rsin A (should all be same)

Average Accuracy: 76.6% → 99.5%

Time: 18.5s

Precision: binary64

Cost: 39040

Math

\[\frac{r \cdot \sin b}{\cos \left(a + b\right)} \]

↓

\[\frac{\sin b}{\mathsf{fma}\left(\sin b, -\sin a, \cos b \cdot \cos a\right)} \cdot r \]

FPCore

(FPCore (r a b) :precision binary64 (/ (* r (sin b)) (cos (+ a b))))

↓

(FPCore (r a b)
 :precision binary64
 (* (/ (sin b) (fma (sin b) (- (sin a)) (* (cos b) (cos a)))) r))

C

double code(double r, double a, double b) {
	return (r * sin(b)) / cos((a + b));
}

↓

double code(double r, double a, double b) {
	return (sin(b) / fma(sin(b), -sin(a), (cos(b) * cos(a)))) * r;
}

Julia

function code(r, a, b)
	return Float64(Float64(r * sin(b)) / cos(Float64(a + b)))
end

↓

function code(r, a, b)
	return Float64(Float64(sin(b) / fma(sin(b), Float64(-sin(a)), Float64(cos(b) * cos(a)))) * r)
end

Wolfram

code[r_, a_, b_] := N[(N[(r * N[Sin[b], $MachinePrecision]), $MachinePrecision] / N[Cos[N[(a + b), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

↓

code[r_, a_, b_] := N[(N[(N[Sin[b], $MachinePrecision] / N[(N[Sin[b], $MachinePrecision] * (-N[Sin[a], $MachinePrecision]) + N[(N[Cos[b], $MachinePrecision] * N[Cos[a], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * r), $MachinePrecision]

Derivation

1. Initial program 74.6%

   \[\frac{r \cdot \sin b}{\cos \left(a + b\right)} \]

2. Simplified 74.6%

   \[\leadsto \color{blue}{\frac{\sin b}{\cos \left(b + a\right)} \cdot r} \]
   Proof

   [Start] 74.6	\[ \frac{r \cdot \sin b}{\cos \left(a + b\right)} \]
   associate-*r/ [<=] 74.6	\[ \color{blue}{r \cdot \frac{\sin b}{\cos \left(a + b\right)}} \]
   *-commutative [<=] 74.6	\[ \color{blue}{\frac{\sin b}{\cos \left(a + b\right)} \cdot r} \]
   +-commutative [=>] 74.6	\[ \frac{\sin b}{\cos \color{blue}{\left(b + a\right)}} \cdot r \]

3. Applied egg-rr 99.5%

   \[\leadsto \frac{\sin b}{\color{blue}{\cos b \cdot \cos a - \sin b \cdot \sin a}} \cdot r \]
   Proof

   [Start] 74.6	\[ \frac{\sin b}{\cos \left(b + a\right)} \cdot r \]
   cos-sum [=>] 99.5	\[ \frac{\sin b}{\color{blue}{\cos b \cdot \cos a - \sin b \cdot \sin a}} \cdot r \]

4. Applied egg-rr 99.5%

   \[\leadsto \frac{\sin b}{\color{blue}{\mathsf{fma}\left(\sin b, -\sin a, \cos b \cdot \cos a\right)}} \cdot r \]
   Proof

   [Start] 99.5	\[ \frac{\sin b}{\cos b \cdot \cos a - \sin b \cdot \sin a} \cdot r \]
   sub-neg [=>] 99.5	\[ \frac{\sin b}{\color{blue}{\cos b \cdot \cos a + \left(-\sin b \cdot \sin a\right)}} \cdot r \]
   +-commutative [=>] 99.5	\[ \frac{\sin b}{\color{blue}{\left(-\sin b \cdot \sin a\right) + \cos b \cdot \cos a}} \cdot r \]
   distribute-rgt-neg-in [=>] 99.5	\[ \frac{\sin b}{\color{blue}{\sin b \cdot \left(-\sin a\right)} + \cos b \cdot \cos a} \cdot r \]
   fma-def [=>] 99.5	\[ \frac{\sin b}{\color{blue}{\mathsf{fma}\left(\sin b, -\sin a, \cos b \cdot \cos a\right)}} \cdot r \]

5. Final simplification 99.5%

   \[\leadsto \frac{\sin b}{\mathsf{fma}\left(\sin b, -\sin a, \cos b \cdot \cos a\right)} \cdot r \]

