2cos (problem 3.3.5)

?

Percentage Accurate: 37.8% → 99.1%
Time: 19.3s
Precision: binary64
Cost: 39177

?

\[\cos \left(x + \varepsilon\right) - \cos x \]
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -6.5 \cdot 10^{-5} \lor \neg \left(\varepsilon \leq 3 \cdot 10^{-5}\right):\\ \;\;\;\;\mathsf{fma}\left(\sin \varepsilon, -\sin x, \cos \varepsilon \cdot \cos x\right) - \cos x\\ \mathbf{else}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\ \end{array} \]
(FPCore (x eps) :precision binary64 (- (cos (+ x eps)) (cos x)))
(FPCore (x eps)
 :precision binary64
 (if (or (<= eps -6.5e-5) (not (<= eps 3e-5)))
   (- (fma (sin eps) (- (sin x)) (* (cos eps) (cos x))) (cos x))
   (- (* -0.5 (* eps (* eps (cos x)))) (* eps (sin x)))))
double code(double x, double eps) {
	return cos((x + eps)) - cos(x);
}
double code(double x, double eps) {
	double tmp;
	if ((eps <= -6.5e-5) || !(eps <= 3e-5)) {
		tmp = fma(sin(eps), -sin(x), (cos(eps) * cos(x))) - cos(x);
	} else {
		tmp = (-0.5 * (eps * (eps * cos(x)))) - (eps * sin(x));
	}
	return tmp;
}
function code(x, eps)
	return Float64(cos(Float64(x + eps)) - cos(x))
end
function code(x, eps)
	tmp = 0.0
	if ((eps <= -6.5e-5) || !(eps <= 3e-5))
		tmp = Float64(fma(sin(eps), Float64(-sin(x)), Float64(cos(eps) * cos(x))) - cos(x));
	else
		tmp = Float64(Float64(-0.5 * Float64(eps * Float64(eps * cos(x)))) - Float64(eps * sin(x)));
	end
	return tmp
end
code[x_, eps_] := N[(N[Cos[N[(x + eps), $MachinePrecision]], $MachinePrecision] - N[Cos[x], $MachinePrecision]), $MachinePrecision]
code[x_, eps_] := If[Or[LessEqual[eps, -6.5e-5], N[Not[LessEqual[eps, 3e-5]], $MachinePrecision]], N[(N[(N[Sin[eps], $MachinePrecision] * (-N[Sin[x], $MachinePrecision]) + N[(N[Cos[eps], $MachinePrecision] * N[Cos[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Cos[x], $MachinePrecision]), $MachinePrecision], N[(N[(-0.5 * N[(eps * N[(eps * N[Cos[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(eps * N[Sin[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\cos \left(x + \varepsilon\right) - \cos x
\begin{array}{l}
\mathbf{if}\;\varepsilon \leq -6.5 \cdot 10^{-5} \lor \neg \left(\varepsilon \leq 3 \cdot 10^{-5}\right):\\
\;\;\;\;\mathsf{fma}\left(\sin \varepsilon, -\sin x, \cos \varepsilon \cdot \cos x\right) - \cos x\\

\mathbf{else}:\\
\;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\


\end{array}

Local Percentage Accuracy vs ?

The average percentage accuracy by input value. Horizontal axis shows value of an input variable; the variable is choosen in the title. Vertical axis is accuracy; higher is better. Red represent the original program, while blue represents Herbie's suggestion. These can be toggled with buttons below the plot. The line is an average while dots represent individual samples.

Herbie found 15 alternatives:

AlternativeAccuracySpeedup

Accuracy vs Speed

The accuracy (vertical axis) and speed (horizontal axis) of each alternatives. Up and to the right is better. The red square shows the initial program, and each blue circle shows an alternative.The line shows the best available speed-accuracy tradeoffs.

Bogosity?

Bogosity

Derivation?

  1. Split input into 2 regimes
  2. if eps < -6.49999999999999943e-5 or 3.00000000000000008e-5 < eps

    1. Initial program 48.2%

      \[\cos \left(x + \varepsilon\right) - \cos x \]
    2. Applied egg-rr98.6%

      \[\leadsto \color{blue}{\left(\cos x \cdot \cos \varepsilon + \left(-\sin x \cdot \sin \varepsilon\right)\right)} - \cos x \]
      Step-by-step derivation

      [Start]48.2%

      \[ \cos \left(x + \varepsilon\right) - \cos x \]

      cos-sum [=>]98.6%

      \[ \color{blue}{\left(\cos x \cdot \cos \varepsilon - \sin x \cdot \sin \varepsilon\right)} - \cos x \]

      sub-neg [=>]98.6%

      \[ \color{blue}{\left(\cos x \cdot \cos \varepsilon + \left(-\sin x \cdot \sin \varepsilon\right)\right)} - \cos x \]
    3. Simplified98.7%

      \[\leadsto \color{blue}{\mathsf{fma}\left(\sin \varepsilon, -\sin x, \cos \varepsilon \cdot \cos x\right)} - \cos x \]
      Step-by-step derivation

