expfmod (used to be hard to sample)

Percentage Accurate: 7.0% → 44.6%
Time: 29.4s
Alternatives: 4
Speedup: 505.0×

Specification

?
\[\begin{array}{l} \\ \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \end{array} \]
(FPCore (x) :precision binary64 (* (fmod (exp x) (sqrt (cos x))) (exp (- x))))
double code(double x) {
	return fmod(exp(x), sqrt(cos(x))) * exp(-x);
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = mod(exp(x), sqrt(cos(x))) * exp(-x)
end function
def code(x):
	return math.fmod(math.exp(x), math.sqrt(math.cos(x))) * math.exp(-x)
function code(x)
	return Float64(rem(exp(x), sqrt(cos(x))) * exp(Float64(-x)))
end
code[x_] := N[(N[With[{TMP1 = N[Exp[x], $MachinePrecision], TMP2 = N[Sqrt[N[Cos[x], $MachinePrecision]], $MachinePrecision]}, Mod[Abs[TMP1], Abs[TMP2]] * Sign[TMP1]], $MachinePrecision] * N[Exp[(-x)], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x}
\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 4 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: 7.0% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \end{array} \]
(FPCore (x) :precision binary64 (* (fmod (exp x) (sqrt (cos x))) (exp (- x))))
double code(double x) {
	return fmod(exp(x), sqrt(cos(x))) * exp(-x);
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = mod(exp(x), sqrt(cos(x))) * exp(-x)
end function
def code(x):
	return math.fmod(math.exp(x), math.sqrt(math.cos(x))) * math.exp(-x)
function code(x)
	return Float64(rem(exp(x), sqrt(cos(x))) * exp(Float64(-x)))
end
code[x_] := N[(N[With[{TMP1 = N[Exp[x], $MachinePrecision], TMP2 = N[Sqrt[N[Cos[x], $MachinePrecision]], $MachinePrecision]}, Mod[Abs[TMP1], Abs[TMP2]] * Sign[TMP1]], $MachinePrecision] * N[Exp[(-x)], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}

\\
\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x}
\end{array}

Alternative 1: 44.6% accurate, 0.3× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\\ \mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 200:\\ \;\;\;\;{\left(\mathsf{expm1}\left(\mathsf{log1p}\left(e^{{\left(\sqrt[3]{\log t_0 - x}\right)}^{2}}\right)\right)\right)}^{\left(\sqrt[3]{\log \left(\left(1 + t_0\right) + -1\right) - x}\right)}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (let* ((t_0 (fmod (exp x) (sqrt (cos x)))))
   (if (<= x -5e-310)
     1.0
     (if (<= x 200.0)
       (pow
        (expm1 (log1p (exp (pow (cbrt (- (log t_0) x)) 2.0))))
        (cbrt (- (log (+ (+ 1.0 t_0) -1.0)) x)))
       1.0))))
double code(double x) {
	double t_0 = fmod(exp(x), sqrt(cos(x)));
	double tmp;
	if (x <= -5e-310) {
		tmp = 1.0;
	} else if (x <= 200.0) {
		tmp = pow(expm1(log1p(exp(pow(cbrt((log(t_0) - x)), 2.0)))), cbrt((log(((1.0 + t_0) + -1.0)) - x)));
	} else {
		tmp = 1.0;
	}
	return tmp;
}
function code(x)
	t_0 = rem(exp(x), sqrt(cos(x)))
	tmp = 0.0
	if (x <= -5e-310)
		tmp = 1.0;
	elseif (x <= 200.0)
		tmp = expm1(log1p(exp((cbrt(Float64(log(t_0) - x)) ^ 2.0)))) ^ cbrt(Float64(log(Float64(Float64(1.0 + t_0) + -1.0)) - x));
	else
		tmp = 1.0;
	end
	return tmp
end
code[x_] := Block[{t$95$0 = N[With[{TMP1 = N[Exp[x], $MachinePrecision], TMP2 = N[Sqrt[N[Cos[x], $MachinePrecision]], $MachinePrecision]}, Mod[Abs[TMP1], Abs[TMP2]] * Sign[TMP1]], $MachinePrecision]}, If[LessEqual[x, -5e-310], 1.0, If[LessEqual[x, 200.0], N[Power[N[(Exp[N[Log[1 + N[Exp[N[Power[N[Power[N[(N[Log[t$95$0], $MachinePrecision] - x), $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision], N[Power[N[(N[Log[N[(N[(1.0 + t$95$0), $MachinePrecision] + -1.0), $MachinePrecision]], $MachinePrecision] - x), $MachinePrecision], 1/3], $MachinePrecision]], $MachinePrecision], 1.0]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\\
\mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\
\;\;\;\;1\\

