right)
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{0.125}{\pi \cdot s} \cdot \left(\frac{e^{-0.3333333333333333 \cdot \frac{r}{s}}}{r} + \frac{e^{\frac{-r}{s}}}{r}\right)} \]
  3. Add Preprocessing

Alternative 4: 99.5% accurate, 1.4× speedup?

\[\begin{array}{l} \\ \frac{\left(e^{\frac{r}{s} \cdot -0.3333333333333333} + e^{\frac{-r}{s}}\right) \cdot 0.125}{\left(\pi \cdot r\right) \cdot s} \end{array} \]
(FPCore (s r)
 :precision binary32
 (/
  (* (+ (exp (* (/ r s) -0.3333333333333333)) (exp (/ (- r) s))) 0.125)
  (* (* PI r) s)))
float code(float s, float r) {
	return ((expf(((r / s) * -0.3333333333333333f)) + expf((-r / s))) * 0.125f) / ((((float) M_PI) * r) * s);
}
function code(s, r)
	return Float32(Float32(Float32(exp(Float32(Float32(r / s) * Float32(-0.3333333333333333))) + exp(Float32(Float32(-r) / s))) * Float32(0.125)) / Float32(Float32(Float32(pi) * r) * s))
end
function tmp = code(s, r)
	tmp = ((exp(((r / s) * single(-0.3333333333333333))) + exp((-r / s))) * single(0.125)) / ((single(pi) * r) * s);
end
\begin{array}{l}

\\
\frac{\left(e^{\frac{r}{s} \cdot -0.3333333333333333} + e^{\frac{-r}{s}}\right) \cdot 0.125}{\left(\pi \cdot r\right) \cdot s}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\color{blue}{\frac{1}{4} \cdot e^{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    3. lift-exp.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot \color{blue}{e^{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    4. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\color{blue}{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    5. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\color{blue}{\mathsf{neg}\left(r\right)}}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    7. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(2 \cdot \pi\right) \cdot s}}{r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  3. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r}} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  4. Taylor expanded in s around 0

    \[\leadsto \color{blue}{\frac{\frac{1}{8} \cdot \frac{e^{-1 \cdot \frac{r}{s}}}{r \cdot \mathsf{PI}\left(\right)} + \frac{1}{8} \cdot \frac{e^{\frac{-1}{3} \cdot \frac{r}{s}}}{r \cdot \mathsf{PI}\left(\right)}}{s}} \]
  5. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{\left(e^{\frac{r}{s} \cdot -0.3333333333333333} + e^{\frac{-r}{s}}\right) \cdot 0.125}{\left(\pi \cdot r\right) \cdot s}} \]
  6. Add Preprocessing

Alternative 5: 43.2% accurate, 2.5× speedup?

\[\begin{array}{l} \\ \frac{0.25}{s \cdot \log \left(e^{\pi \cdot r}\right)} \end{array} \]
(FPCore (s r) :precision binary32 (/ 0.25 (* s (log (exp (* PI r))))))
float code(float s, float r) {
	return 0.25f / (s * logf(expf((((float) M_PI) * r))));
}
function code(s, r)
	return Float32(Float32(0.25) / Float32(s * log(exp(Float32(Float32(pi) * r)))))
end
function tmp = code(s, r)
	tmp = single(0.25) / (s * log(exp((single(pi) * r))));
end
\begin{array}{l}

\\
\frac{0.25}{s \cdot \log \left(e^{\pi \cdot r}\right)}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Taylor expanded in s around inf

    \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
  3. Step-by-step derivation
    1. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    2. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{r}} \]
    3. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{r}} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    5. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    6. lift-PI.f328.9

      \[\leadsto \frac{0.25}{\left(\pi \cdot s\right) \cdot r} \]
  4. Applied rewrites8.9%

    \[\leadsto \color{blue}{\frac{0.25}{\left(\pi \cdot s\right) \cdot r}} \]
  5. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\pi \cdot s\right) \cdot \color{blue}{r}} \]
    2. lift-PI.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot r} \]
    5. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{r \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    6. add-log-expN/A

      \[\leadsto \frac{\frac{1}{4}}{r \cdot \left(s \cdot \log \left(e^{\mathsf{PI}\left(\right)}\right)\right)} \]
    7. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{r \cdot \log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{s}\right)} \]
    8. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{s}\right)}^{r}\right)} \]
    9. pow-unpowN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{\left(s \cdot r\right)}\right)} \]
    10. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{\left(r \cdot s\right)}\right)} \]
    11. pow-unpowN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{r}\right)}^{s}\right)} \]
    12. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \color{blue}{\log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{r}\right)}} \]
    13. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(r \cdot \color{blue}{\log \left(e^{\mathsf{PI}\left(\right)}\right)}\right)} \]
    14. add-log-expN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(r \cdot \mathsf{PI}\left(\right)\right)} \]
    15. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \color{blue}{\left(r \cdot \mathsf{PI}\left(\right)\right)}} \]
    16. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{r}\right)} \]
    17. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{r}\right)} \]
    18. lift-PI.f328.9