      [Start]98.6%

      \[ \left(\cos x \cdot \cos \varepsilon + \left(-\sin x \cdot \sin \varepsilon\right)\right) - \cos x \]

      +-commutative [=>]98.6%

      \[ \color{blue}{\left(\left(-\sin x \cdot \sin \varepsilon\right) + \cos x \cdot \cos \varepsilon\right)} - \cos x \]

      distribute-lft-neg-in [=>]98.6%

      \[ \left(\color{blue}{\left(-\sin x\right) \cdot \sin \varepsilon} + \cos x \cdot \cos \varepsilon\right) - \cos x \]

      *-commutative [=>]98.6%

      \[ \left(\color{blue}{\sin \varepsilon \cdot \left(-\sin x\right)} + \cos x \cdot \cos \varepsilon\right) - \cos x \]

      fma-def [=>]98.7%

      \[ \color{blue}{\mathsf{fma}\left(\sin \varepsilon, -\sin x, \cos x \cdot \cos \varepsilon\right)} - \cos x \]

      *-commutative [=>]98.7%

      \[ \mathsf{fma}\left(\sin \varepsilon, -\sin x, \color{blue}{\cos \varepsilon \cdot \cos x}\right) - \cos x \]

    if -6.49999999999999943e-5 < eps < 3.00000000000000008e-5

    1. Initial program 22.6%

      \[\cos \left(x + \varepsilon\right) - \cos x \]
    2. Taylor expanded in eps around 0 99.8%

      \[\leadsto \color{blue}{-0.5 \cdot \left({\varepsilon}^{2} \cdot \cos x\right) + -1 \cdot \left(\varepsilon \cdot \sin x\right)} \]
    3. Simplified99.8%

      \[\leadsto \color{blue}{-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x} \]
      Step-by-step derivation

      [Start]99.8%

      \[ -0.5 \cdot \left({\varepsilon}^{2} \cdot \cos x\right) + -1 \cdot \left(\varepsilon \cdot \sin x\right) \]

      mul-1-neg [=>]99.8%

      \[ -0.5 \cdot \left({\varepsilon}^{2} \cdot \cos x\right) + \color{blue}{\left(-\varepsilon \cdot \sin x\right)} \]

      unsub-neg [=>]99.8%

      \[ \color{blue}{-0.5 \cdot \left({\varepsilon}^{2} \cdot \cos x\right) - \varepsilon \cdot \sin x} \]

      unpow2 [=>]99.8%

      \[ -0.5 \cdot \left(\color{blue}{\left(\varepsilon \cdot \varepsilon\right)} \cdot \cos x\right) - \varepsilon \cdot \sin x \]

      associate-*l* [=>]99.8%

      \[ -0.5 \cdot \color{blue}{\left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right)} - \varepsilon \cdot \sin x \]
  3. Recombined 2 regimes into one program.
  4. Final simplification99.2%

    \[\leadsto \begin{array}{l} \mathbf{if}\;\varepsilon \leq -6.5 \cdot 10^{-5} \lor \neg \left(\varepsilon \leq 3 \cdot 10^{-5}\right):\\ \;\;\;\;\mathsf{fma}\left(\sin \varepsilon, -\sin x, \cos \varepsilon \cdot \cos x\right) - \cos x\\ \mathbf{else}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\ \end{array} \]