\mathbf{elif}\;x \leq 200:\\
\;\;\;\;{\left(\mathsf{expm1}\left(\mathsf{log1p}\left(e^{{\left(\sqrt[3]{\log t_0 - x}\right)}^{2}}\right)\right)\right)}^{\left(\sqrt[3]{\log \left(\left(1 + t_0\right) + -1\right) - x}\right)}\\

\mathbf{else}:\\
\;\;\;\;1\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < -4.999999999999985e-310 or 200 < x

    1. Initial program 8.7%

      \[\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \]
    2. Step-by-step derivation
      1. exp-neg8.7%

        \[\leadsto \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot \color{blue}{\frac{1}{e^{x}}} \]
      2. associate-*r/8.7%

        \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot 1}{e^{x}}} \]
      3. *-rgt-identity8.7%

        \[\leadsto \frac{\color{blue}{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}{e^{x}} \]
    3. Simplified8.7%

      \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}} \]
    4. Step-by-step derivation
      1. add-exp-log8.7%

        \[\leadsto \frac{\color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}}{e^{x}} \]
      2. div-exp8.8%

        \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    5. Applied egg-rr8.8%

      \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    6. Step-by-step derivation
      1. add-cube-cbrt8.8%

        \[\leadsto e^{\color{blue}{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right) \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}} \]
      2. exp-prod8.8%

        \[\leadsto \color{blue}{{\left(e^{\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
      3. pow28.8%

        \[\leadsto {\left(e^{\color{blue}{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)} \]
    7. Applied egg-rr8.8%

      \[\leadsto \color{blue}{{\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
    8. Taylor expanded in x around inf 70.7%

      \[\leadsto \color{blue}{1} \]

    if -4.999999999999985e-310 < x < 200

    1. Initial program 10.2%

      \[\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \]
    2. Step-by-step derivation
      1. exp-neg10.2%

        \[\leadsto \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot \color{blue}{\frac{1}{e^{x}}} \]
      2. associate-*r/10.2%

        \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot 1}{e^{x}}} \]
      3. *-rgt-identity10.2%

        \[\leadsto \frac{\color{blue}{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}{e^{x}} \]
    3. Simplified10.2%

      \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}} \]
    4. Step-by-step derivation
      1. add-exp-log10.2%

        \[\leadsto \frac{\color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}}{e^{x}} \]
      2. div-exp10.2%

        \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    5. Applied egg-rr10.2%

      \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    6. Step-by-step derivation
      1. add-cube-cbrt10.1%

        \[\leadsto e^{\color{blue}{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right) \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}} \]
      2. exp-prod10.1%

        \[\leadsto \color{blue}{{\left(e^{\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
      3. pow210.1%

        \[\leadsto {\left(e^{\color{blue}{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)} \]
    7. Applied egg-rr10.1%

      \[\leadsto \color{blue}{{\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
    8. Step-by-step derivation
      1. expm1-log1p-u10.1%

        \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \color{blue}{\left(\mathsf{expm1}\left(\mathsf{log1p}\left(\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right)\right)\right)} - x}\right)} \]
      2. expm1-udef10.2%

        \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \color{blue}{\left(e^{\mathsf{log1p}\left(\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right)} - 1\right)} - x}\right)} \]
      3. log1p-udef10.2%

        \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(e^{\color{blue}{\log \left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right)}} - 1\right) - x}\right)} \]
      4. add-exp-log10.2%

        \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\color{blue}{\left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right)} - 1\right) - x}\right)} \]
    9. Applied egg-rr10.2%

      \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \color{blue}{\left(\left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right) - 1\right)} - x}\right)} \]
    10. Step-by-step derivation
      1. expm1-log1p-u10.2%

        \[\leadsto {\color{blue}{\left(\mathsf{expm1}\left(\mathsf{log1p}\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)\right)\right)}}^{\left(\sqrt[3]{\log \left(\left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right) - 1\right) - x}\right)} \]
    11. Applied egg-rr10.2%

      \[\leadsto {\color{blue}{\left(\mathsf{expm1}\left(\mathsf{log1p}\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)\right)\right)}}^{\left(\sqrt[3]{\log \left(\left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right) - 1\right) - x}\right)} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification48.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 200:\\ \;\;\;\;{\left(\mathsf{expm1}\left(\mathsf{log1p}\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)\right)\right)}^{\left(\sqrt[3]{\log \left(\left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right) + -1\right) - x}\right)}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 2: 44.6% accurate, 0.3× speedup?

