Diagrams.Solve.Polynomial:cubForm from diagrams-solve-0.1, D

Percentage Accurate: 98.1% → 98.6%
Time: 32.3s
Alternatives: 2
Speedup: 1.2×

Specification

?
\[\begin{array}{l} \\ \frac{1}{3} \cdot \cos^{-1} \left(\frac{3 \cdot \frac{x}{y \cdot 27}}{z \cdot 2} \cdot \sqrt{t}\right) \end{array} \]
(FPCore (x y z t)
 :precision binary64
 (* (/ 1.0 3.0) (acos (* (/ (* 3.0 (/ x (* y 27.0))) (* z 2.0)) (sqrt t)))))
double code(double x, double y, double z, double t) {
	return (1.0 / 3.0) * acos((((3.0 * (x / (y * 27.0))) / (z * 2.0)) * sqrt(t)));
}
real(8) function code(x, y, z, t)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    code = (1.0d0 / 3.0d0) * acos((((3.0d0 * (x / (y * 27.0d0))) / (z * 2.0d0)) * sqrt(t)))
end function
public static double code(double x, double y, double z, double t) {
	return (1.0 / 3.0) * Math.acos((((3.0 * (x / (y * 27.0))) / (z * 2.0)) * Math.sqrt(t)));
}
def code(x, y, z, t):
	return (1.0 / 3.0) * math.acos((((3.0 * (x / (y * 27.0))) / (z * 2.0)) * math.sqrt(t)))
function code(x, y, z, t)
	return Float64(Float64(1.0 / 3.0) * acos(Float64(Float64(Float64(3.0 * Float64(x / Float64(y * 27.0))) / Float64(z * 2.0)) * sqrt(t))))
end
function tmp = code(x, y, z, t)
	tmp = (1.0 / 3.0) * acos((((3.0 * (x / (y * 27.0))) / (z * 2.0)) * sqrt(t)));
end
code[x_, y_, z_, t_] := N[(N[(1.0 / 3.0), $MachinePrecision] * N[ArcCos[N[(N[(N[(3.0 * N[(x / N[(y * 27.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * 2.0), $MachinePrecision]), $MachinePrecision] * N[Sqrt[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{1}{3} \cdot \cos^{-1} \left(\frac{3 \cdot \frac{x}{y \cdot 27}}{z \cdot 2} \cdot \sqrt{t}\right)
\end{array}

Sampling outcomes in binary64 precision:

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.

Accuracy vs Speed?

Herbie found 2 alternatives:

AlternativeAccuracySpeedup
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.

Initial Program: 98.1% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{1}{3} \cdot \cos^{-1} \left(\frac{3 \cdot \frac{x}{y \cdot 27}}{z \cdot 2} \cdot \sqrt{t}\right) \end{array} \]
(FPCore (x y z t)
 :precision binary64
 (* (/ 1.0 3.0) (acos (* (/ (* 3.0 (/ x (* y 27.0))) (* z 2.0)) (sqrt t)))))
double code(double x, double y, double z, double t) {
	return (1.0 / 3.0) * acos((((3.0 * (x / (y * 27.0))) / (z * 2.0)) * sqrt(t)));
}
real(8) function code(x, y, z, t)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    code = (1.0d0 / 3.0d0) * acos((((3.0d0 * (x / (y * 27.0d0))) / (z * 2.0d0)) * sqrt(t)))
end function
public static double code(double x, double y, double z, double t) {
	return (1.0 / 3.0) * Math.acos((((3.0 * (x / (y * 27.0))) / (z * 2.0)) * Math.sqrt(t)));
}
def code(x, y, z, t):
	return (1.0 / 3.0) * math.acos((((3.0 * (x / (y * 27.0))) / (z * 2.0)) * math.sqrt(t)))
function code(x, y, z, t)
	return Float64(Float64(1.0 / 3.0) * acos(Float64(Float64(Float64(3.0 * Float64(x / Float64(y * 27.0))) / Float64(z * 2.0)) * sqrt(t))))
end
function tmp = code(x, y, z, t)
	tmp = (1.0 / 3.0) * acos((((3.0 * (x / (y * 27.0))) / (z * 2.0)) * sqrt(t)));
end
code[x_, y_, z_, t_] := N[(N[(1.0 / 3.0), $MachinePrecision] * N[ArcCos[N[(N[(N[(3.0 * N[(x / N[(y * 27.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * 2.0), $MachinePrecision]), $MachinePrecision] * N[Sqrt[t], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\frac{1}{3} \cdot \cos^{-1} \left(\frac{3 \cdot \frac{x}{y \cdot 27}}{z \cdot 2} \cdot \sqrt{t}\right)
\end{array}

