| Alternative 1 | |
|---|---|
| Error | 26.4 |
| Cost | 26249 |
\[\begin{array}{l}
t_0 := -1 - {\tan x}^{2}\\
\mathbf{if}\;\tan x \leq -1 \lor \neg \left(\tan x \leq 1\right):\\
\;\;\;\;\frac{1}{t_0}\\
\mathbf{else}:\\
\;\;\;\;\frac{-1}{t_0}\\
\end{array}
\]
(FPCore (x) :precision binary64 (/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (* (tan x) (tan x)))))
(FPCore (x) :precision binary64 (/ (fma (tan x) (tan x) -1.0) (- -1.0 (pow (tan x) 2.0))))
double code(double x) {
return (1.0 - (tan(x) * tan(x))) / (1.0 + (tan(x) * tan(x)));
}
double code(double x) {
return fma(tan(x), tan(x), -1.0) / (-1.0 - pow(tan(x), 2.0));
}
function code(x) return Float64(Float64(1.0 - Float64(tan(x) * tan(x))) / Float64(1.0 + Float64(tan(x) * tan(x)))) end
function code(x) return Float64(fma(tan(x), tan(x), -1.0) / Float64(-1.0 - (tan(x) ^ 2.0))) end
code[x_] := N[(N[(1.0 - N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_] := N[(N[(N[Tan[x], $MachinePrecision] * N[Tan[x], $MachinePrecision] + -1.0), $MachinePrecision] / N[(-1.0 - N[Power[N[Tan[x], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{1 - \tan x \cdot \tan x}{1 + \tan x \cdot \tan x}
\frac{\mathsf{fma}\left(\tan x, \tan x, -1\right)}{-1 - {\tan x}^{2}}
Initial program 0.3
Simplified0.3
Applied egg-rr0.4
Simplified0.3
Final simplification0.3
| Alternative 1 | |
|---|---|
| Error | 26.4 |
| Cost | 26249 |
| Alternative 2 | |
|---|---|
| Error | 0.3 |
| Cost | 26176 |
| Alternative 3 | |
|---|---|
| Error | 29.0 |
| Cost | 13184 |
| Alternative 4 | |
|---|---|
| Error | 26.4 |
| Cost | 13056 |
| Alternative 5 | |
|---|---|
| Error | 29.2 |
| Cost | 64 |
herbie shell --seed 2022340
(FPCore (x)
:name "Trigonometry B"
:precision binary64
(/ (- 1.0 (* (tan x) (tan x))) (+ 1.0 (* (tan x) (tan x)))))