      \[\leadsto \frac{0.25}{s \cdot \left(\pi \cdot r\right)} \]
  6. Applied rewrites8.9%

    \[\leadsto \frac{0.25}{s \cdot \color{blue}{\left(\pi \cdot r\right)}} \]
  7. Step-by-step derivation
    1. lift-PI.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(\mathsf{PI}\left(\right) \cdot r\right)} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{r}\right)} \]
    3. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(r \cdot \color{blue}{\mathsf{PI}\left(\right)}\right)} \]
    4. add-log-expN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(r \cdot \log \left(e^{\mathsf{PI}\left(\right)}\right)\right)} \]
    5. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{r}\right)} \]
    6. lower-log.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{r}\right)} \]
    7. pow-expN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \log \left(e^{\mathsf{PI}\left(\right) \cdot r}\right)} \]
    8. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \log \left(e^{r \cdot \mathsf{PI}\left(\right)}\right)} \]
    9. lower-exp.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \log \left(e^{r \cdot \mathsf{PI}\left(\right)}\right)} \]
    10. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \log \left(e^{\mathsf{PI}\left(\right) \cdot r}\right)} \]
    11. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \log \left(e^{\mathsf{PI}\left(\right) \cdot r}\right)} \]
    12. lift-PI.f3243.2

      \[\leadsto \frac{0.25}{s \cdot \log \left(e^{\pi \cdot r}\right)} \]
  8. Applied rewrites43.2%

    \[\leadsto \frac{0.25}{s \cdot \log \left(e^{\pi \cdot r}\right)} \]
  9. Add Preprocessing

Alternative 6: 10.1% accurate, 2.5× speedup?

\[\begin{array}{l} \\ \frac{0.25}{\log \left(e^{\left(\pi \cdot s\right) \cdot r}\right)} \end{array} \]
(FPCore (s r) :precision binary32 (/ 0.25 (log (exp (* (* PI s) r)))))
float code(float s, float r) {
	return 0.25f / logf(expf(((((float) M_PI) * s) * r)));
}
function code(s, r)
	return Float32(Float32(0.25) / log(exp(Float32(Float32(Float32(pi) * s) * r))))
end
function tmp = code(s, r)
	tmp = single(0.25) / log(exp(((single(pi) * s) * r)));
end
\begin{array}{l}

\\
\frac{0.25}{\log \left(e^{\left(\pi \cdot s\right) \cdot r}\right)}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Taylor expanded in s around inf

    \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
  3. Step-by-step derivation
    1. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    2. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{r}} \]
    3. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{r}} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    5. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    6. lift-PI.f328.9

      \[\leadsto \frac{0.25}{\left(\pi \cdot s\right) \cdot r} \]
  4. Applied rewrites8.9%

    \[\leadsto \color{blue}{\frac{0.25}{\left(\pi \cdot s\right) \cdot r}} \]
  5. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\pi \cdot s\right) \cdot \color{blue}{r}} \]
    2. lift-PI.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot r} \]
    5. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{r \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    6. associate-*r*N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(r \cdot s\right) \cdot \color{blue}{\mathsf{PI}\left(\right)}} \]
    7. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot r\right) \cdot \mathsf{PI}\left(\right)} \]
    8. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot r\right) \cdot \mathsf{PI}\left(\right)} \]
    9. add-log-expN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot r\right) \cdot \log \left(e^{\mathsf{PI}\left(\right)}\right)} \]
    10. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{\left(s \cdot r\right)}\right)} \]
    11. lower-log.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{\left(s \cdot r\right)}\right)} \]
    12. pow-expN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{\mathsf{PI}\left(\right) \cdot \left(s \cdot r\right)}\right)} \]
    13. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{\mathsf{PI}\left(\right) \cdot \left(s \cdot r\right)}\right)} \]
    14. associate-*l*N/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r}\right)} \]
    15. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot r}\right)} \]
    16. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}\right)} \]
    17. lower-exp.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}\right)} \]
    18. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot r}\right)} \]
    19. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r}\right)} \]
    20. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r}\right)} \]
    21. lift-PI.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left(e^{\left(\pi \cdot s\right) \cdot r}\right)} \]
    22. lift-*.f3210.1

      \[\leadsto \frac{0.25}{\log \left(e^{\left(\pi \cdot s\right) \cdot r}\right)} \]
  6. Applied rewrites10.1%

    \[\leadsto \frac{0.25}{\log \left(e^{\left(\pi \cdot s\right) \cdot r}\right)} \]
  7. Add Preprocessing