Alternative 1: 98.6% accurate, 0.7× speedup?

\[\begin{array}{l} \\ {\left(\frac{3}{\cos^{-1} \left(\frac{\mathsf{fma}\left(\sqrt{t}, x \cdot 0.05555555555555555, 0\right)}{y \cdot z}\right)}\right)}^{-1} \end{array} \]
(FPCore (x y z t)
 :precision binary64
 (pow
  (/ 3.0 (acos (/ (fma (sqrt t) (* x 0.05555555555555555) 0.0) (* y z))))
  -1.0))
double code(double x, double y, double z, double t) {
	return pow((3.0 / acos((fma(sqrt(t), (x * 0.05555555555555555), 0.0) / (y * z)))), -1.0);
}
function code(x, y, z, t)
	return Float64(3.0 / acos(Float64(fma(sqrt(t), Float64(x * 0.05555555555555555), 0.0) / Float64(y * z)))) ^ -1.0
end
code[x_, y_, z_, t_] := N[Power[N[(3.0 / N[ArcCos[N[(N[(N[Sqrt[t], $MachinePrecision] * N[(x * 0.05555555555555555), $MachinePrecision] + 0.0), $MachinePrecision] / N[(y * z), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], -1.0], $MachinePrecision]
\begin{array}{l}

\\
{\left(\frac{3}{\cos^{-1} \left(\frac{\mathsf{fma}\left(\sqrt{t}, x \cdot 0.05555555555555555, 0\right)}{y \cdot z}\right)}\right)}^{-1}
\end{array}
Derivation
  1. Initial program 98.1%

    \[\frac{1}{3} \cdot \cos^{-1} \left(\frac{3 \cdot \frac{x}{y \cdot 27}}{z \cdot 2} \cdot \sqrt{t}\right) \]
  2. Add Preprocessing
  3. Taylor expanded in x around 0

    \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\color{blue}{\left(\frac{1}{18} \cdot \frac{x}{y \cdot z}\right)} \cdot \sqrt{t}\right) \]
  4. Step-by-step derivation
    1. *-lowering-*.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\color{blue}{\left(\frac{1}{18} \cdot \frac{x}{y \cdot z}\right)} \cdot \sqrt{t}\right) \]
    2. /-lowering-/.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\left(\frac{1}{18} \cdot \color{blue}{\frac{x}{y \cdot z}}\right) \cdot \sqrt{t}\right) \]
    3. *-lowering-*.f6498.5

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\left(0.05555555555555555 \cdot \frac{x}{\color{blue}{y \cdot z}}\right) \cdot \sqrt{t}\right) \]
  5. Simplified98.5%

    \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\color{blue}{\left(0.05555555555555555 \cdot \frac{x}{y \cdot z}\right)} \cdot \sqrt{t}\right) \]
  6. Applied egg-rr97.3%

    \[\leadsto \color{blue}{\frac{0.3333333333333333}{\mathsf{fma}\left(\pi, 0.5, \sin^{-1} \left(\frac{0.05555555555555555 \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)\right)} \cdot \left(\left(\pi \cdot \pi\right) \cdot 0.25 - {\sin^{-1} \left(\frac{0.05555555555555555 \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right)} \]
  7. Step-by-step derivation
    1. clear-numN/A

      \[\leadsto \color{blue}{\frac{1}{\frac{\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}{\frac{1}{3}}}} \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \frac{1}{4} - {\sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right) \]
    2. /-lowering-/.f64N/A

      \[\leadsto \color{blue}{\frac{1}{\frac{\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}{\frac{1}{3}}}} \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \frac{1}{4} - {\sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right) \]
    3. div-invN/A

      \[\leadsto \frac{1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)\right) \cdot \frac{1}{\frac{1}{3}}}} \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \frac{1}{4} - {\sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right) \]
    4. metadata-evalN/A

      \[\leadsto \frac{1}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)\right) \cdot \color{blue}{3}} \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \frac{1}{4} - {\sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right) \]
    5. *-lowering-*.f64N/A

      \[\leadsto \frac{1}{\color{blue}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)\right) \cdot 3}} \cdot \left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \frac{1}{4} - {\sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right) \]
  8. Applied egg-rr98.8%

