3frac (problem 3.3.3)

Average Error: 9.7 → 0.1

Time: 10.5s

Precision: binary64

Cost: 704

Math

\[\left(\frac{1}{x + 1} - \frac{2}{x}\right) + \frac{1}{x - 1} \]

↓

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

FPCore

(FPCore (x)
 :precision binary64
 (+ (- (/ 1.0 (+ x 1.0)) (/ 2.0 x)) (/ 1.0 (- x 1.0))))

↓

(FPCore (x) :precision binary64 (/ (/ -2.0 x) (* (+ x -1.0) (- -1.0 x))))

C

double code(double x) {
	return ((1.0 / (x + 1.0)) - (2.0 / x)) + (1.0 / (x - 1.0));
}

↓

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

Fortran

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

↓

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

Java

public static double code(double x) {
	return ((1.0 / (x + 1.0)) - (2.0 / x)) + (1.0 / (x - 1.0));
}

↓

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

Python

def code(x):
	return ((1.0 / (x + 1.0)) - (2.0 / x)) + (1.0 / (x - 1.0))

↓

def code(x):
	return (-2.0 / x) / ((x + -1.0) * (-1.0 - x))

Julia

function code(x)
	return Float64(Float64(Float64(1.0 / Float64(x + 1.0)) - Float64(2.0 / x)) + Float64(1.0 / Float64(x - 1.0)))
end

↓

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

MATLAB

function tmp = code(x)
	tmp = ((1.0 / (x + 1.0)) - (2.0 / x)) + (1.0 / (x - 1.0));
end

↓

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

Wolfram

code[x_] := N[(N[(N[(1.0 / N[(x + 1.0), $MachinePrecision]), $MachinePrecision] - N[(2.0 / x), $MachinePrecision]), $MachinePrecision] + N[(1.0 / N[(x - 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_] := N[(N[(-2.0 / x), $MachinePrecision] / N[(N[(x + -1.0), $MachinePrecision] * N[(-1.0 - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Target

Original	9.7
Target	0.3
Herbie	0.1

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

Derivation

1. Initial program 9.7

   \[\left(\frac{1}{x + 1} - \frac{2}{x}\right) + \frac{1}{x - 1} \]

2. Simplified 9.7

   \[\leadsto \color{blue}{\frac{1}{1 + x} - \left(\frac{2}{x} - \frac{1}{x + -1}\right)} \]
   Proof

   [Start] 9.7	\[ \left(\frac{1}{x + 1} - \frac{2}{x}\right) + \frac{1}{x - 1} \]
   associate-+l- [=>] 9.7	\[ \color{blue}{\frac{1}{x + 1} - \left(\frac{2}{x} - \frac{1}{x - 1}\right)} \]
   sub-neg [=>] 9.7	\[ \color{blue}{\frac{1}{x + 1} + \left(-\left(\frac{2}{x} - \frac{1}{x - 1}\right)\right)} \]
   neg-mul-1 [=>] 9.7	\[ \frac{1}{x + 1} + \color{blue}{-1 \cdot \left(\frac{2}{x} - \frac{1}{x - 1}\right)} \]
   metadata-eval [<=] 9.7	\[ \frac{1}{x + 1} + \color{blue}{\left(-1\right)} \cdot \left(\frac{2}{x} - \frac{1}{x - 1}\right) \]
   cancel-sign-sub-inv [<=] 9.7	\[ \color{blue}{\frac{1}{x + 1} - 1 \cdot \left(\frac{2}{x} - \frac{1}{x - 1}\right)} \]
   +-commutative [=>] 9.7	\[ \frac{1}{\color{blue}{1 + x}} - 1 \cdot \left(\frac{2}{x} - \frac{1}{x - 1}\right) \]
   *-lft-identity [=>] 9.7	\[ \frac{1}{1 + x} - \color{blue}{\left(\frac{2}{x} - \frac{1}{x - 1}\right)} \]
   sub-neg [=>] 9.7	\[ \frac{1}{1 + x} - \left(\frac{2}{x} - \frac{1}{\color{blue}{x + \left(-1\right)}}\right) \]
   metadata-eval [=>] 9.7	\[ \frac{1}{1 + x} - \left(\frac{2}{x} - \frac{1}{x + \color{blue}{-1}}\right) \]

3. Applied egg-rr 9.7

   \[\leadsto \frac{1}{1 + x} - \color{blue}{\frac{\frac{-2 + \left(2 \cdot x - x\right)}{x}}{1} \cdot \frac{1}{x + -1}} \]

4. Simplified 9.7

   \[\leadsto \frac{1}{1 + x} - \color{blue}{\frac{1}{x + -1} \cdot \frac{x \cdot 2 - \left(x - -2\right)}{x}} \]
   Proof

   [Start] 9.7	\[ \frac{1}{1 + x} - \frac{\frac{-2 + \left(2 \cdot x - x\right)}{x}}{1} \cdot \frac{1}{x + -1} \]
   *-commutative [=>] 9.7	\[ \frac{1}{1 + x} - \color{blue}{\frac{1}{x + -1} \cdot \frac{\frac{-2 + \left(2 \cdot x - x\right)}{x}}{1}} \]
   /-rgt-identity [=>] 9.7	\[ \frac{1}{1 + x} - \frac{1}{x + -1} \cdot \color{blue}{\frac{-2 + \left(2 \cdot x - x\right)}{x}} \]
   +-commutative [=>] 9.7	\[ \frac{1}{1 + x} - \frac{1}{x + -1} \cdot \frac{\color{blue}{\left(2 \cdot x - x\right) + -2}}{x} \]
   associate-+l- [=>] 9.7	\[ \frac{1}{1 + x} - \frac{1}{x + -1} \cdot \frac{\color{blue}{2 \cdot x - \left(x - -2\right)}}{x} \]
   *-commutative [=>] 9.7	\[ \frac{1}{1 + x} - \frac{1}{x + -1} \cdot \frac{\color{blue}{x \cdot 2} - \left(x - -2\right)}{x} \]