Alternative 7: 8.9% accurate, 2.9× speedup?

\[\begin{array}{l} \\ \frac{\frac{\mathsf{fma}\left(0.16666666666666666, r, -0.25 \cdot s\right)}{s}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \end{array} \]
(FPCore (s r)
 :precision binary32
 (/ (/ (fma 0.16666666666666666 r (* -0.25 s)) s) (* (* s r) (- PI))))
float code(float s, float r) {
	return (fmaf(0.16666666666666666f, r, (-0.25f * s)) / s) / ((s * r) * -((float) M_PI));
}
function code(s, r)
	return Float32(Float32(fma(Float32(0.16666666666666666), r, Float32(Float32(-0.25) * s)) / s) / Float32(Float32(s * r) * Float32(-Float32(pi))))
end
\begin{array}{l}

\\
\frac{\frac{\mathsf{fma}\left(0.16666666666666666, r, -0.25 \cdot s\right)}{s}}{\left(s \cdot r\right) \cdot \left(-\pi\right)}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{-0.125 \cdot \left(e^{\frac{-r}{s}} + e^{-0.3333333333333333 \cdot \frac{r}{s}}\right)}{\left(s \cdot r\right) \cdot \left(-\pi\right)}} \]
  3. Taylor expanded in s around inf

    \[\leadsto \frac{\color{blue}{\frac{-1}{8} \cdot \frac{-1 \cdot r + \frac{-1}{3} \cdot r}{s} - \frac{1}{4}}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  4. Step-by-step derivation
    1. div-addN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \left(\frac{-1 \cdot r}{s} + \frac{\frac{-1}{3} \cdot r}{s}\right) - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    2. associate-*r/N/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \left(-1 \cdot \frac{r}{s} + \frac{\frac{-1}{3} \cdot r}{s}\right) - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    3. associate-*r/N/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \left(-1 \cdot \frac{r}{s} + \frac{-1}{3} \cdot \frac{r}{s}\right) - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    4. distribute-rgt-outN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \left(\frac{r}{s} \cdot \left(-1 + \frac{-1}{3}\right)\right) - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    5. metadata-evalN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \left(\frac{r}{s} \cdot \frac{-4}{3}\right) - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    6. *-commutativeN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \left(\frac{-4}{3} \cdot \frac{r}{s}\right) - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    7. associate-*r/N/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \frac{\frac{-4}{3} \cdot r}{s} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    8. frac-2negN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \frac{\mathsf{neg}\left(\frac{-4}{3} \cdot r\right)}{\mathsf{neg}\left(s\right)} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    9. distribute-lft-neg-outN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \frac{\left(\mathsf{neg}\left(\frac{-4}{3}\right)\right) \cdot r}{\mathsf{neg}\left(s\right)} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    10. metadata-evalN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \frac{\frac{4}{3} \cdot r}{\mathsf{neg}\left(s\right)} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    11. metadata-evalN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \frac{\left(\frac{1}{3} + 1\right) \cdot r}{\mathsf{neg}\left(s\right)} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    12. distribute-rgt1-inN/A

      \[\leadsto \frac{\frac{-1}{8} \cdot \frac{r + \frac{1}{3} \cdot r}{\mathsf{neg}\left(s\right)} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    13. associate-/l*N/A

      \[\leadsto \frac{\frac{\frac{-1}{8} \cdot \left(r + \frac{1}{3} \cdot r\right)}{\mathsf{neg}\left(s\right)} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    14. distribute-frac-neg2N/A

      \[\leadsto \frac{\left(\mathsf{neg}\left(\frac{\frac{-1}{8} \cdot \left(r + \frac{1}{3} \cdot r\right)}{s}\right)\right) - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    15. associate-/l*N/A

      \[\leadsto \frac{\left(\mathsf{neg}\left(\frac{-1}{8} \cdot \frac{r + \frac{1}{3} \cdot r}{s}\right)\right) - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    16. distribute-lft-neg-outN/A

      \[\leadsto \frac{\left(\mathsf{neg}\left(\frac{-1}{8}\right)\right) \cdot \frac{r + \frac{1}{3} \cdot r}{s} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    17. metadata-evalN/A

      \[\leadsto \frac{\frac{1}{8} \cdot \frac{r + \frac{1}{3} \cdot r}{s} - \frac{1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  5. Applied rewrites8.9%