    \[\leadsto \color{blue}{\frac{1}{\mathsf{fma}\left(\pi, 0.5, \sin^{-1} \left(\frac{\mathsf{fma}\left(\sqrt{t}, 0.05555555555555555 \cdot x, 0\right)}{y \cdot z}\right)\right) \cdot 3}} \cdot \left(\left(\pi \cdot \pi\right) \cdot 0.25 - {\sin^{-1} \left(\frac{0.05555555555555555 \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right) \]
  9. Step-by-step derivation
    1. *-commutativeN/A

      \[\leadsto \color{blue}{\left(\left(\mathsf{PI}\left(\right) \cdot \mathsf{PI}\left(\right)\right) \cdot \frac{1}{4} - {\sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right) \cdot \frac{1}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right) + 0}{y \cdot z}\right)\right) \cdot 3}} \]
    2. associate-*r*N/A

      \[\leadsto \left(\color{blue}{\mathsf{PI}\left(\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \frac{1}{4}\right)} - {\sin^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)}^{2}\right) \cdot \frac{1}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right) + 0}{y \cdot z}\right)\right) \cdot 3} \]
    3. associate-*r*N/A

      \[\leadsto \left(\mathsf{PI}\left(\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \frac{1}{4}\right) - {\sin^{-1} \left(\frac{\color{blue}{\left(\frac{1}{18} \cdot x\right) \cdot \sqrt{t}}}{y \cdot z}\right)}^{2}\right) \cdot \frac{1}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right) + 0}{y \cdot z}\right)\right) \cdot 3} \]
    4. *-commutativeN/A

      \[\leadsto \left(\mathsf{PI}\left(\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \frac{1}{4}\right) - {\sin^{-1} \left(\frac{\color{blue}{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right)}}{y \cdot z}\right)}^{2}\right) \cdot \frac{1}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right) + 0}{y \cdot z}\right)\right) \cdot 3} \]
    5. +-rgt-identityN/A

      \[\leadsto \left(\mathsf{PI}\left(\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \frac{1}{4}\right) - {\sin^{-1} \left(\frac{\color{blue}{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right) + 0}}{y \cdot z}\right)}^{2}\right) \cdot \frac{1}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right) + 0}{y \cdot z}\right)\right) \cdot 3} \]
    6. div-invN/A

      \[\leadsto \color{blue}{\frac{\mathsf{PI}\left(\right) \cdot \left(\mathsf{PI}\left(\right) \cdot \frac{1}{4}\right) - {\sin^{-1} \left(\frac{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right) + 0}{y \cdot z}\right)}^{2}}{\left(\mathsf{PI}\left(\right) \cdot \frac{1}{2} + \sin^{-1} \left(\frac{\sqrt{t} \cdot \left(\frac{1}{18} \cdot x\right) + 0}{y \cdot z}\right)\right) \cdot 3}} \]
  10. Applied egg-rr98.8%

    \[\leadsto \color{blue}{{\left(\frac{3}{\cos^{-1} \left(\frac{\mathsf{fma}\left(\sqrt{t}, x \cdot 0.05555555555555555, 0\right)}{y \cdot z}\right)}\right)}^{-1}} \]
  11. Add Preprocessing

Alternative 2: 98.1% accurate, 1.2× speedup?

\[\begin{array}{l} \\ 0.3333333333333333 \cdot \cos^{-1} \left(\sqrt{t} \cdot \frac{x \cdot 0.05555555555555555}{y \cdot z}\right) \end{array} \]
(FPCore (x y z t)
 :precision binary64
 (*
  0.3333333333333333
  (acos (* (sqrt t) (/ (* x 0.05555555555555555) (* y z))))))
double code(double x, double y, double z, double t) {
	return 0.3333333333333333 * acos((sqrt(t) * ((x * 0.05555555555555555) / (y * z))));
}
real(8) function code(x, y, z, t)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    code = 0.3333333333333333d0 * acos((sqrt(t) * ((x * 0.05555555555555555d0) / (y * z))))
end function
public static double code(double x, double y, double z, double t) {
	return 0.3333333333333333 * Math.acos((Math.sqrt(t) * ((x * 0.05555555555555555) / (y * z))));
}
def code(x, y, z, t):
	return 0.3333333333333333 * math.acos((math.sqrt(t) * ((x * 0.05555555555555555) / (y * z))))
function code(x, y, z, t)
	return Float64(0.3333333333333333 * acos(Float64(sqrt(t) * Float64(Float64(x * 0.05555555555555555) / Float64(y * z)))))
end
function tmp = code(x, y, z, t)
	tmp = 0.3333333333333333 * acos((sqrt(t) * ((x * 0.05555555555555555) / (y * z))));
end
code[x_, y_, z_, t_] := N[(0.3333333333333333 * N[ArcCos[N[(N[Sqrt[t], $MachinePrecision] * N[(N[(x * 0.05555555555555555), $MachinePrecision] / N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
0.3333333333333333 \cdot \cos^{-1} \left(\sqrt{t} \cdot \frac{x \cdot 0.05555555555555555}{y \cdot z}\right)
\end{array}
Derivation
  1. Initial program 98.1%

