Octave 3.8, jcobi/4, as called

Average Accuracy: 27.2% → 99.3%

Time: 5.4s

Precision: binary64

Cost: 580

\[i > 0\]

Math

\[\frac{\frac{\left(i \cdot i\right) \cdot \left(i \cdot i\right)}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]

↓

\[\begin{array}{l} \mathbf{if}\;i \leq 0.5:\\ \;\;\;\;i \cdot \left(i \cdot -0.25\right)\\ \mathbf{else}:\\ \;\;\;\;0.0625 + \frac{\frac{0.015625}{i}}{i}\\ \end{array} \]

FPCore

(FPCore (i)
 :precision binary64
 (/
  (/ (* (* i i) (* i i)) (* (* 2.0 i) (* 2.0 i)))
  (- (* (* 2.0 i) (* 2.0 i)) 1.0)))

↓

(FPCore (i)
 :precision binary64
 (if (<= i 0.5) (* i (* i -0.25)) (+ 0.0625 (/ (/ 0.015625 i) i))))

C

double code(double i) {
	return (((i * i) * (i * i)) / ((2.0 * i) * (2.0 * i))) / (((2.0 * i) * (2.0 * i)) - 1.0);
}

↓

double code(double i) {
	double tmp;
	if (i <= 0.5) {
		tmp = i * (i * -0.25);
	} else {
		tmp = 0.0625 + ((0.015625 / i) / i);
	}
	return tmp;
}

Fortran

real(8) function code(i)
    real(8), intent (in) :: i
    code = (((i * i) * (i * i)) / ((2.0d0 * i) * (2.0d0 * i))) / (((2.0d0 * i) * (2.0d0 * i)) - 1.0d0)
end function

↓

real(8) function code(i)
    real(8), intent (in) :: i
    real(8) :: tmp
    if (i <= 0.5d0) then
        tmp = i * (i * (-0.25d0))
    else
        tmp = 0.0625d0 + ((0.015625d0 / i) / i)
    end if
    code = tmp
end function

Java

public static double code(double i) {
	return (((i * i) * (i * i)) / ((2.0 * i) * (2.0 * i))) / (((2.0 * i) * (2.0 * i)) - 1.0);
}

↓

public static double code(double i) {
	double tmp;
	if (i <= 0.5) {
		tmp = i * (i * -0.25);
	} else {
		tmp = 0.0625 + ((0.015625 / i) / i);
	}
	return tmp;
}

Python

def code(i):
	return (((i * i) * (i * i)) / ((2.0 * i) * (2.0 * i))) / (((2.0 * i) * (2.0 * i)) - 1.0)

↓

def code(i):
	tmp = 0
	if i <= 0.5:
		tmp = i * (i * -0.25)
	else:
		tmp = 0.0625 + ((0.015625 / i) / i)
	return tmp

Julia

function code(i)
	return Float64(Float64(Float64(Float64(i * i) * Float64(i * i)) / Float64(Float64(2.0 * i) * Float64(2.0 * i))) / Float64(Float64(Float64(2.0 * i) * Float64(2.0 * i)) - 1.0))
end

↓

function code(i)
	tmp = 0.0
	if (i <= 0.5)
		tmp = Float64(i * Float64(i * -0.25));
	else
		tmp = Float64(0.0625 + Float64(Float64(0.015625 / i) / i));
	end
	return tmp
end

MATLAB

function tmp = code(i)
	tmp = (((i * i) * (i * i)) / ((2.0 * i) * (2.0 * i))) / (((2.0 * i) * (2.0 * i)) - 1.0);
end

↓

function tmp_2 = code(i)
	tmp = 0.0;
	if (i <= 0.5)
		tmp = i * (i * -0.25);
	else
		tmp = 0.0625 + ((0.015625 / i) / i);
	end
	tmp_2 = tmp;
end

Wolfram

code[i_] := N[(N[(N[(N[(i * i), $MachinePrecision] * N[(i * i), $MachinePrecision]), $MachinePrecision] / N[(N[(2.0 * i), $MachinePrecision] * N[(2.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(N[(2.0 * i), $MachinePrecision] * N[(2.0 * i), $MachinePrecision]), $MachinePrecision] - 1.0), $MachinePrecision]), $MachinePrecision]