    \[\leadsto \frac{\color{blue}{\mathsf{fma}\left(1.3333333333333333 \cdot \frac{r}{s}, 0.125, -0.25\right)}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  6. Taylor expanded in s around 0

    \[\leadsto \frac{\frac{\frac{-1}{4} \cdot s + \frac{1}{6} \cdot r}{\color{blue}{s}}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  7. Step-by-step derivation
    1. lower-/.f32N/A

      \[\leadsto \frac{\frac{\frac{-1}{4} \cdot s + \frac{1}{6} \cdot r}{s}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    2. +-commutativeN/A

      \[\leadsto \frac{\frac{\frac{1}{6} \cdot r + \frac{-1}{4} \cdot s}{s}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    3. lower-fma.f32N/A

      \[\leadsto \frac{\frac{\mathsf{fma}\left(\frac{1}{6}, r, \frac{-1}{4} \cdot s\right)}{s}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    4. lower-*.f328.9

      \[\leadsto \frac{\frac{\mathsf{fma}\left(0.16666666666666666, r, -0.25 \cdot s\right)}{s}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  8. Applied rewrites8.9%

    \[\leadsto \frac{\frac{\mathsf{fma}\left(0.16666666666666666, r, -0.25 \cdot s\right)}{\color{blue}{s}}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  9. Add Preprocessing

Alternative 8: 8.9% accurate, 3.1× speedup?

\[\begin{array}{l} \\ \mathsf{fma}\left(-1.3333333333333333, \frac{r}{s}, 2\right) \cdot \frac{0.125}{\left(s \cdot r\right) \cdot \pi} \end{array} \]
(FPCore (s r)
 :precision binary32
 (* (fma -1.3333333333333333 (/ r s) 2.0) (/ 0.125 (* (* s r) PI))))
float code(float s, float r) {
	return fmaf(-1.3333333333333333f, (r / s), 2.0f) * (0.125f / ((s * r) * ((float) M_PI)));
}
function code(s, r)
	return Float32(fma(Float32(-1.3333333333333333), Float32(r / s), Float32(2.0)) * Float32(Float32(0.125) / Float32(Float32(s * r) * Float32(pi))))
end
\begin{array}{l}

\\
\mathsf{fma}\left(-1.3333333333333333, \frac{r}{s}, 2\right) \cdot \frac{0.125}{\left(s \cdot r\right) \cdot \pi}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    2. lift-*.f32N/A

      \[\leadsto \frac{\color{blue}{\frac{1}{4} \cdot e^{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    3. lift-exp.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot \color{blue}{e^{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    4. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\color{blue}{\frac{-r}{s}}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    5. lift-neg.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\color{blue}{\mathsf{neg}\left(r\right)}}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    6. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\color{blue}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
    7. associate-/r*N/A

      \[\leadsto \color{blue}{\frac{\frac{\frac{1}{4} \cdot e^{\frac{\mathsf{neg}\left(r\right)}{s}}}{\left(2 \cdot \pi\right) \cdot s}}{r}} + \frac{\frac{3}{4} \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  3. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{0.125 \cdot e^{\frac{-r}{s}}}{\left(\pi \cdot s\right) \cdot r}} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  4. Applied rewrites97.8%

    \[\leadsto \color{blue}{\left(e^{\frac{r}{s} \cdot -0.3333333333333333} + e^{\frac{-r}{s}}\right) \cdot \frac{0.125}{\left(\pi \cdot s\right) \cdot r}} \]
  5. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\color{blue}{\left(\pi \cdot s\right) \cdot r}} \]
    2. lift-PI.f32N/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\left(\color{blue}{\mathsf{PI}\left(\right)} \cdot s\right) \cdot r} \]
    3. lift-*.f32N/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot s\right)} \cdot r} \]
    4. *-commutativeN/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)} \cdot r} \]
    5. *-commutativeN/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\color{blue}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    6. associate-*r*N/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\color{blue}{\left(r \cdot s\right) \cdot \mathsf{PI}\left(\right)}} \]
    7. *-commutativeN/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\color{blue}{\left(s \cdot r\right)} \cdot \mathsf{PI}\left(\right)} \]
    8. lift-*.f32N/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\color{blue}{\left(s \cdot r\right)} \cdot \mathsf{PI}\left(\right)} \]
    9. lower-*.f32N/A

      \[\leadsto \left(e^{\frac{r}{s} \cdot \frac{-1}{3}} + e^{\frac{-r}{s}}\right) \cdot \frac{\frac{1}{8}}{\color{blue}{\left(s \cdot r\right) \cdot \mathsf{PI}\left(\right)}} \]
    10. lift-PI.f3297.8

