## Heron

Famously, Heron's method of computing the square root of a some number x goes like this:

1. Guess the root, we'll denote the guess by g

2. Compute the quotient q = x/g

3. Update your next guess to be the arithmetic mean of q and g. So g := (x/g + g)/2

4. Goto 2

This can be viewed as a special case of the Newton–Raphson method, and indeed the results become very accurate very fast.

## Mckay

Somewhat less famous is the anecdote about Mckay's theorem.
In this paper by Laurence Sherzer, the author tells the story of an 8th grader (in 1973) named Robert Mckay, who suggests a way to find a number that lies between two fractions. Suppose the fractions are a/b and c/d, Mckay's suggestion is to use (a+c)/(b+d).
This is a mathematical education paper, so it's focus is about how the class and the teacher approached the seemingly weird idea of adding numerators and denominators, and how they explained to themselves why this seems to 'magically' work.
The short version of the explanation is: this amounts to taking a weighted average of the two fractions, where the weights are the denominators. When the denominators are equal, this is exactly the arithmetic mean. When they differ by a lot - the result is much closer to the fraction with the larger denominator.

## McHeron?

Since taking the mean of two roots, in Heron's method, is annoying at times, why not use Mckay's very simple method instead, dubbing it the McHeron Algorithm?
Mathematically, it will give an increasingly better guess in each round, even though it may not be the arithmetic mean.
How would that look?
Suppose we want to compute the square root of 2:
1. Our first guess is 3/2
2. The quotient is 2/(3/2) which is 4/3 ('just invert and multiply' as they say)
3. Our next guess needs to be between 3/2 and 4/3, so we use Mckay's method to get 7/5
4. Our next guess is therefore 7/5
5. The next quotient is 2/(7/5) which is just 2*5/7 = 10/7
6. Using Mckay's theorem - our next guess will be (7+10)/(5+7) = 17/12
7. The next quotient is 2/(17/12) which is just 2*12/17 = 24/17
8. Using Mckay's - (17+24)/(12+17) = 41/29

And indeed 41/29 = 1.41379...
Which is approximates the square root of 2 up to 2 decimal points, which is not bad.

Cool, isn't it?

## But of course, life is never quite so simple

I specifically chose a nice example where the algorithm converges relatively fast.
Had I chosen 715 (whose square root is 26.7394...) as the initial number, it would have taken me a 100 iterations of the algorithm just to get to 26.76... and I will be dealing with denominators with 145 digits by then.
Why would the algorithm perform so bad?
Well, remember how Mckay's method introduces a bias for large denominators? The algorithm above scales the quotient's denominator by the the input number, so the larger the input number, the greater the bias toward the quotient will be in the 'Mckay' step of the calculation.

Heron's algorithm has quadratic convergence (which is amazing), and I don't think showing exactly how bad the convergence of the McHeron algorithm is difficult (I suspect that asymptotically, to get decent results, you'll have to run it as many iterations as the magnitude of the result, so O(2^(n/2)) for an input with n bits, which is terrible), but I should go shopping for the weekend.

## Silver Lining

For small numbers (with small denominators) this works nicely for the same reasons, because Mckay's method gives a decent approximation of the arithmetic mean.

That's all, would love to hear thoughts in the comments, or links if you saw this exact method somewhere else, I haven't (and for a good reason, it yields terrible results in most cases).

The user
@k_yaakov
suggested on Twitter to bring the denominators to roughly the same scale through multiplying by the appropriate power of 10. Since determining the correct power of 10 and multiplying by it can be done by counting the number of digits and adding zeros respectively, this is very easy to do in practice. The consequence is that the bias introduced by Mckay's weighted mean is now bounded by 1/10, rendering a significantly better convergence rate.
Taking the adversarial example of 715 from before: getting a 2 decimal points precision now requires only 17 iterations, compared to over 100 iterations in the previous version of McHeron. Very nice!

## Monday, January 31, 2022

### 3 Golden Rules

"Just as I cannot step in the same river twice,  the person who created this bug and I are two separate beings in the fabric of the universe. Therefore, I will also not be the one who fixes it."

Heraclitus of Ephesus, a programmer

I don't like code manifests.

Rina Artstain once tweeted that we only think we know certain things about parenting because as luck would have it, we haven't had a child to whom all of them don't apply.
That's how I feel about code manifests.

However, I do have a manifest of my own, short though it may be, so I want to frame it differently. What follows are not the three rules I think everyone should follow to get a "cleaner" code or some other metric of goodness. Rather, these are three things I like when I see in other people's code and annoy me when I see blatantly disregarded.

Here we go.

## 1.

"לֹא עָלֶיךָ הַמְּלָאכָה לִגְמוֹר, וְלֹא אַתָּה בֶן חוֹרִין לִבָּטֵל מִמֶּנָּה."

פרקי אבות, ב' טז'

"It is not incumbent upon you to finish the task, but neither are you free to absolve yourself from it."

Pirkei Avot 2:16

This is one of the greatest quotes I know and it sounds so much better in Hebrew.

## 2.

"Entities should not be multiplied beyond necessity."

William of Ockham

Yes, this is the OG Ockham's razor. How amazing it is that a Franciscan friar who lived 700 years ago foresaw the harms of overusing OOP and polymorphism.

## 3.

"Writing good code is superior to writing bad code.
Deleting code is superior to writing good code.
Superior to all is concluding that some code does not have to be written at all."

Confucius

Well, not Confucius, but if one wants people to listen, one should attribute their thoughts to someone famous, preferably dead.

I'm pretty sure Oscar Wilde said that one.