?

Average Accuracy: 51.2% → 100.0%
Time: 24.5s
Precision: binary64
Cost: 26632

?

\[\frac{x - \sin x}{x - \tan x} \]
\[\begin{array}{l} t_0 := \tan x - x\\ \mathbf{if}\;x \leq -0.095:\\ \;\;\;\;\frac{x - \sin x}{x - \tan x}\\ \mathbf{elif}\;x \leq 0.095:\\ \;\;\;\;\left(x \cdot \left(x \cdot 0.225\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\sin x, \frac{1}{t_0}, \frac{-x}{t_0}\right)\\ \end{array} \]
(FPCore (x) :precision binary64 (/ (- x (sin x)) (- x (tan x))))
(FPCore (x)
 :precision binary64
 (let* ((t_0 (- (tan x) x)))
   (if (<= x -0.095)
     (/ (- x (sin x)) (- x (tan x)))
     (if (<= x 0.095)
       (-
        (+
         (* x (* x 0.225))
         (+
          (* -0.009642857142857142 (pow x 4.0))
          (* 0.00024107142857142857 (pow x 6.0))))
        0.5)
       (fma (sin x) (/ 1.0 t_0) (/ (- x) t_0))))))
double code(double x) {
	return (x - sin(x)) / (x - tan(x));
}
double code(double x) {
	double t_0 = tan(x) - x;
	double tmp;
	if (x <= -0.095) {
		tmp = (x - sin(x)) / (x - tan(x));
	} else if (x <= 0.095) {
		tmp = ((x * (x * 0.225)) + ((-0.009642857142857142 * pow(x, 4.0)) + (0.00024107142857142857 * pow(x, 6.0)))) - 0.5;
	} else {
		tmp = fma(sin(x), (1.0 / t_0), (-x / t_0));
	}
	return tmp;
}
function code(x)
	return Float64(Float64(x - sin(x)) / Float64(x - tan(x)))
end
function code(x)
	t_0 = Float64(tan(x) - x)
	tmp = 0.0
	if (x <= -0.095)
		tmp = Float64(Float64(x - sin(x)) / Float64(x - tan(x)));
	elseif (x <= 0.095)
		tmp = Float64(Float64(Float64(x * Float64(x * 0.225)) + Float64(Float64(-0.009642857142857142 * (x ^ 4.0)) + Float64(0.00024107142857142857 * (x ^ 6.0)))) - 0.5);
	else
		tmp = fma(sin(x), Float64(1.0 / t_0), Float64(Float64(-x) / t_0));
	end
	return tmp
end
code[x_] := N[(N[(x - N[Sin[x], $MachinePrecision]), $MachinePrecision] / N[(x - N[Tan[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
code[x_] := Block[{t$95$0 = N[(N[Tan[x], $MachinePrecision] - x), $MachinePrecision]}, If[LessEqual[x, -0.095], N[(N[(x - N[Sin[x], $MachinePrecision]), $MachinePrecision] / N[(x - N[Tan[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 0.095], N[(N[(N[(x * N[(x * 0.225), $MachinePrecision]), $MachinePrecision] + N[(N[(-0.009642857142857142 * N[Power[x, 4.0], $MachinePrecision]), $MachinePrecision] + N[(0.00024107142857142857 * N[Power[x, 6.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision], N[(N[Sin[x], $MachinePrecision] * N[(1.0 / t$95$0), $MachinePrecision] + N[((-x) / t$95$0), $MachinePrecision]), $MachinePrecision]]]]
\frac{x - \sin x}{x - \tan x}
\begin{array}{l}
t_0 := \tan x - x\\
\mathbf{if}\;x \leq -0.095:\\
\;\;\;\;\frac{x - \sin x}{x - \tan x}\\

\mathbf{elif}\;x \leq 0.095:\\
\;\;\;\;\left(x \cdot \left(x \cdot 0.225\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5\\

\mathbf{else}:\\
\;\;\;\;\mathsf{fma}\left(\sin x, \frac{1}{t_0}, \frac{-x}{t_0}\right)\\


\end{array}

Error?

Derivation?

  1. Split input into 3 regimes
  2. if x < -0.095000000000000001

    1. Initial program 99.9%

      \[\frac{x - \sin x}{x - \tan x} \]

    if -0.095000000000000001 < x < 0.095000000000000001

    1. Initial program 1.4%

      \[\frac{x - \sin x}{x - \tan x} \]
    2. Simplified1.4%

      \[\leadsto \color{blue}{\frac{\sin x - x}{\tan x - x}} \]
      Proof

      [Start]1.4

      \[ \frac{x - \sin x}{x - \tan x} \]

      sub-neg [=>]1.4

      \[ \frac{\color{blue}{x + \left(-\sin x\right)}}{x - \tan x} \]