    \[\frac{1}{3} \cdot \cos^{-1} \left(\frac{3 \cdot \frac{x}{y \cdot 27}}{z \cdot 2} \cdot \sqrt{t}\right) \]
  2. Add Preprocessing
  3. Taylor expanded in x around 0

    \[\leadsto \color{blue}{\frac{1}{3} \cdot \cos^{-1} \left(\frac{1}{18} \cdot \left(\sqrt{t} \cdot \frac{x}{y \cdot z}\right)\right)} \]
  4. Step-by-step derivation
    1. *-lowering-*.f64N/A

      \[\leadsto \color{blue}{\frac{1}{3} \cdot \cos^{-1} \left(\frac{1}{18} \cdot \left(\sqrt{t} \cdot \frac{x}{y \cdot z}\right)\right)} \]
    2. acos-lowering-acos.f64N/A

      \[\leadsto \frac{1}{3} \cdot \color{blue}{\cos^{-1} \left(\frac{1}{18} \cdot \left(\sqrt{t} \cdot \frac{x}{y \cdot z}\right)\right)} \]
    3. associate-*r*N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \color{blue}{\left(\left(\frac{1}{18} \cdot \sqrt{t}\right) \cdot \frac{x}{y \cdot z}\right)} \]
    4. associate-*r/N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \color{blue}{\left(\frac{\left(\frac{1}{18} \cdot \sqrt{t}\right) \cdot x}{y \cdot z}\right)} \]
    5. /-lowering-/.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \color{blue}{\left(\frac{\left(\frac{1}{18} \cdot \sqrt{t}\right) \cdot x}{y \cdot z}\right)} \]
    6. associate-*r*N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\frac{\color{blue}{\frac{1}{18} \cdot \left(\sqrt{t} \cdot x\right)}}{y \cdot z}\right) \]
    7. *-lowering-*.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\frac{\color{blue}{\frac{1}{18} \cdot \left(\sqrt{t} \cdot x\right)}}{y \cdot z}\right) \]
    8. *-commutativeN/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\frac{\frac{1}{18} \cdot \color{blue}{\left(x \cdot \sqrt{t}\right)}}{y \cdot z}\right) \]
    9. *-lowering-*.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\frac{\frac{1}{18} \cdot \color{blue}{\left(x \cdot \sqrt{t}\right)}}{y \cdot z}\right) \]
    10. sqrt-lowering-sqrt.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\frac{\frac{1}{18} \cdot \left(x \cdot \color{blue}{\sqrt{t}}\right)}{y \cdot z}\right) \]
    11. *-lowering-*.f6497.3

      \[\leadsto 0.3333333333333333 \cdot \cos^{-1} \left(\frac{0.05555555555555555 \cdot \left(x \cdot \sqrt{t}\right)}{\color{blue}{y \cdot z}}\right) \]
  5. Simplified97.3%

