?

Average Error: 0.0 → 0.0
Time: 10.3s
Precision: binary64
Cost: 832

?

\[\frac{-\left(f + n\right)}{f - n} \]
\[\frac{n}{n - f} + \frac{1}{\frac{n - f}{f}} \]
(FPCore (f n) :precision binary64 (/ (- (+ f n)) (- f n)))
(FPCore (f n) :precision binary64 (+ (/ n (- n f)) (/ 1.0 (/ (- n f) f))))
double code(double f, double n) {
	return -(f + n) / (f - n);
}
double code(double f, double n) {
	return (n / (n - f)) + (1.0 / ((n - f) / f));
}
real(8) function code(f, n)
    real(8), intent (in) :: f
    real(8), intent (in) :: n
    code = -(f + n) / (f - n)
end function
real(8) function code(f, n)
    real(8), intent (in) :: f
    real(8), intent (in) :: n
    code = (n / (n - f)) + (1.0d0 / ((n - f) / f))
end function
public static double code(double f, double n) {
	return -(f + n) / (f - n);
}
public static double code(double f, double n) {
	return (n / (n - f)) + (1.0 / ((n - f) / f));
}
def code(f, n):
	return -(f + n) / (f - n)
def code(f, n):
	return (n / (n - f)) + (1.0 / ((n - f) / f))
function code(f, n)
	return Float64(Float64(-Float64(f + n)) / Float64(f - n))
end
function code(f, n)
	return Float64(Float64(n / Float64(n - f)) + Float64(1.0 / Float64(Float64(n - f) / f)))
end
function tmp = code(f, n)
	tmp = -(f + n) / (f - n);
end
function tmp = code(f, n)
	tmp = (n / (n - f)) + (1.0 / ((n - f) / f));
end
code[f_, n_] := N[((-N[(f + n), $MachinePrecision]) / N[(f - n), $MachinePrecision]), $MachinePrecision]
code[f_, n_] := N[(N[(n / N[(n - f), $MachinePrecision]), $MachinePrecision] + N[(1.0 / N[(N[(n - f), $MachinePrecision] / f), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\frac{-\left(f + n\right)}{f - n}
\frac{n}{n - f} + \frac{1}{\frac{n - f}{f}}

Error?

Try it out?

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation?

  1. Initial program 0.0

    \[\frac{-\left(f + n\right)}{f - n} \]
  2. Simplified0.0

    \[\leadsto \color{blue}{\frac{f + n}{n - f}} \]
    Proof

    [Start]0.0

    \[ \frac{-\left(f + n\right)}{f - n} \]

    sub-neg [=>]0.0

    \[ \frac{-\left(f + n\right)}{\color{blue}{f + \left(-n\right)}} \]

    +-commutative [=>]0.0

    \[ \frac{-\left(f + n\right)}{\color{blue}{\left(-n\right) + f}} \]

    neg-sub0 [=>]0.0

    \[ \frac{-\left(f + n\right)}{\color{blue}{\left(0 - n\right)} + f} \]

    associate-+l- [=>]0.0

    \[ \frac{-\left(f + n\right)}{\color{blue}{0 - \left(n - f\right)}} \]

    sub0-neg [=>]0.0

    \[ \frac{-\left(f + n\right)}{\color{blue}{-\left(n - f\right)}} \]

    neg-mul-1 [=>]0.0

    \[ \frac{-\left(f + n\right)}{\color{blue}{-1 \cdot \left(n - f\right)}} \]

    associate-/r* [=>]0.0

    \[ \color{blue}{\frac{\frac{-\left(f + n\right)}{-1}}{n - f}} \]

    neg-mul-1 [=>]0.0

    \[ \frac{\frac{\color{blue}{-1 \cdot \left(f + n\right)}}{-1}}{n - f} \]

    *-commutative [=>]0.0

    \[ \frac{\frac{\color{blue}{\left(f + n\right) \cdot -1}}{-1}}{n - f} \]

    associate-/l* [=>]0.0

    \[ \frac{\color{blue}{\frac{f + n}{\frac{-1}{-1}}}}{n - f} \]

    metadata-eval [=>]0.0

    \[ \frac{\frac{f + n}{\color{blue}{1}}}{n - f} \]

    /-rgt-identity [=>]0.0

    \[ \frac{\color{blue}{f + n}}{n - f} \]
  3. Applied egg-rr0.2

    \[\leadsto \color{blue}{\frac{1}{n - f} \cdot n + \frac{1}{n - f} \cdot f} \]
  4. Applied egg-rr0.1

    \[\leadsto \frac{1}{n - f} \cdot n + \color{blue}{\frac{1}{\frac{n - f}{f}}} \]
  5. Applied egg-rr0.0

    \[\leadsto \color{blue}{\left(e^{\mathsf{log1p}\left(\frac{n}{n - f}\right)} - 1\right)} + \frac{1}{\frac{n - f}{f}} \]
  6. Simplified0.0

    \[\leadsto \color{blue}{\frac{n}{n - f}} + \frac{1}{\frac{n - f}{f}} \]
    Proof

    [Start]0.0

    \[ \left(e^{\mathsf{log1p}\left(\frac{n}{n - f}\right)} - 1\right) + \frac{1}{\frac{n - f}{f}} \]

    expm1-def [=>]0.0

    \[ \color{blue}{\mathsf{expm1}\left(\mathsf{log1p}\left(\frac{n}{n - f}\right)\right)} + \frac{1}{\frac{n - f}{f}} \]

    expm1-log1p [=>]0.0

    \[ \color{blue}{\frac{n}{n - f}} + \frac{1}{\frac{n - f}{f}} \]
  7. Final simplification0.0

    \[\leadsto \frac{n}{n - f} + \frac{1}{\frac{n - f}{f}} \]

Alternatives

Alternative 1
Error15.9
Cost712
\[\begin{array}{l} \mathbf{if}\;n \leq -1.6 \cdot 10^{+68}:\\ \;\;\;\;1\\ \mathbf{elif}\;n \leq 2.25 \cdot 10^{+21}:\\ \;\;\;\;-2 \cdot \frac{n}{f} + -1\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]
Alternative 2
Error0.0
Cost704
\[\frac{n}{n - f} + \frac{f}{n - f} \]
Alternative 3
Error0.0
Cost448
\[\frac{n + f}{n - f} \]
Alternative 4
Error16.2
Cost328
\[\begin{array}{l} \mathbf{if}\;n \leq -2950000000:\\ \;\;\;\;1\\ \mathbf{elif}\;n \leq 2 \cdot 10^{-13}:\\ \;\;\;\;-1\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]
Alternative 5
Error31.8
Cost64
\[-1 \]

Error

Reproduce?

herbie shell --seed 2023046 
(FPCore (f n)
  :name "subtraction fraction"
  :precision binary64
  (/ (- (+ f n)) (- f n)))