      \[\leadsto \left(e^{\frac{r}{s} \cdot -0.3333333333333333} + e^{\frac{-r}{s}}\right) \cdot \frac{0.125}{\left(s \cdot r\right) \cdot \color{blue}{\pi}} \]
  6. Applied rewrites97.8%

    \[\leadsto \left(e^{\frac{r}{s} \cdot -0.3333333333333333} + e^{\frac{-r}{s}}\right) \cdot \frac{0.125}{\color{blue}{\left(s \cdot r\right) \cdot \pi}} \]
  7. Taylor expanded in s around inf

    \[\leadsto \color{blue}{\left(2 + \left(-1 \cdot \frac{r}{s} + \frac{-1}{3} \cdot \frac{r}{s}\right)\right)} \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
  8. Step-by-step derivation
    1. distribute-rgt-outN/A

      \[\leadsto \left(2 + \frac{r}{s} \cdot \color{blue}{\left(-1 + \frac{-1}{3}\right)}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    2. metadata-evalN/A

      \[\leadsto \left(2 + \frac{r}{s} \cdot \frac{-4}{3}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    3. *-commutativeN/A

      \[\leadsto \left(2 + \frac{-4}{3} \cdot \color{blue}{\frac{r}{s}}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    4. fp-cancel-sign-sub-invN/A

      \[\leadsto \left(2 - \color{blue}{\left(\mathsf{neg}\left(\frac{-4}{3}\right)\right) \cdot \frac{r}{s}}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    5. metadata-evalN/A

      \[\leadsto \left(2 - \frac{4}{3} \cdot \frac{\color{blue}{r}}{s}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    6. associate-/l*N/A

      \[\leadsto \left(2 - \frac{\frac{4}{3} \cdot r}{\color{blue}{s}}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    7. metadata-evalN/A

      \[\leadsto \left(2 - \frac{\left(\frac{1}{3} + 1\right) \cdot r}{s}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    8. distribute-rgt1-inN/A

      \[\leadsto \left(2 - \frac{r + \frac{1}{3} \cdot r}{s}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    9. *-lft-identityN/A

      \[\leadsto \left(2 - 1 \cdot \color{blue}{\frac{r + \frac{1}{3} \cdot r}{s}}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    10. fp-cancel-sub-sign-invN/A

      \[\leadsto \left(2 + \color{blue}{\left(\mathsf{neg}\left(1\right)\right) \cdot \frac{r + \frac{1}{3} \cdot r}{s}}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    11. metadata-evalN/A

      \[\leadsto \left(2 + -1 \cdot \frac{\color{blue}{r + \frac{1}{3} \cdot r}}{s}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    12. fp-cancel-sign-sub-invN/A

      \[\leadsto \left(2 - \color{blue}{\left(\mathsf{neg}\left(-1\right)\right) \cdot \frac{r + \frac{1}{3} \cdot r}{s}}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    13. metadata-evalN/A

      \[\leadsto \left(2 - 1 \cdot \frac{\color{blue}{r + \frac{1}{3} \cdot r}}{s}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
    14. *-lft-identityN/A

      \[\leadsto \left(2 - \frac{r + \frac{1}{3} \cdot r}{\color{blue}{s}}\right) \cdot \frac{\frac{1}{8}}{\left(s \cdot r\right) \cdot \pi} \]
  9. Applied rewrites8.9%

    \[\leadsto \color{blue}{\mathsf{fma}\left(-1.3333333333333333, \frac{r}{s}, 2\right)} \cdot \frac{0.125}{\left(s \cdot r\right) \cdot \pi} \]
  10. Add Preprocessing

Alternative 9: 8.9% accurate, 3.4× speedup?

\[\begin{array}{l} \\ \frac{\mathsf{fma}\left(0.16666666666666666, \frac{r}{s}, -0.25\right)}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \end{array} \]
(FPCore (s r)
 :precision binary32
 (/ (fma 0.16666666666666666 (/ r s) -0.25) (* (* s r) (- PI))))
float code(float s, float r) {
	return fmaf(0.16666666666666666f, (r / s), -0.25f) / ((s * r) * -((float) M_PI));
}
function code(s, r)
	return Float32(fma(Float32(0.16666666666666666), Float32(r / s), Float32(-0.25)) / Float32(Float32(s * r) * Float32(-Float32(pi))))
end
\begin{array}{l}