Alternatives

Alternative 1
Accuracy	99.5%
Cost	39040

\[r \cdot \frac{\sin b}{\mathsf{fma}\left(\cos b, \cos a, \sin b \cdot \left(-\sin a\right)\right)} \]

Alternative 2
Accuracy	99.5%
Cost	32704

\[r \cdot \frac{\sin b}{\cos b \cdot \cos a - \sin b \cdot \sin a} \]

Alternative 3
Accuracy	99.4%
Cost	32512

\[\frac{r}{\mathsf{fma}\left(\frac{\cos b}{\sin b}, \cos a, -\sin a\right)} \]

Alternative 4
Accuracy	77.5%
Cost	26048

\[r \cdot \frac{\sin b}{\mathsf{fma}\left(\cos b, \cos a, 0\right)} \]

Alternative 5
Accuracy	76.4%
Cost	13385

\[\begin{array}{l} \mathbf{if}\;a \leq -1.6 \cdot 10^{-6} \lor \neg \left(a \leq 0.0132\right):\\ \;\;\;\;\sin b \cdot \frac{r}{\cos a}\\ \mathbf{else}:\\ \;\;\;\;r \cdot \tan b\\ \end{array} \]

Alternative 6
Accuracy	76.4%
Cost	13385

\[\begin{array}{l} \mathbf{if}\;a \leq -0.00186 \lor \neg \left(a \leq 0.0132\right):\\ \;\;\;\;\frac{r}{\frac{\cos a}{\sin b}}\\ \mathbf{else}:\\ \;\;\;\;r \cdot \tan b\\ \end{array} \]

Alternative 7
Accuracy	76.4%
Cost	13384

\[\begin{array}{l} \mathbf{if}\;a \leq -0.0018:\\ \;\;\;\;\frac{r}{\frac{\cos a}{\sin b}}\\ \mathbf{elif}\;a \leq 0.0132:\\ \;\;\;\;r \cdot \tan b\\ \mathbf{else}:\\ \;\;\;\;\frac{\sin b \cdot r}{\cos a}\\ \end{array} \]

Alternative 8
Accuracy	76.6%
Cost	13248

\[\sin b \cdot \frac{r}{\cos \left(b + a\right)} \]

Alternative 9
Accuracy	76.4%
Cost	7113

\[\begin{array}{l} \mathbf{if}\;b \leq -0.7 \lor \neg \left(b \leq 0.000195\right):\\ \;\;\;\;r \cdot \tan b\\ \mathbf{else}:\\ \;\;\;\;\frac{b \cdot r}{\cos \left(b + a\right)}\\ \end{array} \]

Alternative 10
Accuracy	76.3%
Cost	6985

\[\begin{array}{l} \mathbf{if}\;b \leq -0.7 \lor \neg \left(b \leq 3.4 \cdot 10^{-5}\right):\\ \;\;\;\;r \cdot \tan b\\ \mathbf{else}:\\ \;\;\;\;r \cdot \frac{b}{\cos a}\\ \end{array} \]

Alternative 11
Accuracy	76.3%
Cost	6985

\[\begin{array}{l} \mathbf{if}\;b \leq -0.7 \lor \neg \left(b \leq 3.2 \cdot 10^{-5}\right):\\ \;\;\;\;r \cdot \tan b\\ \mathbf{else}:\\ \;\;\;\;b \cdot \frac{r}{\cos a}\\ \end{array} \]

Alternative 12
Accuracy	76.3%
Cost	6985

\[\begin{array}{l} \mathbf{if}\;b \leq -0.7 \lor \neg \left(b \leq 0.00035\right):\\ \;\;\;\;r \cdot \tan b\\ \mathbf{else}:\\ \;\;\;\;\frac{b \cdot r}{\cos a}\\ \end{array} \]

Alternative 13
Accuracy	38.7%
Cost	6592

\[\sin b \cdot r \]

Alternative 14
Accuracy	60.1%
Cost	6592

\[r \cdot \tan b \]

Alternative 15
Accuracy	35.2%
Cost	576

\[\frac{r}{b \cdot -0.3333333333333333 + \frac{1}{b}} \]

Alternative 16
Accuracy	34.3%
Cost	192

\[b \cdot r \]

Reproduce

herbie shell --seed 2023157 
(FPCore (r a b)
  :name "rsin A (should all be same)"
  :precision binary64
  (/ (* r (sin b)) (cos (+ a b))))