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\\ \mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 200:\\ \;\;\;\;{\left(e^{{\left(\sqrt[3]{\log t_0 - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(1 + t_0\right) + -1\right) - x}\right)}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (let* ((t_0 (fmod (exp x) (sqrt (cos x)))))
   (if (<= x -5e-310)
     1.0
     (if (<= x 200.0)
       (pow
        (exp (pow (cbrt (- (log t_0) x)) 2.0))
        (cbrt (- (log (+ (+ 1.0 t_0) -1.0)) x)))
       1.0))))
double code(double x) {
	double t_0 = fmod(exp(x), sqrt(cos(x)));
	double tmp;
	if (x <= -5e-310) {
		tmp = 1.0;
	} else if (x <= 200.0) {
		tmp = pow(exp(pow(cbrt((log(t_0) - x)), 2.0)), cbrt((log(((1.0 + t_0) + -1.0)) - x)));
	} else {
		tmp = 1.0;
	}
	return tmp;
}
function code(x)
	t_0 = rem(exp(x), sqrt(cos(x)))
	tmp = 0.0
	if (x <= -5e-310)
		tmp = 1.0;
	elseif (x <= 200.0)
		tmp = exp((cbrt(Float64(log(t_0) - x)) ^ 2.0)) ^ cbrt(Float64(log(Float64(Float64(1.0 + t_0) + -1.0)) - x));
	else
		tmp = 1.0;
	end
	return tmp
end
code[x_] := Block[{t$95$0 = N[With[{TMP1 = N[Exp[x], $MachinePrecision], TMP2 = N[Sqrt[N[Cos[x], $MachinePrecision]], $MachinePrecision]}, Mod[Abs[TMP1], Abs[TMP2]] * Sign[TMP1]], $MachinePrecision]}, If[LessEqual[x, -5e-310], 1.0, If[LessEqual[x, 200.0], N[Power[N[Exp[N[Power[N[Power[N[(N[Log[t$95$0], $MachinePrecision] - x), $MachinePrecision], 1/3], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision], N[Power[N[(N[Log[N[(N[(1.0 + t$95$0), $MachinePrecision] + -1.0), $MachinePrecision]], $MachinePrecision] - x), $MachinePrecision], 1/3], $MachinePrecision]], $MachinePrecision], 1.0]]]
\begin{array}{l}

\\
\begin{array}{l}
t_0 := \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\\
\mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\
\;\;\;\;1\\

\mathbf{elif}\;x \leq 200:\\
\;\;\;\;{\left(e^{{\left(\sqrt[3]{\log t_0 - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(1 + t_0\right) + -1\right) - x}\right)}\\

\mathbf{else}:\\
\;\;\;\;1\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < -4.999999999999985e-310 or 200 < x

    1. Initial program 8.7%

      \[\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \]
    2. Step-by-step derivation
      1. exp-neg8.7%

        \[\leadsto \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot \color{blue}{\frac{1}{e^{x}}} \]
      2. associate-*r/8.7%

        \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot 1}{e^{x}}} \]
      3. *-rgt-identity8.7%

        \[\leadsto \frac{\color{blue}{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}{e^{x}} \]
    3. Simplified8.7%

      \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}} \]
    4. Step-by-step derivation
      1. add-exp-log8.7%

        \[\leadsto \frac{\color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}}{e^{x}} \]
      2. div-exp8.8%

        \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    5. Applied egg-rr8.8%

      \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    6. Step-by-step derivation
      1. add-cube-cbrt8.8%

        \[\leadsto e^{\color{blue}{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right) \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}} \]
      2. exp-prod8.8%

        \[\leadsto \color{blue}{{\left(e^{\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
      3. pow28.8%

        \[\leadsto {\left(e^{\color{blue}{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)} \]
    7. Applied egg-rr8.8%

      \[\leadsto \color{blue}{{\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
    8. Taylor expanded in x around inf 70.7%

      \[\leadsto \color{blue}{1} \]

    if -4.999999999999985e-310 < x < 200

    1. Initial program 10.2%

      \[\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \]
    2. Step-by-step derivation
      1. exp-neg10.2%

        \[\leadsto \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot \color{blue}{\frac{1}{e^{x}}} \]
      2. associate-*r/10.2%