↓

code[i_] := If[LessEqual[i, 0.5], N[(i * N[(i * -0.25), $MachinePrecision]), $MachinePrecision], N[(0.0625 + N[(N[(0.015625 / i), $MachinePrecision] / i), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if i < 0.5

   1. Initial program 28.4%

      \[\frac{\frac{\left(i \cdot i\right) \cdot \left(i \cdot i\right)}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]

   2. Simplified 100.0%

      \[\leadsto \color{blue}{0.25 \cdot \frac{i \cdot i}{\mathsf{fma}\left(i, i \cdot 4, -1\right)}} \]
      Proof

      [Start] 28.4	\[ \frac{\frac{\left(i \cdot i\right) \cdot \left(i \cdot i\right)}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      associate-/r* [=>] 74.8	\[ \frac{\color{blue}{\frac{\frac{\left(i \cdot i\right) \cdot \left(i \cdot i\right)}{2 \cdot i}}{2 \cdot i}}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      associate-/l/ [=>] 74.8	\[ \color{blue}{\frac{\frac{\left(i \cdot i\right) \cdot \left(i \cdot i\right)}{2 \cdot i}}{\left(\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1\right) \cdot \left(2 \cdot i\right)}} \]
      associate-*r* [=>] 74.9	\[ \frac{\frac{\color{blue}{\left(\left(i \cdot i\right) \cdot i\right) \cdot i}}{2 \cdot i}}{\left(\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1\right) \cdot \left(2 \cdot i\right)} \]
      *-commutative [=>] 74.9	\[ \frac{\frac{\left(\left(i \cdot i\right) \cdot i\right) \cdot i}{\color{blue}{i \cdot 2}}}{\left(\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1\right) \cdot \left(2 \cdot i\right)} \]
      times-frac [=>] 83.7	\[ \frac{\color{blue}{\frac{\left(i \cdot i\right) \cdot i}{i} \cdot \frac{i}{2}}}{\left(\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1\right) \cdot \left(2 \cdot i\right)} \]
      times-frac [=>] 83.8	\[ \color{blue}{\frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \cdot \frac{\frac{i}{2}}{2 \cdot i}} \]
      associate-/r* [<=] 83.8	\[ \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \cdot \color{blue}{\frac{i}{2 \cdot \left(2 \cdot i\right)}} \]
      *-commutative [<=] 83.8	\[ \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \cdot \frac{i}{\color{blue}{\left(2 \cdot i\right) \cdot 2}} \]
      *-commutative [=>] 83.8	\[ \color{blue}{\frac{i}{\left(2 \cdot i\right) \cdot 2} \cdot \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1}} \]
      associate-/r* [=>] 83.8	\[ \color{blue}{\frac{\frac{i}{2 \cdot i}}{2}} \cdot \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      *-commutative [=>] 83.8	\[ \frac{\frac{i}{\color{blue}{i \cdot 2}}}{2} \cdot \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      associate-/r* [=>] 83.8	\[ \frac{\color{blue}{\frac{\frac{i}{i}}{2}}}{2} \cdot \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      *-inverses [=>] 83.8	\[ \frac{\frac{\color{blue}{1}}{2}}{2} \cdot \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      metadata-eval [=>] 83.8	\[ \frac{\color{blue}{0.5}}{2} \cdot \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      metadata-eval [=>] 83.8	\[ \color{blue}{0.25} \cdot \frac{\frac{\left(i \cdot i\right) \cdot i}{i}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]

   3. Taylor expanded in i around 0 99.0%

      \[\leadsto \color{blue}{-0.25 \cdot {i}^{2}} \]

   4. Simplified 99.0%

      \[\leadsto \color{blue}{i \cdot \left(i \cdot -0.25\right)} \]
      Proof

      [Start] 99.0	\[ -0.25 \cdot {i}^{2} \]
      *-commutative [=>] 99.0	\[ \color{blue}{{i}^{2} \cdot -0.25} \]
      unpow2 [=>] 99.0	\[ \color{blue}{\left(i \cdot i\right)} \cdot -0.25 \]
      associate-*l* [=>] 99.0	\[ \color{blue}{i \cdot \left(i \cdot -0.25\right)} \]

   if 0.5 < i

   1. Initial program 26.0%

      \[\frac{\frac{\left(i \cdot i\right) \cdot \left(i \cdot i\right)}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]