    \[\leadsto \color{blue}{0.3333333333333333 \cdot \cos^{-1} \left(\frac{0.05555555555555555 \cdot \left(x \cdot \sqrt{t}\right)}{y \cdot z}\right)} \]
  6. Step-by-step derivation
    1. associate-*r*N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\frac{\color{blue}{\left(\frac{1}{18} \cdot x\right) \cdot \sqrt{t}}}{y \cdot z}\right) \]
    2. associate-*l/N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \color{blue}{\left(\frac{\frac{1}{18} \cdot x}{y \cdot z} \cdot \sqrt{t}\right)} \]
    3. associate-*r/N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\color{blue}{\left(\frac{1}{18} \cdot \frac{x}{y \cdot z}\right)} \cdot \sqrt{t}\right) \]
    4. *-lowering-*.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \color{blue}{\left(\left(\frac{1}{18} \cdot \frac{x}{y \cdot z}\right) \cdot \sqrt{t}\right)} \]
    5. associate-*r/N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\color{blue}{\frac{\frac{1}{18} \cdot x}{y \cdot z}} \cdot \sqrt{t}\right) \]
    6. /-lowering-/.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\color{blue}{\frac{\frac{1}{18} \cdot x}{y \cdot z}} \cdot \sqrt{t}\right) \]
    7. *-lowering-*.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\frac{\color{blue}{\frac{1}{18} \cdot x}}{y \cdot z} \cdot \sqrt{t}\right) \]
    8. *-lowering-*.f64N/A

      \[\leadsto \frac{1}{3} \cdot \cos^{-1} \left(\frac{\frac{1}{18} \cdot x}{\color{blue}{y \cdot z}} \cdot \sqrt{t}\right) \]
    9. sqrt-lowering-sqrt.f6498.5

      \[\leadsto 0.3333333333333333 \cdot \cos^{-1} \left(\frac{0.05555555555555555 \cdot x}{y \cdot z} \cdot \color{blue}{\sqrt{t}}\right) \]
  7. Applied egg-rr98.5%

    \[\leadsto 0.3333333333333333 \cdot \cos^{-1} \color{blue}{\left(\frac{0.05555555555555555 \cdot x}{y \cdot z} \cdot \sqrt{t}\right)} \]
  8. Final simplification98.5%

    \[\leadsto 0.3333333333333333 \cdot \cos^{-1} \left(\sqrt{t} \cdot \frac{x \cdot 0.05555555555555555}{y \cdot z}\right) \]
  9. Add Preprocessing

Developer Target 1: 98.1% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \frac{\cos^{-1} \left(\frac{\frac{x}{27}}{y \cdot z} \cdot \frac{\sqrt{t}}{\frac{2}{3}}\right)}{3} \end{array} \]
(FPCore (x y z t)
 :precision binary64
 (/ (acos (* (/ (/ x 27.0) (* y z)) (/ (sqrt t) (/ 2.0 3.0)))) 3.0))
double code(double x, double y, double z, double t) {
	return acos((((x / 27.0) / (y * z)) * (sqrt(t) / (2.0 / 3.0)))) / 3.0;
}
real(8) function code(x, y, z, t)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    code = acos((((x / 27.0d0) / (y * z)) * (sqrt(t) / (2.0d0 / 3.0d0)))) / 3.0d0
end function
public static double code(double x, double y, double z, double t) {
	return Math.acos((((x / 27.0) / (y * z)) * (Math.sqrt(t) / (2.0 / 3.0)))) / 3.0;
}
def code(x, y, z, t):
	return math.acos((((x / 27.0) / (y * z)) * (math.sqrt(t) / (2.0 / 3.0)))) / 3.0
function code(x, y, z, t)
	return Float64(acos(Float64(Float64(Float64(x / 27.0) / Float64(y * z)) * Float64(sqrt(t) / Float64(2.0 / 3.0)))) / 3.0)
end
function tmp = code(x, y, z, t)
	tmp = acos((((x / 27.0) / (y * z)) * (sqrt(t) / (2.0 / 3.0)))) / 3.0;
end
code[x_, y_, z_, t_] := N[(N[ArcCos[N[(N[(N[(x / 27.0), $MachinePrecision] / N[(y * z), $MachinePrecision]), $MachinePrecision] * N[(N[Sqrt[t], $MachinePrecision] / N[(2.0 / 3.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 3.0), $MachinePrecision]
\begin{array}{l}

\\
\frac{\cos^{-1} \left(\frac{\frac{x}{27}}{y \cdot z} \cdot \frac{\sqrt{t}}{\frac{2}{3}}\right)}{3}
\end{array}

Reproduce

?
herbie shell --seed 2024195 
(FPCore (x y z t)
  :name "Diagrams.Solve.Polynomial:cubForm  from diagrams-solve-0.1, D"
  :precision binary64

  :alt
  (! :herbie-platform default (/ (acos (* (/ (/ x 27) (* y z)) (/ (sqrt t) (/ 2 3)))) 3))

  (* (/ 1.0 3.0) (acos (* (/ (* 3.0 (/ x (* y 27.0))) (* z 2.0)) (sqrt t)))))