        \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot 1}{e^{x}}} \]
      3. *-rgt-identity10.2%

        \[\leadsto \frac{\color{blue}{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}{e^{x}} \]
    3. Simplified10.2%

      \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}} \]
    4. Step-by-step derivation
      1. add-exp-log10.2%

        \[\leadsto \frac{\color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}}{e^{x}} \]
      2. div-exp10.2%

        \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    5. Applied egg-rr10.2%

      \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    6. Step-by-step derivation
      1. add-cube-cbrt10.1%

        \[\leadsto e^{\color{blue}{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right) \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}} \]
      2. exp-prod10.1%

        \[\leadsto \color{blue}{{\left(e^{\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
      3. pow210.1%

        \[\leadsto {\left(e^{\color{blue}{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)} \]
    7. Applied egg-rr10.1%

      \[\leadsto \color{blue}{{\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
    8. Step-by-step derivation
      1. expm1-log1p-u10.1%

        \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \color{blue}{\left(\mathsf{expm1}\left(\mathsf{log1p}\left(\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right)\right)\right)} - x}\right)} \]
      2. expm1-udef10.2%

        \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \color{blue}{\left(e^{\mathsf{log1p}\left(\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right)} - 1\right)} - x}\right)} \]
      3. log1p-udef10.2%

        \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(e^{\color{blue}{\log \left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right)}} - 1\right) - x}\right)} \]
      4. add-exp-log10.2%

        \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\color{blue}{\left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right)} - 1\right) - x}\right)} \]
    9. Applied egg-rr10.2%

      \[\leadsto {\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \color{blue}{\left(\left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right) - 1\right)} - x}\right)} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification48.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 200:\\ \;\;\;\;{\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(1 + \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)\right) + -1\right) - x}\right)}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 3: 44.6% accurate, 1.0× speedup?

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 200:\\ \;\;\;\;\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \end{array} \]
(FPCore (x)
 :precision binary64
 (if (<= x -5e-310)
   1.0
   (if (<= x 200.0) (/ (fmod (exp x) (sqrt (cos x))) (exp x)) 1.0)))
double code(double x) {
	double tmp;
	if (x <= -5e-310) {
		tmp = 1.0;
	} else if (x <= 200.0) {
		tmp = fmod(exp(x), sqrt(cos(x))) / exp(x);
	} else {
		tmp = 1.0;
	}
	return tmp;
}
real(8) function code(x)
    real(8), intent (in) :: x
    real(8) :: tmp
    if (x <= (-5d-310)) then
        tmp = 1.0d0
    else if (x <= 200.0d0) then
        tmp = mod(exp(x), sqrt(cos(x))) / exp(x)
    else
        tmp = 1.0d0
    end if
    code = tmp
end function
def code(x):
	tmp = 0
	if x <= -5e-310:
		tmp = 1.0
	elif x <= 200.0:
		tmp = math.fmod(math.exp(x), math.sqrt(math.cos(x))) / math.exp(x)
	else:
		tmp = 1.0
	return tmp
function code(x)
	tmp = 0.0
	if (x <= -5e-310)
		tmp = 1.0;
	elseif (x <= 200.0)
		tmp = Float64(rem(exp(x), sqrt(cos(x))) / exp(x));
	else
		tmp = 1.0;
	end
	return tmp
end
code[x_] := If[LessEqual[x, -5e-310], 1.0, If[LessEqual[x, 200.0], N[(N[With[{TMP1 = N[Exp[x], $MachinePrecision], TMP2 = N[Sqrt[N[Cos[x], $MachinePrecision]], $MachinePrecision]}, Mod[Abs[TMP1], Abs[TMP2]] * Sign[TMP1]], $MachinePrecision] / N[Exp[x], $MachinePrecision]), $MachinePrecision], 1.0]]
\begin{array}{l}

\\
\begin{array}{l}
\mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\
\;\;\;\;1\\

\mathbf{elif}\;x \leq 200:\\
\;\;\;\;\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}\\