\\
\frac{\mathsf{fma}\left(0.16666666666666666, \frac{r}{s}, -0.25\right)}{\left(s \cdot r\right) \cdot \left(-\pi\right)}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Applied rewrites99.5%

    \[\leadsto \color{blue}{\frac{-0.125 \cdot \left(e^{\frac{-r}{s}} + e^{-0.3333333333333333 \cdot \frac{r}{s}}\right)}{\left(s \cdot r\right) \cdot \left(-\pi\right)}} \]
  3. Taylor expanded in r around 0

    \[\leadsto \frac{\color{blue}{\frac{1}{6} \cdot \frac{r}{s} - \frac{1}{4}}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  4. Step-by-step derivation
    1. metadata-evalN/A

      \[\leadsto \frac{\frac{1}{6} \cdot \frac{r}{s} - \frac{1}{4} \cdot \color{blue}{1}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    2. fp-cancel-sub-sign-invN/A

      \[\leadsto \frac{\frac{1}{6} \cdot \frac{r}{s} + \color{blue}{\left(\mathsf{neg}\left(\frac{1}{4}\right)\right) \cdot 1}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    3. metadata-evalN/A

      \[\leadsto \frac{\frac{1}{6} \cdot \frac{r}{s} + \frac{-1}{4} \cdot 1}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    4. metadata-evalN/A

      \[\leadsto \frac{\frac{1}{6} \cdot \frac{r}{s} + \frac{-1}{4}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    5. lower-fma.f32N/A

      \[\leadsto \frac{\mathsf{fma}\left(\frac{1}{6}, \color{blue}{\frac{r}{s}}, \frac{-1}{4}\right)}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
    6. lift-/.f328.9

      \[\leadsto \frac{\mathsf{fma}\left(0.16666666666666666, \frac{r}{\color{blue}{s}}, -0.25\right)}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  5. Applied rewrites8.9%

    \[\leadsto \frac{\color{blue}{\mathsf{fma}\left(0.16666666666666666, \frac{r}{s}, -0.25\right)}}{\left(s \cdot r\right) \cdot \left(-\pi\right)} \]
  6. Add Preprocessing

Alternative 10: 8.9% accurate, 3.9× speedup?

\[\begin{array}{l} \\ \frac{\frac{0.25}{r} - \frac{0.16666666666666666}{s}}{\pi \cdot s} \end{array} \]
(FPCore (s r)
 :precision binary32
 (/ (- (/ 0.25 r) (/ 0.16666666666666666 s)) (* PI s)))
float code(float s, float r) {
	return ((0.25f / r) - (0.16666666666666666f / s)) / (((float) M_PI) * s);
}
function code(s, r)
	return Float32(Float32(Float32(Float32(0.25) / r) - Float32(Float32(0.16666666666666666) / s)) / Float32(Float32(pi) * s))
end
function tmp = code(s, r)
	tmp = ((single(0.25) / r) - (single(0.16666666666666666) / s)) / (single(pi) * s);
end
\begin{array}{l}

\\
\frac{\frac{0.25}{r} - \frac{0.16666666666666666}{s}}{\pi \cdot s}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Taylor expanded in s around inf

    \[\leadsto \color{blue}{\frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)} - \frac{1}{6} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s}} \]
  3. Step-by-step derivation
    1. div-subN/A

      \[\leadsto \frac{\frac{1}{4} \cdot \frac{1}{r \cdot \mathsf{PI}\left(\right)}}{s} - \color{blue}{\frac{\frac{1}{6} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s}} \]
    2. associate-*r/N/A

      \[\leadsto \frac{\frac{\frac{1}{4} \cdot 1}{r \cdot \mathsf{PI}\left(\right)}}{s} - \frac{\color{blue}{\frac{1}{6}} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s} \]
    3. metadata-evalN/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r \cdot \mathsf{PI}\left(\right)}}{s} - \frac{\frac{1}{6} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s} \]
    4. associate-/r*N/A

