| Alternative 1 | |
|---|---|
| Accuracy | 75.5% |
| Cost | 7113 |
\[\begin{array}{l}
\mathbf{if}\;x \leq 0.0015 \lor \neg \left(x \leq 1.4 \cdot 10^{-7}\right):\\
\;\;\;\;\frac{1}{B} - \frac{x}{\tan B}\\
\mathbf{else}:\\
\;\;\;\;\frac{1}{\sin B}\\
\end{array}
\]
(FPCore (B x) :precision binary64 (+ (- (* x (/ 1.0 (tan B)))) (/ 1.0 (sin B))))
(FPCore (B x) :precision binary64 (- (/ 1.0 (sin B)) (/ x (tan B))))
double code(double B, double x) {
return -(x * (1.0 / tan(B))) + (1.0 / sin(B));
}
double code(double B, double x) {
return (1.0 / sin(B)) - (x / tan(B));
}
real(8) function code(b, x)
real(8), intent (in) :: b
real(8), intent (in) :: x
code = -(x * (1.0d0 / tan(b))) + (1.0d0 / sin(b))
end function
real(8) function code(b, x)
real(8), intent (in) :: b
real(8), intent (in) :: x
code = (1.0d0 / sin(b)) - (x / tan(b))
end function
public static double code(double B, double x) {
return -(x * (1.0 / Math.tan(B))) + (1.0 / Math.sin(B));
}
public static double code(double B, double x) {
return (1.0 / Math.sin(B)) - (x / Math.tan(B));
}
def code(B, x): return -(x * (1.0 / math.tan(B))) + (1.0 / math.sin(B))
def code(B, x): return (1.0 / math.sin(B)) - (x / math.tan(B))
function code(B, x) return Float64(Float64(-Float64(x * Float64(1.0 / tan(B)))) + Float64(1.0 / sin(B))) end
function code(B, x) return Float64(Float64(1.0 / sin(B)) - Float64(x / tan(B))) end
function tmp = code(B, x) tmp = -(x * (1.0 / tan(B))) + (1.0 / sin(B)); end
function tmp = code(B, x) tmp = (1.0 / sin(B)) - (x / tan(B)); end
code[B_, x_] := N[((-N[(x * N[(1.0 / N[Tan[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]) + N[(1.0 / N[Sin[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[B_, x_] := N[(N[(1.0 / N[Sin[B], $MachinePrecision]), $MachinePrecision] - N[(x / N[Tan[B], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\left(-x \cdot \frac{1}{\tan B}\right) + \frac{1}{\sin B}
\frac{1}{\sin B} - \frac{x}{\tan B}
Results
Initial program 99.7%
Simplified99.8%
[Start]99.7 | \[ \left(-x \cdot \frac{1}{\tan B}\right) + \frac{1}{\sin B}
\] |
|---|---|
+-commutative [=>]99.7 | \[ \color{blue}{\frac{1}{\sin B} + \left(-x \cdot \frac{1}{\tan B}\right)}
\] |
unsub-neg [=>]99.7 | \[ \color{blue}{\frac{1}{\sin B} - x \cdot \frac{1}{\tan B}}
\] |
associate-*r/ [=>]99.8 | \[ \frac{1}{\sin B} - \color{blue}{\frac{x \cdot 1}{\tan B}}
\] |
*-rgt-identity [=>]99.8 | \[ \frac{1}{\sin B} - \frac{\color{blue}{x}}{\tan B}
\] |
Final simplification99.8%
| Alternative 1 | |
|---|---|
| Accuracy | 75.5% |
| Cost | 7113 |
| Alternative 2 | |
|---|---|
| Accuracy | 75.5% |
| Cost | 7113 |
| Alternative 3 | |
|---|---|
| Accuracy | 50.6% |
| Cost | 6857 |
| Alternative 4 | |
|---|---|
| Accuracy | 51.7% |
| Cost | 704 |
| Alternative 5 | |
|---|---|
| Accuracy | 26.6% |
| Cost | 521 |
| Alternative 6 | |
|---|---|
| Accuracy | 51.4% |
| Cost | 320 |
| Alternative 7 | |
|---|---|
| Accuracy | 3.2% |
| Cost | 192 |
| Alternative 8 | |
|---|---|
| Accuracy | 27.0% |
| Cost | 192 |
herbie shell --seed 2023159
(FPCore (B x)
:name "VandenBroeck and Keller, Equation (24)"
:precision binary64
(+ (- (* x (/ 1.0 (tan B)))) (/ 1.0 (sin B))))