Alternatives

Alternative 1
Accuracy99.1%
Cost39177
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -6.5 \cdot 10^{-5} \lor \neg \left(\varepsilon \leq 3 \cdot 10^{-5}\right):\\ \;\;\;\;\mathsf{fma}\left(\sin \varepsilon, -\sin x, \cos \varepsilon \cdot \cos x\right) - \cos x\\ \mathbf{else}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\ \end{array} \]
Alternative 2
Accuracy99.1%
Cost39177
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -3.7 \cdot 10^{-5} \lor \neg \left(\varepsilon \leq 2.5 \cdot 10^{-5}\right):\\ \;\;\;\;\mathsf{fma}\left(\cos x, \cos \varepsilon, \sin \varepsilon \cdot \left(-\sin x\right)\right) - \cos x\\ \mathbf{else}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\ \end{array} \]
Alternative 3
Accuracy99.1%
Cost39112
\[\begin{array}{l} t_0 := \cos \varepsilon \cdot \cos x\\ \mathbf{if}\;\varepsilon \leq -4.5 \cdot 10^{-5}:\\ \;\;\;\;\left(t_0 - \sin \varepsilon \cdot \sin x\right) - \cos x\\ \mathbf{elif}\;\varepsilon \leq 2.3 \cdot 10^{-5}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\ \mathbf{else}:\\ \;\;\;\;t_0 - \mathsf{fma}\left(\sin \varepsilon, \sin x, \cos x\right)\\ \end{array} \]
Alternative 4
Accuracy99.1%
Cost32841
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -2.3 \cdot 10^{-5} \lor \neg \left(\varepsilon \leq 3.5 \cdot 10^{-5}\right):\\ \;\;\;\;\cos \varepsilon \cdot \cos x - \left(\cos x + \sin \varepsilon \cdot \sin x\right)\\ \mathbf{else}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\ \end{array} \]
Alternative 5
Accuracy99.1%
Cost32841
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -3.8 \cdot 10^{-5} \lor \neg \left(\varepsilon \leq 4.6 \cdot 10^{-5}\right):\\ \;\;\;\;\left(\cos \varepsilon \cdot \cos x - \sin \varepsilon \cdot \sin x\right) - \cos x\\ \mathbf{else}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\ \end{array} \]
Alternative 6
Accuracy68.1%
Cost26244
\[\begin{array}{l} \mathbf{if}\;\cos \left(\varepsilon + x\right) - \cos x \leq -1 \cdot 10^{-16}:\\ \;\;\;\;\cos \varepsilon + -1\\ \mathbf{else}:\\ \;\;\;\;\sin \varepsilon \cdot \left(-\sin x\right)\\ \end{array} \]
Alternative 7
Accuracy76.1%
Cost13768
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -0.047:\\ \;\;\;\;-2 \cdot {\sin \left(\varepsilon \cdot 0.5\right)}^{2}\\ \mathbf{elif}\;\varepsilon \leq 0.0078:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \left(\varepsilon \cdot \cos x\right)\right) - \varepsilon \cdot \sin x\\ \mathbf{else}:\\ \;\;\;\;\cos \varepsilon - \cos x\\ \end{array} \]
Alternative 8
Accuracy75.8%
Cost13632
\[-2 \cdot \left(\sin \left(0.5 \cdot \left(\varepsilon - x \cdot -2\right)\right) \cdot \sin \left(\varepsilon \cdot 0.5\right)\right) \]
Alternative 9
Accuracy75.8%
Cost13632
\[-2 \cdot \left(\sin \left(0.5 \cdot \left(x + \left(\varepsilon + x\right)\right)\right) \cdot \sin \left(\varepsilon \cdot 0.5\right)\right) \]
Alternative 10
Accuracy70.8%
Cost13449
\[\begin{array}{l} \mathbf{if}\;x \leq -4 \cdot 10^{-44} \lor \neg \left(x \leq 2.8 \cdot 10^{-26}\right):\\ \;\;\;\;\sin \varepsilon \cdot \left(-\sin x\right)\\ \mathbf{else}:\\ \;\;\;\;-2 \cdot {\sin \left(\varepsilon \cdot 0.5\right)}^{2}\\ \end{array} \]
Alternative 11
Accuracy66.6%
Cost13388
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -0.043:\\ \;\;\;\;\cos \varepsilon + -1\\ \mathbf{elif}\;\varepsilon \leq 1.4 \cdot 10^{-57}:\\ \;\;\;\;\varepsilon \cdot \left(-\sin x\right)\\ \mathbf{elif}\;\varepsilon \leq 5.2 \cdot 10^{-5}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \varepsilon\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \varepsilon - \cos x\\ \end{array} \]
Alternative 12
Accuracy66.6%
Cost13388
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -0.043:\\ \;\;\;\;\cos \varepsilon + -1\\ \mathbf{elif}\;\varepsilon \leq 1.4 \cdot 10^{-57}:\\ \;\;\;\;\mathsf{log1p}\left(\varepsilon \cdot \left(-\sin x\right)\right)\\ \mathbf{elif}\;\varepsilon \leq 5.6 \cdot 10^{-5}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \varepsilon\right)\\ \mathbf{else}:\\ \;\;\;\;\cos \varepsilon - \cos x\\ \end{array} \]
Alternative 13
Accuracy66.3%
Cost6988
\[\begin{array}{l} t_0 := \cos \varepsilon + -1\\ \mathbf{if}\;\varepsilon \leq -0.043:\\ \;\;\;\;t_0\\ \mathbf{elif}\;\varepsilon \leq 1.35 \cdot 10^{-57}:\\ \;\;\;\;\varepsilon \cdot \left(-\sin x\right)\\ \mathbf{elif}\;\varepsilon \leq 0.00016:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \varepsilon\right)\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]
Alternative 14
Accuracy46.5%
Cost6857
\[\begin{array}{l} \mathbf{if}\;\varepsilon \leq -0.043 \lor \neg \left(\varepsilon \leq 0.00016\right):\\ \;\;\;\;\cos \varepsilon + -1\\ \mathbf{else}:\\ \;\;\;\;-0.5 \cdot \left(\varepsilon \cdot \varepsilon\right)\\ \end{array} \]
Alternative 15
Accuracy21.3%
Cost320
\[-0.5 \cdot \left(\varepsilon \cdot \varepsilon\right) \]

Reproduce?

herbie shell --seed 2023178 
(FPCore (x eps)
  :name "2cos (problem 3.3.5)"
  :precision binary64
  (- (cos (+ x eps)) (cos x)))