      \[\leadsto \frac{\frac{\frac{\frac{1}{4}}{r}}{\mathsf{PI}\left(\right)}}{s} - \frac{\color{blue}{\frac{1}{6}} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}{s} \]
    5. associate-/r*N/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r}}{\mathsf{PI}\left(\right) \cdot s} - \frac{\color{blue}{\frac{1}{6} \cdot \frac{1}{s \cdot \mathsf{PI}\left(\right)}}}{s} \]
    6. *-commutativeN/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r}}{s \cdot \mathsf{PI}\left(\right)} - \frac{\frac{1}{6} \cdot \color{blue}{\frac{1}{s \cdot \mathsf{PI}\left(\right)}}}{s} \]
    7. associate-*r/N/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r}}{s \cdot \mathsf{PI}\left(\right)} - \frac{\frac{\frac{1}{6} \cdot 1}{s \cdot \mathsf{PI}\left(\right)}}{s} \]
    8. metadata-evalN/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r}}{s \cdot \mathsf{PI}\left(\right)} - \frac{\frac{\frac{1}{6}}{s \cdot \mathsf{PI}\left(\right)}}{s} \]
    9. associate-/r*N/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r}}{s \cdot \mathsf{PI}\left(\right)} - \frac{\frac{\frac{\frac{1}{6}}{s}}{\mathsf{PI}\left(\right)}}{s} \]
    10. associate-/l/N/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r}}{s \cdot \mathsf{PI}\left(\right)} - \frac{\frac{\frac{1}{6}}{s}}{\color{blue}{\mathsf{PI}\left(\right) \cdot s}} \]
    11. *-commutativeN/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r}}{s \cdot \mathsf{PI}\left(\right)} - \frac{\frac{\frac{1}{6}}{s}}{s \cdot \color{blue}{\mathsf{PI}\left(\right)}} \]
    12. sub-divN/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{r} - \frac{\frac{1}{6}}{s}}{\color{blue}{s \cdot \mathsf{PI}\left(\right)}} \]
  4. Applied rewrites8.9%

    \[\leadsto \color{blue}{\frac{\frac{0.25}{r} - \frac{0.16666666666666666}{s}}{\pi \cdot s}} \]
  5. Add Preprocessing

Alternative 11: 8.9% accurate, 6.0× speedup?

\[\begin{array}{l} \\ \frac{\frac{0.25}{s}}{\pi \cdot r} \end{array} \]
(FPCore (s r) :precision binary32 (/ (/ 0.25 s) (* PI r)))
float code(float s, float r) {
	return (0.25f / s) / (((float) M_PI) * r);
}
function code(s, r)
	return Float32(Float32(Float32(0.25) / s) / Float32(Float32(pi) * r))
end
function tmp = code(s, r)
	tmp = (single(0.25) / s) / (single(pi) * r);
end
\begin{array}{l}

\\
\frac{\frac{0.25}{s}}{\pi \cdot r}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Taylor expanded in s around inf

    \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
  3. Step-by-step derivation
    1. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    2. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{r}} \]
    3. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{r}} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    5. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    6. lift-PI.f328.9

      \[\leadsto \frac{0.25}{\left(\pi \cdot s\right) \cdot r} \]
  4. Applied rewrites8.9%

    \[\leadsto \color{blue}{\frac{0.25}{\left(\pi \cdot s\right) \cdot r}} \]
  5. Step-by-step derivation
    1. lift-/.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{\left(\pi \cdot s\right) \cdot r}} \]
    2. metadata-evalN/A

      \[\leadsto \frac{\frac{1}{4} \cdot 1}{\color{blue}{\left(\pi \cdot s\right)} \cdot r} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot 1}{\left(\pi \cdot s\right) \cdot \color{blue}{r}} \]
    4. lift-PI.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot 1}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    5. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot 1}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    6. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4} \cdot 1}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot r} \]
    7. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4} \cdot 1}{r \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    8. times-fracN/A

      \[\leadsto \frac{\frac{1}{4}}{r} \cdot \color{blue}{\frac{1}{s \cdot \mathsf{PI}\left(\right)}} \]
    9. associate-/r*N/A

      \[\leadsto \frac{\frac{1}{4}}{r} \cdot \frac{\frac{1}{s}}{\color{blue}{\mathsf{PI}\left(\right)}} \]
    10. frac-timesN/A

      \[\leadsto \frac{\frac{1}{4} \cdot \frac{1}{s}}{\color{blue}{r \cdot \mathsf{PI}\left(\right)}} \]
    11. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{4} \cdot \frac{1}{s}}{\color{blue}{r \cdot \mathsf{PI}\left(\right)}} \]
    12. associate-*r/N/A

      \[\leadsto \frac{\frac{\frac{1}{4} \cdot 1}{s}}{\color{blue}{r} \cdot \mathsf{PI}\left(\right)} \]
    13. metadata-evalN/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{s}}{r \cdot \mathsf{PI}\left(\right)} \]
    14. lower-/.f32N/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{s}}{\color{blue}{r} \cdot \mathsf{PI}\left(\right)} \]
    15. *-commutativeN/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{s}}{\mathsf{PI}\left(\right) \cdot \color{blue}{r}} \]
    16. lower-*.f32N/A

      \[\leadsto \frac{\frac{\frac{1}{4}}{s}}{\mathsf{PI}\left(\right) \cdot \color{blue}{r}} \]
    17. lift-PI.f328.9

      \[\leadsto \frac{\frac{0.25}{s}}{\pi \cdot r} \]
  6. Applied rewrites8.9%

    \[\leadsto \frac{\frac{0.25}{s}}{\color{blue}{\pi \cdot r}} \]
  7. Add Preprocessing