   2. Simplified 50.3%

      \[\leadsto \color{blue}{\frac{\frac{i \cdot i}{\frac{4 \cdot \left(i \cdot i\right)}{i \cdot i}}}{4 \cdot \left(i \cdot i\right) + -1}} \]
      Proof

      [Start] 26.0	\[ \frac{\frac{\left(i \cdot i\right) \cdot \left(i \cdot i\right)}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right)}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      associate-/l* [=>] 50.3	\[ \frac{\color{blue}{\frac{i \cdot i}{\frac{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right)}{i \cdot i}}}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      swap-sqr [=>] 50.3	\[ \frac{\frac{i \cdot i}{\frac{\color{blue}{\left(2 \cdot 2\right) \cdot \left(i \cdot i\right)}}{i \cdot i}}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      metadata-eval [=>] 50.3	\[ \frac{\frac{i \cdot i}{\frac{\color{blue}{4} \cdot \left(i \cdot i\right)}{i \cdot i}}}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) - 1} \]
      sub-neg [=>] 50.3	\[ \frac{\frac{i \cdot i}{\frac{4 \cdot \left(i \cdot i\right)}{i \cdot i}}}{\color{blue}{\left(2 \cdot i\right) \cdot \left(2 \cdot i\right) + \left(-1\right)}} \]
      swap-sqr [=>] 50.3	\[ \frac{\frac{i \cdot i}{\frac{4 \cdot \left(i \cdot i\right)}{i \cdot i}}}{\color{blue}{\left(2 \cdot 2\right) \cdot \left(i \cdot i\right)} + \left(-1\right)} \]
      metadata-eval [=>] 50.3	\[ \frac{\frac{i \cdot i}{\frac{4 \cdot \left(i \cdot i\right)}{i \cdot i}}}{\color{blue}{4} \cdot \left(i \cdot i\right) + \left(-1\right)} \]
      metadata-eval [=>] 50.3	\[ \frac{\frac{i \cdot i}{\frac{4 \cdot \left(i \cdot i\right)}{i \cdot i}}}{4 \cdot \left(i \cdot i\right) + \color{blue}{-1}} \]

   3. Taylor expanded in i around inf 99.6%

      \[\leadsto \color{blue}{0.0625 + 0.015625 \cdot \frac{1}{{i}^{2}}} \]

   4. Simplified 99.6%

      \[\leadsto \color{blue}{0.0625 + \frac{\frac{0.015625}{i}}{i}} \]
      Proof

      [Start] 99.6	\[ 0.0625 + 0.015625 \cdot \frac{1}{{i}^{2}} \]
      associate-*r/ [=>] 99.6	\[ 0.0625 + \color{blue}{\frac{0.015625 \cdot 1}{{i}^{2}}} \]
      metadata-eval [=>] 99.6	\[ 0.0625 + \frac{\color{blue}{0.015625}}{{i}^{2}} \]
      unpow2 [=>] 99.6	\[ 0.0625 + \frac{0.015625}{\color{blue}{i \cdot i}} \]
      associate-/r* [=>] 99.6	\[ 0.0625 + \color{blue}{\frac{\frac{0.015625}{i}}{i}} \]

3. Recombined 2 regimes into one program.

4. Final simplification 99.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq 0.5:\\ \;\;\;\;i \cdot \left(i \cdot -0.25\right)\\ \mathbf{else}:\\ \;\;\;\;0.0625 + \frac{\frac{0.015625}{i}}{i}\\ \end{array} \]

Alternatives

Alternative 1
Accuracy	99.5%
Cost	576

\[\frac{0.25}{4 + \frac{-1}{i \cdot i}} \]

Alternative 2
Accuracy	99.1%
Cost	452

\[\begin{array}{l} \mathbf{if}\;i \leq 0.5:\\ \;\;\;\;i \cdot \left(i \cdot -0.25\right)\\ \mathbf{else}:\\ \;\;\;\;0.0625\\ \end{array} \]

Alternative 3
Accuracy	50.4%
Cost	64

\[0.0625 \]

Reproduce

herbie shell --seed 2023133 
(FPCore (i)
  :name "Octave 3.8, jcobi/4, as called"
  :precision binary64
  :pre (> i 0.0)
  (/ (/ (* (* i i) (* i i)) (* (* 2.0 i) (* 2.0 i))) (- (* (* 2.0 i) (* 2.0 i)) 1.0)))