      +-commutative [=>]1.4

      \[ \frac{\color{blue}{\left(-\sin x\right) + x}}{x - \tan x} \]

      neg-sub0 [=>]1.4

      \[ \frac{\color{blue}{\left(0 - \sin x\right)} + x}{x - \tan x} \]

      associate-+l- [=>]1.4

      \[ \frac{\color{blue}{0 - \left(\sin x - x\right)}}{x - \tan x} \]

      sub0-neg [=>]1.4

      \[ \frac{\color{blue}{-\left(\sin x - x\right)}}{x - \tan x} \]

      neg-mul-1 [=>]1.4

      \[ \frac{\color{blue}{-1 \cdot \left(\sin x - x\right)}}{x - \tan x} \]

      sub-neg [=>]1.4

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{x + \left(-\tan x\right)}} \]

      +-commutative [=>]1.4

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{\left(-\tan x\right) + x}} \]

      neg-sub0 [=>]1.4

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{\left(0 - \tan x\right)} + x} \]

      associate-+l- [=>]1.4

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{0 - \left(\tan x - x\right)}} \]

      sub0-neg [=>]1.4

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{-\left(\tan x - x\right)}} \]

      neg-mul-1 [=>]1.4

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{-1 \cdot \left(\tan x - x\right)}} \]

      times-frac [=>]1.4

      \[ \color{blue}{\frac{-1}{-1} \cdot \frac{\sin x - x}{\tan x - x}} \]

      metadata-eval [=>]1.4

      \[ \color{blue}{1} \cdot \frac{\sin x - x}{\tan x - x} \]

      *-lft-identity [=>]1.4

      \[ \color{blue}{\frac{\sin x - x}{\tan x - x}} \]
    3. Taylor expanded in x around 0 100.0%

      \[\leadsto \color{blue}{\left(0.225 \cdot {x}^{2} + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5} \]
    4. Applied egg-rr100.0%

      \[\leadsto \left(\color{blue}{\left(0 + x \cdot \left(x \cdot 0.225\right)\right)} + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]
      Proof

      [Start]100.0

      \[ \left(0.225 \cdot {x}^{2} + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      add-log-exp [=>]100.0

      \[ \left(\color{blue}{\log \left(e^{0.225 \cdot {x}^{2}}\right)} + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      *-un-lft-identity [=>]100.0

      \[ \left(\log \color{blue}{\left(1 \cdot e^{0.225 \cdot {x}^{2}}\right)} + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      log-prod [=>]100.0

      \[ \left(\color{blue}{\left(\log 1 + \log \left(e^{0.225 \cdot {x}^{2}}\right)\right)} + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      metadata-eval [=>]100.0

      \[ \left(\left(\color{blue}{0} + \log \left(e^{0.225 \cdot {x}^{2}}\right)\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      add-log-exp [<=]100.0

      \[ \left(\left(0 + \color{blue}{0.225 \cdot {x}^{2}}\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      *-commutative [=>]100.0

      \[ \left(\left(0 + \color{blue}{{x}^{2} \cdot 0.225}\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      unpow2 [=>]100.0

      \[ \left(\left(0 + \color{blue}{\left(x \cdot x\right)} \cdot 0.225\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      associate-*l* [=>]100.0

      \[ \left(\left(0 + \color{blue}{x \cdot \left(x \cdot 0.225\right)}\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]
    5. Simplified100.0%

      \[\leadsto \left(\color{blue}{x \cdot \left(x \cdot 0.225\right)} + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]
      Proof

      [Start]100.0

      \[ \left(\left(0 + x \cdot \left(x \cdot 0.225\right)\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

      +-lft-identity [=>]100.0

      \[ \left(\color{blue}{x \cdot \left(x \cdot 0.225\right)} + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5 \]

    if 0.095000000000000001 < x

    1. Initial program 100.0%

      \[\frac{x - \sin x}{x - \tan x} \]
    2. Simplified100.0%

      \[\leadsto \color{blue}{\frac{\sin x - x}{\tan x - x}} \]
      Proof

      [Start]100.0

      \[ \frac{x - \sin x}{x - \tan x} \]

      sub-neg [=>]100.0

      \[ \frac{\color{blue}{x + \left(-\sin x\right)}}{x - \tan x} \]

      +-commutative [=>]100.0

      \[ \frac{\color{blue}{\left(-\sin x\right) + x}}{x - \tan x} \]

      neg-sub0 [=>]100.0

      \[ \frac{\color{blue}{\left(0 - \sin x\right)} + x}{x - \tan x} \]

      associate-+l- [=>]100.0

      \[ \frac{\color{blue}{0 - \left(\sin x - x\right)}}{x - \tan x} \]

      sub0-neg [=>]100.0

      \[ \frac{\color{blue}{-\left(\sin x - x\right)}}{x - \tan x} \]

      neg-mul-1 [=>]100.0

      \[ \frac{\color{blue}{-1 \cdot \left(\sin x - x\right)}}{x - \tan x} \]

      sub-neg [=>]100.0

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{x + \left(-\tan x\right)}} \]