\mathbf{else}:\\
\;\;\;\;1\\


\end{array}
\end{array}
Derivation
  1. Split input into 2 regimes
  2. if x < -4.999999999999985e-310 or 200 < x

    1. Initial program 8.7%

      \[\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \]
    2. Step-by-step derivation
      1. exp-neg8.7%

        \[\leadsto \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot \color{blue}{\frac{1}{e^{x}}} \]
      2. associate-*r/8.7%

        \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot 1}{e^{x}}} \]
      3. *-rgt-identity8.7%

        \[\leadsto \frac{\color{blue}{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}{e^{x}} \]
    3. Simplified8.7%

      \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}} \]
    4. Step-by-step derivation
      1. add-exp-log8.7%

        \[\leadsto \frac{\color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}}{e^{x}} \]
      2. div-exp8.8%

        \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    5. Applied egg-rr8.8%

      \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
    6. Step-by-step derivation
      1. add-cube-cbrt8.8%

        \[\leadsto e^{\color{blue}{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right) \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}} \]
      2. exp-prod8.8%

        \[\leadsto \color{blue}{{\left(e^{\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
      3. pow28.8%

        \[\leadsto {\left(e^{\color{blue}{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)} \]
    7. Applied egg-rr8.8%

      \[\leadsto \color{blue}{{\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
    8. Taylor expanded in x around inf 70.7%

      \[\leadsto \color{blue}{1} \]

    if -4.999999999999985e-310 < x < 200

    1. Initial program 10.2%

      \[\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \]
    2. Step-by-step derivation
      1. exp-neg10.2%

        \[\leadsto \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot \color{blue}{\frac{1}{e^{x}}} \]
      2. associate-*r/10.2%

        \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot 1}{e^{x}}} \]
      3. *-rgt-identity10.2%

        \[\leadsto \frac{\color{blue}{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}{e^{x}} \]
    3. Simplified10.2%

      \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification48.5%

    \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -5 \cdot 10^{-310}:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 200:\\ \;\;\;\;\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 4: 43.4% accurate, 505.0× speedup?

\[\begin{array}{l} \\ 1 \end{array} \]
(FPCore (x) :precision binary64 1.0)
double code(double x) {
	return 1.0;
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = 1.0d0
end function
public static double code(double x) {
	return 1.0;
}
def code(x):
	return 1.0
function code(x)
	return 1.0
end
function tmp = code(x)
	tmp = 1.0;
end
code[x_] := 1.0
\begin{array}{l}

\\
1
\end{array}
Derivation
  1. Initial program 9.2%

    \[\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot e^{-x} \]
  2. Step-by-step derivation
    1. exp-neg9.3%

      \[\leadsto \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot \color{blue}{\frac{1}{e^{x}}} \]
    2. associate-*r/9.3%

      \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) \cdot 1}{e^{x}}} \]
    3. *-rgt-identity9.3%

      \[\leadsto \frac{\color{blue}{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}{e^{x}} \]
  3. Simplified9.3%

    \[\leadsto \color{blue}{\frac{\left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}{e^{x}}} \]
  4. Step-by-step derivation
    1. add-exp-log9.3%

      \[\leadsto \frac{\color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right)}}}{e^{x}} \]
    2. div-exp9.3%

      \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
  5. Applied egg-rr9.3%

    \[\leadsto \color{blue}{e^{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}} \]
  6. Step-by-step derivation
    1. add-cube-cbrt9.3%

      \[\leadsto e^{\color{blue}{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right) \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}} \]
    2. exp-prod9.3%

      \[\leadsto \color{blue}{{\left(e^{\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x} \cdot \sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
    3. pow29.3%

      \[\leadsto {\left(e^{\color{blue}{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)} \]
  7. Applied egg-rr9.3%

    \[\leadsto \color{blue}{{\left(e^{{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}^{2}}\right)}^{\left(\sqrt[3]{\log \left(\left(e^{x}\right) \bmod \left(\sqrt{\cos x}\right)\right) - x}\right)}} \]
  8. Taylor expanded in x around inf 46.7%

    \[\leadsto \color{blue}{1} \]
  9. Final simplification46.7%

    \[\leadsto 1 \]

Reproduce

?
herbie shell --seed 2023279 
(FPCore (x)
  :name "expfmod (used to be hard to sample)"
  :precision binary64
  (* (fmod (exp x) (sqrt (cos x))) (exp (- x))))