I found a pretty strange piece of code in my code directory recently. The file was a few months old. It was short (around 15 loc). Even though it was called
compute.py, I had no idea what it was meant to compute:
from math import sqrt a_n = 1.0 b_n = 1.0/sqrt(2.0) t_n = 1.0/4.0 p_n = 1.0 for i in range(4): a_n1 = (a_n+b_n)/2.0 b_n1 = sqrt(a_n*b_n) t_n1 = t_n - p_n * ((a_n - a_n1) * (a_n - a_n1)) p_n1 = 2*p_n print((a_n1 + b_n1)**2 / (4*t_n1)) a_n, b_n, t_n, p_n = a_n1, b_n1, t_n1, p_n1
So this is some math stuff, but what was I thinking about when I wrote that ? It was easy to see that there was no malware in this, so I ran it.
$ python compute.py 3.1405792505221686 3.141592646213543 3.141592653589794 3.141592653589794
The memory came back. A few months ago, I was interested in finding decimals of pi, so… I wrote a program to do so. That’s where this piece of code is awesome.
It’s a very short program. It expected computing pi to be a complicated task, then I found the Gauss-Legendre algorithm. It’s trivial to implement. As you can see, 15 loc are enough and it could be golfed a bit more.
It’s also beautiful that, despite its simplicity, the algorithm has quadratic convergence : the number of correct digits doubles with each iteration of the algorithm. That’s way better than Monte-Carlo’s algorithm I spoke about earlier, where you need 100 times more iterations to get one more digits.
The core idea is that we will compute the arithmetic–geometric mean of two numbers cleverly chosen and a relationship between all the values will let us approximate pi. The Wikipedia page has more details on the derivation of this result.
As for us, with specific initial values for a0, b0, t0 and p0:
we can compute the next values of the sequence:
and out of these values, with n large enough, we can compute an approximation of pi:
Due to the quadratic convergence, n = 4 is already enough to have a good enough approximation.
See a typo ? You can suggest a modification on Github.