      +-commutative [=>]100.0

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{\left(-\tan x\right) + x}} \]

      neg-sub0 [=>]100.0

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{\left(0 - \tan x\right)} + x} \]

      associate-+l- [=>]100.0

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{0 - \left(\tan x - x\right)}} \]

      sub0-neg [=>]100.0

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{-\left(\tan x - x\right)}} \]

      neg-mul-1 [=>]100.0

      \[ \frac{-1 \cdot \left(\sin x - x\right)}{\color{blue}{-1 \cdot \left(\tan x - x\right)}} \]

      times-frac [=>]100.0

      \[ \color{blue}{\frac{-1}{-1} \cdot \frac{\sin x - x}{\tan x - x}} \]

      metadata-eval [=>]100.0

      \[ \color{blue}{1} \cdot \frac{\sin x - x}{\tan x - x} \]

      *-lft-identity [=>]100.0

      \[ \color{blue}{\frac{\sin x - x}{\tan x - x}} \]
    3. Applied egg-rr100.0%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sin x, \frac{1}{\tan x - x}, -\frac{x}{\tan x - x}\right)} \]
      Proof

      [Start]100.0

      \[ \frac{\sin x - x}{\tan x - x} \]

      div-sub [=>]100.0

      \[ \color{blue}{\frac{\sin x}{\tan x - x} - \frac{x}{\tan x - x}} \]

      div-inv [=>]100.0

      \[ \color{blue}{\sin x \cdot \frac{1}{\tan x - x}} - \frac{x}{\tan x - x} \]

      fma-neg [=>]100.0

      \[ \color{blue}{\mathsf{fma}\left(\sin x, \frac{1}{\tan x - x}, -\frac{x}{\tan x - x}\right)} \]
  3. Recombined 3 regimes into one program.
  4. Final simplification100.0%

    \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -0.095:\\ \;\;\;\;\frac{x - \sin x}{x - \tan x}\\ \mathbf{elif}\;x \leq 0.095:\\ \;\;\;\;\left(x \cdot \left(x \cdot 0.225\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5\\ \mathbf{else}:\\ \;\;\;\;\mathsf{fma}\left(\sin x, \frac{1}{\tan x - x}, \frac{-x}{\tan x - x}\right)\\ \end{array} \]

Alternatives

Alternative 1
Accuracy100.0%
Cost14152
\[\begin{array}{l} \mathbf{if}\;x \leq -0.095:\\ \;\;\;\;\frac{x - \sin x}{x - \tan x}\\ \mathbf{elif}\;x \leq 0.095:\\ \;\;\;\;\left(x \cdot \left(x \cdot 0.225\right) + \left(-0.009642857142857142 \cdot {x}^{4} + 0.00024107142857142857 \cdot {x}^{6}\right)\right) - 0.5\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\frac{\tan x - x}{\sin x - x}}\\ \end{array} \]
Alternative 2
Accuracy100.0%
Cost13640
\[\begin{array}{l} \mathbf{if}\;x \leq -0.028:\\ \;\;\;\;\frac{x - \sin x}{x - \tan x}\\ \mathbf{elif}\;x \leq 0.023:\\ \;\;\;\;\left(x \cdot x\right) \cdot \left(0.225 + x \cdot \left(x \cdot -0.009642857142857142\right)\right) + -0.5\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\frac{\tan x - x}{\sin x - x}}\\ \end{array} \]
Alternative 3
Accuracy99.4%
Cost13513
\[\begin{array}{l} \mathbf{if}\;x \leq -2.6 \lor \neg \left(x \leq 2.6\right):\\ \;\;\;\;1 + \frac{\tan x - \sin x}{x}\\ \mathbf{else}:\\ \;\;\;\;\left(x \cdot x\right) \cdot \left(0.225 + x \cdot \left(x \cdot -0.009642857142857142\right)\right) + -0.5\\ \end{array} \]
Alternative 4
Accuracy100.0%
Cost13513
\[\begin{array}{l} \mathbf{if}\;x \leq -0.028 \lor \neg \left(x \leq 0.023\right):\\ \;\;\;\;\frac{x - \sin x}{x - \tan x}\\ \mathbf{else}:\\ \;\;\;\;\left(x \cdot x\right) \cdot \left(0.225 + x \cdot \left(x \cdot -0.009642857142857142\right)\right) + -0.5\\ \end{array} \]
Alternative 5
Accuracy98.9%
Cost1096
\[\begin{array}{l} \mathbf{if}\;x \leq -2.9:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 3:\\ \;\;\;\;\left(x \cdot x\right) \cdot \left(0.225 + x \cdot \left(x \cdot -0.009642857142857142\right)\right) + -0.5\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]
Alternative 6
Accuracy98.8%
Cost712
\[\begin{array}{l} \mathbf{if}\;x \leq -2.6:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 4.5:\\ \;\;\;\;-0.5 + 0.225 \cdot \left(x \cdot x\right)\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]
Alternative 7
Accuracy98.5%
Cost328
\[\begin{array}{l} \mathbf{if}\;x \leq -1.55:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 1.6:\\ \;\;\;\;-0.5\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]
Alternative 8
Accuracy49.9%
Cost64
\[-0.5 \]

Error

Reproduce?

herbie shell --seed 2023142 
(FPCore (x)
  :name "sintan (problem 3.4.5)"
  :precision binary64
  (/ (- x (sin x)) (- x (tan x))))