This is something I learned at EuroPython 2011. I think it came up in a lightning talk by Alex Martelli, but I don’t recall exactly.
Continued fractions are a representation of real numbers that allows for arbitrary-precision arithmetic.
If you’ve worked with floating-point numbers in Python (or most any other programming language, for that matter), you are aware of precision problems like this:
x = 1.0 / 3.0
total = 0.0
for i in range(300):
total += x
print repr(total)
print total == 100.0
This prints 99.99999999999966, not 100.0. The reason is that the IEEE 754 floating-point representation of 1/3 isn’t exact, and this (initially small) error accumulates 300 times.
There is a different representation for real numbers: continued fractions.
- Consider the number PI = 3.141592653589793.
- This can also be written as: 3 + 1 / 7.062513305931052
- This can be written as: 3 + 1 / (7 + 1 / 15.996594406684103)
- This can be written as: 3 + 1 / (7 + 1 / (15 + 1 / 1.0034172310150002))
- This can be written as: 3 + 1 / (7 + 1 / (15 + 1 / (1 + 1 / 292.6345908750162)))
- This can be written as: 3 + 1 / (7 + 1 / (15 + 1 / (1 + 1 / (292 + 1 / 1.5758184357354204))))
This can be stored efficiently in some form of list: PI = [3, 7, 15, 1, 292, 1, …]. The “cf” module is a Python implementation of continued fractions by Marcin Ciura that uses lazy evaluation. Here’s the previous example rewritten using continued fractions:
from cf import cf
x = cf(1.0) / cf(3.0)
total = cf(0.0)
for i in range(300):
total += x
print repr(float(total)) # prints 100.0
print total == 100.0
The mathematical background is explained on Wikipedia and in this presentation by Mark Jason Dominus.