Alternative 12: 8.9% accurate, 6.4× speedup?

\[\begin{array}{l} \\ \frac{0.25}{s \cdot \left(\pi \cdot r\right)} \end{array} \]
(FPCore (s r) :precision binary32 (/ 0.25 (* s (* PI r))))
float code(float s, float r) {
	return 0.25f / (s * (((float) M_PI) * r));
}
function code(s, r)
	return Float32(Float32(0.25) / Float32(s * Float32(Float32(pi) * r)))
end
function tmp = code(s, r)
	tmp = single(0.25) / (s * (single(pi) * r));
end
\begin{array}{l}

\\
\frac{0.25}{s \cdot \left(\pi \cdot r\right)}
\end{array}
Derivation
  1. Initial program 99.5%

    \[\frac{0.25 \cdot e^{\frac{-r}{s}}}{\left(\left(2 \cdot \pi\right) \cdot s\right) \cdot r} + \frac{0.75 \cdot e^{\frac{-r}{3 \cdot s}}}{\left(\left(6 \cdot \pi\right) \cdot s\right) \cdot r} \]
  2. Taylor expanded in s around inf

    \[\leadsto \color{blue}{\frac{\frac{1}{4}}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
  3. Step-by-step derivation
    1. lower-/.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\color{blue}{r \cdot \left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    2. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{r}} \]
    3. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot \color{blue}{r}} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    5. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    6. lift-PI.f328.9

      \[\leadsto \frac{0.25}{\left(\pi \cdot s\right) \cdot r} \]
  4. Applied rewrites8.9%

    \[\leadsto \color{blue}{\frac{0.25}{\left(\pi \cdot s\right) \cdot r}} \]
  5. Step-by-step derivation
    1. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\pi \cdot s\right) \cdot \color{blue}{r}} \]
    2. lift-PI.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    3. lift-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{\left(\mathsf{PI}\left(\right) \cdot s\right) \cdot r} \]
    4. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\left(s \cdot \mathsf{PI}\left(\right)\right) \cdot r} \]
    5. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{r \cdot \color{blue}{\left(s \cdot \mathsf{PI}\left(\right)\right)}} \]
    6. add-log-expN/A

      \[\leadsto \frac{\frac{1}{4}}{r \cdot \left(s \cdot \log \left(e^{\mathsf{PI}\left(\right)}\right)\right)} \]
    7. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{r \cdot \log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{s}\right)} \]
    8. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{s}\right)}^{r}\right)} \]
    9. pow-unpowN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{\left(s \cdot r\right)}\right)} \]
    10. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{\left(r \cdot s\right)}\right)} \]
    11. pow-unpowN/A

      \[\leadsto \frac{\frac{1}{4}}{\log \left({\left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{r}\right)}^{s}\right)} \]
    12. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \color{blue}{\log \left({\left(e^{\mathsf{PI}\left(\right)}\right)}^{r}\right)}} \]
    13. log-pow-revN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(r \cdot \color{blue}{\log \left(e^{\mathsf{PI}\left(\right)}\right)}\right)} \]
    14. add-log-expN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(r \cdot \mathsf{PI}\left(\right)\right)} \]
    15. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \color{blue}{\left(r \cdot \mathsf{PI}\left(\right)\right)}} \]
    16. *-commutativeN/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{r}\right)} \]
    17. lower-*.f32N/A

      \[\leadsto \frac{\frac{1}{4}}{s \cdot \left(\mathsf{PI}\left(\right) \cdot \color{blue}{r}\right)} \]
    18. lift-PI.f328.9

      \[\leadsto \frac{0.25}{s \cdot \left(\pi \cdot r\right)} \]
  6. Applied rewrites8.9%

    \[\leadsto \frac{0.25}{s \cdot \color{blue}{\left(\pi \cdot r\right)}} \]
  7. Add Preprocessing

Reproduce

?
herbie shell --seed 2025130 
(FPCore (s r)
  :name "Disney BSSRDF, PDF of scattering profile"
  :precision binary32
  :pre (and (and (<= 0.0 s) (<= s 256.0)) (and (< 1e-6 r) (< r 1000000.0)))
  (+ (/ (* 0.25 (exp (/ (- r) s))) (* (* (* 2.0 PI) s) r)) (/ (* 0.75 (exp (/ (- r) (* 3.0 s)))) (* (* (* 6.0 PI) s) r))))