Average Error: 0.5 → 0.4
Time: 17.9s
Precision: binary32
\[-1 \leq cosTheta_i \land cosTheta_i \leq 1 \land -1 \leq cosTheta_O \land cosTheta_O \leq 1 \land -1 \leq sinTheta_i \land sinTheta_i \leq 1 \land -1 \leq sinTheta_O \land sinTheta_O \leq 1 \land 0.1 < v \land v \leq 1.5707964\]
\[[cosTheta_i, cosTheta_O]=\mathsf{sort}([cosTheta_i, cosTheta_O])\]
\[\frac{e^{-\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \frac{cosTheta_i \cdot cosTheta_O}{v}}{\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot v} \]
\[cosTheta_O \cdot \left(\left(\frac{1}{v} \cdot \frac{1}{v}\right) \cdot \frac{cosTheta_i}{e^{\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \left(2 \cdot \sinh \left(\frac{1}{v}\right)\right)}\right) \]
\frac{e^{-\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \frac{cosTheta_i \cdot cosTheta_O}{v}}{\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot v}
cosTheta_O \cdot \left(\left(\frac{1}{v} \cdot \frac{1}{v}\right) \cdot \frac{cosTheta_i}{e^{\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \left(2 \cdot \sinh \left(\frac{1}{v}\right)\right)}\right)
(FPCore (cosTheta_i cosTheta_O sinTheta_i sinTheta_O v)
 :precision binary32
 (/
  (* (exp (- (/ (* sinTheta_i sinTheta_O) v))) (/ (* cosTheta_i cosTheta_O) v))
  (* (* (sinh (/ 1.0 v)) 2.0) v)))
(FPCore (cosTheta_i cosTheta_O sinTheta_i sinTheta_O v)
 :precision binary32
 (*
  cosTheta_O
  (*
   (* (/ 1.0 v) (/ 1.0 v))
   (/
    cosTheta_i
    (* (exp (/ (* sinTheta_i sinTheta_O) v)) (* 2.0 (sinh (/ 1.0 v))))))))
float code(float cosTheta_i, float cosTheta_O, float sinTheta_i, float sinTheta_O, float v) {
	return (expf(-((sinTheta_i * sinTheta_O) / v)) * ((cosTheta_i * cosTheta_O) / v)) / ((sinhf(1.0f / v) * 2.0f) * v);
}
float code(float cosTheta_i, float cosTheta_O, float sinTheta_i, float sinTheta_O, float v) {
	return cosTheta_O * (((1.0f / v) * (1.0f / v)) * (cosTheta_i / (expf((sinTheta_i * sinTheta_O) / v) * (2.0f * sinhf(1.0f / v)))));
}

Error

Bits error versus cosTheta_i

Bits error versus cosTheta_O

Bits error versus sinTheta_i

Bits error versus sinTheta_O

Bits error versus v

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.5

    \[\frac{e^{-\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \frac{cosTheta_i \cdot cosTheta_O}{v}}{\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot v} \]
  2. Simplified0.4

    \[\leadsto \color{blue}{cosTheta_O \cdot \frac{\frac{cosTheta_i}{v}}{v \cdot \left(\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot e^{\frac{sinTheta_i \cdot sinTheta_O}{v}}\right)}} \]
  3. Using strategy rm
  4. Applied *-un-lft-identity_binary320.4

    \[\leadsto cosTheta_O \cdot \frac{\frac{cosTheta_i}{\color{blue}{1 \cdot v}}}{v \cdot \left(\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot e^{\frac{sinTheta_i \cdot sinTheta_O}{v}}\right)} \]
  5. Applied *-un-lft-identity_binary320.4

    \[\leadsto cosTheta_O \cdot \frac{\frac{\color{blue}{1 \cdot cosTheta_i}}{1 \cdot v}}{v \cdot \left(\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot e^{\frac{sinTheta_i \cdot sinTheta_O}{v}}\right)} \]
  6. Applied times-frac_binary320.4

    \[\leadsto cosTheta_O \cdot \frac{\color{blue}{\frac{1}{1} \cdot \frac{cosTheta_i}{v}}}{v \cdot \left(\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot e^{\frac{sinTheta_i \cdot sinTheta_O}{v}}\right)} \]
  7. Applied times-frac_binary320.4

    \[\leadsto cosTheta_O \cdot \color{blue}{\left(\frac{\frac{1}{1}}{v} \cdot \frac{\frac{cosTheta_i}{v}}{\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot e^{\frac{sinTheta_i \cdot sinTheta_O}{v}}}\right)} \]
  8. Simplified0.4

    \[\leadsto cosTheta_O \cdot \left(\color{blue}{\frac{1}{v}} \cdot \frac{\frac{cosTheta_i}{v}}{\left(\sinh \left(\frac{1}{v}\right) \cdot 2\right) \cdot e^{\frac{sinTheta_i \cdot sinTheta_O}{v}}}\right) \]
  9. Simplified0.4

    \[\leadsto cosTheta_O \cdot \left(\frac{1}{v} \cdot \color{blue}{\frac{cosTheta_i}{v \cdot \left(e^{\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \left(2 \cdot \sinh \left(\frac{1}{v}\right)\right)\right)}}\right) \]
  10. Using strategy rm
  11. Applied *-un-lft-identity_binary320.4

    \[\leadsto cosTheta_O \cdot \left(\frac{1}{v} \cdot \frac{\color{blue}{1 \cdot cosTheta_i}}{v \cdot \left(e^{\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \left(2 \cdot \sinh \left(\frac{1}{v}\right)\right)\right)}\right) \]
  12. Applied times-frac_binary320.4

    \[\leadsto cosTheta_O \cdot \left(\frac{1}{v} \cdot \color{blue}{\left(\frac{1}{v} \cdot \frac{cosTheta_i}{e^{\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \left(2 \cdot \sinh \left(\frac{1}{v}\right)\right)}\right)}\right) \]
  13. Applied associate-*r*_binary320.4

    \[\leadsto cosTheta_O \cdot \color{blue}{\left(\left(\frac{1}{v} \cdot \frac{1}{v}\right) \cdot \frac{cosTheta_i}{e^{\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \left(2 \cdot \sinh \left(\frac{1}{v}\right)\right)}\right)} \]
  14. Final simplification0.4

    \[\leadsto cosTheta_O \cdot \left(\left(\frac{1}{v} \cdot \frac{1}{v}\right) \cdot \frac{cosTheta_i}{e^{\frac{sinTheta_i \cdot sinTheta_O}{v}} \cdot \left(2 \cdot \sinh \left(\frac{1}{v}\right)\right)}\right) \]

Reproduce

herbie shell --seed 2021196 
(FPCore (cosTheta_i cosTheta_O sinTheta_i sinTheta_O v)
  :name "HairBSDF, Mp, upper"
  :precision binary32
  :pre (and (<= -1.0 cosTheta_i 1.0) (<= -1.0 cosTheta_O 1.0) (<= -1.0 sinTheta_i 1.0) (<= -1.0 sinTheta_O 1.0) (< 0.1 v) (<= v 1.5707964))
  (/ (* (exp (- (/ (* sinTheta_i sinTheta_O) v))) (/ (* cosTheta_i cosTheta_O) v)) (* (* (sinh (/ 1.0 v)) 2.0) v)))