5. Applied egg-rr 24.9

   \[\leadsto \color{blue}{\frac{-1 \cdot \left(x \cdot x - x\right) - \left(-1 - x\right) \cdot \left(x + -2\right)}{\left(-1 - x\right) \cdot \left(x \cdot x - x\right)}} \]

6. Simplified 24.9

   \[\leadsto \color{blue}{\frac{\left(x + 1\right) \cdot \left(-2 + x\right) + x \cdot \left(1 - x\right)}{\left(x \cdot \left(x + -1\right)\right) \cdot \left(-1 - x\right)}} \]
   Proof

   [Start] 24.9	\[ \frac{-1 \cdot \left(x \cdot x - x\right) - \left(-1 - x\right) \cdot \left(x + -2\right)}{\left(-1 - x\right) \cdot \left(x \cdot x - x\right)} \]
   *-commutative [=>] 24.9	\[ \frac{-1 \cdot \left(x \cdot x - x\right) - \left(-1 - x\right) \cdot \left(x + -2\right)}{\color{blue}{\left(x \cdot x - x\right) \cdot \left(-1 - x\right)}} \]

7. Taylor expanded in x around 0 0.3

   \[\leadsto \frac{\color{blue}{-2}}{\left(x \cdot \left(x + -1\right)\right) \cdot \left(-1 - x\right)} \]

8. Applied egg-rr 27.6

   \[\leadsto \color{blue}{e^{\mathsf{log1p}\left(\frac{-2}{x \cdot \left(\left(x + -1\right) \cdot \left(-1 - x\right)\right)}\right)} - 1} \]

9. Simplified 0.1

   \[\leadsto \color{blue}{\frac{\frac{-2}{x}}{\left(x + -1\right) \cdot \left(-1 - x\right)}} \]
   Proof

   [Start] 27.6	\[ e^{\mathsf{log1p}\left(\frac{-2}{x \cdot \left(\left(x + -1\right) \cdot \left(-1 - x\right)\right)}\right)} - 1 \]
   expm1-def [=>] 18.0	\[ \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{-2}{x \cdot \left(\left(x + -1\right) \cdot \left(-1 - x\right)\right)}\right)\right)} \]
   expm1-log1p [=>] 0.3	\[ \color{blue}{\frac{-2}{x \cdot \left(\left(x + -1\right) \cdot \left(-1 - x\right)\right)}} \]
   associate-/r* [=>] 0.1	\[ \color{blue}{\frac{\frac{-2}{x}}{\left(x + -1\right) \cdot \left(-1 - x\right)}} \]

10. Final simplification 0.1

    \[\leadsto \frac{\frac{-2}{x}}{\left(x + -1\right) \cdot \left(-1 - x\right)} \]

Alternatives

Alternative 1
Error	1.2
Cost	841

\[\begin{array}{l} \mathbf{if}\;x \leq -0.86 \lor \neg \left(x \leq 1\right):\\ \;\;\;\;\frac{-2}{x \cdot \left(x \cdot \left(-1 - x\right)\right)}\\ \mathbf{else}:\\ \;\;\;\;-2 \cdot x + \frac{-2}{x}\\ \end{array} \]

Alternative 2
Error	1.0
Cost	841

\[\begin{array}{l} \mathbf{if}\;x \leq -0.86 \lor \neg \left(x \leq 1\right):\\ \;\;\;\;\frac{\frac{\frac{2}{x}}{x + 1}}{x}\\ \mathbf{else}:\\ \;\;\;\;-2 \cdot x + \frac{-2}{x}\\ \end{array} \]

Alternative 3
Error	1.2
Cost	840

\[\begin{array}{l} \mathbf{if}\;x \leq -0.86:\\ \;\;\;\;\frac{2}{x \cdot \left(x + x \cdot x\right)}\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;-2 \cdot x + \frac{-2}{x}\\ \mathbf{else}:\\ \;\;\;\;\frac{-2}{x \cdot \left(x \cdot \left(-1 - x\right)\right)}\\ \end{array} \]

Alternative 4
Error	1.0
Cost	840

\[\begin{array}{l} \mathbf{if}\;x \leq -0.86:\\ \;\;\;\;\frac{\frac{-2}{x \cdot \left(-1 - x\right)}}{x}\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;-2 \cdot x + \frac{-2}{x}\\ \mathbf{else}:\\ \;\;\;\;\frac{\frac{\frac{2}{x}}{x + 1}}{x}\\ \end{array} \]

Alternative 5
Error	0.3
Cost	704

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

Alternative 6
Error	15.5
Cost	585

\[\begin{array}{l} \mathbf{if}\;x \leq -0.52 \lor \neg \left(x \leq 1\right):\\ \;\;\;\;\frac{2}{x \cdot x}\\ \mathbf{else}:\\ \;\;\;\;\frac{-2}{x}\\ \end{array} \]

Alternative 7
Error	10.6
Cost	448

\[1 + \left(-1 + \frac{-2}{x}\right) \]

Alternative 8
Error	30.4
Cost	192

\[\frac{-2}{x} \]

Alternative 9
Error	61.9
Cost	64

\[-1 \]

Reproduce

herbie shell --seed 2023187 
(FPCore (x)
  :name "3frac (problem 3.3.3)"
  :precision binary64

  :herbie-target
  (/ 2.0 (* x (- (* x x) 1.0)))

  (+ (- (/ 1.0 (+ x 1.0)) (/ 2.0 x)) (/ 1.0 (- x 1.0))))